FUNCIONES ESPECÍFICAS DEL TRÁFICO ENDOLISOSOMAL EN

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UNIVERSIDAD AUTÓNOMA DE MADRID
Facultad de Ciencias
Departamento de Biología Molecular
Tesis Doctoral
FUNCIONES ESPECÍFICAS DEL TRÁFICO ENDOLISOSOMAL
EN LA PROGRESIÓN Y RESPUESTA A TERAPIA
DEL MELANOMA
DIRENA ALONSO CURBELO
Madrid, 2013
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AUTONOMOUS UNIVERSITY OF MADRID
Faculty of Science
Department of Molecular Biology
SPECIFIC ROLES OF ENDOLYSOSOMAL TRAFFICKING IN
MELANOMA PROGRESSION AND DRUG RESPONSE
A doctoral thesis submitted to the Autonomous University of Madrid for the
degree of Doctor of Philosophy in Molecular Biology
Direna Alonso Curbelo
Thesis Director
Dr. María S. Soengas
Melanoma Group (Molecular Pathology Program)
Spanish National Cancer Research Center
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Dr. María S. Soengas, Director of the Molecular Pathology Program and Head of the Melanoma group at
the Spanish National Cancer Research Center (CNIO)
CERTIFIES:
That the Doctoral Thesis “Specific roles of endolysosomal trafficking in melanoma progression and
drug response” developed by Ms Direna Alonso Curbelo meets the necessary requirements to obtain
the PhD Degree in Molecular Biology and, to this purpose, will be presented at the Autonomous
University of Madrid. The thesis has been carried out under my direction and hereby I authorize it to be
defended to the appropriate Thesis Tribunal.
I hereby issue this certification in Madrid on April 30st 2013.
María S. Soengas
PhD Thesis Director
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Dr. Jaime Millán Martínez, Head of group of Cell Biology of Inflammation at the Centro de Biología
Molecular Severo Ochoa (CBMSO)
CERTIFIES:
That the Doctoral Thesis “Specific roles of endolysosomal trafficking in melanoma progression and
drug response” developed by Ms Direna Alonso Curbelo meets the necessary requirements to obtain
the PhD Degree in Molecular Biology and, to this purpose, will be presented at the Autonomous
University of Madrid. The thesis has been carried out under my direction and hereby I authorize it to be
defended to the appropriate Thesis Tribunal.
I hereby issue this certification in Madrid on April 30st 2013.
Jaime Millán Martínez
PhD Thesis Tutor
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The work presented in this doctoral thesis was carried out in the Melanoma Group at the Spanish
National Cancer Research Center (CNIO) from June 2008 to June 2013 under the supervision of María S.
Soengas.
This work has been supported by the following fellowships and grants:
 “Formación de Profesorado Universitario” (FPU) PhD Fellowship, awarded by the Spanish
Ministry of Science and Education. Direna Alonso Curbelo (2008 – 2012)
 INNPACTO program. María S. Soengas (2012 – 2013)
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“Lo imposible es posible intentarlo”
José Miguel Alonso Fernández-Aceytuno
“The impossible is always possible to be pursued”
José Miguel Alonso Fernández-Aceytuno (1951 – 2004)
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A mi padre
del que tanto aprendí
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Acknowledgements
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Esta tesis representa el final de una etapa que he vivido intensamente y en la que he aprendido
muchísimo, tanto a nivel científico como a nivel personal. Y si hoy me encuentro ante esta página en
blanco que llenar con mis más sinceros sentimientos de gratitud es gracias al apoyo, a la inspiración, a la
energía positiva y a la ayuda incondicional que me habéis dado todos a lo largo de estos años. A todos
vosotros, GRACIAS.
GRACIAS Marisol por haber confiado en mis ganas de aprender aquel agosto de 2008 en el que
hablamos por primera vez, dándome la gran oportunidad de embarcarme en este apasionante mundo
de la ciencia a través de tu laboratorio y del CNIO. Gracias muy especialmente por haber reconocido
también las ganas del resto de mis compañeros y construir este grupo de investigación tan estupendo. Y
gracias de corazón por tu gran apoyo que no sólo ha hecho posible esta tesis, sino que además me ha
abierto las puertas de la siguiente etapa, que espero con muchísima ilusión.
THANKS MELANOMA GROUP! I have no words to express all the gratitude and love I feel for you guys. It
has been a real privilege to work with and learn from you all along these years. You have been the best
travel companions and my seat belts on this PhD roller coaster. You are the definitely the faces of these
last years and one of the most valuable things I take from them. I am sure that in a distant future, when
my memories of western blotting and cell line #9 have vanished away, I´ll always remember the
awesome time we had together, in and outside the lab. Estela, eres la mejor lab manager, compañera, y
“writing consultant” que se puede tener, pero sobre todo, eres una gran persona y una excelente amiga.
GRACIAS por todo tu cariño, por cuidar siempre de mí. No sabes lo que voy a echar de menos tu risa y la
energía positiva que desprendes… Damià, “pseudo-jefe”, contigo di mis primeros pasitos del doctorado
y desde entonces no he parado de aprender de ti. Tu capacidad para transformar las ideas en hechos, tu
ilusión por mejorar lo que nos rodea, y tu forma de hacerlo, siempre con sonrisa puesta,
admirables. Eva, no te imaginas lo importante que ha sido para mí tenerte a mi lado todos estos años.
Tu paciencia, tu forma de hacer, de estar y de ser siempre han sido un gran ejemplo para mí. Gracias
también por tu disposición para escuchar y ayudar a los demás, que además creo que son
fundamentales para el laboratorio en general. Erica, muchas gracias por tus siempre sabias palabras,
capaces de devolver la necesaria dosis de perspectiva a los momentos difíciles. He aprendido muchísimo
de ti; de tu fortaleza, de tu optimismo y de tu sinceridad. Lisa, my lab “big sister”, my german “Other
Self”, thanks so much for being such a good friend and filling the lab atmosphere with your
incombustible inner glow. Your big smile is very small compared to your huge heart. And many THANKS
too for the English editing of the thesis! Metehan, I want to thank you very much for all your support,
for having so much patience with my incessant questions, for so many great conversations and for
always seeking and coming up with an original idea, solution, or strategy to make our lives a lot easier.
Takis, today, here, I am not going to emphasize my admiration to your pipetting muscles. I really want to
thank you for always having that friendly “yes” sitting at the tip of your tongue. Thanks also for your
constant willingness to help me and others whenever you can. DOC, el flautista de Hamelín más majo y
coqueto del CNIO y una pieza clave del laboratorio, muchas gracias por haberme enseñado tanto sobre
metástasis, ¡y los mejores lugares de tapas del centro! Tonan, gracias de verdad, no sólo por tu siempre
excelente ayuda técnica, que además ha sido FUNDAMENTAL para este trabajo, sino también por todo
tu cariño. Eres la gasolina que mantiene rodando el laboratorio (y mi entropía en cierto orden!). He
aprendido muchísimo de ti. Gracias! David Sáenz, ¡cómo te he echado de menos estos últimos años en
el laboratorio! Existen pocos como tú, con esa entrega incondicional hacia los demás y hacia su trabajo,
y con todo eso de buena persona que tienes y que tanto te caracteriza. Lionel y Agi, thanks a lot for
everything you taught me and for showing me what persistence in science means. María, ¡eres una
crack! Me ha encantado conocerte y descubrir cómo si se quiere, se puede. Si vuelvo del postdoc en
Nueva York pareciéndome un poquito más a ti, ya me puedo dar más que por satisfecha. Alicia,
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muchísimas gracias por tu compresión y por todo tu apoyo ;) ¡Estoy segura de que el futuro del pICPEI
está en excelentes manos! ¡Suerte con todo! Ángel, el pichichi en geles del labo, muchas gracias por tu
excelente ayuda técnica y, sobre todo por encargarte, aún sin hacerlo a conciencia, de mantener el buen
rollo en el laboratorio. Raúl, no sabes la penita que me da que no poder coincidir más tiempo contigo en
el laboratorio. ¡¿Por qué no llegaste antes?! Bueno, no sé si ya lo sabes, pero es tradición en el
laboratorio que los doctorandos de más de 1.90m de altura mantengan SIEMPRE la curiosidad y la
ilusión. Daniela, te dejo encargada de que la gente del labo acabe diciendo “SENIO” en lugar de CNIO
jeje. Muchísimas suerte con el doctorado, aunque sé que no te hará falta, porque eres
buenísima. Napala, thanks SO MUCH for your constant smile and for the English editing of this thesis in
record time. Carla, Renata y Carol, thanks for bringing a little closer to the lab the best energy of Brazil
(and the brigadeiros!). By the way Marisol, perhaps we should include “cachaça” in the lab´s reagents
list! Y a todos los demás que, en algún momento habéis formado parte de este equipo (Iván, Marco,
Elisa, Joe, Bobby, Elena, Silvia, Marta…), gracias también por vuestra apoyo.
MUCHAS GRACIAS también a los miembros de mi Comité de Tesis en el CNIO: Xosé Bustelo, Mirna
Pérez-Moreno y Manuel Serrano por haber compartido conmigo toda vuestra experiencia, que ha sido
fundamental para el desarrollo de este proyecto así como para mi aprendizaje a nivel científico y
personal.
MANY THANKS to the Epithelial Carcinogenesis Group (CNIO) for their support and input during the
Monday lab meetings, as well as for being SUCH COOL LAB NEIGHBOURS. THANKS as well to the
Lymphoma Group (CNIO), and very especially to Elena Rodriguez, for “adopting” me when I was just
about to start the PhD and the Michigan Melanoma group was still moving to the CNIO.
MUCHAS GRACIAS también a nuestros colaboradores del Hospital 12 de Octubre de Madrid: los
doctores José Luis Peralto, Pablo Ortiz, y Erica Riveiro por haber hecho posible el estudio de RAB7 en
muestras humanas. Ha sido emocionante ver como un proyecto que se inició y se desarrolló en la
poyata adquiere una dimensión de realidad, haciendo que esta experiencia sea más enriquecedora y
merecedora de todo este esfuerzo.
De la misma manera, quiero dar las gracias a Damià y a su equipo de Bioncotech Therapeutics por
intentar que los frutos de la investigación se traduzcan finalmente en una mejora real en la expectativa
de vida de pacientes. ¡No existe mejor motivación que ésta para hacer ciencia!
I really want to thank all of my colleagues who actively participated in the RAB7 project. Hopefully, all
the effort will soon be rewarded! THANKS to Gonzalo Gómez and Osvaldo Graña (Bioinformatics
Groups, CNIO) for your important contribution to this work. In addition, I would also like to thank all the
people working at the CNIO Flow Cytometry, Histopathology, Genomics, and Animal Facility Units; the
CNIO Tumor Bank; and to José Manuel (from CNIO Information Technologies) for their excellent
technical support.
VERY VERY SPECIAL THANKS to Diego Megías and his great Confocal Microscopy Unit team, Ximo
Soriano and Manu Pérez for their unconditional help and for being the coolest microscopy guys ever.
Without you guys this thesis would not have been possible!
THANKS to Dr. Reuven Agami (NKI, Amsterdam) and to Dr. Johanna Joyce (MSKCC, NY) for giving me the
enriching opportunity of joining their labs as a visiting PhD student. During those months I met great
scientists and friends that made my stays in Amsterdam and NY an unforgettable experience: Arnold
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Bos, Carlos Melo, Maritt Terweij, Dominika Bijos, Hayley Moore, Nicolas Leveillé, Carlos Le Sage, and,
of course David Ontoso, in Amsterdam; and Sonia Mulero, Chema Carvajal, Alberto Schuhmacher, Joni
Van Der Meulen, Silvia Domcke, Lisa Sevenich, Leila Akkari, Hao-Wei Wang, Oakley Olson, Bobby
Bowman, Carlos Carmona, Richard Stein, Neils Weinhold, and Nick Gauthier in New York. THANKS SO
MUCH FOR MAKING FEEL AT HOME!
Gracias también a los chicos de Mantenimiento de CNIO por ser tan simpáticos y eficaces; así como a
Emma y al resto del equipo de la Cafetería del CNIO por alimentarme casi como una madre y por, como
no, las tapas de los viernes!
Quiero darle las GRACIAS también a muchos compañeros del CNIO que, con su amistad, con su ayuda, o
tan sólo mediante un cruce de sonrisas cómplices por los pasillos, han hecho que mi estancia aquí haya
sido tan agradable. GRACIAS muy especialmente a Eva Sánchez, Juanlu, Alba, Ana del Río, Eva Briso,
Lina, Laia, Sara Mainardi, Carolina Navas, Dani Martín, Bea H, Daniela, Martina, Javier Leandro, Lara,
Marta Shahbazi, Miguel Foronda, Patricia Nieto, y muchos otros (porque sería imposible nombraros a
todos) por ser tan majos y los protagonistas de muchos de los recuerdos que me llevo del CNIO. Laura y
Bárbara, a vosotras muy en especial, MUCHÍSIMAS GRACIAS por vuestro apoyo incondicional y por
regalarme vuestra amistad. Haberme embarcado en el doctorado ya mereció la pena el día que os
conocí.
También quiero agradecer el apoyo que he recibido de viejos y nuevos amigos que me han acompañado
a lo largo de esta etapa de tesis. Habéis sido mis “gatorades” en esta maratón. MUCHÍSIMAS GRACIAS
Marty, Mer y Auro; porque vuestra amistad siempre me ha hecho más feliz, mejor persona y más
fuerte. Sois mi mejor equipo. GRACIAS Tere. Me siento muy afortunada por haber compartid carrera,
hospital, tesis y casa con una gran persona y amiga como tú. Eres muy grande, que lo sepas! GRACIAS
Daniel Movilla por tantos buenos momentos en los que hemos arreglado el mundo y nuestras vidas.
“Redescubrirte” ha sido el mejor regalo del 2012 (Birdybirdybirdy). GRACIAS David Ontoso por ser un
amigo sin igual. Hasta la “Dire muerta de hambre” sólo tendría buenas palabras para ti ;). GRACIAS
Carlos Gordo y Marc por todo vuestro cariño. GRACIAS también a Helena, Carmen, y a Ángela por ser
tan buenas amigas y las mejores compañeras de piso. MUCHAS gracias también a “La Cuadrilla” de
Madrid por hacerme sentir como si fuera del “Jesús Maestro”. MUCHAS GRACIAS a Mari Mar y a Paco,
por haber formado una familia tan estupenda y por todo esos buenos ratos y ratitos de mesa y
sobremesa (y por los tápers de carne picada! jeje).
MUCHAS GRACIAS a mis amigos de Las Palmas, muy especialmente a Lidu, Alfredo, Héctor, Aday,
Laura, Nolo, Juan, Laura Merino, y Cris Santana por el día a día y los largos veranos de ayer, y por los
“Encuentros” revitalizadores de hoy. Con vosotros, la distancia no existe.
Y por último quisiera dedicar los últimos agradecimientos a las personas más importantes de mi vida,
mis grandes pilares, mis norte-sur-este-y-oeste. ¡MUCHÍSIMAS GRACIAS A MI MARAVILLOSA FAMILIA!
Sois muchos y sólo tengo buenas palabras para cada uno de vosotros. GRACIAS muy especialmente a
mis abuelas, por todo vuestro amor y por enseñarme las claves para ser feliz; a Ana Mari, porque para
mí eres un gran referente, y a Margarita Curbelo, Cristina Curbelo, Nano y Marina, por haber creído
tanto en mí y demostrármelo siempre.
MUCHISÍSISISISIMAS GRACIAS a Jorge y Ana, ¡por ser los mejores hermanos del mundo! No paro de
aprender de vosotros, a pesar de ser yo la hermana mayor. ¡Os quiero muchísimo!
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Javi, MUCHAS GRACIAS por haber hecho que estos años hayan sido inolvidables, por dibujarme una
sonrisa cada mañana y hacer de la tesis un “paraíso con gastos pagados”. Recuerdo las ganas de
empezar el día en Galileo 25 y los trayectos en la “olivita” hacia el CNIO del principio… qué rápido ha
pasado el tiempo la verdad, aunque no me extraña, porque estos años no los he medido en días, sino en
fines de semana. Muchas gracias por tu enorme apoyo, por hacerme reír tantísimo, por subir el “phD de
mi piel”, por tantos buenos momentos y viajes juntos, por creer tanto en mí, por todo tu amor. TANGO
QUÉBEC.
PARA MIS PADRES NUNCA TENDRÉ SUFICIENTES PALABRAS DE AGRADECIMIENTO… Papi, te llevo en el
corazón, muy cerquita, siempre, a todas partes. Y, aunque mientras escribo estas líneas las lágrimas
evidencien la tremenda nostalgia y el vacío irremplazable que siento (porque te echo muchísimo de
menos y deseo que pudieras estar aquí con nosotros), el recuerdo de tu incombustible ilusión, de tu
siempre optimista mirada hacia el futuro, y de la entereza que te caracterizó hasta el final me da la
fuerza para seguir siendo una persona muy feliz. Gracias por enseñarme tanto y por ser una grandísima
persona. Mami, a ti te dedico las últimas palabras porque, si en la vida dicen que uno va eligiendo su
propio camino, tú eres mi brújula, mi mapa, mi gasolina, mi “airbag” cuando tropiezo, y sobre todo, la
mejor compañera y guía de viaje. Un millón de gracias por tu enorme corazón, por tu fuerza, por tu
apoyo incondicional, y por tu bien criterio. Gracias también por tus zumos revitalizadores de papaya con
naranja y tus palabras sanadoras, y por cuidar tan bien de mí y de Jorge y Ana. ¡Sin duda tus hijos somos
los más afortunados del mundo!
Gracias por último a J.S. Bach, y a todos los que desde chiquitita me inculcaron el amor por la MÚSICA,
que me ha dado tantos momentos de placer y es mi mejor anestesia.
¡MUCHAS GRACIAS A TODOS POR ACOMPAÑARME EN ESTA ETAPA! Sólo puedo terminar esta etapa de
tesis y estos agradecimientos, como diría Sabina: añadiendo al punto final, dos puntos suspensivos…
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"En este proceso mental, precursor del descubrimiento, nada es inútil:
los primeros grosos errores, así como las falsas rutas donde la
imaginación se aventura, son necesarios, pues acaban por conducirnos
al verdadero camino, y entran, por tanto, en el éxito final, como entran
en el acabado cuadro del artista los primeros informes bocetos."
Santiago Ramón y Cajal (1852-1934)
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ABBREVIATIONS
SUMMARY
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RESUMEN
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INTRODUCTION
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1. THE MELANOMA CHALLENGE: WHERE ARE WE NOW?
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2. THE CELLULAR ORIGIN OF MELANOMA: THE MELANOCYTE
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3. CLASSIFICATION OF CUTANEOUS MELANOCYTIC LESIONS
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3.1 BENIGN MELANOCYTIC LESIONS: NEVI
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3.2. MALIGNANT MELANOCYTIC LESIONS: MELANOMA
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4. DEVELOPMENT AND PROGRESSION OF MELANOCYTIC TUMORS
4.1 HISTOLOGIC,
BIOLOGIC
AND
GENETIC
FEATURES
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ASSOCIATED
WITH
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MELANOMA PROGRESSION
4.2. INTRATUMOR HETEROGENEITY AND MELANOMA-CELL PLASTICITY
5. MELANOMA ONCOGENES AND “NON-ONCOGENE” DEPENDENCIES
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5.1. MELANOMA ONCOGENES: “CLASSICAL” VERSUS “LINEAGE-SPECIFIC” FACTORS
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5.2. NON-ONCOGENE DEPENDENCIES IN MELANOMA: AUTOPHAGY AND BEYOND
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6. TREATMENT OF CUTANEOUS MELANOMA
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OBJECTIVES
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OBJETIVOS
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MATERIALS AND METHODS
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1. CELLS
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2. GENE SET ENRICHMENT ANALYSIS (GSEA) IN MULTITUMOR DATASETS
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3. OLIGONUCLEOTIDE ARRAY CGH (COMPARATIVE GENOMIC HYBRIDIZATION)
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4. TISSUE MICROARRAYS (TMAS) AND IMMUNOHISTOCHEMISTRY (IHC)
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5. KAPLAN-MEIER SURVIVAL ANALYSES
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6. PROTEIN IMMUNOBLOTTING
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7. IMMUNOFLUORESCENCE AND CONFOCAL-BASED SINGLE-CELL QUANTIFICATION IN
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TISSUES
8. IMMUNOFLUORESCENCE IN FIXED CELLS
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9. RAB7 EXPRESSION IN MELANOMA “INVASIVE” OR “PROLIFERATIVE” GENE
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SIGNATURES
10. STABLE INHIBITION OF RAB7 FUNCTION
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11. SITE-DIRECTED MUTAGENESIS AND RAB7 shRNA- RESCUE ASSAYS
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12. siRNA-MEDIATED GENE SILENCING OF ATG7, RAB7, VPS34, SOX10 AND MITF
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13. BECLIN1 STABLE RNA INTERFERENCE
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14. CELL PROLIFERATION AND COLONY FORMATION ASSAYS
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15. ANIMAL EXPERIMENTS: XENOGRAFT ASSAYS AND MELANOMA MODELS
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16. MATRIGEL INVASION ASSAYS
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17. ASSESSMENT OF LYSOSOMAL FUNCTION
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18. GENERATION OF PEI-COMPLEXED PIC GENERATION OF PEI-COMPLEXED PIC
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19. DRUG TREATMENTS AND VIABILITY ASSAYS
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20. FLUID PHASE ENDOCYTOSIS ASSAYS
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21. RNA EXTRACTION, RT-PCR AND HIGH THROUGHPUT RNA SEQUENCING
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22. VISUALIZATION AND QUANTITATIVE ANALYSIS OF CYTOSKELETAL ALTERATIONS
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(CYTOOCHIPS)
23. VIDEO AND FIXED-CELL FLUORESCENCE MICROSCOPY OF ENDOCYTIC AND
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AUTOPHAGIC TRAFFICKING
24. TRANSMISSION ELECTRON MICROSCOPY
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25. PROTEIN SECRETION ASSAYS
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26. ONCOGENE-INDUCED SENESCENCE ASSAYS IN PRIMARY HUMAN MELANOCYTES
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27. STATISTICAL ANALYSES
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RESULTS
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1. LINEAGE-RESTRICTED TRAITS ASSOCIATED WITH THE LYSOSOME IN MELANOMA
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2. LINEAGE-RESTRICTED OVEREXPRESSION OF RAB7 IN MELANOMA
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3. MITF-INDEPENDENT OVEREXPRESSION OF RAB7 IN MELANOMA
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4. LINEAGE-ADDICTION OF MELANOMA CELLS TO RAB7
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5. MELANOMA CELL MORPHOLOGY AND INVASIVE POTENTIAL CONTROLLED BY RAB7
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6. RAB7 IS AN EARLY-INDUCED MELANOMA DRIVER TUNED DOWN AT INVASIVE
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STAGES OF TUMOR PROGRESSION IN VIVO
7. HALTED DEGRADATION OF NON-CANONICAL AUTOPHAGOSOMES AND
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MACROENDOSOMES IN RAB7-DEPLETED MELANOMA CELLS
8. DERAILED VESICLE TRAFFIC BY RAB7 DOWNREGULATION PROMOTES THE SECRETION
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OF LYSOSOMAL PROTEASES
9. GLOBAL CHANGES IN GENE EXPRESSION AND PROTEIN SECRETION PROGRAMS BY
MODULATION OF RAB7 LEVELS
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10. UPSTREAM REGULATION OF RAB7 BY MELANOCYTE DEVELOPMENTAL PATHWAYS
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11. REGULATION OF RAB7 EXPRESSION AND FUNCTION BY ONCOGENIC SIGNALING
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PATHWAYS IN MELANOMA CELLS
12. ACTIVATION OF ONCOGENIC SIGNALING IN NORMAL MELANOCYTES DEREGULATES
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RAB7 AND ITS ASSOCIATED VESICLE TRAFFICKING PATHWAYS
13. ONCOGEN-DRIVEN ACTIVATION OF RAB7 IN VIVO
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14. MODULATION OF RAB7-ASSOCIATED ENDOLYSOSOMAL VESICLE TRAFFICKING BY
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TREATMENT WITH ds-RNA-BASED NANOCOMPLEXES
15. RAB7-MEDIATED VESICLE TRAFFICKING IS ACTIVELY INVOLVED IN THE ANTI-
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MELANOMA ACTIVITY OF ds-RNA-BASED NANOCOMPLEXES
DISCUSSION
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1. LESSONS FROM MULTITUMOR GSEA IN MELANOMA GENE DISCOVERY
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2. BIOLOGICAL IMPLICATIONS OF MELANOMA-ASSOCIATED TRAITS IDENTIFIED BY GSEA
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3. CELL LINEAGE AS A DETERMINANT OF RAB7 EXPRESSION AND FUNCTION IN CANCER
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4. RAB7 EXPRESSION AND FUNCTION IN MELANOMA PROGRESSION
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5. RAB7 VERSUS MITF AND OTHER LINEAGE-SPECIFIC MELANOMA DRIVERS
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6. DOWNSTREAM EFFECTOR PATHWAYS OF RAB7 IN MELANOMA CELLS
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7. ANTITUMOR THERAPEUTIC OPPORTUNITIES TARGETING ENDOLYSOSOMAL
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PATHWAYS
8. PERSPECTIVES
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CONCLUSIONS
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CONCLUSIONES
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REFERENCES
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APPENDIX
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1. SUPPLEMENTARY TABLES
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2. SUPPLEMENTARY FIGURE
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3. SUPPLEMENTARY VIDEO LEGENDS
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4. PUBLICATIONS
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5. PRESENTATIONS
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Abbreviations
Abbreviations
“Lo bueno, si breve, dos veces bueno”
Baltasar Gracián (1601-1658)
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Abbreviations
AJCC - American Joint Committee on Cancer
AFU - Arbitrary Fluorescence Units
AKT - v-Akt murine thymoma viral oncogene homolog
ATG - Autophagy-related gene
ATP - Adenosine triphosphate
AURKB - Aurora kinase B
BCL2 - B-cell lymphoma 2
BECN1- Beclin1
BRAF - v-Raf murine sarcoma viral oncogene homolog B1
BRN2 - PUO class 3 homeobox 2 (POU3F2)
BSA - Bovine serum albumin
CCND1 - Cyclin D1
CCLE - Cancer Cell Line Encyclopedia
CDC - Cell division cycle
CDK - Cyclin-dependent kinase
CDKN2A - Cyclin-dependent kinase inhibitor 2A
cDNA - Complementary DNA
CEACAM1 - Carcinoembryonic antigen-related cell adhesion molecule 1
CGH - Comparative genomic hybridization
CI - Confidence intervals
CM - Conditioned media
CMT2B - Charcot-Marie-Tooth type 2B
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Abbreviations
CNIO - Centro Nacional de Investigaciones Oncológicas
CSC - Cancer stem cell
CQ - Chloroquine
CTLA-4 - Cytotoxic T-lymphocyte antigen-4
CTRL - Control
CTS - Cathepsin
DAPI - 4,6-diamidino-2-phenylindole
DFS- Disease Free Survival
DMBA - 7,12-dimethylbenz[a]anthracene
DMEM - Dulbecco’s Modified Eagle’s Medium
DMSO - Dimethyl sulfoxide
DN - Dominant negative
DNA - Deoxyribonucleic acid
dsRNA - Double-stranded RNA
E2F1 - E2F transcription factor 1
EDNRB - Endothelin receptor type B
EDTA - Ethylenediaminetetra-acetic acid
EGFR - Epidermal growth factor receptor
EIPA - 5-(N-ethyl-N-isopropyl) amiloride
EMT - Epithelial-to-mesenchymal transition
ER - Endoplasmic reticulum
10
Abbreviations
ERK - ERK, extracellular signal-regulated kinase
ETV1 - Ets variant 1
FACS - Fluorescence-activated cell sorting
FBS - Fetal Bovine Serum
FDA - US Food and Drug Administration
FDR - False discovery rate
FGF - Fibroblast growth factor
FGM - Fibroblast growth medium
FYCO1 - FYVE and coiledcoil domain containing 1
GAP - GTPase-activating protein
GAPDH - Glyceraldehydes‐3‐phosphate dehydrogenase
GDP - Guanosine diphosphate
GEF - Guanine nucleotide exchange factor
GFP - Green fluorescent protein
GLI2 - Glioma-associated oncogene family member-2
GO - Gene ontology
GNAQ - Guanine nucleotide binding protein (G protein), q polypeptide
GSEA - Gene Set Enrichment Analysis
GTP - Guanosine 5'-triphosphate
GTPase - Guanine nucleotide triphosphatase
H&E - Hematoxylin and eosin
11
Abbreviations
HOPs - Homotypic fusion and protein sorting complex
HR - Hazard ratio
HRAS - v-Ha-ras harvey rat sarcoma viral oncogene homolog
HRP – Horseradish peroxidase
HSP70 - 70-kDa heat shock protein
IF- Immunofluorescence
IFNα – Interferon-alpha
IgG – Immunoglobulin G
IHC - Immunohistochemistry
IL - Interleukin
INH - Inhibitor
kDa - Kilodalton
KEGG - Kyoto Encyclopedia of Genes and Genomes
KGM - Keratinocyte growth medium
KIT - v‐kit Hardy‐Zuckerman 4 feline sarcoma viral oncogene homologue
LAMP - Lysosomal membrane protein
LC3 - Microtubule-associated protein 1 light chain 3
LDH - Lactate dehydrogenase
LTR - Lysotracker
3-MA - 3-Methyladenine
MAPK - Mitogen-activated protein kinase
MC1R - Melanocortin-1 receptor
12
Abbreviations
MDA-5 - Melanoma differentiation-associated protein 5
MEF - Mouse embryonic fibroblasts
MEK - mitogen-activated protein/extracellular signal-regulated kinase kinase
MET - met proto-oncogene (hepatocyte growth factor receptor)
MGM -Melanocyte growth medium
miRNA - microRNA
MITF - Microphthalmia-associated transcription factor
MMP - Matrix metalloproteinase
mRNA - Messenger RNA
MSRC - Matrix screening remote control
mTOR - Mammalian target of rapamycin
MUT - Mutated/mutant
MVB - Multivesicular bodies
MYC - v-Myc myelocytomatosis viral oncogene homolog
NCCN - National Comprehensive Cancer Network
NCI - National Cancer Institute
NEDD9 -Neural precursor cell expressed, developmentally down-regulated 9
NF1 - Neurofibromatosis Type 1
NRAS - v-Ras neuroblastoma viral oncogene homolog
NT - Non treated
OIS - Oncogene Induced Senescence
13
Abbreviations
ORP1L - OSBP (oxysterol-binding protein) related protein
OS - Overall Survival
P - Probability values
PAX3 -Paired box-3
PBS - Phosphate-Buffered Saline
PBS-T Phosphate-Buffered Saline with Tween
PCR - Polymerase chain reaction
PD1 - Programmed death 1
PDL1 - Programmed cell death 1 ligand
PEI - Polyethyleneimine
PET-CT -Positron emission tomography - computed tomography
PFA - Paraformaldehyde
PGC1α - PPARGC1A
PI3K - phosphoinositide-3 kinase
PI3KC3 - Class III type phosphoinositide 3-kinase
pIC - Polyinosine-polycytidylic acid
[pIC]PEI - Polyinosine-polycytidylic acid complexed with polyethyleneimine
PKC - Protein kinase C
PTEN - Phosphatase and tensin homolog
qRT- PCR - Real-time reverse transcription polymerase chain reaction
RAB - Ras-related in brain
14
Abbreviations
Rabring7 - Rab7-interacting ring-finger protein
RAC1 - Ras-related C3 botulinum toxin substrate 1
RAS - at sarcoma viral oncogene homolog
RB - Retinoblastoma
RILP - Rab7-interacting lysosomal protein
RGP - Radial-growth Phase
RNA - Ribonucleic acid
RNAi - RNA interference
RECIST - Response Evaluation Criteria In Solid Tumors
RT - Room Temperature
RTK - Receptor tyrosine kinase
SA-β-Gal - Senescence-associated β-galactosidase
SAHF - Senescence-associated Heterochromatin Foci
SD - Standard deviation
SDS - Sodium dodecyl sulfate
SEM - Standard error of estimate of mean value
shRAB7 - RAB7 shRNA
shCtrl - Control shRNA
shRNA - Short hairpin RNA
siRNA - Small interfering RNAs
SMO - Smoothened
15
Abbreviations
SNARE - Soluble N-ethylmaleimide-sensitive factor attachment protein receptor
SOX10 - SRY-box-containing gene 10
TBC1D15 - TBC1 domain family, member 15
TBC1D16 - TBC1 domain family, member 16
TF - Transcription factor
TFDP1 - Transcription factor Dp-1
TGFα - transforming growth factor-alpha
TGFβ - transforming growth factor-beta
TGN - Trans-Golgi network
TNM - Tumor-Node-Metastasis
TMA -Tissue Microarrays
TP53 - tumor protein 53
TRP2 - Tyrosinase-related protein 2
TYR - Tyrosinase
UV - Ultraviolet
UVRAG - UV radiation resistance-associated gene; Vps, vacuolar protein sorting
VEGF - vascular endothelial growth factor
VGP - Vertical-growth Phase
VPS34 - Vacuolar protein sorting 34
WB - Western blotting
WHO - World Health Organization
16
Abbreviations
WNT - Wingless‐type MMTV integration site family
WT - Wild Type
17
Summary
18
Abbreviations
Summary
19
Summary
20
Summary
Melanoma was first described as a tumor entity in 1806, and it has since remained a prime example of a
heterogeneous, aggressive and treatment-resistant malignancy. Despite great progress made in the
understanding of the molecular basis underlying melanoma initiation and progression, the field still lacks
clinically relevant biomarkers, consensus on metastatic progression mechanisms and effective
treatments for the management of advanced stages. Consequently, this PhD thesis was set to: (1)
identify new genes driving melanoma pathogenesis, (2) characterize their role in tumor initiation and
progression, and (3) use this information for the development of novel therapeutic strategies. We
focused on the study of lineage-specific traits as a strategy to identify novel factors that might be
inherently and distinctively altered in melanoma. Mining of multi-tumor gene expression data sets
identified a cluster of lysosomal genes that is uniquely enriched in melanoma cells and that distinguishes
this tumor type from over 35 malignancies. Within this cluster, we demonstrated a dependency of
melanoma cells on the GTPase RAB7, which was observed to maintain cell proliferation in a tumor typeselective manner. In contrast to classical melanoma-associated oncogenes such as BRAF, whose
depletion blocks both cell proliferation and invasion, tuning down RAB7 favored the transition to
metastatic stages. RAB7 levels were found to affect melanoma cell phenotype by modulating the fate of
PI3K-driven vesicles, which instead of being directed towards the lysosome for degradation,
accumulated and were diverted into secretory pathways when RAB7 expression was tuned-down. The
outcome of derailed RAB7-regulated vesicle traffic translated into melanoma-cell selective changes in
gene expression profiles, cytoskeletal reorganization, and secretion modulators of extracellular
proteolysis and matrix remodeling. Importantly, we found RAB7 to be expressed independently of MITF,
the best known lineage-specific melanoma oncogene known to date. Instead, we identified that,
in melanoma cells, RAB7 levels are controlled by both SOX10, an early driver of the melanocytic lineage,
and PI3K signaling, which is frequently activated during tumor initiation. These results were revealed by
computational methods, live microscopy, histological and functional analyses of human biopsies, cell
lines and mouse models. Moreover, the clinical relevance of these results was demonstrated in followup studies of patient prognosis. Finally, here we demonstrated that tumor-cell specific features of RAB7dependent vesicle traffic have the potential to be exploited therapeutically. Specifically, we found a
novel strategy (based on dsRNA-based nanocomplexes) to promote an efficient self killing of melanoma
cells by inducing a massive mobilization of autophagosomes, endosomes, and lysosomes, and the
subsequent activation of apoptotic caspases. Together, the results of this PhD thesis underscore a
unique lineage-restricted wiring of endolysosomal pathways that actively contributes to melanoma
progression and serves as a tractable vulnerability that can be pursued for drug development.
21
Summary
22
Summary
Resumen
23
Resumen
24
Resumen
El melanoma se describió por primera vez como una entidad tumoral en 1806, y desde entonces, se
mantiene como ejemplo de neoplasia agresiva, heterogénea y quimiorresistente. A pesar de avances
notables en la compresión de las bases moleculares de la progresión del melanoma, no se dispone de
biomarcadores con suficiente valor pronóstico. Del mismo modo, no existe un consenso sobre los
mecanismos que subyacen al proceso de metástasis, ni se han desarrollado tratamientos eficaces para
las fases avanzadas de la enfermedad. Por todo ello, esta tesis doctoral se ha centrado en: (1) identificar
nuevos genes esenciales para el desarrollo del melanoma, (2) definir su regulación y su función en la
progresión tumoral, y (3) utilizar esta información para el desarrollo de nuevas estrategias terapéuticas.
En particular, nos centramos en el estudio de características específicas de linaje celular con el fin de
identificar nuevos factores pro-oncogénicos inherentes al melanoma. El análisis de perfiles de expresión
génica de diversos tipos tumorales reveló que las muestras de melanoma presentan un enriquecimiento
selectivo de genes codificantes de proteínas lisosomales, que distingue a este tipo de cáncer de más de
otros 35 tipos tumorales distintos. Dentro de esta huella genética, identificamos la GTPasa RAB7 como
un nuevo gen esencial para el mantenimiento de la capacidad proliferativa de estas células tumorales. A
diferencia de “oncogenes” clásicos como BRAF, cuya inactivación inhibe tanto la proliferación como la
invasión tumoral, la reducción en los niveles de RAB7 favorece la transición a estadios metastásicos.
Encontramos que esta doble función oncogénica de RAB7 se debe a su capacidad para regular el destino
final (degradación o reciclaje) de vesículas citoplasmáticas inducidas por rutas oncogénicas que activan
PI3K. La desregulación de tráfico vesicular controlado por RAB7 produce cambios globales en los perfiles
de expresión génica de las células de melanoma, afectando a genes implicados en rutas de señalización
clave en cáncer. Además, afecta al citoesqueleto y la secreción de factores involucrados en la
remodelación de la matriz extracelular. Por otro lado, determinamos que RAB7 se expresa y actúa de
manera independiente de MITF, el oncogén específico de melanoma mejor conocido hasta el momento.
En cambio, demostramos que la expresión selectiva de RAB7 en las células de melanoma está
controlada específicamente por SOX10, el factor más apical en la diferenciación melanocítica, y por la
vía de señalización de PI3K, activada frecuentemente durante la iniciación tumoral. El papel de RAB7 en
la progresión del melanoma se determinó mediante estudios en líneas celulares humanas, biopsias
clínicas y modelos animales. Además, la relevancia clínica de estos datos se determinó en estudios de
seguimiento a 10 años, en los que se demostró que los niveles de expresión de RAB7 determinan el
riesgo de desarrollo de metástasis en pacientes. Finalmente, demostramos que las rutas de tráfico
vesicular dependientes de RAB7 que están específicamente activadas en células tumorales pueden
constituir nuevas dianas terapéuticas. En concreto, desarrollamos una estrategia (basada en
25
Resumen
nanopartículas de ARN de doble cadena) para inducir la autodestrucción de las células tumorales a
través de la movilización de macroendosomas, autofagosomas y lisoaomas, y la posterior activación de
caspasas apoptóticas. En conjunto, los resultados de esta tesis doctoral han revelado una regulación y
activación de la maquinaria endolisosomal que se establece de forma específica en el melanoma,
contribuyendo a la progresión de esta enfermedad y que, por otro lado, también confiere una
vulnerabilidad a las células tumorales que puede ser explotada con fines terapéuticos.
26
Summary
Introduction
27
Resumen
28
Introduction
1. THE MELANOMA CHALLENGE: WHERE ARE WE NOW?
Malignant melanoma is a cancer that arises from specialized pigment-producing cells, the melanocytes,
which predominantly reside in the skin1. This tumor type is characterized by having an intrinsic capacity
to metastasize2, 3 and an unyielding resistance to chemotherapy4. Thus, despite accounting for only a
small proportion of skin cancer cases (less than 5%), melanomas are responsible for over 80% of skin
cancer related deaths5, 6. During the last 30 years, the number of new melanoma cases has strikingly
increased worldwide5, 7, 8, becoming an unsolved public health problem in many parts of the globe9. In
the USA, 1 in 35 men and 1 in 54 women are expected to develop melanoma during their lifetime, a
probability that places this tumor type as the fifth and seventh most frequently occurring cancers in
males and females, respectively5.
The increasing incidence and persistent resistance of melanoma to treatment has sparked many efforts
aimed at elucidating the etiology and pathogenesis of this disease, as well as developing improved
therapies. To date, these efforts have resulted in important scientific milestones (reviewed in 10). These
range from comprehensive genomic analyses11-13 to the discovery of new promising antitumoral drugs1416
. In addition, early detection and prevention campaigns have effectively increased awareness about
this disease, consequently improving patient survival in countries with high-incidence rates, such as
Australia, the United States, and Northwestern Europe17-19.
Despite this extensive scientific progress,
melanoma is still a paradigm of aggressiveness
in human cancer. So far, this tumor is only
curable by surgical resection at very early
stages5, and the median overall survival of
patients
with
metastatic
disease
rarely
surpasses one year16, 20-22. Genetic complexity12,
histopathological and biological heterogeneity23,
24
, and the inherent ability of melanoma cells to
circumvent emerging targeted therapy16,
are
some of
the
main challenges
25, 26
that
complicate the attainment of a cure for
Fig. 1 Age-adjusted Melanoma Death Rates per Sex,
European Union, 1975 – 2006. Rates per 100,000
population. Source: Ref. 27
29
Introduction
metastatic melanoma. Consequently, and in contrast to most cancer types (which have shown
decreasing mortality rates during the last three decades), melanoma remains one of the few exceptions
currently exhibiting an increasing trend in mortality (Fig. 1), especially among Caucasian individuals of 50
years of age and older5, 27. The challenge, therefore, persists.
2. THE CELL OF ORIGIN OF MELANOMA: THE MELANOCYTE
Melanomas arise from the malignant transformation
of melanocytes. These cells are located primarily in
the skin1, the largest organ of the human body28 . As
depicted in Fig. 2, the skin is comprised of three main
layers: i) the outer layer, the epidermis, mostly
composed of keratinocytes; ii) the middle layer, the
Fig. 2. The skin
architecture. At
the top, the
close-up shows
melanocytes in
the basal layer
of the epidermis,
surrounded by
keratinocytes
(basal cells)
dermis, containing fibroblasts, immunocompetent
mast cells and macrophages, and structures such as
blood and lymph vessels, hair roots and sweat glands;
and (iii) the most inner layer, the subcutaneous layer,
mostly composed of fatty tissue29-31. Specifically,
melanocytes reside along the basal layer of the
Source: National
Cancer Institute
website
(http://www.can
cer.gov)
epidermis and in the hair follicles32. Through dendritic
projections, each melanocyte establishes contacts with about 36 keratinocytes, forming the so-called
epidermal-melanin unit29, 33.
Epidermal and follicular melanocytes derive from highly motile neural crest progenitors that migrate to
the skin during early embryonic stage34. Once differentiated, melanocytes are the manufacturers of
melanin pigment, which they transfer to neighbouring keratinocytes within specialized membranebound organelles termed melanosomes29,
35
. By producing and delivering melanin to keratinocytes,
melanocytes provide photoprotection, thermoregulation, and the visible pigmentation of the skin and
hair. More importantly, as melanin functions as an absorptive pigment, melanocytes provide protection
against ultraviolet (UV) damage to the skin and the underlying tissues36, 37. The function and survival of
melanocytes is highly dependent on neighbouring cells (such as epidermal keratinocytes and dermal
fibroblasts) as well as on external signals from the environment (such as UV irradiation)38, 39. Alterations
30
Introduction
of these cutaneous melanocytes can give rise to benign and malignant proliferative disorders (nevi and
malignant melanoma, respectively) as detailed in the following section.
In addition to the skin, melanocytes can also be found in extracutaneous tissues of the body, such as
pigmented tissues of the eye40, the leptomeninges41, the inner ear42,
44
respiratory, gastrointestinal and genitourinary tracts , and the heart
45, 46
43
, mucosal surfaces from
. Malignant transformation of
these melanocytes results in noncutaneous forms of melanoma, which account for about 5% of all
malignant melanocytic tumors47. These include ocular melanomas48, leptomeningeal melanomas49, and
mucosal melanomas50, 51, among others. The anatomic location of melanocytes is emerging as a key
factor that defines developmental patterns, morphology, function, and gene expression profile in these
cells23,
32
. Consequently, the impact of the anatomic location on the epidemiological, clinical,
histopathological, and genetic differences between cutaneous and noncutaneous melanomas is
currently being studied23.
3. CLASSIFICATION OF CUTANEOUS MELANOCYTIC LESIONS
Cutaneous melanocytic tumors encompass a variety of lesions that display a heterogeneous spectrum of
clinical, histopathological and molecular presentations. As this heterogeneity can be observed even at
the early onset of the lesions, melanocytic tumors have been classified into multiple subtypes23, 52, 53.
3.1. BENIGN MELANOCYTIC LESIONS: NEVI
Nevi (commonly known as moles) are indolent clonal proliferations of melanocytes6, 52. Although there is
still no universal consensus on a coherent classification scheme for nevi54-56, the conventional system
grossly divides nevi according the time of onset (congenital or acquired) and histopathology (junctional,
compound, or dermal)57. Congenital nevi are those present at birth, or that appear shortly thereafter58.
Acquired nevi, in contrast, start to appear after 6th months of age, and increase in number until a peak
during the third decade of life59. These can be subdivided into junctional, dermal, and compound nevi,
according to the histologic location of the melanocytic nests within the skin: in the dermal-epidermal
junction, in the dermis, or both in the epidermis and the dermis, respectively57,
59
. Junctional or
compound acquired nevi exhibiting architectural and cytological atypia are termed dysplastic nevi52, and
they often occur in a familial manner60. These and other clinical and histopathological criteria are the
31
Introduction
basis
of
the
current
World
Health
Clinicopathologic
subtype of nevi
Organization (WHO) classification of benign
Most commonly
mutated oncogene
nevi, which recognizes different categories,
such as common acquired nevi, congenital
nevi, spitz nevi and blue nevi, among others52
Common
acquired
BRAF
Spitz
HRAS
Congenital
NRAS
(see examples in Fig. 3). Importantly, it has
been demonstrated that the clinicopathologic
heterogeneity of nevi correlates with the
presence of activating mutations in specific
oncogenes (Fig. 3)61-66.
These activating
mutations are also found in malignant
Blue
GNAQ
melanoma. However, in the case of benign
nevi, operant senescence pathways (see
section 4) are thought to prevent malignant
Fig. 3. Representative subtypes of nevi and their most
frequently mutated oncogene. Sources: Refs. 61-66
transformation of melanocytes.
The distinction of different types of nevi is clinically relevant for various reasons. First, most nevi remain
benign for decades67. However, specific subtypes, such as dysplastic or large congenital nevi are
considered to be potential precursors of melanoma68-72 and mark individuals with an increased risk of
melanoma development73-77. Nevertheless, the extent to which melanocytic nevi can transform into
melanoma cells is controversial60, 78. Secondly, nevi can be pathologically complex and mimic histological
features of melanomas, therefore resulting in misdiagnosis. In fact, misdiagnosis of melanoma is the
second most common reason for cancer malpractice claims in the United States79-82. Therefore, main
efforts in the field are oriented to define and validate molecular biomarkers that accurately distinguish
benign nevi from malignant melanomas83-85.
3.2. MALIGNANT MELANOCYTIC LESIONS: MELANOMA
Melanomas are the result of malignant transformation of melanocytes1, 6. Since their first description as
an independent disease entity by Dr. René Laennec in 180686, 87, it has become clear that melanomas
are, in fact, markedly heterogeneous23, 53, 88. For decades, clinical and histological features have been the
basis for melanoma classification23, 53. Currently, with the advent of molecular profiling techniques,
32
Introduction
these classification schemes are being redefined89. An overview of different classifications of melanoma
is presented below.
Clinicopathological classification
The site of presentation and histologic growth pattern have been traditionally used to classify cutaneous
melanomas into four major subtypes: superficial spreading, lentigo malignant, acral-lentiginous, and
nodular melanomas90-94. Table S1 (Appendix) shows the key defining clinical and histopathological
features of these melanoma subtypes. The WHO classification52 includes these frequent melanomas and
more uncommon ones: namely, desmoplastic melanoma95, naevoid melanoma96, melanomas arising
from a blue naevus97, melanomas arising in a congenital nevi98, melanoma of the childhood99, and
persistent melanoma100, all of which differ in their specific clinical and/or histological presentation.
It was originally suggested that the major subtypes of cutaneous melanoma were associated with
characteristic biologic behaviors and different patient outcomes91-93. However, more complex analyses
of larger datasets demonstrated no significant difference in overall survival between subtypes when
tumors of equivalent thickness were compared101, 102. Consequently, most, if not all, current guidelines
for melanoma staging and treatment are
formulated as if it were a single disease
entity23,
below,
Clinicopathologic subtypes
of melanoma
103, 104
. However, as detailed
classification
schemes
for
melanoma are currently being redefined
and are expected to gain significant
Superficial spreading
melanoma
BRAF 59-78%
NRAS 3-22%
Lentigo maligna
melanoma
BRAF 40-60%
KIT 16-28%
NRAS 15-29%
Acral melanoma
BRAF 12-23%
KIT 9-36%
NRAS 8-15%
Nodular melanoma
BRAF 43-68%
NRAS 12-31%
Uveal melanoma
GNAQ 50%
KIT 1-76%
Mucosal melanoma
KIT 15-39%
NRAS 5-15%
BRAF 3-11%
clinical relevance in the coming years.
Emerging clinicogenetic classifications
Comprehensive genomic studies
11, 105-108
have revealed that distinct genomic
profiles do in fact associate well with the
classical
clinicopathological
features
distinguished above; specifically, with the
anatomical site of presentation and the
Commonly
mutated oncogenes
Fig. 4. Melanoma clinicopathologic subtypes and their most
109
frequently mutated oncogenes. Adapted from Ref.
33
Introduction
degree of sun damage. A brief summary of some of the most commonly mutated genes found in each
melanoma subtype is depicted in Fig. 4109. These genomic studies have been highly relevant from a basic
and translational point of view. They have provided molecular evidence supporting the long-suspected
heterogeneity of the clinicopathological melanoma subtypes, setting the basis for the recognition of
putative divergent routes for melanomagenesis thought to result from a complex relationship between
melanoma and sun exposure23,
110, 111
.
In addition, these studies have led to the redefinition of
melanoma classification schemes, which are expected to gain significant relevance in the clinical
management of future melanoma patients23, 88, 89, 112-114. The precise number of clinicogenetic melanoma
subtypes and their definitive defining criteria are still, however, under determination23, 115, and will most
likely evolve along with the development of additional technological advances and emerging concepts.
4. DEVELOPMENT AND PROGRESSION OF MELANOCYTIC LESIONS
Despite the great progress made in the clinicopathologic and molecular classification of malignant
melanoma, it is clear that even within each subgroup, lesions can display notable intra- and inter-tumor
heterogeneity116. As presented below, this additional level of melanoma heterogeneity has important
biological and clinical implications as it derives from, but also fosters, cancer progression117-120.
4.1. HISTOLOGIC, BIOLOGIC AND GENETIC FEATURES ASSOCIATED WITH MELANOMA
PROGRESSION
Cancer progression has been conceptualized as a multistep process whereby normal cells accumulate
genetic alterations that enable tumor growth and metastatic dissemination121.
In the case of melanocytic neoplasia, different histologic lesions are thought to reflect different steps of
this process6, 122, 123. This was first recognized by Dr. Clark and colleagues in the mid 1980´s, proposing a
landmark model for melanoma progression comprised of five different clinicopathologic steps: i) benign
nevus, characterized by an increased number of nested melanocytes; ii) dysplastic nevus, a benign
lesion with random and discontinuous cytologic atypia; iii) radial-growth phase (RGP) melanoma, a
malignant lesion in which tumor cells grow restricted to the epdiermis; iv) vertical-growth phase (VGP)
melanoma, defined by the presence of nodular dermal invasion; and v) metastatic melanoma,
distinguished by the presence of melanoma cells growing at sites different from the site of origin122.
34
Introduction
The traditional multi-step model for melanoma progression
Normal Skin
implies a transition from a benign (nevi) to malignant
(melanoma) lesion6,
122
. However, this concept has raised
controversy60, 78, as up to 80% of melanomas lack histological
signs of a pre-existing nevus69, 124-128. This has prompted the
Dysplastic
Nevus
Bening Nevus
definition of a revised model for melanoma progression (Fig.
5)129, 130, which theorizes melanoma as developing de novo,
i.e. directly from normal melanocytes or precursor cells,
?
RGP
?
although the contribution of melanocyte stem cells or nonpigment producing melanoblasts to melanomagenesis
remains poorly characterized131, 132.
VGP
Despite this controversy, and as detailed below, it has been
widely demonstrated that nevi, RGP, VGP, and metastatic
melanomas
reflect
distinct
molecular
and
biologic
characteristics associated with the malignant and metastatic
potential of melanocytic tumors6, 123, 133.
Metastatic
Melanoma
Fig. 5. Models for melanoma progression.
Adapted from Ref. 130
Nevi and melanocyte oncogene-induced senescence (OIS)
As mentioned above, nevi are the benign counterpart of melanomas6, 123, 130, 134. They harbor activating
mutations in oncogenes such as BRAF, NRAS, or HRAS66, but their malignant degeneration is thought to
be prevented by the activation of fail-safe mechanisms, the best characterized being oncogene-induced
senescence (OIS)67, 135, 136. OIS was described and proposed as a barrier to tumorigenesis more than a
decade ago, in a study in which the overexpression of oncogenic HRAS was found to trigger an
irreversible arrest in primary human and rodent fibroblasts137. This premature form of senescence is
mediated by tumor suppressor pathways, primarily p16(INK4a)/Rb and p19(ARF)/p53/p21 (reviewed in
ref.
138
). Not surprisingly, these pathways are commonly inactivated in many cancer types, including
melanoma135,
139
. Dysplastic nevi, classically considered precursors of melanoma6,
60, 122
forms of melanoma67 also harbor genetic aberrations in these tumor suppressor pathways.
35
, and familial
Introduction
Ultimately, OIS induces phenotypic and molecular changes that have come to be regarded as “markers”
of the process, and have been instrumental in identifying novel tumor suppressors and oncogenes135, 140,
141
. These changes include: senescence-associated β-galactosidase activity (SA-β-Gal); morphological
changes; increased expression of p16, ARF, p21 or p53; senescence-associated heterochromatin foci
(SAHF); DNA damage; decreased Ki-67 proliferation marker; and the absence of gross telomere
shortening, among others67, 135, 142.
Studies in human cells, and in mice and fish in vivo, have reinforced the concept of active OIS blunting
the transformation of melanocytes143-145.
136, 144-149
. Curiously, the expression of oncogenic BRAF, HRAS,
and NRAS in primary human melanocytes triggers distinct types of OIS143, 150. For example, OIS driven by
HRAS (and not by BRAF) is associated with a massive cytosolic vacuolization (see Fig. 6) and an induction
of the Unfolded Protein Response (UPR), an adaptive intracellular signaling pathway that responds to
metabolic stress, oxidative stress, and inflammatory response pathways (reviewed in
151 143
) . Moreover,
different from other human and murine cells, p53, p21CIP/WAF, p16INK4A, and p14ARF are not essential
drivers of OIS in melanocytic cells152.
Normal
HRASG12V
BRAFV600E
Fig. 6. Differential OIS programmes
induced by HRASG12V and BRAFB600E
in primary human melanocytes. Both
oncogenes result in the induction of
positive SA-β-Gal staining (bue), but
BRAFV600E-expressing melancoytes do
not exhibit the characteristic cytosolic
vacuolization of their HRASG12V
143
counteraparts. Adapted from Ref.
Importantly, human nevi can manifest features of OIS, such of SA-β-Gal, giant and multinucleate cells,
decreased levels of the proliferative marker Ki67, and high levels of p16136,
144-149
. However, the
specificity of the association of some of these OIS markers to benign, but not malignant, melanocytic
tumors has been debated145,
153-156
. This raises the need to better define bona fide markers of
senescence in vivo78. These definitions could hopefully serve as the gold standard for the correct
distinction between nevi and melanomas. Moreover, the precise genetic determinants of the different
subtypes of nevi have yet to be determined.
36
Introduction
RGP melanoma and tumor initiation
One of the early events in the pathogenesis of melanoma is the activation of the mitogen-activated
protein kinase phosphatase (MAPK) and/or phosphoinositide-3 kinase (PI3K) pathways (mainly by
mutations in BRAF or NRAS but also in upstream receptor tyrosine kinases such as KIT or ERBB4)157, 158 .
However, activation of these pathways is not sufficient to promote the malignant transformation of
melanocytes159, 160. The development of radial growth phase (RGP) of melanoma requires the acquisition
of additional genetic mutations by melanocytes, that prevent or bypass the OIS barrier, and/or
cooperate in malignant transformation161. Via these additional genetic aberrations, RGP melanoma cells
acquire the ability to actively proliferate; however, they do so within the epidermis because they are still
keratinocyte-dependent for survival and are not yet tumorigenic nor invasive6.
The identification of the genetic combinations that synergize with oncogenic BRAF or NRAS to
successfully promote melanoma initiation has been the subject of active investigation in the last decade.
Extensive research using in vitro and/or in vivo experimental models of melanomagenesis has yielded
the identification of a handful of initiating genetic alterations, mainly the loss of tumor suppressors such
as CDKN2A162, 163, PTEN164-166, TP53167, 168, RB1168 or NF1169, and the activation of additional oncogenes,
such as AKT3170 and MITF171, shown to cooperate with oncogenic BRAF in the malignant transformation
of melanocytic cells. Importantly, these driving genetic aberrations have been identified in human
melanoma biopsies, albeit at different relative frequencies160 (see Table 1 in section 5). Still, the onset
and underlying mechanisms driving these molecular changes are not yet completely understood172-175.
For example, PTEN loss has been shown to promote both initiation and metastatic progression in
experimental melanoma models164-166, 176, 177. However, it is not clear whether PTEN loss is an early or
late event in human melanomas12, 175, 178, 179. Thus, there is a remaining need to better delineate the
increasing list of melanoma tumor suppressors and oncogenes within the initiation and/or progression
of the human disease.
VGP melanoma and the acquisition of the competency to metastasize
During the vertical growth phase (VGP), melanoma cells acquire the competency to invade. They
become immortal and tumorigenic, can escape from the anchorage to surrounding keratinocytes, and
37
Introduction
invade the basement membrane to grow intradermally. There, melanoma cells can induce angio- and
lymphangiogenesis and intravasate into the lymphatic or blood circulation. The acquisition of these
functional capabilities has been associated with decreased differentiation119, downregulation of proapoptotic genes180, or aberrant expression of miRNAs181, 182. Other events involve the deregulation of cell
adhesion and matrix remodeling factors, such as loss of E-cadherin and overexpression of N-cadherin,
matrix metalloproteinase-2 (MMP-2), cathepsins, integrin αVβ3, and the carcinoembryonic antigenrelated cell adhesion molecule 1 (CEACAM1), among others6, 183-185. VGP melanoma cells can also secrete
angiogenic factors–mainly vascular endothelial growth factors (VEGFs), fibroblast growth factor-2 (FGF2), Interleukin (IL) -8, and transforming growth factors α and β (TGF-α and β) –that function in
cooperation with receptors for extracellular matrix, integrins, and MMPs186. In addition, VGP melanoma
cells can also promote metastasis by interaction with stromal and immune cells (mainly fibroblasts,
macrophages, mast cells, and endothelial cells), directly through cell-cell contacts and also by secretion
of soluble factors and extracellular matrix molecules187,
188
. Melanoma cells also promote cancer
progression by blocking the anti-tumor immune response of immune cells residing in or recruited to the
different
stages
progression
transition
of
(Fig.
7)
between
Skin
VGP
RGP
Nevus
Primary
(TMA) analyses performed along the
Nevus
gene expression and tissue microarray
Skin
Interestingly, several high-throughput
Metatasis
tumor microenvironment189, 190.
melanoma
highlight
thin
and
the
thick
primary melanomas as the point of
greatest molecular change180,
These
studies
have
also
191-195
.
been
fundamental to identify the epithelial-tomesenchymal (EMT) transition as a
major
determinant
of
melanoma
progression196. However, the number of
clinically validated biomarkers of disease
progression is still limited
83, 197
.
Fig. 7. Examples of high-throughput gene expression (left) and
TMA (right) analyses at different stages of melanoma
progression. Sources: Ref. 192 (left) and Ref. 195 (right)
38
Introduction
Metastatic melanoma and the colonization of distal tissues
In the last step of melanoma progression, termed metastatic melanoma, circulating tumor cells can
successfully extravasate, survive, and colonize distal locations6, 198. The most common sites of regional
metastasis are nearby skin, sub-cutaneous tissue, and lymph nodes, while distant metastases involve the
skin, lung, brain, liver, bone, and intestine199. Recent evidence has demonstrated that primary
melanoma tumors send signals (i.e. small vesicles named exosomes200, 201 or soluble factors like VEGFC202,
203
) to optimize the conditions for tumor cell recruitment, extracellular matrix deposition, and
vascular proliferation at distal sites, preparing the so-called “pre-metastatic niche”204.
4.2. INTRATUMOR HETEROGENEITY AND MELANOMA-CELL PLASTICITY
Despite great advances in the histologic, biologic, and molecular characterization of the distinct steps of
melanoma progression, the understanding of the mechanisms that ultimately drive this process forward
remains incomplete. The fact is that neoplasms, and melanomas are no exception, are not static
entities117. In the classical view, melanoma progression was understood as a one-way, linear process
resulting from the irreversible accumulation of genomic, genetic, and epigenetic aberrations that
conferred a survival advantage for tumor cells6, 123. This scenario has become more complex in light of an
emerging body of evidence that uncovers tumor-cell plasticity and intratumor heterogeneity, two
closely related phenomena that result from and drive cancer progression117. Thus, new models of
melanoma progression recognizing this complexity are currently under discussion119, 205.
The phenotype switch model suggests that melanoma progression –and its associated phenotypic
heterogeneity– is driven by distinct gene expression programmes imposed by a changing
microenvironment206-208. This model stemmed from various gene-expression studies performed in
melanoma cell lines and tissue biopsies (reviewed in Ref191) that reported the existence of two distinct
subpopulations of melanoma cells: one characterized by high expression of melanocytic lineagespecification genes and proliferation promoting factors (the so-called “proliferative” signature); and the
other by a low expression of these genes and high expression of genes involved in invasion and
microenvironment remodeling (the so-called “invasive” signature). In addition, functional studies
showed that these two gene expression signatures correlate well with the metastatic209-211 and
chemoresistant212 capacities of melanoma cells. Importantly, while melanoma cells seem to exhibit a
characteristic transcriptional profile when cultured in vitro191, 209, it has been shown that, in vivo, they
39
Introduction
can dynamically switch back-and-forth between these two differentiation or biologic states206, 208. This
has been visualized in real time by intravital imaging of melanoma allografts in nude mice213. This
phenotype switch model is consistent with EMT-like gene expression patterns that several molecular
profiling studies have reported for genes involved in melanocyte differentiation (e.g. MITF, BRN2),
proliferation (e.g. Cyclin D1), and invasiveness (e.g. GLI2, WNT5A)192, 195, 196, 214, 215. Specifically, during the
RGP-to-VGP transition, pro-invasive genes were found to be increased and differentiation and
proliferation genes decreased; these changes were found to be found reverted in distal metastases192,
195, 196, 214, 215
. Among the “oscillating” genes reported, the transcription factors MITF, GLI2, and BRN2
have been proposed as the mediators of the profound gene expression changes that accompany
melanoma progression216-218.
An alternative model for melanoma development involves cancer stem cells (CSCs). CSCs have been
defined as a subpopulation with long-term survival, high self-renewal tumorigenic capacities, and, most
notably, the ability to generate phenotypically diverse, non-tumorigenic progeny24,
206, 219
. Thus,
according to the CSC model, intratumor heterogeneity is hierarchically organized and epigenetically
controlled220. However, both the existence and exact nature of CSCs in melanomas have been
controversial. While some studies have proposed a specific and rare subpopulation as the driver of
melanoma growth and metastasis221-223, others have reported that, in fact, most melanoma cells have
the ability to initiate tumors and recapitulate intratumor heterogeneity24,
224
. More reliable CSCs
markers225 and experimental protocols117 might help to clarify the current understanding of CSCs in
melanoma progression. In this context, an emerging concept is that stemness might not be a fixed
property. Instead, dynamic and reversible changes in the expression of putative CSC melanoma markers
have been demonstrated. For example, melanoma CSCs marked by JARID1B expression have been
shown to be a dynamically changing subpopulation resulting from the phenotypic switching of more
“differentiated” melanoma cells205, 226. In addition, the expression of OCT4, a stemness gene227 recently
found to control melanoma progression, has been also shown to be dynamically regulated in a hypoxiadependent manner228.
Despite the controversy regarding the source of intratumor heterogeneity and the drivers of melanoma
cell plasticity, the hope remains that further understanding of these phenomena will result in
improvements in melanoma patient care229. In addition, the recognition of the phenotypic complexity of
melanoma tumors has opened new exciting avenues of research, such as the identification of its
40
Introduction
molecular regulators, the understanding of the contribution of the tumor microenvironment, and its
implications in the response to targeted chemotherapy207, 230, 231. However, a unifying model–one that
reconciles the different views of melanoma progression and frames them within the currently accepted
models of cancer evolution in general232–is pending.
5. ONCOGENES AND “NON-ONCOGENE” DEPENDENCIES IN MELANOMA
In light of the genetic complexity and phenotypic plasticity of melanoma, one of the most challenging
and active areas of research in the field involves identifying tumor dependencies (i.e. genes or pathways
that are specifically required for tumor maintenance).
Multiple melanoma oncogenes have been identified to date (see below in Table 1), and have set the
basis for the emerging era of personalized medicine in melanoma. Additionally, deregulation of
pathways related to cellular energetics and metabolism have been recently demonstrated as additional
points of vulnerability for tumor cells that could also be exploited therapeutically233. These pathways are
not inherently oncogenic themselves, but have been shown to be essential in supporting the oncogenic
phenotype of tumor cells, an intriguing idea that has been recently termed “non-oncogene
addiction”233. The next section summarizes the key melanoma oncogenes and “non-oncogene
addictions” described in melanoma.
5.1. MELANOMA ONCOGENES: “CLASSICAL” VERSUS “LINEAGE-SPECIFIC” FACTORS
As shown in Table 1, the majority of melanoma oncogenes function either by activating the MAPK
and/or PI3K pathways (e.g. BRAF, NRAS, ERBB4 or AKT3), or by deregulating cell cycle check-points (e.g.
CCND1 or CDK4). These factors suffer activating genetic aberrations which are frequently shared among
different tumor types160 and have been termed “classical oncogenes”234.
A less characterized type of tumor dependency in melanoma relates to lineage-specific genes. These
genes are required for the survival and differentiation of normal precursor cells, but can be “hijacked”
by tumor cells to favor cancer initiation and/or progression. This newly-recognized kind of dependency
has been termed “lineage addiction/dependency“, and does not necessarily involve the acquisition of
activating genetic mutations234, 235.
41
Introduction
Gene
Alterations
Frequency
Pathway affected
BRAF
Poi nt mutation
50%
MAPK
NRAS
Poi nt mutation
20%
MAPK, PI3K
ERBB4
Poi nt mutation
15-20%
MAPK, PI3K
KIT
Poi nt mutation
1% overa l l (10% a cra l
l entigi nous , 10% mucos a l )
MAPK, PI3K
AKT3
Ampl i fi ca tion
25%
PI3K
CCND1
Ampl i fi ca tion
10%
Cel l cycl e
NEDD9
Ampl i fi ca tion
50-60%
Sca ffol d protei n
(Integri n β3 a nd Src*)
CDK4
Poi nt mutation or
a mpl i fi ca tion
5%
Cel l cycl e
MITF
Ampl i fi ca tion
20%
Mel a nocyte l i nea ge
ETV1
Ampl i fi ca tion
15%
MITF
PTEN
Ampl i fi ca tion
50-60%
PI3K
TP53
Ampl i fi ca tion
Poi nt mutation or
del etion
5%
Cel l cycl e
30%
Cel l cycl e
Ki na s es or s i gna l i ng fa ctors
Tra ns cri ption fa ctors
Tumor Suppres s ors
CDKN2A/p16
Table 1. Melanoma Oncogenes and Tumor Suppressors. Adapted from Ref. 160, and from Ref. 235
The best characterized melanoma lineage-specific oncogene is the microphthalmia-associated
transcription factor (MITF). MITF acts as a master regulator of melanocyte development, function, and
survival by inducing the transcription of differentiation and pigmentation genes (e.g. TYR, RAB27), and
proliferation and anti- apoptotic factors (e.g. BCL2, CDK2)234, 236-239. The expression and activity of MITF is
tightly controlled upstream by key regulatory pathways involved in melanocyte commitment from
neural crest stem progenitors. Specifically, MITF is subjected to: i) transcriptional regulation by PAX3 and
SOX10, and ii) signaling regulation predominantly by Wnt/β-Catenin, melanocortin-1 receptor (MC1R),
and KIT signaling pathways240,
241
(Fig. 8). Interestingly, many of the factors regulating MITF also
contribute to melanoma maintenance or progression (i.e. WNT242, KIT243, NRAS106, BRAF244, PAX3245-247,
and SOX10248, 249)160, 241, 250. Similarly, pro-oncogenic functions have been also been demonstrated for
certain downstream targets of MITF, namely RAB27251 and BCL2A1252.
42
Introduction
MITF has long been known for its critical roles in melanocytic cell biology253,
254
. However, the
recognition of MITF as a melanoma oncogene in melanoma stemmed, in fact, from a multi-tumor
comparison of genomic aberrations across different cancer types171. MITF was found to be specifically
amplified in melanoma cell lines and essential for melanoma proliferation. However, MITF amplification
was found to occur in only 20% of melanoma biopsies, most of which were metastatic and lead to poor
survival prognosis171. Moreover, it has been shown that MITF expression can be silenced by different
inhibitory mechanisms216,
melanomas
257
255, 256
, as it is commonly found to be downregulated in advanced
(except in those in which MITF is amplified257,
primary tumors
214, 257
and melanoma cell lines
216, 217
258
). In fact, these low-MITF expressing
are, surprisingly, highly invasive and metastatic. The
recognition of these opposing roles for the lineage-specific transcription factor MITF (i.e. required for
tumor cell survival/proliferation but promoting invasiveness when tuned-down) has expanded the
prevailing notion–that oncogenes are typically hyperactivated and sustained along tumor progression–
to a framework that includes not only the usurpation of developmental pathways in cancer2, 234 , but also
their dynamic regulation to favor metastatic dissemination217, 259. Whether additional lineage-specific
oncogenes exist, acting beyond the MITF transcriptional program and favoring melanoma progression, is
unclear.
Fig. 8. The MITF regulatory axis in melanocytic cells. Source: Ref.
43
160
Introduction
5.2. NON-ONCOGENE DEPENDENCIES IN MELANOMA: AUTOPHAGY AND BEYOND
In addition to the aforementioned role of “classical” or “lineage”-specific oncogenes, melanoma cells
have also been proposed to become addicted to “non-oncogene” mediators of tumorigenesis.
Autophagy
Macroautophagy (hereafter autophagy) or 'self-eating' has recently emerged as a “non-oncogene”
dependency of melanoma cells. Autophagy is a highly conserved, lysosomal-mediated, catabolic process
whereby damaged organelles and proteins are degraded within double-layered vesicles called
autophagosomes. This process has essential roles in survival, development, and homeostasis260. Thus,
autophagy is constitutively active in most, if not all, eukaryotic cells. Moreover, autophagy can be
hyperactivated under situations of cellular stress including nutrient or growth factor deprivation,
hypoxia, reactive oxygen species, DNA damage, protein aggregates, damaged organelles, or intracellular
pathogens261.
Rapamycin
AUTOPHAGY
mTOR
Phagophore
Autophagosome
LC3 conjugation
ATGs
BECLIN1/VPS34
Class III PI3K
PI3K
Inhibitors
Damaged
organelles or
proteins
RAB7
SNAREs
UVRAG
LAMP1/2
Amphisome
Autolysosome
Chloroquine
Bafilomycin A1
Lysosome
Plasma
membrane
proteins
LYSOSOMAL
DEGRADATION
Hydrolases
Permeases
RAB7
RAB5
Early
Endosomes
Extracellular
material
Late Endosomes
ENDOCYTOSIS
Plasma membrane
Fig. 9. Overview of the autophagic pathway. Examples of factors regulating the early and late stages of autophagy and
endocytosis are marked in blue; and of pharmacological agents modulating the process, in white. Sources: Refs.262 and 266.
44
Introduction
Autophagy is a multi-step and tightly regulated process. Fig. 9 illustrates distinct steps of the process
and its key regulatory factors (marked in blue). The initiation of autophagy involves the nucleation of an
isolation membrane or phagophore. This structure then elongates and closes itself to form the doublemembrane autophagosome, sequestering the cytoplasmic cargo that will be subsequently degraded.
These steps are dependent on so-called autophagy-specific genes (ATG) such as ATG7262, 263, BECLIN1,
and the Class III PI3K (also known as VPS34264), among others, and require the lipidation and insertion of
the LC3/ATG8 protein into the autophagosome8. Next, the formed autophagosome fuses with the
lysosome to form autolysosomes. In most cases, this final step is preceded by a maturation step, during
which the autophagosome receives input from the endocytic pathway (early endosomes, late
endosomes, and multivesicular bodies (MVBs)) and forms the so-called amphisome265. Interestingly,
this late stage of autophagy (maturation and fusion with the lysosomal compartment) depends on
molecular actors that are also involved in the endocytic and/or lysosome biogenesis pathways, such as
small GTPase RAB7266, 267, UVRAG268, and LAMP2269, among others8 (Fig. 9). Consequently, the lysosome
is the major degradation site of eukaryotic cells, not only for cellular proteins via autophagy, but also for
material internalized via the endocytic pathway and coming from the plasma membrane or the
extracellular environment (Fig. 9)270.
Mechanisms regulating autophagy are complex. A main modulator is the mammalian target of
rapamycin (mTOR), a bioenergetic sensor that limits the initiation of autophagy under normal
physiological non-stressful cellular conditionns271. Thus, rapamycin can be used as an experimental tool
to induce autophagosome formation272. Autophagy can also be pharmacologically blocked, both at early
stages (by inhibitors of PI3KC3) or at late stages (by lysosomal inhibitors, such as Chloroquine or
Bafilomycin1273) (Fig. 9). The status of autophagy can be detected experimentally using different
Electron Microscopy
GFP-LC3 aggregation
LC3-I to LC3-II conversion
+
-
-
+
LC3-I
LC3-II
β-Actin
Fig. 10. Commonly used methods for the detection of autophagosomes: Left, electron microscopy imaging of autophagy
induced by cysplatin treatment (source: Ref. 275); middle, fluorescence microscopy of rapamycin--induced GFP-LC3- foci
(source: ref. 276); and right, western blot of LC3-I/II in bafilomycin1-treated cells (source: Ref. 277)
45
Introduction
methods, such as, electron microscopy image analysis, fluorescence detection of GFP-LC3 dots, or
western blot detection of LC3 lipidation, all of which indicate an accumulation of autophagosomes273-276
(Fig. 10).
In cancer, autophagy can display complex and paradoxical roles: it can be pro-277 or anti-278,
279
tumorigenic, and, if modulated by chemotherapy, it can promote survival280 or cell death281, 282. Thus, the
exact role of autophagy in cancer is context-dependent.
In the case of melanoma, it has been proposed as an “Achilles’ heel”283 in light of an increasing body of
evidence demonstrating that melanoma cells actively utilize and, more importantly, become addicted to
autophagy for survival274. Specifically, inhibition of basal autophagic degradation –by either knock-down
of the ATG5 gene or chloroquine treatment– induces melanoma cell death274. Moreover, the
hyperactivation of autophagy by an acidic microenvironment284 or by arginine and leucine deprivation285288
is required for melanoma cells to survive under these stressful growth conditions. In addition to
tumor maintenance, some studies in vitro are suggestive of a pro-tumorigenic role of autophagy in
melanoma cell invasiveness289,
290
; however, histopathological analyses along the distinct steps of
progression in human samples are actually controversial291-293, and this matter requires further
investigation291-293. Finally, in the context of melanoma treatment, preclinical models have unraveled
autophagy as a chemoresistance mechanism that limits the efficacy of several anticancer drugs289, 294-298.
Thus, targeting autophagy, which is mostly done by inhibiting lysosomal degradation, is emerging as a
promising strategy in the fight against melanoma.
It is also becoming clearer that autophagy is a highly dynamic process and that, under specific
circumstances of cellular stress, melanoma cells can mount pro-survival adaptative responses that rely
on the inhibition (not always the activation) of this pathway. Specifically, while being a protective
mechanism in counteracting aminoacid deprivation287, 288, autophagy can also drive melanoma cell death
in the context of glucose deprivation299. This type of death occuring by autophagy (not just with
autophagy) has been termed “autophagic cell death”300, and has also been shown to participate in the
mode of action of certain chemotherapies, such as bortezomib301 and metformin302. In addition,
activation of autophagy has been proposed to increase the efficacy of immunotherapy, particularly at
early stages of melanoma development303, 304. Given these multifaceted roles of autophagy in cancer,
46
Introduction
there is a pending need to better understand the mechanisms that might underlie the contextdependency of this pathway.
Beyond autophagy: an emerging role of vesicle trafficking regulators
Autophagy is just one of the numerous vesicle-mediated pathways that transport proteins throughout
the intracellular space of eukaryotic cells. Additional pathways, namely endocytosis and exocytosis,
exert critical functions in organelle biogenesis and protein transport between intracellular
compartments and to and from the extracellular environment270. Vesicle trafficking is receiving
increasing attention in the cancer field due to its impact on intra-cellular and extra-cellular signaling305307
, yet its contribution to melanoma pathogenesis remains poorly characterized.
Vesicle
trafficking
is
finely
orchestrated by the RAB proteins
(as depicted in Fig. 11), the largest
family of small GTPases, which
function as molecular switches that
alternate
between
two
conformational states: the GTPbound 'on' form and the GDPbound 'off' form308. This switch is
controlled by guanine nucleotide
exchange factors (GEFs), which
trigger the binding of GTP, and
GTPase-activating proteins (GAPs),
which accelerate hydrolysis of the
bound GTP to GDP309,
310
. RAB
proteins also undergo a membrane
insertion
and
extraction
cycle,
which is partially coupled to the
nucleotide cycle311. The ability to
Fig. 11. Localization and function of Rab GTPases as coordinators of vesicle
traffic. Each step of membrane traffic requires a specific RAB protein.
308
Source: Ref.
cycle between GTP- and GDP-bound states and to specifically function at distinct intracellular
47
Introduction
membranes, confer RAB proteins the capacity to temporally and spatially regulate membrane
transport312. Specifically, RAB proteins control each of the four major steps in membrane traffic (namely
vesicle budding, delivery, tethering, and fusion), functions that are carried out by a diverse collection of
effector molecules that bind to specific RABs in their GTP-bound/membrane-bound state311.
RAB proteins are emerging as critical players in cancer. An illustrative example is RAB25, an epithelialcell-specific RAB that has been implicated in various cancer types, yet with reports presenting it both as
an oncogene313-318 and a tumour-suppressor gene319-323. Another example is RAB8, which has been
shown to mediate invasiveness of adenocarcinoma cells through the exocytosis of MT1-matrix
metalloproteinase (MT1-MMP) 324.
Interestingly, recently developed bioinformatic algorithms aiming to predict putative drivers of
tumorigenesis have suggested a promising, yet uncharacterized role, for vesicle trafficking regulators in
melanoma251. In particular, this computational framework revealed frequent genetic aberrations in
vesicle trafficking genes in cultured melanoma cells. Two of these genes (namely RAB27 ,an MITF target
involved in melanosome and exosome transport236, 325; and TBC1D16, a Rab GAP involved in endocytic
recycling326) were empirically demonstrated to be required for the in vitro proliferation of a subset of
melanoma cell lines by mechanisms that need to be further elucidated251. Nevertheless, these results
certainly encourage a more in-depth analysis of the role of vesicular trafficking in melanoma251, 327.
6. TREATMENT OF CUTANEOUS MELANOMA
As with other malignancies, the clinical management of patients with
cutaneous melanoma initially depends on the stage at the time of diagnosis.
Breslow
(mm)
5-year Survival
Rates (%)
The TNM classification (Table S2) and stage grouping of melanoma patients
<1.0
95-100
(Table S3) is based on extensively revised clinical and histopathological
prognostic factors, included in American Joint Committee on Cancer (AJCC)
1.0-2.0
80-96
2.1-4
60-75%
>4.0
37-50%
101
Melanoma Staging Database . The depth of primary tumor invasion (or
Breslow Thickness328) is one of the most relevant histological prognostic
factor for metastatic disease and poor overall survival (Fig. 12)5, 101. Other
clinically relevant predictors of poor prognosis included in the AJCC TNM
Fig. 12. Breslow thickness
and patient prognosis.
Source: Melanoma Research
Foundation
website:
http://www.melanoma.org/
system include: presence of ulceration and mitotic figures in the primary tumor; presence of melanoma
48
Introduction
cells in lymphatic vessels, sentinel lymph nodes or distant organs; and elevated serum lactate
dehydrogenase (LDL) (Table S2)101.
The standard of treatment of localized melanoma is surgical excision with adequate margins. Complete
sentinel lymph node(s) dissection is recommended for patients with involved regional nodes, although
at present, there is no clear survival benefit for this approach329. The only Federal Drug Administration
(FDA) approved effective adjuvant therapy for patients who have undergone a complete surgical
resection, but are considered to be at high risk for relapse, is high dose of pegylated interferon alpha
(IFNα)-2b, which has substantial side effects330. Once melanoma has spread to distant sites, this disease
is rarely curable331. Since 1970 and until very recently, the only standard therapy for patients with
metastatic disease had been dacarbazine. Response rates with this alkylating agent are usually less than
10% and are generally transient332. IL-2 was also approved by the FDA in 1998 on the basis of durable,
long-term, and complete responses. However, this response was seen in only a small proportion (0-8%)
of patients treated and was associated with significant secondary toxicities332. More recently, two new
strategies have widened the therapeutic armamentarium for melanoma. These correspond to (i) a fully
humanized immunoglobulin G1 monoclonal antibody that blocks cytotoxic T-lymphocyte-associated
antigen 4 (CTLA-4) to potentiate an antitumor T-cell response (Ipilibumab)14,
333
; and (ii) a selective
inhibitor of BRAF V600E kinase (Vemurafenib)15, indicated only for those patients with a demonstrated
BRAF V600E mutation by an FDA-approved test331. In addition to these two approved drugs, other
treatment options are under clinical evaluation331. Examples include vaccines against immunogenic
melanoma antigens334-336; immunotherapy targeting PD1 or PDL1160; targeted therapy against KIT, MEK,
PI3K, AKT, NRAS, mTOR, and CDK4160; and several combinatorial approaches160, among many other
strategies. Radiotherapy is employed for symptomatic relief of brain and visceral metastases that cannot
be resected; however, its optimal role in the treatment of melanoma is highly controversial332.
Despite the strategies that have been developed to fight against metastatic melanoma, we have not
attained a curative treatment for patients with metastatic disease and still face several challenges. First,
melanoma cells are intrinsically death-resistant. The precise mechanisms accounting for this resistance
are still unknown, but in part involve a high expression of anti-apoptotic factors (of the Bcl-2 family and
others) inherited from their precursor cells, the melanocytes4, 252. Further rewiring of pro-apoptotic and
survival pathways during tumor progression4, 121 results in increased resistance to cell death. In this line,
the remarkable genetic heterogeneity, stemness properties, and differentiation plasticity associated
with cancer progression have also been proposed to contribute to the therapeutic refractoriness of
49
Introduction
melanoma cells337. Consequently, targeted therapy can only be applied to a fraction of patients who,
unfortunately, eventually relapse due to the acquisition of an array of additional genetic alterations, at a
median interval of 6 months on therapy16, 25. Finally, in the case of immunotherapy, relatively slow
responses, serious side effects, and a lack of response biomarkers compromise its promising clinical
benefits16, 338. With this scenario, new strategies for overcoming the intrinsic and acquired resistance of
melanoma cells are urgently needed.
50
Objetives
Objectives
51
Introduction
52
Objectives
Melanoma encompasses a heterogeneous group of tumors that display an array of distinct
histopathologic, biologic, and molecular features. Despite this variability, melanomas share an inherent
aggressiveness, cell plasticity, and resistance to standard anticancer therapies. Thus, the ultimate goal of
this PhD thesis was to identify novel molecular players involved in melanoma progression and drug
response. As even highly unstable cancers retain features that trace back to the cell type of origin, the
study of lineage-specific traits offers the potential of identifying new pro-oncogenic drivers that could be
inherently and distinctively altered in melanomas.
It is becoming clear that melanoma cells hijack transcription factors and signaling molecules involved in
the development and function of melanocytes. In the case of melanoma, two tissue-specific oncogenes
have been identified to date, namely MITF and its target BCL2A1. However, these oncogenes are
amplified in only a subset (<30%) of tumors. Moreover, the transcriptional program controlled by MITF
is sometimes shut off in advanced stages of the disease. The existence of additional lineage-dependent
oncogenic drivers underlying the different spectrum of melanomas and acting beyond the control of
MITF remains unclear.
Therefore, the specific objectives of this PhD thesis were:
1. THE STUDY OF MELANOMA LINEAGE-RESTRICTED TRAITS FOR THE IDENTIFICATION OF NOVEL
CANDIDATE MELANOMA DRIVER GENES
2. FUNCTIONAL CHARACTERIZATION OF CANDIDATE DRIVER GENES IN MELANOMA PROGRESSION
3. THE IDENTIFICATION AND CHARACTERIZATION OF NOVEL THERAPEUTIC STRATEGIES FOR THE
TREATMENT OF MELANOMA
53
Introduction
54
Objetives
Objetivos
55
Introduction
56
Objetivos
El melanoma abarca un grupo heterogéneo de tumores malignos que muestran una gran variabilidad
histopatológica, biológica y molecular. A pesar de esta heterogeneidad, los melanomas comparten una
inherente agresividad, plasticidad celular y resistencia a las terapias antitumorales convencionales. Por
lo tanto, el objetivo último de esta tesis doctoral era identificar nuevos mecanismos implicados en la
progresión del melanoma y en su respuesta a fármacos citotóxicos. En esta tesis nos centramos en el
estudio de características específicas de linaje celular con el fin de identificar nuevos factores prooncogénicos inherentes al melanoma.
En este sentido, se ha propuesto que las vías de señalización y factores de transcripción involucrados en
la diferenciación y función de los melanocitos desempeñan un papel activo en la progresión del
melanoma. Dos oncogenes específicos de tejido, MITF y su diana transcripcional BCL2A1, han sido
identificados hasta la fecha en melanoma. No obstante, estos oncogenes sólo se encuentran
amplificados en una fracción (<30%) de pacientes. Además, el programa transcripcional regulado por
MITF puede inactivarse en estadios avanzados de la enfermedad. Se desconoce si existen mecanismos
pro-oncogénicos alternativos asociados al linaje celular que actúen de forma independiente de la ruta
de MITF en melanoma.
Por lo tanto, los objetivos específicos de esta tesis doctoral fueron:
1. EL ESTUDIO COMPARATIVO DE LA EXPRESION GÉNICA EN DISTINTOS TIPOS TUMORALES PARA
IDENTIFICAR NUEVOS GENES PRO-ONCOGÉNICOS ESPECÍFICOS DEL MELANOMA.
2. LA CARACTERIZACIÓN DEL PAPEL DE GENES CANDIDATOS EN LA PROGRESIÓN DEL MELANOMA
3. LA IDENTIFICACIÓN Y CARACTERIZACIÓN DE NUEVAS ESTRATEGIAS TERAPÉUTICAS PARA EL
TRATAMIENTO DEL MELANOMA
57
Introduction
58
Objetives
“Ever tried. Ever failed. No matter.
Try again. Fail again. Fail better”.
Samuel Beckett (1906-1989)
Materials and Methods
59
Introduction
60
Materials and Methods
1. CELLS
The human melanoma cell lines (SK-Mel-5, SK-Mel-19, SK-Mel-28, SK-Mel-29, SK-Mel-103, SK-Mel-147,
SK-Mel-173, G-361, UACC-62, Mel-1, WM-164, 1205Lu, WM-1366, Mel1, WM-88, WM-983B, WM-852,
WM-209, WM-793B, WM-902B, WM-278, WM-115, WM-35) and the other human cell lines -T98G
(glioblastoma), U251 (glioma), A549 (non-small cell lung cancer), MiaPaca-2 (pancreatic cancer), RWP1
(pancreatic cancer), PC3 (prostate cancer), SW1710 (bladder cancer), 639V (bladder cancer), HeLa
(cervical cancer), HCT116 (colorectal cancer), HT29 (colorectal cancer), SW480 (colorectal cancer),
SW620 (colorectal cancer), LoVo (colorectal cancer), BT549 (breast cancer), MCF7 (breast cancer), MBAMD-231 (breast cancer). FTC-133 (thyroid cancer), CAL-62 (thyroid cancer), 8505C (thyroid cancer), U20S
(osteosarcoma) and 293FT (transformed human embryonic kidney cells) were cultured in Dulbecco’s
modified Eagle’s medium (Invitrogen; Carlsbad, CA, USA) supplemented with 10% fetal bovine serum
(Lonza, Basel, Switzerland). Primary human melanocytes, fibroblasts and keratinocytes were isolated
from neonatal foreskins (obtained from the Hospital Niño Jesús, Madrid, Spain), and cultured as
described339. Melanocytes were maintained in Medium 254 supplemented with melanocyte growth
factors (HMG-1) containing 10ng/ml phorbol 12-myristate 13-acetate (Invitrogen); fibroblasts were
maintained in 10% FBS DMEM Medium and keratinocytes in Epilife medium (Invitrogen), containing
Human Keratinocyte Growth Supplement (Invitrogen).
2. GENE SET ENRICHMENT ANALYSIS (GSEA) IN MULTITUMOR DATASETS
GSEA340 was performed using annotations from whole-genome Biocarta, KEGG, Reactome and
GenMAPP pathway databases. Genes were ranked using the t statistic. After Kolmogorov-Smirnoff
testing, those pathways showing false discovery rates (FDR) <0.25, were considered enriched between
classes under comparison. Gene Ontology (GO) terms (Biological Process, Cellular Component and
Molecular Function) from level 3 to 19 were also evaluated by GSEA. Additionally, we customized the
data mining including trafficking gene sets annotated according to the InterPro database and published
literature308. GSEA was applied to multi-cancer NCI-60 panel, spanning 60 different human cancer cell
lines across 9 different tumor types using previously reported datasets341, 342. The GSEA findings were
confirmed in the Cancer Cell Line Encyclopedia (CCLE) dataset, spanning 807 samples from different
tumor types343. The GSEA enrichment plots show the running enrichment score (ES, marked in green)
for the indicated gene set as the analysis walks down the ranked list of genes. Also shown is the ranked
gene set, where the members of the gene set appear in the ordered genome-wide dataset.
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Materials and Methods
3. OLIGONUCLEOTIDE ARRAY CGH (COMPARATIVE GENOMIC HYBRIDIZATION)
DNA samples from melanoma cell lines (SK-Mel-19, -28, -29, -103, -147, -173, UACC-62 and G-361) were
hybridized against Human Genome CGH 44K microarrays (G4410B and G4426B) (Agilent Technologies,
CA, USA), spanning the entire human genome at a median resolution of ~75Kb. Human genomic female
DNA from Promega was used as reference. The hybridizations and data analyses were performed
according to the manufacturer’s protocols. Slides were scanned with an Agilent Scanner, and data were
analyzed with Agilent Feature Extraction and CGH Analytic software 3.5.14 (Agilent Technologies).
4. TISSUE MICROARRAYS (TMAS) AND IMMUNOHISTOCHEMISTRY (IHC)
Paraffin-embedded whole-tissue sections and TMAs comprising duplicate samples from common nevi
(N=45), primary radial growth phase malignant melanomas (N=16), primary vertical growth phase
malignant melanomas (N=97), and skin and visceral melanoma metastases (59), were stained with
antibodies against RAB7A (Prestige Antibody, from Sigma, St Louis, MO, USA) and Cyclin D1 (FLEX, Clone
SP4, from Dako, Glostrup, Denmark) following previously described protocols195. Additionally, RAB7 was
stained in a multi-tumor tissue microarray (TMA) containing tissue samples (in duplicates) from the
following cancer types: melanoma (N=23), lymphoma (N=11), sarcoma (N=15), basal cell carcinoma
(N=2), ovarian (8), breast (N=4), colon (N=7), pancreatic (N=3), renal cell (N=7), lung (N=10), prostate
(N=4), thyroid (N=9), neuroglial (N=7), liver (N=3), testicular (N=4), endometrial (N=2) and bladder (N=2)
tumors. RAB7 protein expression was scored blinded according to staining intensity by two independent
dermatopathologists. The percentage of CCND1-positive cells was determined using an automated
scanning microscope and computerized image analysis system (Ariol SL-50; Genetix, Hampshire, UK).
5. KAPLAN-MEIER SURVIVAL ANALYSES
Clinical data and immunohistochemistry scoring were performed blind by two pathologists, and data
were compiled only after all analyses were completed. Complete follow-up survival data were available
for 112 patients, including 15 cases of radial growth phase and 97 cases of vertical growth phase
melanomas. The specimens were classified as low intensity or high intensity of RAB7 staining. The
overall survival and disease-free survival curves were estimated with Kaplan-Meier and curves were
62
Materials and Methods
compared using logrank test. The hazard ratio was calculated using Cox regression and adjusted with
univariate and multivariate model adjusted by Breslow.
6. PROTEIN IMMUNOBLOTTING
To determine relative differences in protein levels, 2x106 cells were harvested at the indicated time
points. Protein samples extracted from total cell lysates using RIPA or Laemmli buffers were subjected to
electrophoresis in 10%, 12% or 15% polyacrylamide SDS gels under reducing conditions, and
subsequently transferred to Immobilon-P membranes (Millipore, Bedford, MA, USA). Protein bands
were detected using the ECL system (GE Healthcare, Buckighamshire, UK). Primary antibodies included:
RAB7 (Clone RAB7-117), RAB27A (Prestige antibody), Fibronectin (clone IST-4), β-actin (clone AC-15) and
α-Tubulin (clone DM1A) from Sigma (St Louis, MO, USA); Microphthalmia transcription factor (MITF; Ab1, Clone C5) from Thermo Scientific (Fremont, CA, USA); RAB5A, SOX10, CDC2 p34, CDC6 and Hsp70
from Santa Cruz Biotechnology Inc. (Santa Cruz, CA, USA); RAB8 and RAB11 from BD Transduction
Laboratories (Franklin Lakes, NJ, USA); LC3B , phospho-AKT (Ser 473) and CEACAM1, from Cell Signaling
(Danvers, MA, USA); Cathepsin –B, -D, -X, and –S from R&D Systems (Minneapolis, MN USA ); TFDP1
(DP1 Ab-6) from NeoMarkers (Fremont, CA, USA); GAPDH (hybridoma supernatant) from the CNIO
Monoclonal Antibodies Core Unit; and Nucleolin and AURKB from Abcam (Cambridge, UK). HRPconjugated secondary antibodies were from GE Healthcare; and anti-goat-HRP, from Jackson
Immunoresearch (West Grove, PA, USA). When indicated, image J software was used to quantify
proteins levels. β-actin, α-Tubulin or Nucleolin were used as loading controls.
7. IMMUNOFLUORESCENCE
AND CONFOCAL-BASED SINGLE-CELL QUANTIFICATION IN
TISSUES
Tissue sections were deparaffinized, incubated overnight with primary antibodies at 4 °C in a humidified
chamber and then rinsed and incubated with fluorescent secondary antibodies for 1 hour at room
temperature. Nuclei were counterstained with Prolong Gold (Invitrogen, concentration 5µg/mL) 20
minutes before imaging. The following primary antibodies were used: RAB7A (Prestige Antibody,
powered by Atlas Antibodies) purchased from Sigma (St Louis, MO, USA); and S100 (Ab-1, Clone 4C4.9)
and Microphthalmia transcription factor (MITF; Ab-1, Clone C5) from Thermo Scientific (Fremont, CA,
USA). For detection, anti-rabbit Alexa Fluor 555 or anti-mouse Alexa Fluor 488 secondary antibodies
63
Materials and Methods
from Invitrogen were used. In the case of immunofluorescence (IF) on mouse tissues, M.O.M Mouse IgG
Blocking Reagent (purchased from Vector Laboratories; Burlingame, CA, USA); and Image-iT FX signal
enhancer (from Invitrogen; Carlsbad, CA, USA) were used before the primary antibody incubation
according to manufacturers´ protocols. The fluorescence emission was acquired using a confocal TCSSP5-WLL (AOBS-UV) spectral microscope (Leica Mycrosystems, Wetzlar, Germany). To quantify the
intensity of RAB7 signal/cell in melanoma whole-tissue sections, tissues were stained with RAB7 and
S100 antibodies, and image mosaics were acquired at 40x (HCX PL APO 1.2 N.A) with the matrix screener
application from LAS AF software (Leica). Micrographs were subsequently analyzed with Definiens XD
software, first segmenting all the nuclei to delimit single cells, and secondly assigning the different
classes according to their IF intensity. The different IF intensity classes are indicated with the following
coloring of single cells: green for < 35 arbitrary fluorescence units (AFU), yellow for 35-50 AFU, orange
for 50-75 AFU and red for >75 AFU. Blue color represents stromal cells (negative for the melanocytic
maker S100). For high-throughput confocal analyses of immunofluorence stainings in tissue-microarrays
(TMA), image acquisition was performed using “matrix screening remote control” (MSRC), a new tool for
intelligent screening, developed at the CNIO, which improves the quality and speed of image acquisition.
In brief, the MSRC tool manages a first fast scan with low resolution settings to generate one image per
slide. This fist image is subsequently analyzed by the MSRC software to localize and extract the
coordinates of the regions of interest (i.e. tissue samples within the slide). With this spatial information,
the MSRC application interacts with the microscope and loads high resolution settings to scan
automatically the areas of interest. After image acquisition, TMA analysis was performed by Definiens
XD software, first identifying single cells within every tissue and, then, measuring the fluorescence
intensities of green (MITF staining) and red (RAB7 staining) channels per cell.
8. IMMUNOFLUORESCENCE IN FIXED CELLS
Cells were fixed with 4% paraformaldehyde in PBS at room temperature for 20 min. Cells were then
washed twice with 0.1M glycine in PBS for 10min each, permeabilized with 0.2% Triton X-100 in PBS for
5 min, washed twice with PBS and incubated with 1% BSA in PBS at room temperature for 30 min. Fixed
cells were incubated with primary antibody diluted in blocking buffer (1%BSA in PBS) at room
temperature for 1 h. Cells were then washed three times with PBS and incubated with Invitrogen´s
Alexa-conjugated secondary antibodies at room temperature for 1h. Following incubation cells were
washed with PBS and mounted with ProLong® Gold Antifade Reagent with DAPI (Invitrogen). The
64
Materials and Methods
following primary antibodies were used: RAB5 sc-309 antibody, from Santa Cruz Biotechnology Inc.,
(Santa Cruz, CA, USA); RAB7 HPA006964 Prestige antibody, from Sigma (St Louis, MO, USA); and
Cathepsin B AF953 antibody, from R&D Systems (Minneapolis, MN USA). Alexa Fluor 555 anti-rabbit IgG
and Alexa Fluor 488 anti-mouse IgG (Invitrogen) were used as secondary antibodies. In RNA interference
experiments using RAB7 shRNA, cells were fixed and stained with the indicated antibodies at day 6 post
lentiviral-infection.
9. RAB7 EXPRESSION IN MELANOMA “INVASIVE” OR “PROLIFERATIVE” GENE SIGNATURES
RAB7 mRNA expression was analyzed, together with a total of 111 trafficking-related genes, in 6
independent melanoma gene expression datasets as previously described208, 344. Briefly, melanoma gene
expression profiles of each dataset were classified into “Proliferative” (Pro) or “Invasive” (Inv) categories
according to the relative expression of proliferation- and invasion- promoting factors. The “proliferative“
signature is associated high expression of proliferation promoting factors and lineage-specification
genes (e.g. SOX10, EDNRB, MITF, CCDN1, etc.) while the “invasive” signature is associated with low
expression of these genes and high expression of genes involved in invasion and microenvironment
remodeling (e.g. WNT5A, INHBA, COL5A1, and SERPINE1)208, 211, 259. A Student’s t-test was conducted to
examine the significance of the difference between Pro and Inv values for each of trafficking gene-probe
(N=111) and melanoma-data set (N=6). A combined t-test value was calculated using Fisher’s combined
probability analysis. Benjamini and Hochberg’s False Discovery Rate was used to correct for multiple
testing error. Probe sets with a multiple testing adjusted combined p-value < 0.05 were considered
significant.
10. STABLE INHIBITION OF RAB7 FUNCTION
RAB7 function was stably inhibited by two independent approaches: (i) lentivirus-driven gene silencing
using three previously validated shRNA (here in named as shRAB7 -1, 2 -and -3, targeting the sequences
TAGGAGCTGACTTT, TTTCCTGAACCTAT, GATTGACCTCGAAA, respectively), purchased from Sigma (St
Louis, MO, USA); and (ii) stable over-expression of the well-described RAB7 dominant negative mutant
(eGFP-RAB7(T22N)345, cloned into the pLVO-puro lentiviral vector. pLKO scrambled-shRNA vector
(Sigma), pLV empty vector and/or the pLV-GFP-RAB7 wild-type construct were used as controls.
Lentiviral infections were performed as previously described143 and the potency and specificity of each
construct was determined after puromycin selection (1µg/mL) by protein immunloboting or RT-PCR.
65
Materials and Methods
Unless otherwise indicated, cells were plated for expression and functional assays at day 6 postinfection, after selection with puromycin (1µg/mL, 48h).
11. SITE-DIRECTED MUTAGENESIS AND RAB7 shRNA- RESCUE ASSAYS
GFP-RAB7 coding sequence, cloned into the pLV-puro lentiviral vector, was made resistant to RAB7
shRNA (Sigma shRNA construct 3, used in all different functional experiments) by generating four silent
mutations in the shRNA recognition sequence through site-directed mutagenesis using the QuickChange
II XL Site-Directed Mutagenesis Kit (Agilent Technologies, CA, USA), according to manufacturer´s
protocols.
The
following
mutagenesis
primers
were
5´GGGAAACAAGATCGATCTTGAGAACAGACAAGTGGCCACAAAGCGG
3´,
used:
and
forward
reverse
primer
primer
5`.
CCGCTTTGTGGCCACTTGTCTGTTCTCAAGATCGATCTTGTTTCCC 3´. The mutated plasmid was verified by
sequencing. For rescue experiments, SK-Mel-103 cells were infected at different dilutions with pLV-puro
lentiviral vector encoding for wild-type GFP-RAB7 or shRNA-resistant GFP-RAB7 to obtain ectopic
expression RAB7 levels comparable to endogenous RAB7, according to western blot analyses performed
one week after infection. Cells expressing GFP-RAB7 wild-type (wt) and mutated forms were then
infected with RAB7 shRNA (construct 3). The selective efficiency of RAB7shRNA depletion of endogenous
and ectopic wt GFP-RAB7 vs the shRNA-resistant GFP-RAB7 mutant was verified western blot at day 6
post-shRNA infection.
12. siRNA-MEDIATED GENE SILENCING OF ATG7, RAB7, VPS34, SOX10 AND MITF
Cells were transfected with specific short interfering RNA (siRNA) molecules using Lipofectamine 2000
Transfection Reagent (Invitrogen; Carlsbad, CA, USA) according to manufacturer´s protocol. Specifically,
for downregulation of Microphthalmia-associated transcription factor (MITF), previously validated
siRNAs were used346 at a final concentration of 100nM (for SK-Mel-2 and UACC-62 cells) or 250nM (for
SK-Mel-28 and SK-Mel-29 cells). To deplete the classical autophagy regulatory gene ATG7, the following
specific pair of matched RNA molecules (5’-AAACCUUUGAUCCAAACCCACUGGC-3’ and complement),
purchased from Sigma (Carlsbad, CA) was used at a final concentration of 10nM. For VPS34 (PI3KC3),
RAB7 and SOX10 silencing, ON-TARGETplus SMART pools from Dharmacon Thermo Scientific (Fremont,
CA, USA) were used (Cat # L-005250-00-0005, # L-010388-00-0005 and # L-017192-00-0005,
respectively). RAB7 and VPS34 siRNAs were used at a final concentration of 100nM; and SOX10 siRNAs
were used at 100nM (for SK-Mel-2 and UACC-62 cells) or 250nM (for SK-Mel-28 and SK-Mel-29
cells).100nM final concentration siGENOME Non-Targeting siRNA #1 (# D-001210-01-20) was used as
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Materials and Methods
control siRNA. Expression analyses were performed at 72h post-transfection, by protein immunbloting
and/or RT-PCR.
13. BECLIN1 STABLE RNA INTERFERENCE
To stably downregulate the expression of Beclin1 by RNA interference (RNAi), oligonucleotides allowing
for the generation of 19-bp short hairpin RNAs (shRNA) were designed following indications by the
OligoRetriever Database (http://katahdin. cshl.org:9331/RNAi_web/scripts/main2.pl). BLAST search was
done to ensure at least 4-nucleotide (nt) differences with annotated human genes. The corresponding
oligonucleotides (shRNA1: CAGTTACAGATGGAGCTAA, and shRNA2: CGTGGAATGGAATGAGATT) were
annealed and cloned under the control of the H1 promoter into a self-inactivating lentiviral vector.
Lentiviral infections were performed as previously described143 and the potency and specificity of each
construct was determined by RT-PCR.
14. CELL PROLIFERATION AND COLONY FORMATION ASSAYS
For proliferation assays, 5000 cells were plated in 96-well optical bottom plates one week after lentiviral
transduction. At the indicated time intervals, cells were fixed with 4% paraformaldehyde and stained
with DAPI. For each time point, total cell number was quantified by automated high-throughput
confocal detection of DAPI-stained nuclei (Invitrogen; Carlsbad, CA, USA) using the OPERA HCS platform
and the Acapella Analysis Software (Perkin Elmer). Analyses of cell cycle proliferation were performed
by flow cytometry using a FACS Canto II flow cytometer and the FlowJo software (BD Biosciences, San
Jose, CA, USA). For colony formation assays, 4000 cells per well were seeded onto 6-well plates and
were allowed to grow for 15-20 days. The colonies were then stained with crystal violet (0.4g/L),
purchased from Sigma (St Louis, MO, USA). When indicated, number of macroscopic colonies were
quantified using ImageJ from cystal violet scan images. Blinded scoring of cell scattering was performed
in a minimum of 75 colonies per replicate. Colonies were scored as ”compact”, “loose” or “scattered”,
according to whether colonies maintained >90%, 30-90% or <30% of cells with cell–cell contacts,
respectively. β-galactosidase staining at acidic pH was performed as previously described143. Unless
otherwise indicated, proliferation, colony formation and β-galactosidease assays were plated 6 days
after lentiviral infections. All experiments were done in triplicates and were repeated at least twice.
Data are presented as means ± SEMs of two independent experiments performed with three replicates
each.
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Materials and Methods
15. ANIMAL EXPERIMENTS: XENOGRRAFT ASSAYS AND MELANOMA MODELS
To assess tumor growth in mouse xenograft models, 2.0x106 UACC-62 cells, 1.0x106 SK-Mel-103, or
1.0x106 SK-Mel-147 melanoma cells, infected with scrambled shRNA or RAB7 shRNA1, were harvested at
day 6 after infection and subcutaneously injected (suspended in 0.1 mL of PBS) bilaterally into the back
region of nude mice (N=10 tumors per condition). Tumor growth was measured by an investigator
blinded to the experimental conditions. At the indicated time intervals, two orthogonal external
diameters were measured with a calliper. Tumor volume was calculated using the formula (a x b2 x 0,52),
being“a” the bigger diameter and“b” the smaller diameter of the tumor. When tumours reached a
size of 1.5 cm3 they were surgically excised and processed for histology. Endogenous melanomas were
generated in the melanocyte-specific Tyr:CreERT2; BRAFV600E/PTENloxP/loxP and Tyr:NRASQ61K;INK4a/ARF-/mouse models as previously described165,
347, 348
. Tumors were surgically excised when reaching a
diameter of 1cm, and were processed for histology. Melanoma was confirmed by TRP2
immunohistochemical staining and histological analysis by a pathologist. All experiments with mice met
the Animal Welfare guidelines and were performed in accordance with protocols approved by the
Institutional Ethics Committee of the CNIO.
16. MATRIGEL INVASION ASSAYS
The invasive activity of melanoma cells was determined by matrigel transwell invasion assays using
Boyden chambers (0.8 µm BD BioCoat™ Matrigel™ Invasion Chambers; from BD Biosciences, San Jose,
CA, USA), according to the manufacturer guidelines. Briefly, cells were serum-starved overnight and
were seeded in serum-free DMEM onto the upper chamber. DMEM containing 10% FBS was placed in
the lower chamber. After incubation for the indicated time intervals, invading and non-invading cells
were first fixed with 4% paraformaldehyde and then stained with DAPI. Single cells were visualized by
confocal detection of DAPI-stained nuclei through the 20x objective of a TCS-SP5-WLL (AOBS-UV)
spectral microscope (Leica Mycrosystems, Wetzlar, Germany). The transwell membrane was also
visualized by laser reflection. LAS AF Matrix screening Software was used for an automated highthroughput acquisition across the total width of the matrigel membrane in 9 different fields per
experimental condition. IMARIS 6.3 Software was used to quantify the % of invading cells (normalized to
the total cell number per field). Data are presented as means ± SEMs of three independent
experiments performed in duplicates.
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Materials and Methods
17. ASSESSMENT OF LYSOSOMAL FUNCTION
The proteolytic activity and acidity of the lysosomal cmpartment were determined by fluorescence
detection of proteolyzed DQ-Green BSA (Invitrogen, Carlsbad, CA, USA), and Lysotracker Red or Blue
(Invitrogen, Carlsbad, CA, USA) stainings, respectively, as previously described348. Briefly, DQ™ Green
BSA, Lysotracker Red and Lysotracker Blue were used at a final concentration of 10µg/mL, 50nM and
200nM, respectively, and were added to cultured cells 1h before confocal or FACS analyses. For confocal
analyses, images were acquired with the TCS-SP5-WLL (AOBS-UV) spectral microscope (Leica
Mycrosystems, Wetzlar, Germany) and MetaMorph software was used for co-localization analysis. Mean
fluorescence intensities per cell were quantified using ImageJ software in a minimum of 50 randomly
chosen cells per condition and pooled data are represented as means ± SEM. For live microscopy
experiments, a Delta Vision RT microscope (Applied Precision, Washington, USA) coupled to a CO 2 and
temperature-controlled incubation chamber was used. For FACS analysis, LTR-Red and DQ-BSA green
fluorescence signals were acquired with a FACS Aria Cytometer, using constant voltages settings for all
samples analyzed. 10 000 singlets and live cells (DAPI negatives) suspended in FACS buffer (PBS without
Ca and Mg, 0.1-0.5% BSA, 3-5mM EDTA) were acquired per condition. When indicated, cells were
infected with scrambled or RAB7 shRNA(3) lentivirus. 5h pre-treatment with the 20µM Chloroquine
(purchased from Sigma, St Louis, MO, USA) served as control to monitor DQ-Green BSA emission in cells
with blocked lysosomal activity. All experiments were performed in duplicates and were repeated at
least twice.
18. GENERATION OF PEI-COMPLEXED PIC GENERATION OF PEI-COMPLEXED PIC
The synthetic analog of dsRNA, pIC, was purchased from InvivoGen (San Diego, CA). jetPEI , jetPEI-FluoR
and the formulation invivo-jetPEI were purchased to Polyplus-transfection (Ikirch, France). These
reagents were used to complex pIC using an N/P ratio (nitrogen residues of JetPEI per RNA phosphate)
of 1 to 5, according to the manufacturer’s indications. Unless otherwise indicated, the concentrations of
pIC were 1 µg/ml in cultured cells.
19. DRUG TREATMENTS AND VIABILITY ASSAYS
Bortezomib (used at 10nM) was obtained from Millenium Pharmaceuticals Inc (Cambridge, MA);
doxorubicin (used at 0.2µg/mL) and SB202190 (used at 5µM), from Sigma Chemical (St.Louis, MO);
U0126 (used at 5µM) and LY294002 (used at 10µM) from Calbiochem (Germany). Chloroquine (used at
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Materials and Methods
20µM), bafilomycinA1, E64d and pepstatin A were from Sigma Chemical (St Louis, MO, USA). The
percentage of cell death at the indicated times and drug concentrations was estimated by standard
trypan blue exclusion assays. To quantify the sensitivity of tumor cell lines to lysosome inhibition by
chloroquine treatment, cells were plated at equal cell numbers in duplicates and were incubated with
20µM chloroquine for 48h. After fixation, viable cells were stained with crystal violet. For quantitative
viability assessment, cells were plated in 96-well glass bottom plates, were treated as indicated and
viable cells were fixed with 4% paraformaldehyde, were stained with DAPI (Invitrogen; Carlsbad, CA,
USA) and were quantified by automated high-throughput confocal detection of DAPI-stained nuclei
using the OPERA HCS platform and the Acapella Analysis Software (Perkin Elmer). Pooled quantification
data are presented as means ± SEM of two independent experiments. To verify the efficiency of
lysosomal inhibition by chloroquine, the accumulation the autophagosomal marker LC3-II was assessed
by Western blot at 8h treatment.
20. FLUID PHASE ENDOCYTOSIS ASSAYS
To visualize bulk fluid phase endocytosis, cells were incubated in pre-warmed growth medium
containing 1mg/mL Lucifer Yellow (Sigma; St Louis, MO, USA) for 30 minutes. Alternatively, to
specifically study macropinocytosis, cells were incubated for the indicated times with 2mg/mL 70000 Da
rhodamine-labeled dextran (Invitrogen, Carlsbad, CA, USA), a classical macropinocytic tracer349, 350. After
incubation with fluid phase markers, cells were washed and fixed with 4% paraformaldehyde. When
indicated, Alexa Fluor 568 Phalloidin (Invitrogen; Carlsbad, CA, USA) was added to stain cytoskeletal
actin. The incorporation of Lucifer yellow and rhodamine-labeled dextran were visualized under a TCSSP5-WLL (AOBS-UV) spectral microscope (Leica Mycrosystems, Wetzlar, Germany), or a Nikon ECLIPSE
TiE fluorescence microscope (Izasa, Barcelona, Spain). OPERA HCS platform and the Acapella Analysis
Software were used for single-cell quantification of dextran uptake. For quantification of cytosolic
vacuolization, cells were fixed with 4% PFA and a minimum of 200 cells per condition were scored
according to the number and size of vacuoles. Experiments with RAB7-depleted cells were performed at
day 6 after infection with shRNA-lentivirus, or at 72h after transient transfection with siRNA pool. When
indicated, cells were either treated with 10µM LY294002, 0.5µM ETP-46992 (a pan-Class I PI3K inhibitor
with Ki,app 2.4, 94.1, 8.0 and 62.9nM for p110α, β, δ and δ, respectively)351, or 0.5µM ETP-38 (a Class I
PI3K α,δ inhibitor with Ki,app 2.38 and 2.42 nM for p110α and δ, respectively)352, to inhibit Class I PI3Kdriven signaling; were co-transfected with VPS34 siRNA or treated with 3-methyl adenine (1-5mM), to
inhibit Class III-PI3K-dependent trafficking; or were co-transfected with ATG7 siRNA, to inhibit the
70
Materials and Methods
formation classical autophagosomes. All experiments were done in triplicate and were repeated at least
twice. Pooled quantification data are presented as means ± SEM of two independent experiments.
21. RNA EXTRACTION, qRT-PCR AND HIGH-THROUGHPUT RNA SEQUENCING
Total RNA was extracted from cell pellets using QIAshredder and Rneasy Mini Kit from Qiagen (Valencia,
CA, USA), according to manufacturer´s protocol. For real-time (RT) PCR and qRT-PCR, 2μg total RNA was
reverse-transcribed using the high capacity cDNA reverse transcriptase kit (Applied Biosystems, Foster
City, CA), following manufacturer´s instructions. Single stranded cDNA products were then analyzed
using a G-storm termocicler (bioNova científica sl) or the 7900HT Fast Real-Time PCR system (Applied
Biosystems), and the following primers: for Beclin1, forward primer 5´ GTGGAAAAGAACCGCAAGATAGTG
3´
and
reverse
primer
5´TCCCAGAAAAACCGCAACCC
3´;
for
ATG7,
forward
primer
5´
ACCTGGCATCTGCTGACC 3´ and reverse primer 5´ GCGGGCTTGCTCCAGAGTG 3´; for RAB7, forward
primer 5´CATCCTGGGAGATTCTGGAGTCGGG 3´ and reverse primer 5´CGAGAGACTGGAACCGTTCCTGTCCT
3´; for SOX10, forward primer 5´ GCAAGCTCTGGAGGCTGCTGAACG 3´ and reverse primer 5´
GGCGCTCTTGTAGTGGGCCTGG 3´; and for VPS34, forward primer 5´ CGGAAAAGCAGTGCCTGTAGGAGG
3´ and reverse primer 5´ GCTTTGGTGAGCTTGGCAAGACGG 3´. The following primers for 18S were used
as loading controls: forward primer 5´ CTTTCGAGGCCCTGTAATTG 3´ and reverse primer 5´
GGCCTGCTTTGAACACTCTAA 3´. For high throughput RNA sequencing, total RNA from three independent
experiments was extracted from tumor cell lines (SK-Mel-28, UACC-62, HCT116), stably expressing
scrambled shRNA or RAB7 shRNA (shRNA 3) and harvested at day 3 after lentiviral infection. RNA
Integrity Numbers were in the range 8.6 to 10 when assayed on an Agilent 2100 Bioanalyzer (Agilent
Technologies, CA, USA), PolyA+ RNA fraction was extracted and randomly fragmented, converted to
double stranded cDNA and processed through subsequent enzymatic treatments of end-repair, dAtailing, and ligation to adapters as in Illumina's "TruSeq RNA Sample Preparation v2 Protocol" (Part #
15026494 Rev. C, Illumina, Inc., San Diego, CA, USA). Adapter-ligated library was completed by 8 cycles
of PCR with Illumina PE primers. The resulting purified cDNA library was applied to an Illumina flow cell
for cluster generation (TruSeq cluster generation kit v5) and sequenced on the Genome Analyzer IIx with
SBS TruSeq v5 reagents following manufacturer's protocols. Read files were quality-checked with FastQC
(Babraham Bioinformatics group, http://www.bioinformatics.babraham.ac.uk/). The 40-nt single-end
reads that passed quality filters were aligned to the human genome (GRCh37/hg19) with TopHat-2.0.4353
(using Bowtie 0.12.7354 and Samtools 0.1.16355), allowing two mismatches and five multihits. Transcripts
assembly, estimation of their abundances and differential expression were calculated with Cufflinks
71
Materials and Methods
1.3.0353, using as transcripts annotation set the human genome annotation data set from Ensembl
(Homo_sapiens.GRCh37.65). Gene Set Enrichment Analysis (GSEA)340 was performed to test for relevant
pathways in our data. The functional annotation of significantly deregulated genes (FDR<0.05) was
analyzed using Panther database (www.pantherdb.org). The expression of differentially induced /
silenced genes (FDR < 0.05) was validated by protein immunoblotting and/or qRT-PCR. Data is available
in the GEO repository with the accession number GSE42735.
22. VISUALIZATION AND QUANTITATIVE ANALYSIS OF CYTOSKELETAL ALTERATIONS
(CYTOOCHIPS)
The indicated melanoma cells, infected with scrambled shRNA or RAB7 shRNA (shRNA 3), were seeded
onto commercially available micropatterned coverslips (CYTOOChips) purchased from Cytoo Inc.
(Boston, MA, USA). 5 hours after seeding, cells were fixed in 4% paraformaldehyde and were processed
for immunofluorescence as previously described143. The paxillin antibody (clone 5H11) was purchased
from Millipore (Bedford, MA, USA). Alexa Fluor 568 Phalloidin (Invitrogen; Carlsbad, CA, USA) was added
to visualize F-actin. Preparations were mounted in ProLong Gold antifade reagent with DAPI
(Invitrogen). Individual cells were imaged through a 40x/1.25 oil objective with a confocal TCS-SP5-WLL
(AOBS-UV) spectral microscope (Leica Mycrosystems, Wetzlar, Germany). To obtain the “average cell”
image, the spatial distribution of paxillin or phalloidin was calculated in a minimum of 20 pictures per
condition as previously described356. In brief, individual cell images were aligned and stacked, and the
average intensity of each pixel over stacked picture was quantified with Image J and Huygens software.
A color-coded rainbow intensity range was be used to highlight the main sites of the distribution. This
procedure has been previously used to quantitatively study the spatial organization of the actin network
and focal adhesions356.
23. VIDEO AND FIXED-CELL FLUORESCENCE MICROSCOPY OF ENDOCYTIC AND AUTOPHAGIC
TRAFFICKING
To visualize endosomes and autophagosomes, eGFP-RAB5, eGFP-RAB7, eGFP-LC3, and Cherry-LC3 were
cloned into the pLVO-puro lentiviral vector and lentiviral-mediated gene transfer was performed as
previously described143. Lysosomal-rich/acidic compartments were visualized with Lysotracker Red or
Lysotracker Blue (Invitrogen, Carlsbad, CA), used at a final concentration of 50nM or 200nM,
72
Materials and Methods
respectively. For time-lapse videomicroscopy, all microscopes used were coupled to a CO2 and
temperature-controlled incubation chamber to allow for short- and long-term imaging of live cells, using
a Delta Vision RT microscope (Applied Precision, Washington, USA). Differential interference contrast
DIC videos and images were acquired in a TCS-SP5-WLL (AOBS-UV) spectral microscope (Leica
Mycrosystems, Wetzlar, Germany). Bright filed videos for cell free movement were acquired in a
DMI6000 B fluorescence microscope (Leica Mycrosystems, Wetzlar, Germany) or a Delta Vision RT
microscope. Fluorescence emission of 4% paraformaldehide-fixed cells expressing these constructs was
imaged using a TCS-SP5-WLL (AOBS-UV) spectral microscope or DMI6000 B fluorescence microscope
(Leica Mycrosystems). When indicated, 25nM rapamycin treatment (6h) was used to induce and
visualize (mTOR-dependent) autophagy dynamics in GFP-LC3 expressing melanoma cells. Experiments
with shRNA RAB7-expressing cells were performed after puromycin selection, at day 6 after infection
with shRNA (3) lentivirus vector, and including the corresponding scrambled shRNA control cells. To
quantify GFP-LC3 rings in RAB7 and/or ATG7-depleted cells, the percentage of cells harbouring one or
more GFP-LC3 rings of >2µm diameter was determined in a minimum of 200 cells, imaged under a
DMI6000 B fluorescence microscope, at 72h after siRNA transduction. Pooled data are presented as
means ± SEM of two independent experiments performed in duplicate. To screen for chemo and
immunomodulators mobilizing the endolysosomal machinery, SK-Mel-103 melanoma cells stably
expressing GF-RAB7 were plated at least 12 hours before drug treatment at equal cell numbers in
confocal microscopy chambers, were treated as indicated and were fixed after 9h of treatment with 4%
PFA. Nuclei were counterstained with DAPI and cells were imaged under a TCS-SP5-WLL (AOBS-UV)
spectral microscope.
24.
TRANSMISSION ELECTRON MICROSCOPY
For transmission electron microscopy (TEM), the indicated cell populations were rinsed with 0.1
Sorensen’s buffer (pH 7.5), fixed in 2.5% glutaraldehyde for 1.5 h, and subsequently dehydrated and
embedded in Spurr’s resin. Then, the block was sectioned at 60-100 nm ultra thin sections and picked up
on copper grids. For routine analysis ultrathin sections were stained with 2% uranyl acetate and lead
citrate. Electron micrographs were acquired with a Philips CM-100 transmission electron microscope
(FEI, Hillsbrough, OR) and a Kodak 1.6 Megaplus digital camera.
73
Materials and Methods
25. PROTEIN SECRETION ASSAYS
Conditioned media were prepared by incubating the indicated number of cells, plated in 100mm dishes,
for 18 hours in 10mL serum-free DMEM. Conditioned media were harvested, clarified by centrifugation,
filtered through a 0.45μm filter and then concentrated in Amicon Ultra-15 centrifugal filter devices with
Ultracel-3 membrane 3kDa NMWL (Millipore, Bedford, MA, USA) by centrifugation at 4000g for 5h in a
swinging bucket rotor. For active-site labeling of cysteine cathepsins using the biotinylated activitybased probe DCG-04357, 20µL of concentrated conditioned media were incubated with 1μM DCG-04 for
1h at room temperature. The samples were then boiled for 5 minutes, subsequently subjected to
electrophoresis in 15% polyacrylamide gradient SDS gels under reducing conditions, and transferred to
Immobilon-P membranes (Millipore, Bedford, MA, USA). Blots were then blocked overnight, were
incubated with Avidin-horse radish peroxidase (BD Pharmingen) and, after washing, the labeled
cathepsins were detected using the ECL system (GE Healthcare, Buckighamshire, UK). Alternatively, to
detect specific proteins, 10uL of DCG-04 unlabeled concentrated conditioned media were subjected to
protein immunobloting as described above. All experiments with shRNA RAB7-expressing cells were
performed after puromycin selection, at day 6 post-infection with shRNA (3) vector, and including the
corresponding scrambled shRNA control. To avoid the effect of differential growth rates on the total
number of cells from which the conditioned media is harvested, control and RAB7 shRNA-expressing
cells were plated at equal numbers and were incubated with the serum-free DMEM 8h after plating.
When indicated, LY294002 (10µM) was added to the serum-free DMEM to assess the impact of PI3K
signaling on protein secretion.
26. ONCOGENE-INDUCED SENESCENCE ASSAYS IN PRIMARY HUMAN MELANOCYTES
Primary human melanocytes were transduced with validated HRASG12V, BRAFV600E, NRASQ61R and
NRASG12V-expressing vectors, as previously described143. To address the role of RAB7 in OIS, two
sequential infections of 5h each were performed, first with GFP-RAB7 wild-type or T22N viral supernants
and secondly with oncogenic-RAS or –BRAF–conding lentivirus. Non-infected and infected cells
expressing the empty vector were also included as controls. Infection efficiencies were estimated at day
6 after infection by imaging of green fluorescence protein and by Western blot using the appropriate
antibodies. To inhibit PI3K and MEK function, LY294002 (10µM) and U0126 (10µM) were added at day1
post-HRASG12V infection and were refreshed every 24h. To address macropinocytic trafficking, cells at
day 6 post-HRASG12V infection were incubated with 70 kD Rhodamine(Rhd)-Dextran349, 350 (2mg/mL) for
74
Materials and Methods
2.5h. Cells were then washed, fixed with 4% paraformaldehyde and imaged under a Nikon ECLIPSE TiE
fluorescence microscope or a TCS-SP5-WLL (AOBS-UV) spectral microscope. Visualization of actin-driven
ruffling and macropinocytic vesicles through phalloidin and RAB7 immunofluorescence staining,
respectively, was performed using a TCS-SP5-WLL (AOBS-UV) spectral confocal microscope. Senescenceassociated β-galactosidease staining was performed at day 6 post-infection, as previously described143.
Cytosolic vacuolization was quantified by scoring the number of vacuolized cells and the size of vacuoles
(≥ 1µm diameter) using a Nikon ECLIPSE TiE fluorescence microscope (Izasa, Barcelona, Spain) and the
Nikon NIS-Elements BR software. Pooled quantification data of percentage
-Galactosidase positive or
vacuolized cells are presented as means ± SEM of two independent experiments.
27. STATISTICAL ANALYSES
For proliferation curves in vitro and tumor growth in vivo, the nonparametric generalized Mann-Whitney
test was used to compare the values of continuous variables between two groups and p <0.05 was
considered significant. The differences between two groups were evaluated by the two-tailed Student´s
t-test and p < 0.05 was considered significant. For GSEA, gene sets showing FDR <0.25 after KolmogorovSmirnoff testing were considered enriched between classes under comparison. RAB7A, RAB27A and
RAB8A
expression
box
plot
using
data
from
the
CCLE
project
was
obtained
from
http://www.broadinstitute.org/ccle/home. A chi-square test was used to compare the expression of
RAB7 among different melanocytic lesions. To compare primary melanoma Breslow depth across RAB7
expression categories, a non-parametric test of trend for the ranks of across ordered groups was
performed. The overall survival (OS) and Disease free survival (DFS) predictive value of RAB7 expression
were explored using Kaplan-Meier, log-rank test, and Cox regression analysis. p < 0.05 was considered
significant. In general, for group comparisons, "*" stands for p< 0.05, "**" for p< 0.01, and "***" for p<
0.001.
75
Materials and Methods
76
Objetives
“The experimenter who does not know what he is looking for
will not understand what he finds”
Claude Bernard (1813-1878)
Results
77
Materials and Methods
78
Results
1. LINEAGE-RESTRICTED TRAITS ASSOCIATED WITH THE LYSOSOME IN MELANOMA
To identify potential processes uniquely regulated in melanoma, Gene Set Enrichment Analysis (GSEA)
was performed on independent multicancer-type transcriptional datasets341, 342, including the recently
reported Cancer Cell Line Encyclopedia (CCLE)358 . This allowed for a comprehensive evaluation of
melanoma-restricted gene signatures compared to over 35 different tumor types.
significantly enriched in melanoma (Table
Salivary Gland
Pancreas
Intestine
Oesophagous
Auton. ganglia
Prostate
Pleura
be
Bone
Ovary
to
Breast
found
Stomach
were
Hematopoietic
and lymphoid
(FDR=1.8x10 )
Component
Kidney
GO-Cellular
-6
the
Lung
melanosome
and
MELANOMA
(FDR<3.6x10-6)
Processes
a
Central Nervous System
Endometrium
biosynthesis Gene Ontology (GO)-Biological
Soft Tissue
Urinary Tract
Thyroid
Aerodigestive Tract
Liver
As expected, pigmentation and melanin
S4 and results not shown). Interestingly,
gene sets scored even more significantly
(FDR<1.0x10-8, Table S4). Within these
gene sets, a cluster of lysosome-associated
factors was found to be uniquely coregulated in melanoma cells (see heatmap
for the CCLE dataset in Fig. 12a, separating
55
melanoma
cell
lines
from
LYSOSOME (GO:0005764)
vacuole, lytic vacuoles, and lysosome GO
>750
examples of other tumor types, and Fig.
plot). These genes code for lytic enzymes
(such as ACP5, cathepsins K, B and H,
among others) as well as for regulatory
proteins involved in lysosome biogenesis
and
function
359, 360
(such
RAB7A)
(Fig. S1).
Lysosomes
share
as
LAMP2
common
b
LYSOSOME (GO:0005764)
Enrichment
Score (ES)
12b for the corresponding enrichment
Ranked
gene list
and
precursor
organelles and constitutive factors with
melanosomes361-370. Therefore, although
0.6
0.5
0.4
0.3
0.2
0.1
0.0
“Melanoma”
postively correlated
“Melanoma”
negatively correlated
Fig 12. Lineage-specific enrichment of lysosomal factors in the
transcriptome of melanoma cells. (a) GSEA heat map showing a
selective enrichment of the Lysosome Gene Ontology cluster
(GO:0005764) in melanoma cells compared to the rest of CCLE
tumor cell lines. The corresponding enrichment plot for lysosomal
genes (GSEA FDR<0.05) is depicted in (b).
79
Results
they develop via divergent programmes (Fig. 13a) and have different biological functions, it was
imperative to determine if the enrichment of the GO-lysosome cluster in melanoma cells reflected
simply a high load of pigmentation-related genes, characteristic of this specific cell type. To this end,
extensive proteomic datasets371 were mined for a systematic analysis of factors contained in lysosomes
and melanosomes. GSEA was then ran across the CCLE dataset after removal of genes common to both
a
c
Lysosome
b
Melanosome
Lysosome
145 128
1246
LYSOSOME GENE SET (GO:0005764)
WITHOUT MELANOSOMAL GENES
Vable cells
(%, relative to NT)
Enrichment
score (ES)
e
SK-Mel147
UACC62
100
80
60
40
20
0
f
Non-melanoma cells
SK-Mel19
639V
Non-melanoma
cells
***
“Melanoma”
negatively correlated
Melanoma cells
SK-Mel103
*
d
0.5
0.4
0.3
0.2
0.1
0.0
-0.1
Ranked
gene list
“Melanoma”
postively correlated
Melanoma cells
1200
1000
800
600
400
200
0
SK-Mel-5
SK-Mel-19
SK-Mel-28
SK-Mel-29
SK-Mel-103
SK-Mel-143
UACC-62
1205Lu
MCF7
HCT116
CAL62
FTC-133
639V
HeLa
U2OS
Lysosomes
Bodipy-Green
HeLa
NT
CAL-62
FTC-133
SK-Mel-5
SK-Mel-19
SK-Mel-28
SK-Mel-29
SK-Mel-103
SK-Mel-28
SK-Mel-147
UACC-62
SK-Mel-29
1205Lu
MCF7
SK-Mel-103
HCT116
UACC-62
BT549
CAL62
HCT116
FTC-133
639V
SW620
639V
HeLa
HeLa
Late
Endosomes
DQ-BSA Green
Median Intensity (AU)
Melanosomes
CQ:
LC3-I
+ - + - + - + - + - + -+ -
Early
endosomes
Chloroquine
DQ-BSABodipy-Green
LC3-II
CQ
β-Actin
Fig. 13. Comparative analysis of activity and requirement of lysosomal function in different cancer cell lines. (a) Divergent
pathways for melanosome and lysosome biogenesis (adapted from Ref. 371). (b) Enrichment plot for the GO:0005764lysosome cluster after removing genes whose products are also present in melanosomes (GSEA FDR =0.068). (c) Analysis of
lysosomal proteolytic activity by FACS-driven quantification of the median fluorescence intensities of DQ-BSA Green
(10µg/mL, 1h) in the indicated tumor cell lines. (d) Viability (relative to non-treated (NT) controls) of the indicated cell lines
treated with 20µm Chloroquine for 48h. (e) Crystal violet staining of viable cells after treatment with vehicle (NT) or
chloroquine (CQ) as described in (d). (f) Western blot showing the accumulation of the autophagosomal marker LC3-II in all
CQ-treated populations from the indicated tumor lines. β-actin immunoblot is shown as loading control. Melanoma cell
lines are marked in blue.
80
Results
organelles. As shown in Fig 13b, “lysosome-only” genes were still found significantly enriched in
melanoma. In addition to computational analyses, we experimentally investigated the (i) proteolytic
activity and (ii) sensitivity to lysomotropic agents of a panel of representative melanoma and nonmelanoma tumor cell lines. Independent of their pigmentation status, melanoma cell lines showed an
overall higher lysosomal-associated proteolytic activity compared to cells of other cancer types, as
reflected by the cleavage of the fluorogenic substate DQ-Green-BSA, specific for lysosomal proteases372,
373
(Fig 13c). Moreover, inhibition of basal lysosomal activity by treatment with the lysosomotropic agent
chloroquine374-376 revealed an enhanced sensitivity of melanoma cells to impaired lysosomal degradation
(Fig. 13d,e). Of note, this was the case despite the fact that chloroquine inhibited global lysosomal
function with a similar efficiency in all cell lines tested, as measured by the characteristic accumulation
of the LC3-II autophagosome marker by western blot analysis (Fig. 13f). Together, these data support a
melanoma-specific wiring of lysosomal-associated degradative pathways.
2. LINEAGE-RESTRICTED OVEREXPRESSION OF RAB7 IN MELANOMA
The tissue-based traits identified above raised the possibility that the melanoma-restricted lysosome
gene expression signature might harbor new lineage-specific cancer drivers. Among the top scoring
lysosomal genes, RAB7A (hereafter referred to as RAB7 for simplicity) was selected as a candidate for
histologic and functional validation based on the following criteria: (i) RAB7 maps to a genomic region
frequently amplified in melanoma (see array CGH data in Fig. 14a and additional information in Table
S5). This is consistent with elegant computational algorithms251 that were applied to independent
melanoma-only datasets and underscored putative driver genetic aberrations affecting this gene. (ii)
RAB7 mRNA showed the highest enrichment in melanoma, exceeding that of RAB27A (Fig. 14b and
results not shown), an MITF target known to be required for the proliferation of a subset of melanoma
cells251. While RAB7 and RAB27 regulate melanosome transport377, RAB7 has a variety of lysosomeassociated functions not shared with RAB27. (iii) In fact, RAB7 was the only factor from the lysosome
cluster with pivotal roles in lysosome biogenesis360 and lysosome-mediated turnover of cytoplasmic
vesicles378-380 (Fig. 11), that were also found to be overrepresented in melanoma cells according to GSEA
(Table S4). (iv) Finally, RAB7 has been reported as a ubiquitous regulator of vesicle trafficking312, 360, 378380
, but was not noted as having tumor-type specific regulation and/or function(s). In this context, there
is no clear consensus regarding the specific roles of RAB7 in cancer cells, as pro381, 382 and anti383-385 tumorigenic effects have been described in discrete cultured cell types upon RAB7 inactivation.
Expression studies in vivo are limited to cDNA arrays in human mesotheliomas386, and to thyroid
81
Results
hormone production in thyroid adenomas387, but the specific contribution of this factor to the initiation
and progression of human tumors, including melanomas, has yet to be defined.
b
+1
0
-1
-2
Chromosome 3q21.3
11
10
9
SK-Mel-5
SK-Mel-19
SK-Mel-28
SK-Mel-29
SK-Mel-103
UACC-62
WM-164
T98G
U251
A549
MIAPaca-2
RWP-1
PC3
SW1710
639V
HeLa
HCT116
HT29
BT549
Non-Melanoma
RAB7
β-Actin
d
e
N = 121
Proportion of samples
RAB7A – EntrezID:7879
12
Melanoma (61)
Mesothelioma (11)
Esophagus (25)
AML (34)
Colorectal (61)
Stomach (38)
Pancreas (44)
Bile Duct (8)
Urinary tract(27)
Breast (58)
Upper Aerodigestive (32)
Hodgkin Lymphoma (12)
Thyroid (12)
Other Leukemia(1)
Ovary (51)
Kidney (34)
Chondrosarcoma (4)
Meningioma (3)
LungNSC (131)
Glioma (62)
CML (15)
Prostate (7)
T-cell –all- (16)
Soft Tissue (21)
Other (15)
Endometrium (27)
Osteosarcoma (10)
Lymphoma DLBCL (18)
Multiple Myeloma (30)
Liver(28)
Neuroblastoma (17)
Lymphoma –other- (28)
B-cell –all- (15)
Lung Small Cell (53)
Medulloblastoma (4)
Ewings Sarcoma (12)
Burkitt lymphoma (11)
Melanoma
c
mRNA expression (RNA)
+2
UACC-62
Normalized Log2 Ratio
a
100%
80%
60%
40%
20%
0%
High
Low
Negative
Melanoma
Lymphoma
Breast
Cancer
Colon
Cancer
Renal Cell
Cancer
Lung Cancer
Prostate
Cancer
Thyroid
Cancer
Neuroglial
Tumor
Sarcoma
Fig. 14. The lysosome-asociated RAB7 small GTPase as a candidate lineage-specific cancer gene in melanoma. (a) ArrayCGH profile of the 3q21.3 chromosomal region for the UACC-62 melanoma cell line showing mapping of RAB7A CGH probes
(marked in blue) in an amplified genomic region. Displacements to the top or bottom of the horizontal line represent
genomic gains or losses, respectively, and are colored in grey.. See Table S5 for additional cell lines. (b) Box plots showing
the relative expression of RAB7 mRNA across the different tumor types in the CCLE dataset
(http://www.broadinstitute.org/ccle/home). (c) Detection of RAB7 and β-actin (loading control) proteins by WB in total cell
extracts. (d) Quantification of RAB7 expression levels, assessed by IHC, in the indicated human cancer types (e) Visualization
of RAB7 by IHC (pink) in representative tissue biopsies.
To validate GSEA findings, RAB7 protein levels were assessed by western blotting (WB) in a wide panel
of melanoma and non-melanoma tumor cell lines. In addition, RAB7 expression was investigated in
human biopsies by immunohistochemistry (IHC) staining on tissue microarrays (TMAs) of 17 different
cancer types. These expression analyses confirmed a selective enrichment of RAB7 in melanoma cell
lines (Fig. 14c) and tumors (Figs. 14d,e). Interestingly, this was the case even compared to
mesotheliomas (Fig. 14b) and thyroid cancers (Figs. 14d,e).
82
Results
3. MITF-INDEPENDENT OVEREXPRESSION OF RAB7 IN MELANOMA
We next sought to determine whether the overexpression of RAB7 in melanoma cells was dependent on
the melanocyte lineage transcription factor MITF. This was relevant because MITF is the bona fide
lineage-restricted oncogene in melanoma251 and can regulate other RAB proteins, such as RAB27236.
However, its expression can be shut down completely during melanoma progression216, 255, 256. Western
blot analysis revealed that, different from RAB27, RAB7 was still expressed in MITF-negative melanoma
cells (Fig. 15a). In addition, genetic depletion of MITF by siRNA in representative melanoma cell lines did
not compromise RAB7 expression (Fig. 15b,c). The independency of RAB7 and MITF expression in
melanoma cells was also confirmed in vivo by double immunofluorescence and single-cell confocalbased quantification of both proteins in human biopsies (Fig. 15e). These results demonstrate that RAB7
is not placed within the transcriptional program of MITF, indicating that this small GTPase could
represent an independent lineage-restricted oncogene in melanoma.
MITF
RAB27
RAB27
RAB7
β-Actin
β-Actin
d
Merge
MITF
LN melanoma met
Case #90671
Primary melanoma
Case #90601
83
Control
MITF
Control
MITF
Control
MITF
Control
MITF
Control
MITF
Mean RAB7 signal / cell (A.F.U)
RAB7
Melanoma specimens
Control
MITF
siRNA:
MITF
RAB7
Fig. 15. MITF-independent
expression of RAB7. (a)
24h
48h
72h
Relative levels of RAB7, MITF,
and RAB27, assessed by WB in
siRNA:
the indicated melanoma cell
lines (b) Downregulation of
MITF
RAB27 but not RAB7 upon
siRNA-mediated depletion of
MITF in melanoma cells. (c)
RAB27
Kinetics of the downregulation
RAB7
of RAB27 but not RAB7 upon
MITF
siRNA-mediated
α-Tubulin
depletion in UACC-62 cells. (d)
IF staining of RAB7
e Single-cell quantification Double
(red) and MITF (green) in a
human melanoma specimens.
Case # 90671
Nuclei are counterstained with
DAPI. The cases #90671 and
#90601 exemplify melanomas
with high RAB7 and MITF
Case #90601
expression (compare to low
levels of both proteins in the
stroma), whereas the case
#90603 shows positive RAB7
staining in a melanoma
Case # 90603
expressing negligible levels of
MITF.
(e)
Confocal-based
quantification of the relative
expression per cell of RAB7 and
Primary melanoma
MITF (in Arbitrary Fluorescence
Case #90603
Mean MITF signal / cell (A.F.U)
Units, A.F.U) of specimens
shown in (d)
c
Control
MITF
b
SK-Mel-5
SK-Mel-19
SK-Mel-28
SK-Mel-29
SK-Mel-103
G-361
SK-Mel-147
UACC-62
Mel1
WM-1366
WM-164
a
Results
4. LINEAGE-ADDICTION OF MELANOMA CELLS TO RAB7
Melanoma-restricted roles of RAB7 were investigated by stable transduction of three independent short
hairpin interfering RNAs (shRNAs) in a panel of melanoma cell lines (N=8) and in representative
examples of cell lines (N= 8) from frequent solid tumors. Melanoma cells responded to RAB7
downregulation with a significant inhibition of cell proliferation (Figs. 16a-c). These effects were
associated with the acquisition of senescence-like features such as lysosomal β-galactosidase activity (βGal) at acidic pH (see below in Figs. 18e,f). In contrast, under the same conditions, reduction of RAB7
levels had negligible effects on the proliferative capacity of pancreatic cancer (MiaPaca-2), colon cancer
(HCT116), bladder cancer (639V), and thyroid carcinoma (FTC-133, CAL-62) cell lines, or promoted
moderate delays in the proliferation of U251 (Glioma), A549 (lung adenocarcinoma) and cervical cancer
(HeLa) cells, respectively (Fig. 16a-c and results not shown).
a
Non infected
Ctrl
-
RAB7 (1)
RAB7 (2)
shRNA: -
RAB7 (1)
RAB7 (2)
Ctrl
a
shRAB7 (1)
shControl
shRAB7 (2)
UACC-62
RAB7
HCT116
β-Actin
HCT116
UACC-62
bb
Melanoma
HCT116
16
12
8
4
0
UACC-62
SK-Mel-28
HCT116
FTC-133
CAL-62
HeLa
UACC-62
SK-Mel-28
0
4
1
8
6
4
2
0
2
3
0
4
1
MiaPaca-2 15
2
3
639V
10
5
0
1 2 3 4 5 6
Days
1 2 3 4 5 6
3
4
A549
10
8
6
4
2
0
*
1
Days
* ***
2
3
5
Days
7
HCT116
3
SK-Mel-28
2,5
2
** 1,5
1
0,5
0
4
1
FTC-133
2
Days
SK-Mel-103
8
** *** 4
CAL-62
* *** ***
0
SK-Mel-103
12
2
2
1 2 3 4 5 6
Ctrl
RAB7
Ctrl
RAB7
Ctrl
RAB7
Ctrl
RAB7
Ctrl
RAB7
Ctrl
RAB7
Ctrl
RAB7
shRNA (3):
4
WM-164
4
HeLa
Cell number
(fold)
-
β-Actin
c
c
UACC-62
shControl
shRAB7
SK-Mel-103
Cell number
(fold)
Ctrl
A549
Ctrl
-
Ctrl
-
6
1
RAB7
-
Ctrl
RAB7
shRNA (3):
RAB7
Ctrl
RAB7
Non-melanoma
HCT116 MiaPaca-2 639V
RAB7
-
RAB7
Ctrl
-
RAB7
-
Ctrl
RAB7
Ctrl
shRNA (3): RAB7
β-Actin
RAB7
UACC-62 WM-164 SK-Mel-103 SK-Mel-28
shControl
RAB7
β-Actin
shRAB7
Fig. 16. Lineage-dependent effects of RAB7 depletion on tumor cell proliferation. (a-c) Downregulation of RAB7 by
different lentiviral shRNA constructs in the indicated melanoma (blue) and non-melanoma (black) cell lines. Left panels
show RAB7 and β-actin WBs of total cell lysates, and right panels show the effect of control or RAB7 shRNA on cell
proliferation, reflected by (a) micrographs (at day 6 after shRNA transduction), (b) proliferation curves (relative cell
numbers expressed as means ± SEM of two independent experiments), or (c) crystal violet staining of viable cells from the
indicated populations plated at equal cell numbers. Proliferation assays were plated at day 6 after shRNA transduction.
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Results
Colony formation assays were next performed to assess the effect of RAB7 depletion on the tumorigenic
potential of melanoma and non-melanoma tumor cells. As shown in Fig. 17a, transduction of RAB7
shRNA significantly abrogated the clonogenic growth of melanoma cells, but did not exert major
detrimental effects on the tumorigenicity of non-melanoma tumor cell lines. Conversely, overexpression
of wild-type RAB7 increased the colony formation ability of melanoma cells (Fig. 17b). Functional
experiments with the well-characterized RAB7 (T22N) dominant negative mutant345 (Fig 17a,b), and with
a shRNA-resistant RAB7 mutant (Fig. 17c) were performed to validate the specificity of RAB7 shRNA.
Importantly, the inhibitory effects of RAB7 shRNA and dominant negative RAB7 mutant translated into a
significantly reduced tumorigenic potential in vivo of melanoma cells subcutaneously injected into nude
mice (Fig 17d).
a
Non-melanoma
A549
639V
SK-Mel-147 HCT116
RAB7 T22N
Vector
UACC-62 SK-Mel-147 WM-164SK-Mel-28 SK-Mel-103 HCT116 MiaPaca2 U251
shRAB7
shControl
Melanoma
c
d
Empty GFP-RAB7 GFP-RAB7
T22N
vector
WT
β-Actin
Tumor vol (mm3)
shRAB7 shControl
-
Ctrl
RAB7
-
Ctrl
RAB7
Ctrl
RAB7
-
GFP- GFPRAB7- RAB7WT
MUT
SK-Mel-103 SK-Mel-147
1000
500
**
SK-Mel-103
***
*** 500
0
0
2500
10 20 30 40
Days
shControl
shRAB7
(3)
2000
1500
0
2000
10
20
Days
30
Vector
GFP-RAB7
T22N
1500
* 1000
500
500
0
β-Actin
shControl
(3)
shRAB7
1500
1000
1000
GFP-RAB7
RAB7endog
2000
shControl
shRAB7
2000
1500
SK-Mel-147 (NRAS Q61R)
Tumor vol (mm 3)
RAB7endog
shRNA:
2500
0
Empty
vector
GFP-RAB7
UACC-62 (BRAFV600E) SK-Mel-103 (NRAS Q61R)
Empty GFP-RAB7 GFP-RAB7
vector
WT
MUT
Empty vector
GFP-RAB7 WT
GFP-RAB7 T22N
Empty vector
GFP-RAB7 WT
GFP-RAB7 T22N
SK-Mel-143 SK-Mel-103
b
**
***
0
0
10 20 30 40
Days
0
10
20 30 40
Days
Fig. 17. Lineage-dependent effects of RAB7 depletion on tumorigenicity and tumor growth in vivo. (a) Colony formation
ability of the indicated tumor cells expressing RAB7 shRNA (3), T22N dominant negative mutant, or their respective vector
controls. (b) Impact of the overexpression of wild-type (WT) or dominant negative (T22N) GFP-RAB7 on the clonogenic
capacity of the indicated melanoma cell lines. Empty vector is shown as control and the corresponding immunoblots of total
cell extracts probed for RAB7 and β-actin are shown in the bottom panels. (c) Expression of a mutated (MUT) version of
GFP-RAB7, resistant to RAB7 shRNA (construct 3), rescues shRNA(3)-driven effects on the clonogenic capacity of SK-Mel-103
melanoma cells. (d) Growth of xenografts generated with the indicated melanoma cell populations after subcutaneous
implantation into nude mice (means ± SEM).
85
T22N downregulation or RAB7 T22N dominant negative expression in the context of cell proliferation (b); colony formation,
numbers represent mean number of colonies per 35mm plate ± SEM (c); and growth after subcutaneous implantation in
nude mice (d). Downregulation of RAB7 expression by two different lentiviral shRNA constructs in the indicated melanoma
Results
Of note, abrogation of melanoma cell proliferation by inhibition of RAB7 in vitro and in vivo was
independent of basal MITF levels and effective in BRAF or NRAS mutated melanoma cells (Figs. 17a,d
and Table S5). Together, these data demonstrate that RAB7 is broadly required to sustain the
proliferation of melanoma cells, a function which is exerted in a lineage-selective manner.
Given the lineage-dependent requirement of RAB7 for melanoma cell proliferation, we next determined
whether the “addiction” of melanoma cells to RAB7 was an intrinsic feature of the melanocytic lineage
(i.e. whether it was already present in normal melanocytes). To this end, we first performed immunoblot
analysis to assess the basal expression levels of RAB7 in preparations of genetically matched human
normal skin cells (i.e. melanocytes, keratinocytes and fibroblasts from the same donor). This revealed
intrinsically higher levels of RAB7 in melanocytes compared to their non-melanocytic normal
counterparts (Fig. 18a).
b
3 1
2
shRNA: -
3
β-Actin
d
1.2
shControl
0.8
-
Fibroblasts Melanocytes UACC-62
shControl
1
shRAB7
0.6
shRAB7
0.4
0.2
0
Fibroblasts Melanocytes UACC-62
f
100
80
shControl
shRAB7
60
Melanocytes Fibroblasts UACC-62
shControl
Cell number increase
(fold relative to shControls)
RAB7
β-Actin
-
RAB7
2
Ctrl
1
RAB7
3
40
shRAB7
e
2
RAB7
β-Gal positive cells (%)
c
1
Ctrl
Melanocytes Fibroblasts Keratinocytes
Skin biopsy:
RAB7
Fibroblasts Melanocytes UACC-62
Ctrl
a
20
0
Fibroblasts Melanocytes UACC-62
Fig. 18. Lineage-dependent expression
and function of RAB7 in normal skin
cells. (a) Expression of RAB7 and βActin WB in three sets of human
primary skin cells isolated from the
same donor. (b) Depletion of RAB7 by
shRNA (3) in genetically matched
primary normal skin melanocytes and
fibroblasts, and in the melanoma cell
line UACC-62. (c) Relative increase in
cell number (means ± SEM) for the
indicated populations plated at equal
cell numbers at day 6-post infection
and cultured for four days. (d) Crystal
violet staining of the indicated cell
populations plated at equal cell
numbers at day 6-post infection and
cultured for ten days. (e) Percentage
of cells positive for lysosomal stress βGalactosidase assay at acidic pH
(means ± SEM). Representative
micrographs of the indicated cell
populations are shown in (f).
To investigate the functional role of RAB7 in normal cells, we expressed control or RAB7 shRNAs in
genetically matched melanocytes and fibroblasts (the latter as controls for non-melanocytic normal
cells). UACC-62 melanoma cells were included as a reference control (Fig. 18b). As shown in Figs. 18c
and d, fibroblasts were unaffected by complete depletion of RAB7, whereas the proliferation of
melanocytes was reduced. Nevertheless, melanocytes were affected to a lesser extent than melanoma
86
Results
cells by RAB7 dowregulation and showed no induction of lysosomal β-Gal staining (Figs. 18b-f). Overall,
these results suggest that melanoma cells may exploit (and depend on) proliferative roles of RAB7
already present in normal precursors, but acquire additional signals that impose an increased
dependence on this GTPase.
5. MELANOMA CELL MORPHOLOGY AND INVASIVE POTENTIAL CONTROLLED BY RAB7
Further analyses of RAB7-depleted cells revealed that RAB7 function did not only affect the proliferative
capacity of melanoma cells. Specifically, video-microscopy showed marked morphological changes in
RAB7-depleted melanoma cells, most frequently leading to increased filopodia or to prominent cytosolic
vacuolization (Fig 19a, and see Videos S1 and S2 showing the dynamic behaviour of representative
melanoma cell lines expressing mutant BRAF or NRAS, respectively). Morphological changes induced by
RAB7 downregulation in melanoma cells translated into an increased motility, which resulted in a
scattered growth pattern (see representative melanoma cell colonies in Figs. 19b,c). Interestingly, these
marked phenotypic changes were not observed in RAB7-depleted normal melanocytes, fibroblasts and
other tumor cells from 7 different cancer types (Figs. 19a-c).
Given the marked morphological changes and scattered growth pattern induced by RAB7
downregulation in melanoma cells, we next questioned whether RAB7 would control the invasive
capacity of these cells. Matrigel invasion assays revealed that RAB7 downregulation significantly
enhanced the invasive potential of moderately metastatic melanoma cell lines, yet this alone could not
confer de novo invasive capacities to non-invasive melanoma cell lines (Fig. 19d and results not shown).
Moreover, we found that the melanoma cell lines showing the highest metastatic potential were those
in which the basal RAB7 levels were constitutively lower compared to non-metastatic counterparts (Fig.
19e). Interestingly, this was not the case for other RAB GTPases, such as RAB-5, RAB-8 or RAB-11 (which
have roles in endocytosis, exocytosis, and endosome recycling, respectively, but are not directly linked
to lysosomal function312) (Fig. 19f).
These results suggested that RAB7 may represent a new class of melanoma “rheostats” that while being
required for tumor cell proliferation, can favor metastatic dissemination when downmodulated. To
extend the relationship between RAB7 expression and melanoma cell phenotypes, mRNA levels of RAB7
(along with the mRNA levels of other vesicle trafficking modulators) were analyzed across six
independently generated melanoma expression datasets344 in relation to two previously identified
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Results
expression signatures associated with melanoma “proliferative” or “invasive” phenotypes208. As
depicted in Fig. 19g, RAB7 levels were found to be positively correlated with the “proliferative”
signature and inversely correlated with the “invasive” gene set (p < 1.5 x10-8). Together, these results
show that RAB7 exerts opposing roles in melanoma cell proliferation and invasiveness.
a
b
Melanoma tumor cells
Mel1*
UACC-62
SK-Mel-28
WM-164
SK-Mel-29
SK-Mel-19
Melanocytes
CAL-62
Fibroblasts
SK-Mel-103
HCT116
shRAB7
shRAB7
shControl
shControl
SK-Mel-103* SK-Mel-147*
Non-melanoma tumor cells
A549
HCT116
U251
MiaPaca2
639V
HeLa
FTC-133
c
SK-Mel-103
shControl
Compact
***
shRAB7
Colonies (%)
100
HCT116
Loose
80
80
60
60
40
40
20
20
0
0
shCtrl shRAB7
Mel-1
SK-Mel-103
RAB11
RAB8
Adjusted combined p-value
0
0
RAB5
Melanoma Signatures
Mel-1
20
SK-Mel-103
SK-Mel-147
UACC-62
2
RAB7
SK-Mel-28
40
SK-Mel-29
4
shCtrl shRAB7
g
Melanoma cells
SK-Mel-19
60
SK-Mel-28
shRAB7(3)
shRAB7(2)
0
80
6
SK-Mel-147
0.5
8
UACC-62
1
RAB7 levels (Western Blot)
Invasiveness (Matrigel
Boyden Chambers)
SK-Mel-29
1.5
shControl
Invading cells (fold)
2
Relative protein levels
**
**
f
Invasive cells in 24h (%)
e
SK-Mel-19
d
Scattered
100
1E-23
“Invasive”
“Proliferative”
1E-18
1E-13
RAB7
1E-08
0.001
RAB27
β-Actin
-2.5
-1.5
-0.5
0.5
1.5
2.5
Log2 Average ratio
Fig. 19. Reduced RAB7 levels enhance melanoma cell invasiveness. (a) Representative micrographs showing morphological
changes induced by RAB7 shRNA(3) in melanocytic (top) and non-melanocytic (bottom) cells. NRAS-mutated melanoma cell
lines are marked with an asterisk. (b) Representative micrographs of colonies formed by the indicated cell populations of
melanoma (blue) and non-melanoma (black) cell lines. The quantification of cell scattering of three independent experiments
is shown in (c) (mean ± SEM). (d) Invasiveness of SK-Mel-28 melanoma cells expressing shControl or shRAB7 (constructs 2 and
3), evaluated by 48h matrigel invasion assay. (e) Inverse correlation of RAB7 protein levels and melanoma cell invasiveness. (f)
Relative expression of RAB7, RAB5, RAB11, RAB8, and RAB27 in the indicated melanoma cells, determined by WB. Highly
invasive melanoma cell lines (identified by matrigel invasion assay) are marked in green. β-actin immunoblot is shown as
loading control. (g) Volcano plot showing the expression of 110 vesicle trafficking gene probes (including RAB7, marked in red)
queried in parallel on six independent melanoma gene expression data sets. Shown is the average Log2 fold change (ratio of
gene probe expression in “proliferative”/“invasive” signatures, x axis) plotted against the adjusted combined p-value (Fisher's
combined probability analysis, y axis). High RAB7 mRNA levels significantly correlate with the proliferative signature (adjusted
combined p values p=4.9x10-11 and p=1.5x10-8, for RAB7 probes 211961_s_at and 211960_s_at, respectively).
88
Results
6. RAB7 IS AN EARLY-INDUCED MELANOMA DRIVER TUNED DOWN AT INVASIVE STAGES OF
TUMOR PROGRESSION IN VIVO
A corollary from the functional studies shown above was that the regulation of RAB7 along human
melanoma progression would differ from that of “classical” oncogenes, whose expression is either
sustained (i.e. BRAF388) or progressively increased (i.e., Myc389 or DEK390, 391). Instead, our data predicted
EMT-like expression patterns, such as those reported for MITF or CYCLIN D1 (CCND1). These are
melanoma oncogenes, but have been found to be downregulated at invasive stages195, 208, 214.
To address these possible scenarios and validate in vivo the roles for RAB7 identified herein using human
melanoma cell lines, we investigated RAB7 expression along the progression of human melanoma by
immunohistochemical analyses using TMAs containing biopsies from benign nevi and radial growth
phase (RGP), vertical growth phase (VGP) and metastatic melanomas (N=152 cases). Consistent with a
pro-oncogenic role for RAB7 in melanoma, this GTPase was found to be overexpressed in melanoma
specimens compared to benign nevi, being already induced in early-stage RGP specimens (Figs. 20a,b, p
< 0.001). However, RAB7 expression was not homogeneously expressed at all stages of melanoma
progression; it was seen to be significantly reduced at the RGP-to-VGP transition (Fig. 20b). This was
further confirmed by single cell analyses in whole-tissue primary sections of primary melanomas which
revealed a decreasing gradient of RAB7 expression towards the dermal-invading front of the tumor (Fig.
20c). Nonetheless, consistent with a lineage-addiction of melanoma to this factor, no RAB7-negative
melanoma tumor was identified, and those classified as “low-expressors” still expressed higher levels of
RAB7 than the surrounding stroma (marked with asterisks in Fig. 20a). Of note, the RAB7 levels were
found to correlate with CCDN1 (p < 0.001, N=88; see representative example in Fig. 20d), further
supporting an association between RAB7 and the proliferative potential of melanoma cells.
As the acquisition of metastatic properties by melanoma cells is associated with the RGP-to-VGP
transition180, 191-194, we further characterized the expression of RAB7 in primary melanoma in relation to
the best prognostic indicator of metastasis development, namely the depth of primary tumor invasion
or Breslow depth101. As shown in Fig. 20e, an inverse correlation between RAB7 expression and depth of
invasion was confirmed in an independent cohort of melanomas (p < 1.0 x 10-3, N=116). This prompted a
retrospective 10-year follow-up analysis to determine whether the levels of RAB7 expression in primary
melanomas could predict metastatic potential. This analysis demonstrated that patients with low
expression of RAB7 in the primary tumor have an increased risk for metastasis development and a
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Results
poorer overall survival (Fig. 20f; and Tables S6; N=112). Importantly, the value of RAB7 as an
independent prognostic indicator in melanoma was underscored by Breslow-adjusted analyses (Tables
S6). These results provide physiological relevance supporting the enhanced pro-invasive features
identified in vitro upon inactivation of RAB7 in melanoma cell lines.
d
e
*
*
RAB7
*
80µm
*
a*
’
*
c
’
b
’
d
’
50
0
*
80 µm
e
RAB7 signal / cell
Maximum
Medium
Low
Minimum
S100 negative cells (stroma)
Proportion of cases
c
500 µm
d
100%
Low
100
e
’
*
Medium
*** ***
Viscelral Mets (22)
Visceral
Metastasis
VGP (29)
*
High
Skin
Metastasis
Skin Mets (37)
a
RGP
VGP
(Non-invasive) (Invasive)
b
c
RGP (16)
Dermal
Nevus
b
MALIGNANT
MELANOMAS
Dermal Nevi (48)
BENIGN
LESIONS
TMA samples (%)
a
Low expression
High expression
N = (7)
(40)
(7) (22)
(30)
75%
50%
25%
0%
RAB7
Breslow Depth
f
1.00
Kaplan-Meier survival estimates
0.75
0.50
0.50
0.25
Low RAB7 expression
P = 0.001
0.00
CCND1
High RAB7 expression
0.75
0.25
Disease Free
Survival
1.00
0.00
F
0
2
0
Number at risk
rab7 = No 64
rab7 = Si 48
RAB7 High
RAB7 Low
500 µm
2
64
48
4
6
4analysis time6
52
42 Years36
35
22
15
52
42
36
rab7 = No
35
22
15
8
10
8
10
29
12
26
9
29
12
rab7 = Si
26
9
Fig. 20. RAB7 is an early-induced melanoma driver undergoing dynamic modulation in vivo. (a) RAB7 IHC (pink) in TMAs
representing the indicated human benign (a) and malignant melanocytic lesions (b-e). Asterisks mark stromal cells.
Quantification of RAB7 protein levels is shown in (b). The number of biopsies analyzed for each clinicopathologic stage is
indicated in parenthesis below the bar graph. (c) Confocal microscopy-based single cell analysis of mean RAB7 protein
expression in melanoma cells from a representative whole tissue VGP melanoma. Blue color represents stromal cells. (d)
Staining of RAB7 and CyclinD1 by IHC in consecutive sections of same tissue shown in (c). (e) Inverse correlation between
RAB7 levels and primary tumor thickness (Breslow Depth, in millimeters, mm). N indicates the total number of cases
analyzed in each group (p<0.001). (f) Kaplan–Meier curves showing 10-year disease-free survival (left) and 10-year overall
survival (right) following resection of primary melanomas, analyzed as a function of high vs low RAB7 protein levels.
90
Results
7.
HALTED
DEGRADATION
OF
NON-CANONICAL
AUTOPHAGOSOMES
AND
MACROENDOSOMES IN RAB7-DEPLETED MELANOMA CELLS
Next, we sought to understand the molecular basis underlying the melanoma-restricted and leveldependent roles of RAB7 in tumor cell proliferation and invasion. Given the pleiotropic functions of
lysosomal-related factors in the biology of cancer cells392, we investigated both the downstream
consequences and upstream regulators of RAB7 levels, as detailed in this and the following sections.
RAB7 is the RAB family member that regulates the biogenesis of lysosomes360 and the fusion of these
organelles to mature autophagosomes and late endosomes378-380 (see diagram in Fig. 9). As it was
selected from the melanoma-enriched lysosome cluster, we first assessed whether RAB7 inactivation
disrupted lysosomal function. Lysotracker (LTR) and DQ-BSA probes indicated that RAB7-depleted
melanoma cells were, in fact, not defective in the number and activity of lysosomes, respectively (Fig.
21a). Therefore, we next investigated the impact of RAB7 downregulation on autophagy and
endocytosis, as vesicles from these pathways are known to depend on this GTPase for their fusion to
lysosomes378-380. Immunoblot analysis of the autophagy marker LC3-II confirmed an accumulation of
autophagosomes in RAB7-depleted melanoma cells (Fig 21b). This was of relevance because melanoma
cells rely on active autophagy to sustain their proliferation274. However, downregulation of canonical
autophagy genes like BECLIN1265, 393, 394 did not recapitulate the phenotypic changes of RAB7-depleted
melanoma cells (Fig. 21c), suggesting the involvement of additional pathways. Consistent with this
hypothesis, microscopy imaging of a GFP-tagged LC3 revealed that it accumulated in unusually large
ring-shaped vesicles in RAB7-depleted melanoma cells, clearly distinct from the “classical” compact LC3
foci that are induced by treatment with rapamycin, a standard autophagy inducer (Fig. 21d). Moreover,
the accumulation of these large LC3-rings was not reverted by depletion of ATG7, a critical factor for the
formation of “classical” double-membrane autophagosomes (Fig. 21e).
To define the nature of the “non-canonical” large LC3-vesicles that accumulated upon RAB7 depletion in
melanoma cells, we considered three possible origins: (i) deregulated Golgi-derived endomembranes (ii)
homotypic fusions of smaller endosomes and/or (ii) large endocytic vesicles arising from the plasma
membrane395. Fluorescent videomicroscopy performed to investigate the dynamics of fluorescentlytagged LC3 and RAB7 on control (i.e. RAB7-expressing) melanoma cells unveiled that a large fraction of
LC3 is constitutively loaded into large (>1µm) pre-existing RAB7-positive vesicles originating from the
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Results
b
Lysotracker-Red
c
b
c
shRNA:
shControl
shBECLIN1
shControl
shRAB7
RAB7
DQ-Green-BSA
Ctrl
a
shControl
a
RAB7
shRAB7
LC3-I
c
LC3-II
α-Tubulin
20µm
GFP-LC3
siRNA:
shRAB7
Non infected
Ctrl
RAB7
e
e
dd
GFP-LC3
siATG7
siCtrl
RAB7
siRAB7 + siAtg7
shControl
shControl +
Rapamycin
siRNA:
Ctrl
ATG7
ATG7+ RAB7
18S
siATG7+ siRAB7
siRAB7
ATG7
RAB7
7.5 µm
7.5 µm
18S
ff
g
g
+15´
hh
GFP-RAB5
+20´
Lucifer Yellow
shCtrl
h
shRAB7
+10´
shCtrl
GFPRAB7
+5´
shRAB7
+0´
CherryLC3
LTR
blue
Merge
2 µm
Fig. 21. RAB7-dependent non-canonical autophagy in melanoma cells. (a-h) Representative examples in SK-Mel-103
untransduced or expressing control or RAB7 shRNA3 as indicated. (a) Confocal visualization of the acid-dependent
Lysotracker (red) and the proteolysis-dependent DQ-Green-BSA (green) fluorescent probes. (b) Changes in the
electrophoretic mobility of endogenous LC3 protein upon RAB7 downregulation. (c) Micrographs of cells expressing RAB7
or BECLIN1 shRNA , and their corresponding scrambled shRNA controls. (d) Fluorescence imaging of GFP-LC3 in the
indicated cell populations. (e, left) RT-PCR verification of siRNA-mediated downregulation of RAB7 and/or ATG7. (e, right)
Fluorescence imaging of GFP-LC3 in the indicated cell populations. Arrow mark non-canonical GFP-LC3 rings. (f) Snapshots
of live videomicroscopy of GFP-RAB7 (green), Cherry-LC3 (red) and Lysotracker (LTR) Blue (blue) in control SK-Mel-103 cells.
Arrows point to the initial images where the corresponding markers are recruited to pre-existing RAB7-positive
macroendocytic vesicles. Numbers indicate time-point intervals of 5 minutes. (g) Confocal visualization of the early
endosomal marker GFP-RAB5 (green) in the indicated cell populations. (h) Visualization of the fluid-phase endocytic marker
Lucifer Yellow (green) incorporated in control or RAB7-downregulated melanoma cells.
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Results
plasma membrane (Video S3). The recruitment of LC3 to large RAB7-positive vesicles occurred prior to
internalization and fusion to lysosomes, as shown by visualization of lysosomes using the LTR blue probe
(Fig. 21f). These large vesicles into which LC3 was loaded were suggestive of macroendocytic vesicles, as
they derived from originally large vesicles generated from plasma membrane ruffling (Video S3 and
results not shown). LC3-recruiting macroendosomes were confirmed by direct imaging of i) the early
endosomal maker, GFP-RAB5396,
397
, and ii) fluid phase tracers, such as Lucifer Yellow398 or 70kD-
Rhodamine-labeled dextrans, which also were found to massively accumulate in the cytosol of RAB7depleted melanoma cells (Figs. 21g,h and results not shown). Together, these data reveal that
melanoma cells exhibit a constitutively active “non-canonical” macroendocytic pathway which serves a
novel non-canonical autophagy route (i.e. not mediated by classical autophagy genes such as ATG7) and
is dependent on RAB7 for efficient lysosomal turnover.
8. DERAILED VESICLE TRAFFIC BY RAB7 DOWNREGULATION PROMOTES THE SECRETION OF
LYSOSOMAL PROTEASES
The role of the endolysosomal pathway in melanoma remains poorly characterized despite the fact that
its deregulation can impact diverse cellular processes (such as signal transduction, cytoskelal
organization, and motility, among others)399, 400 and is an emerging hallmark of cancer cells306. Therefore,
we next investigated cellular factors that could be deregulated by halted macroendocytosis in RAB7depleted melanoma cells. Cathepsins (CTS) are lysosomal proteases known to be sorted to the lysosome
via endosomes401, and were of interest because they were found herein to be enriched in the melanoma
lineage (Figs. 12a and S1) and are key effectors of tumor-cell invasion402. IF staining of CTS (shown for
CTS-B) revealed that RAB7 downregulation induced a change in their cellular distribution: control cells
exhibited a low and perinuclear staining for CTS, while cells lacking RAB7 showed CTS an accumulation
of CTS towards the cell periphery within the RAB5-positive macroendosomes (Figs. 22a,b). Lysosomal
CTS can also be detected extracellularly403, 404, where they degrade the extracellular matrix to promote
metastatic dissemination405,
406
. Thus, we next investigated whether the mislocalization of CTS upon
RAB7 downregulation could be coupled to their enhanced secretion. To this end, we incubated the
conditioned media from control and RAB7-depleted melanoma cells with the biotinylated activity-based
probe DCG-04, which binds a large fraction of active cathepsins and can be subsequently detected by
WB analysis357. This assay revealed increased levels of active extracellular CTS in the conditioned media
from RAB7-downregulated melanoma cells (Fig. 22c), which we additionally confirmed by WB analysis
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Results
for all individual CTS analyzed (see CTS-B, -D, -K, and –S in Fig. 22d). RAB7-depletion exerted these roles
independently of, and without affecting, basal MITF levels (Fig. 22d).
Comparison of melanoma and non-melanoma tumor cell lines showed that the particular
macroendocytic activity and the quantity of cathepsins in the intracellular and extracellular
compartments varied for each specific cell type (Fig. 22c-e and results not shown). However, nonmelanoma cell lines did not respond to RAB7 downregulation with the same burst of CTS secretion that
was identified in melanoma cells (see HCT116 in Figs 22c-e and two thyroid carcinoma cell lines and
HeLa cells in Fig 22e). This further supports a lineage-dependent wiring of endolysosomal pathways in
cancer and a particular dependence of melanoma cells on RAB7.
RAB5
CTS-B
b
Merge
RAB7
β-Actin
CTS-DCM
CTS-XCM
shRNA:
Ponceau CM
HCT116
FTC-133
CAL-62
HeLa
UCC-62
e
Ctrl
RAB7
Ctrl
RAB7
Ctrl
RAB7
Ctrl
RAB7
Ctrl
RAB7
Ctrl
RAB7
SK-Mel-28
CTS-SCM
CTS-B
CTS-D
CTS-BCM
CTS-B
CTS-X
CTS-S
RAB7
RAB7
MITF
α-Tubulin
β-Actin
94
Ctrl
-
RAB7
UACC-62
SK-Mel-28
-
RAB7
-
Ctrl
RAB7
HCT116
CTS-BCM
Ctrl
shRNA: -
DCG-04CM
Ponceau CM
Intracellular
SK-Mel-103
shRAB7
RAB7
-
Ctrl
RAB7
-
d
SK-Mel-28
Extracellular
Extracellular
shRNA:
Ctrl
HCT116
Extracellular
UACC-62
shControl
shControl
shRAB7
c
Intracellular
SK-Mel-28
CTS-B
Intracellular
a
Fig.22. Mislocalization of
lysosomal proteases upon
RAB7 downregulation. (a)
RAB5 (green) and cathepsin
(CTS)-B (red) double-IF in
shControl and shRAB7 SK-Mel28 melanoma cells. (b) IF
staining of CTS-B in the
indicated
melanoma
cell
populations. Arrows mark the
enriched
distribution
of
cathepsin B-positive large
vesicles towards the cell
periphery in RAB7-depleted
cells.
(c-e)
Immunoblot
analyses in conditioned media
(CM) or total cell extracts from
the indicated non-melanoma
(black) and melanoma (blue)
cell lines, expressing control or
RAB7 shRNA, and probed with
biotinylated DCG-04 or the
indicated antibodies.
Results
9. GLOBAL CHANGES IN GENE EXPRESSION AND PROTEIN SECRETION PROGRAMS BY
MODULATION OF RAB7 LEVELS
Vesicle trafficking can impact multiple cellular processes, including signaling cascades306,
399, 400
.
Therefore, RNA sequencing (RNA seq) and GSEA was performed in control and RAB7-downregulated
melanoma cells to identify potential processes affected by RAB7. The cell line HCT116 was used as a
non-melanoma reference to further assess tumor type-specific responses to RAB7 depletion in cancer.
The rationale for this approach was to avoid oversimplifications that would necessarily result from
single-gene studies, as membrane trafficking factors are inherently pleiotropic and have the potential of
interfering with multiple signaling cascades
306, 407
. Moreover, as transcriptomic profiling has not been
reported before upon interfering with RAB7 expression, we expected to provide new insights on the
pathways that depend on the action of this GTPase. Transcriptomic changes were analyzed at early time
points (day 3 after shRNA transduction) in order to search for deregulated pathways with a likely driver
role in shRAB7-driven phenotypes (instead of byproducts of altered cell cycle arrest and morphological
alterations).
Numerous genes and pathways with key roles in tumor cell proliferation and invasiveness were found to
be deregulated by RAB7 downregulation in melanoma cells. Consistent with the functions of RAB7
identified by functional assays, a large fraction of the significantly inhibited genes (FDR<0.05) by RAB7
downregulation clustered in proliferation-related GO-categories (e.g. cell cycle progression, mitosis, and
cytokinesis). In turn, significantly up-regulated genes were found to be involved in invasion-related
pathways (e.g. cell-adhesion, motility, and extracellular matrix remodeling) (see Fig.23a for the GOcategorization of the significantly deregulated genes found in the UACC-62 melanoma cell line, and
Table S7 for GSEA results in all three cell lines analyzed). Notably, RAB7 depletion also lead to
alterations in the transcriptome of HCT116, but these changes were either less significant or even
opposite to the effects in melanoma cells (see GSEA results in Table S7), perhaps reflecting
compensatory responses.
To validate the RNA sequencing data, we specifically selected deregulated genes or pathways that are
known to be critical for melanoma maintenance or metastatic progression. The downregulation of the
E2F1 cascade (Fig. 23b), which is essential for melanoma proliferation408, was confirmed by immunoblot
analyses that showed a reduced expression of the E2F1 cofactor, TFDP1409, and the downstream cell
cycle effectors, CDC2, CDC6 and AURKB, in RAB7-depleted melanoma cells (Fig. 23c, left panels). In
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Results
addition, we showed the induction of CEACAM1, a clinically relevant pro-metastatic melanoma gene410413
, in RAB7-downregulated melanoma cells (Fig 23c, right panel). Of note, CEACAM1 has also been
found to be upregulated in thick VGP melanomas of poor prognosis183, 413.
Downregulated
Upregulated
shRNA:
cell cycle
cytokinesis
chromosome segregation
cellular component organization
cell communication
cell motion
cell adhesion
RAB7
shRNA:
CEACAM1
β-Actin
TDFP1
Fibronectin CM
CDC2
CDC6
Hsp70CM
AURKB
GAPDH CM
Nucleolin
Ponceau CM
b
Ctrl
RAB7
Ctrl
RAB7
Ctrl
RAB7
c
Ctrl
RAB7
Ctrl
RAB7
Ctrl
RAB7
a
d
0.1
0.0
-0.1
-0.2
-0.3
-0.4
-0.5
-0.6
-0.7
Ranked
gene list
RAB7 KD
Negatively
correlated
Paxillin
shRAB7
shControl
Example
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0.0
RAB7 KD
Positively
correlated
Phalloidin
shControl
shRAB7
MEMBRANE TRAFFICKING
RAB7 KD
Positively
correlated
RAB7 KD
Negatively
correlated
Average
Enrichment
score (ES)
E2F PATHWAY
10 µm
N = 20
Fig. 23. Molecular consequences of RAB7 downregulation in melanoma (vs non-melanoma) cell lines. (a) Pie chart
representing the distribution of the significantly down- and up-regulated genes (FDR<0.05) upon RAB7 downregulation in
UACC-62 melanoma cells, according to GO-cellular process categorization. (b) Enrichment plots showing representative
examples of significantly downregulated (left panel, FDR = 5.48E-04) and upregulated (right panel, FDR = 0.016) pathways in
shRAB7 UACC-62 melanoma cells, identified by GSEA. (c) Immunoblot analyses in cell lysates to validate the opposing effect
of shRAB7 on the levels of cell cycle regulators (TFDP1, CDC2, CDC6); left) and of the pro-invasive factor CEACAM1 (right) in
melanoma cells (labeled in blue). HCT116 colon cancer cells (labeled in black) are included as non-melanoma controls. Also
shown are the immunoblot analyses in CM showing an enhanced secretion of the indicated proteins in shRAB7 melanoma
cells (right). Ponceau S staining of proteins from the CM and nucleolin blot of cell lysates are shown as loading controls. (d)
Representative examples (upper panels) and average stainings from 20 randomly-selected cells per condition (lower panels)
of SK-Mel-103 shControl and shRAB7 cells plated on crossbow-shaped fibronectin micropatterns (CYTOO-chips) and stained
for actin (phalloidin) and focal adhesions (paxillin). The polarized cortical actin organization and large focal adhesions
visualized in control but not in shRAB7 cells are marked with dashed lines and arrows, respectively.
RNA sequencing also predicted an upregulation of several pathways involved in membrane trafficking,
protein secretion, and extracellular matrix remodeling upon RAB7 downregulation in melanoma cells
(Figs 23a,b and Table S7). Thus, we performed additional proteomic analyses in the conditioned media
(CM) from RAB7-expressing and RAB7-downregulated melanoma cells. This revealed that reduction of
RAB7 levels enhances the secretion of a series of factors involved in tumor-cell invasiveness and immune
modulation, namely fibronectin414,
415
, HSP70200,
416
, and GAPDH (exosome maker200) (Fig. 23c, right
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Results
panels), broadening the secretory phenotype from the initially identified lysosomal cathepsins. Finally,
cytoskeletal reorganizations induced by RAB7 downregulation were visualized by direct assessment of
cortical actin and focal adhesions (by means of staining with phalloidin and paxillin, respectively) using
bow-shaped CYTOOchip assays356 (Fig. 23d).
Together, these data provide molecular evidence to further support the lineage-dependent impact of
RAB7 function in cancer and reveal novel specific downstream effects of RAB7 on the transcriptome and
the proteome of melanoma cells.
10. UPSTREAM REGULATION OF RAB7 BY MELANOCYTE DEVELOPMENTAL PATHWAYS
Characterization of the pathways deregulated upon RAB7 knockdown provided molecular evidence
supporting the dual (and opposing) roles of RAB7 in melanoma cell proliferation and invasiveness, as
well as its lineage-dependent impact on cancer cell phenotype. Still, an unanswered question remained
why RAB7, which is ubiquitously expressed in different normal and tumor cells, was specifically enriched
and dynamically regulated in melanoma cells.
We were intrigued by the fact that RAB7 expression was not controlled by MITF (Fig. 15), the best
characterized melanocyte-lineage transcription factor241,
254
and a key regulator of melanoma cell
phenotype171, 417, described to have oscillatory expression patterns along melanoma progression207, 208,
214
. The expression analyses of RAB7 and MITF presented above showed that, although RAB7 is
expressed in MITF-negative cells, high MITF-expressing melanoma lines invariably expressed high levels
of RAB7, suggesting that both factors could share a common upstream regulator. Thus, we next studied
whether additional melanocytic transcription factors functioning upstream of MITF, namely PAX3 and
SOX10241, 418, 419, could be regulating RAB7 expression levels in an MITF-independent manner. SiRNAmediated inactivation of PAX3 or SOX10 revealed that RAB7 expression was minimally affected by PAX3
siRNA (Fig. 24a and results not shown). In contrast, SOX10 siRNA effectively reduced RAB7 mRNA as
efficiently as its inhibition of MITF (Figs. 24a,b). SOX10-mediated regulation of RAB7 was confirmed at
the protein level in all melanoma cell lines tested (Fig. 24c). Interestingly, SOX10 expression mimicked
that of RAB7, as it was also retained in MITF-negative melanoma cells (Fig. 24d) and was found
expressed at lower levels in highly invasive cell lines (Fig. 24d). Whether SOX10 controls RAB7 mRNA
directly or indirectly needs further analysis as no consensus binding sites were identified for this
transcription factor in the RAB7 promoter. Nevertheless, these data illustrate a novel lineage-dependent
regulation of RAB7 and uncover a novel branching of developmental pathways in melanoma, whereby
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Results
tumor type-dependent drivers can be expressed and act in an MITF-independent manner. Moreover,
these results suggest that the decreased levels of RAB7 found in highly invasive stages of tumor
progression might stem from the acquisition of a more dedifferentiated status by melanoma cells.
1
0.8
siSOX10
siControl
RAB7 SOX10 PAX3
SOX10
0.6
0.4
RAB7
0.2
MITF
0
siControl
siPAX3
18S
siSOX10
SOX10
RAB7
RAB7
SOX10
MITF
MITF
β-Actin
α-Tubulin
Mel-1
SK-Mel-147
SK-Mel-103
SK-Mel-28
UACC-62
siSOX10
siControl
siSOX10
siControl
siSOX10
siControl
siSOX10
siControl
SK-Mel-19
d
c
Sk-Mel-29
Relative mRNA levels
(fold to siControl)
1.2
siControl
b
siSOX10
a
Fig. 24. SOX10-dependent regulation of
RAB7 in melanoma cells. (a) qRT-PCR
analyses of RAB7, SOX10 and PAX3 mRNA
levels in UACC-62 melanoma cells expressing
(siControl), SOX10 (siSOX10), or PAX3
(siPAX3) siRNAs. (b) RT-PCR analyses of
SOX10, RAB7 and MITF mRNA levels in the
indicated melanoma cell lines expressing
control (siControl) or SOX10 (siSOX10)
siRNAs. (c) Impact of SOX10 siRNA (siSOX10)
on SOX10, RAB7 and MITF protein levels
analyzed by western blot in the indicated
melanoma cell lines. α-Tubulin is shown as
loading control. (d) Immunoblots of total
cell extracts isolated from indicated
melanoma cell lines and probed for basal
RAB7, SOX10, and MITF. α-Tubulin is shown
as loading control. Highly invasive melanoma
cell lines are highlighted in green.
11. REGULATION OF RAB7 EXPRESSION AND FUNCTION BY ONCOGENIC SIGNALING
PATHWAYS IN MELANOMA CELLS
The identification of RAB7 as a new functional target of SOX10 revealed an unexpected interplay
between lineage-specification and the endolysosomal machinery of melanoma cells. However, this could
not explain the enriched levels of RAB7, and increased dependence to this factor, observed in malignant
melanocytic cells (Figs. 18 and 19a). This suggested that oncogenic pathways may additionally modulate
this GTPase in melanoma. To address this possibility, we assessed whether oncogenic signaling
frequently activated during melanomagenesis contributed to RAB7 regulation and function.
Using pharmacologic inhibitors of the most frequently activated oncogenic signaling pathways in
melanoma, we found that the Class I phosphoinositide 3-kinase (PI3K) inhibitor LY294002 significantly
inhibited RAB7 protein levels (Fig. 25a). This was not the case for inhibitors of the MAPK pathway (data
not shown). Class I PI3K inhibitors were also found to efficiently revert the accumulation of cytosolic
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Results
vacuoles and enhanced cathepsin secretion observed in RAB7-downregulated melanoma cells (Figs.
25b,c), indicating that PI3K signaling regulates both the expression and function of this vesicle trafficking
regulator. Consistently, Class I PI3K inhibitors also abrogated melanoma-cell basal macroendocytic
uptake (Fig. 25d). In addition, pharmacologic (by 3-MA treatment) and genetic (by VPS34 siRNA)
inhibition of PI3KC3, a critical effector of macroendocytosis420, also reverted shRAB7-driven phenotypes
in melanoma cells (Figs. 25e,f and results not shown). Although PI3KC3 also regulates classical
autophagy, ATG7 siRNA did not affect shRAB7-driven vacuolization, further supporting a major
contribution of non-canonical autophagy to the phenotypic changes induced by RAB7 downregulation in
melanoma cells (Figs. 25e,f).
c
SK-Mel-28 UACC-62 SK-Mel-103
α-Tubulin
ETP-46992
shRNA:
LY294002:
RAB7
β-Actin
- - + +
- -
+ + - -
+ +
CTS-B
shRAB7
SK-Mel-103
ETP-38
Ctrl
RAB7
Ctrl
RAB7
RAB7
LY294002
Ctrl
RAB7
Ctrl
RAB7
Ctrl
RAB7
Ctrl
RAB7
Non Treated
shControl
NT
b
LY294002
a
CTS-D
Ponceau
SK-Mel-28
**
70kD-Rhd-Dextran
f
*
4
***
2.0
0
1.0
0
1.0
0
0.0
0
0.0
0
***
3
2
siCtrl
siRAB7
2.0
0
Vacuolized cells
(fold increase)
Uptake / cell (AFU)
Lucifer Yellow
ns
5
1
0
siCtrl
siVPS34
siVPS34 + siRAB7
e
siCtrl
SIATG7
SIATG7 + SIRAB7
d
ATG7
VPS34
RAB7
RAB7
RAB7
18S
18S
18S
Fig. 25. Class I/III PI3K-dependent regulation of RAB7 in melanoma cells. (a) Immunoblots of total cell extracts isolated
from the indicated melanoma cell line treated with LY294002, 3-MA or vehicle control (NT) for 24h, and probed for RAB7.
α-Tubulin and β-Actin are included as loading controls. (b) Bright field micrographs of shControl and shRAB7 SK-Mel-103
cells in the presence and absence of three different Class I PI3K inhibitors (LY294002 and ETP-46992 are pan- Class I PI3K
inhibitors, whereas ETP-38 is a specific Class I PI3K α,δ inhibitor). (c) Immunoblot analyses of CTS-B and –D in conditioned
media from the indicated melanoma populations in the presence and absence of LY294002. (d) Confocal-based
quantification of the uptake of Lucifer Yellow (left) and 70kD Rhodamine-Dextran (right) by SK-Mel-103 melanoma cells
treated with LY294002 vehicle control (NT). (e) Impact of control- (siCtrl), VPS34- (siVPS34) and ATG- (siATG) siRNAs, on
siRAB7-induced cytosolic vacuolization. (f) RT-PCR verification of siRNA-mediated knock-down of VPS34 (C3PI3K), ATG7
and RAB7 for the same cell populations shown in (e).
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Results
Together, these results demonstrate an additional level of regulation of RAB7 by oncogenic signaling,
and a critical contribution of PI3K-driven macroendocytosis to RAB7-dependent phenotypes in
melanoma. This is important because normal melanocytes, positive expressors of both SOX10 and RAB7,
were not found to exhibit constitutively active macroendocytic trafficking (Fig. 26a).
12. ACTIVATION OF ONCOGENIC SIGNALING IN NORMAL MELANOCYTES DEREGULATES RAB7
AND ITS ASSOCIATED VESICLE TRAFFICKING PATHWAYS
Once determined that PI3K induces RAB7 and its associated vesicle trafficking pathways in melanoma
cells, we set to determine whether this is an early trait in tumor development. To this end, primary
human melanocytes were transduced with oncogenes frequently activated in melanocytic lesions
(HRASG12V, NRASQ61R, NRASG12V and BRAFV600E)160. Oncogenic H/N-RAS mutants, direct triggers of PI3K
activation, were found to activate RAB7-dependent macroendocytosis and recapitulate the trafficking
features identified in melanoma cells. This was demonstrated by i) activation of uptake of
macroendocytic tracers, like 70kD-Rhodamine Dextran (Fig. 26b); ii) mobilization of RAB7 to large
macroendosomes (Fig. 26c) and iii) time-lapse videomicroscopy, which clearly showed an active
generation of macropinosomes from actin-driven membrane ruffling in RAS-expressing melanocytes
(Video S4). Importantly, modulation of MEK/ERK signaling alone activated endocytosis, although it was
not sufficient to mimic PI3K-driven macropinocytosis (results not shown).
Interestingly, primary human melanocytes expressing the oncogenic forms of RAS failed to upregulate
RAB7 levels and, as reported85, activated premature oncogene-induced senescence (OIS), driven by PI3K
and associated with massive cytosolic vacuolization (Fig. 26d,e). Therefore, we proceeded to ectopically
overexpress and inhibit RAB7 function in order to assess whether this factor could be participating in
melanocyte OIS. Overexpression of wild-type RAB7 (Fig. 26e) significantly abrogated SA-β-Gal staining
and resolved the massive cytosolic vacuolization observed in control cells (Fig. 26f-h). Conversely,
overexpression of the dominant negative mutant of RAB7 strikingly induced the number and size of RASdriven macropinosomes (Fig 26g and results not shown), recapitulating the morphological phenotypes
observed in RAB7-inhibited NRAS-mutated melanoma cells. Together, these results show that increased
RAB7 levels prevent aberrant accumulation of PI3K-driven macroendosomes, which suggests a possible
additional, pro-oncogenic role for this trafficking regulator in tumor initiation, particularly by
counteracting oncogenic stress acquired during malignant transformation of melanocytes.
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Results
a
a
SK-Mel-103
(NRASQ61R )
UACC-62
(BRAFV600E)
HRASG12V
Empty vector
70K Rdh-Dextran
SK-Mel-103
Bright Field
Melanocytes
b
b
dd
Vacuolized
cells (%)
RAB7
30
20
10
3.36 µm
RAB7 WT
RAB7 T22N
NRASQ61R
Vector
GFP-RAB7 WT
GFP-RAB7 T22N
Vector
GFP-RAB7 WT
GFP-RAB7 T22N
Vector
GFP-RAB7 WT
GFP-RAB7 T22N
Vector
GFP-RAB7 WT
GFP-RAB7 T22N
Vector BRAFV660E HRASG12V NRASQ61R NRASG12V
Vector
GFP-RAB7 WT
GFP-RAB7 T22N
Vector
BRAFV600E
SA-β-Gal
positive cells
(%)
0
80
60
40
20
0
3µm
ee
ef
DMSO
LY294002
U0126
Vector
HRASG12V
HRASG12V
cc
NRASG12V
BRAF
Pan-RASectopic
Pan-RASendogenous
GFP-RAB7ectopic
RAB7endogenous
α-Tubulin
hh
pLV Vector
GFP-RAB7 WT
20
15
10
5
NRASG12V
NRASQ61R
0
HRASG12V
***
GFP-RAB7 T22N
25
BRAFV600E
***
> 12
Diametr of vacuoles (µm)
30
Vector
SA-Β-Gal positive celss (%)
g
g
10
8
6
4
2
0
Vector RAB7 RAB7
WT T22N
101
Fig. 26. Activation of RAB7dependent vesicle trafficking
driven by PI3K signaling in
primary human melanocytes
expressing RAS oncogenes. (a)
Uptake of 70 kD RhodamineDextran in melanocytes and
representative melanoma cell
lines of the indicated genetic
backgrounds. (b) Bright field and
fluorescence
micrographs
showing the activation of 70kD
Rhodamine(Rhd)-Dextran uptake
in control and oncogenic RASexpressing
melanocytes.
(c)
Confocal
immunofluorescence
microscopy of RAB7-positive
macropinocytic
vesicles
in
oncogenic
RAS-expressing
melanocytes. (d) β-Gal-positive
and vacuolized cells in vector- or
HRASG12V- expressing melanocytes
treated as indicated (see details in
Materials and Methods). (e)
Immunoblot analyses of total cell
extracts
isolated
from
melanocytes co-expressing the
indicated oncogenes and wildtype (WT) or dominant negative
(T22N) GFP-RAB7, or their
corresponding
empty vector
controls, and probed for the
indicated
antibodies.
(f)
Representative
micrographs
showing the effect of RAB7 wildtype (WT) or dominant negative
(T22N)
overexpression
on
senescence
associated
βgalactosidase
staining
and
cytoplasmic
vacuolization
in
primary melanocytes expressing
oncogenic mutants of BRAF, HRAS
and NRAS. The quantification of βgalactosidase positive cells is
summarized in (g). (h) Dot plot
showing the impact of RAB7 wildtype (WT) or dominant negative
(T22N) overexpression in the size
of HRASG12V-induced vacuoles
(vacuoles of ≥1µm in diameter
were individually measured).
Results
13. ONCOGEN-DRIVEN ACTIVATION OF RAB7 IN VIVO
To validate in vivo the activation of RAB7 and macroendocytosis by oncogenic signaling, both events
were studied in two different genetically-modified melanoma mice models that involve the activation of
PI3K signaling: (i) the transgenic system Tyr:NrasQ61K; Ink4a/Arf-/-, expressing NrasQ61K in the melanocytic
lineage in the context of Ink4a/Arf deficiency421; and (ii) the inducible Tyr::CreERT2;BrafCA;PTENfl/fl), a
knock in model driving active BrafV600E expression and Pten deletion also in melanocytic cells165, 421. High
magnification confocal imaging of RAB7 IF staining confirmed large macroendocytic vesicles in early
malignant melanomas generated in both melanoma models, but not in the surrounding non-melanocytic
stroma (Fig. 27a, compare RAB7 staining in S100/melanocytic marker-positive and -negative cells).
Tyr:NrasQ61K; Ink4a/Arf-/-
Tyr::CreERT2;BrafCA;Ptenfl/fl
RAB7
a
S100 -
1µm
1µm
S100+
S100 -
1µm
1µm
Merge
S100
S100+
5µm
5µm
PRIMARY MELANOMA
NORMALSKIN
RAB7
bb
1.59µm
0.84µm
Merge
S100
1.28µm
25µm
7.5µm
25µm
SPITZ NEVUS (HRASG12V)
7.5µm
COMPOUND NEVUS (BRAFV600E)
1.50µm
RAB7
1.80µm
Merge
S100
1.33µm
25µm
7.5µm
25µm
7.5µm
102
Fig. 27. Confocal visualization of
putative
oncogene-driven
RAB7positive macropinosomes in vivo. (a,b)
Co-staining of RAB7 (red) and S100
(green) in paraffin-embedded sections
of the indicated melanoma mouse
models (a) of human melanocytic
lesions
(b). Melanocytic cells are
marked by positive S100 staining. Note
in (a) the differential levels and cytosolic
distribution of RAB7 in melanocytic
lesions (S100 positive, S100+) versus
stromal cells (S00 negative. S100-). In
(b), dotted lines separate melanocytic
lesions from the stroma, negative for
the melanocytic marker S100. The size
of
representative
RAB7-coated
macroendocytic vesicles visualized in
lesions harbouring active PI3K signaling
(i.e. melanomas and HRASG12V-Spitz
nevus) is also indicated.
Results
Importantly, RAB7-positive macroendosomes were not just a feature of mouse melanomas. Putative
RAB7-positive macropinosomes were also detected in human melanoma biopsies but not in normal skin
melanocytes or in compound nevi (harbouring oncogenic BRAF) (Fig. 27b). In contrast, they were found
to be massively accumulated in melanocytic cells from Spitz nevi (linked to mutated HRAS), confirming
evidence obtained in vitro with RAS-induced senescent melanocytes (Fig. 27b). These results provide
physiological evidence of the direct involvement of this GTPase in the active turnover of macroendocytic
vesicles generated by the activation of PI3K signaling during melanoma development.
14. MODULATION OF RAB7-ASSOCIATED ENDOLYSOSOMAL VESICLE TRAFFICKING BY
TREATMENT WITH dsRNA-BASED NANOCOMPLEXES
The results presented above demonstrated RAB7 as a novel downstream effector of melanocytic lineage
commitment (SOX10) and oncogenic signaling pathways (PI3K), which melanoma cells deploy in order to
favor cancer progression. In addition, we showed that melanoma cells exhibit an enhanced influx of
RAB7-driven macropinocytosis, which is not found in normal cells. Therefore, we next questioned
whether the differential wiring of RAB7-dependent endolysosomal pathways in melanoma could
represent a novel window for therapeutic intervention.
To explore the potential therapeutic implications of RAB7-mediated vesicle trafficking, we next used SKMel-103 melanoma cells stably expressing constitutive levels of GFP-tagged RAB7 to screen for
anticancer agents with different modes of action that could be targeting the endolysosomal machinery.
Multiple drugs were found to deregulate RAB7-associated vesicle trafficking, without significantly
affecting cell viability (i.e. cyclopamine, a specific Hedgehog signaling pathway antagonist of
Smoothened, Smo)422) (Fig 28a). However, death inducers were also found. In particular, dsRNA mimic
polyinosine-polycytidylic acid423 complexed with the cytosolic carrier polyethyleneimine (PEI)424 ([pIC]PEI)
was found to induce a potent mobilization of RAB7 (Fig. 28a) and was associated with large vesicular
structures visualized by electron microscopy (Fig. 28b). These results were intriguing as pIC had been
linked to the activation of autophagy in immune cells425, but not in the context of tumor cell death.
Therefore, we next investigated the cellular machinery responsible for sensing [pIC]PEI and executing the
cytotoxic response of melanoma cells to [pIC]PEI.
103
Results
a
a
NT
[pIC]PEI
(dsRNA mimmic)
U0126
(MEK inh)
TW-37
(Mcl-1 inh)
bb
Control
[pIC]PEI
20 µm
[pIC]PEI
Bortezomib
(Proteasome inh)
Cyclopamine
(Smo inhibitor)
Doxorubicin
(DNA damaging)
SB202190
(p38 inh)
500 nm
Fig. 28. Drug-induced mobilization of melanoma cell RAB7-dependent trafficking (a) Confocal microscopy images
showing the deregulation of GFP-RAB7 upon treatment with the indicated agents for 8h (see additional details in
Materials and Methods section) (b) Representative bright field (top panels) and electron microscope (bottom panel)
micrographs of SK-Mel-103 treated with 1µg/mL [pIC]PEI for 30 h.
15. RAB7-MEDIATED VESICLE TRAFFICKING IS ACTIVELY INVOLVED IN THE ANTI-MELANOMA
ACTIVITY OF dsRNA-BASED NANOCOMPLEXES
Enlarged RAB7-positive vesicles could result either from an increased generation (influx) of RAB7dependent trafficking, or by abrogation of lysosomal function. In the second scenario, vesicles would
grow in size as a consequence of accumulation of improperly degraded material. This was ruled out by
confirmation of i) an effective recruitment of lysosomes to the large RAB7-positve vesicles, by
videomicroscopy of fluorescently tagged RAB7 and lysotracker-stained lysosomes (Fig. 29a), and ii)
functional lysosomal proteolytic activity, using the DQ-BSA probe (Fig. 29b). Time-lapse videomicroscopy
consistently revealed a massive hyperactivation of RAB7-positive macroendosomes in tumor cells
treated with [pIC]PEI (Fig. 29c). The mobilization of the endolysosomal machinery by [pIC]PEI occurred
along with activation of the classical and the “non-canonical” endosome-mediated autophagy (Fig 29d
and results not shown).
104
Results
Lysotracker
b
Merge
DQ-BSA
Merged
Chloroquine
[pIC]PEI
[pIC]PEI
5s
9s
27s
NT
+95’
+90’
+130’
+100’
+95’
+140’
+100’
+145’
+110’
+105’
+150’
+115 ’
+110’
+155’
+120’
+115’
+160’
+125’
+120’
+170’
5 µm
10 µm
97s
d
60+95’
[pIC]PEI
GFPRAB7
+125’
94s
+105’
Cherry-LC3
+85’
5 µm
81s
[pIC]PEI
60+90’
+105’
54s
+130’
LTR-blue
0s
+150’
+5´
Merge
[pIC]PEI
c
Lysotracker
Control
GFP-RAB7 WT
NT
a
+25´
+45´
5 µm
Fig. 29. [pIC]PEI enhances RAB7-mediated macroendocytic trafficking. (a) SK-Mel-103 cells stably transfected with GFPRAB7 WT treated with [pIC]PEI (1µg/mL,8h) were incubated with Lysotracker-Red for visualization of RAB7 (green) and
lysosomes (red). The lower sequence of confocal microphotographs taken at the indicated time intervals (in seconds)
illustrates the incorporation of lysosomes to RAB7-positive vesicles. (b) DQ-BSA (Green) emission in control, [pIC]PEI
(1µg/mL,8h) or Chloroquine (20µM,5h) treated SK-Mel-103 cells. Lysotracker-Red stains the lysosomal compartment. (c)
Sequential images of control or [pIC]PEI-treated SK-Mel-103 melanoma cells expressing GFP-RAB7, captured at indicated
time intervals (in minutes). Cells were imaged 1h after treatment with [pIC]PEI (1µg/mL) or control vehicle. (d) Fluorescence
visualization of non-canonical autophagy in [pIC]PEI-treated SK-Mel-103 cells expressing Cherry-LC3 (red), GFP-RAB7 (green)
and incubated in the presence of Lysotracker (LTR) (blue) to detect autophagosomes, endosomes and lysosomes,
respectively (arrows mark the first images where the corresponding markers can be visualized).
105
Results
To demonstrate a lysosomal-dependent mode of action of [pIC]PEI, we pre-incubated melanoma cells
with several agents that block lysosomal function: the lysomotropic agent, chloroquine; broad spectrum
protease inhibitors, E64d and pepstatin A; and the vacuolar ATPase blocker, bafilomycin. Surprisingly, all
of these agents protected melanoma cells against [pIC]PEI-driven cell death (Fig. 30a). In addition, we
tested and confirmed a protective effect of pre-treatment with pharmacological blockers of the early
stages of the endocytic, macroendocytic and autophagic pathways, namely Class I PI3K and Class III PI3K
inhibitors (LY294003 and 3-MA, respectively) and EIPA, an inhibitor of the Na+/H+ exchanger that
specifically inhibits macropinocytosis426 (Fig. 30b). Together, these results show that the mobilization of
endolysosomal compartments is actively involved in the anti-melanoma activity of [pIC]PEI.
Importantly, [pIC]PEI was found to act in a tumor-cell selective manner, as it resulted innocuous for
normal melanocytes (Fig. 30e). Preliminary results support that the differential activity of
endolysosomal trafficking between normal and tumor cells might underlie this selectivity. Consistent
with an endolysosomal attenuated activity in normal melanocytes compared to melanoma cells (shown
in Fig. 27), normal cells exhibited negligible uptake of fluorescently labeled- [pIC]PEI (Fig. 30d).
Interestingly, preliminary data showed that activation of oncogenes in normal melanocytes can activate
the uptake of [pIC]PEI (Fig. 30d) and make them responsive to this agent (Fig. 30e).
Finally, other members of the laboratory demonstrated that, in addition to the mobilization of vesicle
trafficking pathways, [pIC]PEI induced: i) a subsequent activation of apoptotic cell death triggered by the
dsRNA sensor MDA5, NOXA, and caspases, and ii) a potent antitumor activity in vivo (see Fig. 35 in the
discussion section). Together, these results served as the proof-of-principle for the ability of [pIC]PEI to
drive tumor-cell selective cell death by coordinated targeting of lysosomal and apoptotic mechanisms.
Moreover, they demonstrate that re-wired endolysosomal pathways represent a point of vulnerability
of tumor cells that could be exploited therapeutically to enable selective drug uptake and cell death.
106
Results
a
c
75
SK-Mel-103
UACC-62
Melanocytes
UACC-62
SK-Mel-28
NT
NT
[pIC]PEI
Melanocytes
50
25
[pIC]PEI
Dead Cells (%)
100
Ctrl Bafil Chlor
NT
b
PEP
[pIC]PEI
d
FG12 vectortransduced
melanocytes
HRASG12Vexpressing
melanocytes
Merge
DMSO
[pIC]PEI-Rhd-labeled
LY294002
EIPA
e
FG12 vector
HRASG12V
BRAFV600E
NRASQ61R
NRASG12V
[pIC]PEI
NT
Non infected
Fig. 30. Endolysosomal trafficking can be targeted by [pIC]PEI to induce tumor-cell selective cell death (a) Inhibitory effect of
1h-pretreatment with 100 µM Bafilomycin (Bafil), 20 µM Chloroquine (Chlor) or 10µg/ml Pepstatin (PEP) on cell death
estimated by trypan blue 20h after treatment with vehicle (white bars) or 1µg/mL [pIC]PEI (black bars). (b) Inhibitory effect of
5h-pretreatment with 10µm LY294402 and 10µM EIPA (on cell death estimated by crystal violet staining of viable cells 48h
after treatment with vehicle or 1µg/mL [pIC]PEI. (c) Representative bright field images of normal melancoytes and the
indicated melanoma cell lines after 48h after treatment with vehicle or 0.5µg/mL [pIC]PEI. (d) Analysis of the uptake of [pIC]PEI
by confocal visualization of pIC complexed with a rhodamine (Rhd)-labeled PEI in UACC-62 melanoma cells, normal
melanocytes, and melanocytes expressing FG12 empty vector or oncogenic HRAS (at day 5 post-infection). Cells were
incubated with 0.5ug/mL labeled-[pIC]PEI for 18h, washed and fixed with 4% PFA. Nuclei are counterstained in blue. (e)
Representative bright field images of normal melancoytes, or melanocytes expressing FG12 vector, empty or coding for the
indicated oncogenes 48h after treatment with vehicle or 0.5µg/mL [pIC]PEI
107
Results
108
Objetives
“Never lose sight of the big picture”
(Anonymous)
Discussion
109
Results
110
Discussion
Here we have identified a lineage-specific wiring of the endolysomal pathway that melanoma cells
exploit to favor tumor maintenance and progression. Importantly, we have also shown that the
endolysosomal pathway of melanoma cells can be harnessed for therapeutic intervention.
In brief, we have shown that (i) RAB7 is selectively upregulated in melanoma, as part of a lysosomalassociated signature that distinguishes this malignancy from over 35 different cancer types. (ii) This
induction occurs at early stages of melanoma development, and is predictive of patient outcome. (iii)
RAB7 is intrinsically required for melanoma cell proliferation, but expression studies in clinical biopsies
combined with functional studies in cultured cells indicate that this GTPase is partially tuned-down by
highly invasive melanoma cells to favor metastatic dissemination. At the cellular level (iv) RAB7 governs
the fate of oncogene-driven cytoplasmic vesicles which are funneled towards the lysosome for
degradation but accumulate and are diverted into secretory pathways when RAB7 is tuned-down. (v)
The ultimate balance of RAB7-dependent traffic determines melanoma-cell phenotype by, at least, relocalizing lysosomal proteases, tuning gene expression programs, and altering cytoskeleton and
membrane dynamics. (vi) We have also assessed the upstream regulators of RAB7 that define the
lineage-specific enrichment of this protein in melanoma cells. Specifically, we showed that RAB7 is
modulated at two levels, driven respectively by the melanocyte lineage specifier SOX10, and by
melanoma-associated oncogenic activation of PI3K pathways. (vii) Together, our data demonstrate that
the expression, regulation and function of RAB7 is distinct from MITF, the best known lineage-specific
driver of melanoma progression known to date, and thus, opens new avenues of research in this field.
(viii) Finally, we have identified dsRNA-nanocomplexes as a novel strategy against melanoma,
demonstrating that tumor-cell specific wiring of endolysosomal pathways can be therapeutically
exploited.
1. LESSONS FROM MULTITUMOR GSEA IN MELANOMA GENE DISCOVERY
Most of the genome-wide gene expression or genomic studies aimed at identifying novel drivers of
melanoma (i) have focused on genes that, individually, suffer frequent activating genetic alterations in
datasets generated using metastatic melanomas 12, 13, 106, 244, 251, 427, or (ii) have compared different stages
of melanoma progression180, 192, 194, 428. Here we have investigated pathways and lineage-specific traits in
melanoma by performing GSEA on multitumor transcriptomic datasets. Together, we analyzed over 800
tumor cells and 35 cancer types. GSEA identified unexpected melanoma-enriched gene sets not
111
Discussion
previously anticipated to be regulated or to act in a lineage-dependent manner, and led to the
identification of: i) a melanoma-specific lysosome gene expression signature, ii) an intrinsic sensitivity of
melanoma cells to the lysomotropic agent chloroquine, and iii) RAB7 as a novel melanoma-lineage
dependency with implications in patient prognosis.
Two other previous reports have used a multitumor-comparison strategy to identify lineage-restricted
genes contributing to the particular features of melanoma. The first study was directed at identifying
molecular signatures that could account for the characteristic immune responsiveness of melanoma,
and analyzed gene expression data from tissues of different cancer types429. This approach led to the
identification of several functional signatures descriptive of melanoma-specific immune functions, yet
no validation of the differentially expressed genes was performed. Although not analyzed in this study, it
is interesting that RAB7 and several other lysosome-associated genes appeared as significantly enriched
in melanoma tissues, supporting our data. Without functional data mining by GSEA a lineage-dependent
wiring of lysosome-associated trafficking genes was missed. This underscores the power of multitumor
genome-wide GSEA, combined with mechanistic analyses of gene expression and function, to identify
novel lineage-restricted pathways (rather than individual genes) in melanoma.
A second very important study used a multitumor-comparison approach to identify melanomarestricted oncogenes171. Specifically, this study performed an integrated analysis of genomic and gene
expression data from tumor cell lines included in the NCI-60 panel. Different from our GSEA, this analysis
was restricted to genes within amplified genomic regions, which excluded the analysis of functional
gene expression clusters. However, it yielded the identification of the first melanoma-lineage specific
oncogene, MITF171. Interestingly, the second melanoma-lineage oncogene reported to date, BCL2A1,
was identified by comparing tumor versus normal tissues, not by a multitumor comparison approach252.
Of note, BCL2A1 was found to be a target of MITF and, as this transcription factor, it was found to be
expressed and required just in a subset of melanomas252. Similarly, other MITF targets, such as RAB27236,
251
and PGC1α430, 431, are not expressed in all melanomas (see below). Finding that RAB7 is expressed
and required in melanomas, independently of MITF, broadens the spectrum of lineage-specific drivers in
melanoma.
Importantly, our multitumor GESA demonstrated that, although lysosomes are essential to all
mammalian cells, lysosomal-related vesicle trafficking can be rewired in a lineage specific manner in
cancer.
112
Discussion
2. BIOLOGICAL IMPLICATIONS OF MELANOMA-ASSOCIATED TRAITS IDENTIFIED BY GSEA
Melanoma tumors are known for their intrinsic genetic complexity358,
432
and histological
heterogeneity24. Therefore, one of the most intriguing results of this study is the identification of a
uniform clustering of lysosomal-associated genes in a large panel of melanoma cell lines. Importantly,
the melanoma-enriched lysosomal cluster that we identified includes genes that, individually, had been
previously shown to have pro-tumorigenic role in melanoma and other tumor types, such as ACP53, 433,
cathepsin-K434, 435, or cathepsin-B185, 436. Therefore, finding that lysosomal-associated genes could be coderegulated in a lineage-dependent manner was highly unexpected.
An attractive scenario that may account for the simultaneous co-expression of a cluster of lysosomal
genes in melanoma cells is that these factors are coordinately involved in functions that are unique to
this tumor type. In this context, it is interesting to note that some lysosomal factors can also be present
in melanosomes362, 437, the best known lineage-dependent organelle of melanocytic cells. In addition,
melanosome maturation, transport and transfer to surrounding keratinocytes involve the participation
of various RAB proteins, some of which (i.e. RAB38, RAB27 and RAB17) are direct transcriptional targets
of MITF438. RAB7 itself is also well known for participating in melanosome maturation439. Therefore, it is
certainly plausible that melanoma cells exploit genes with shared functions in melanosome and
lysosome biology, thus “priming” their degradative features. However, while melanoma cells can
completely shut-down pigmentation programs (i.e. MITF and its downstream targets), they invariably
retain RAB7 levels and depend on active lysosomal-associated functions to counteract hyperactivated
vesicle trafficking. The biological relevance of the lysosome cluster is further reinforced by two
additional groups of results:
First, we have uncovered for the first time that lysosomal factors that are not shared with melanosomes
(e.g. cathepsins, peptidases, lipases, acid ceramidases and acid phosphatases, among others enzymes
with lytic activities) are particularly overexpressed in a lineage-dependent manner in melanoma.
Curiously, and different from RAB7, not all factors involved in melanosome biology are overexpressed in
all melanoma cells and tumors. This second situation can be exemplified by RAB27 or RAB8377, 440-442 (Fig.
31).
113
that
a
blunt
these
lysosome-associated
identified
functionally
cancer
chloroquine
compared to cells of other cancer types.
Chloroquine is a lysosomotropic agent that,
although it exerts various effects on lysosomal
function and on apoptosis 295, it is widely used
autophagic
“metabolic”
traits
could
associated
with
the
and
cells
genes,
melanoma-enriched
be
relevant
endocytic
degradation288, 443, 444. The increased sensitivity
of melanoma cells to chloroquine might reflect
are
especially
“degradative”. This is consistent with the
GSEA
gene
lysosomal
sets
pathways446. In agreement with our GSEA data,
mitochondrial
Melanoma (61)
Mesothelioma (11)
Esophagus (25)
AML (34)
Colorectal (61)
Stomach (38)
Pancreas (44)
Bile Duct (8)
Urinary tract(27)
Breast (58)
Upper Aerodigestive (32)
Hodgkin Lymphoma (12)
Thyroid (12)
Other Leukemia(1)
Ovary (51)
Kidney (34)
Chondrosarcoma (4)
Meningioma (3)
LungNSC (131)
Glioma (62)
CML (15)
Prostate (7)
T-cell –all- (16)
Soft Tissue (21)
Other (15)
Endometrium (27)
Osteosarcoma (10)
Lymphoma DLBCL (18)
Multiple Myeloma (30)
Liver(28)
Neuroblastoma (17)
Lymphoma –other- (28)
B-cell –all- (15)
Lung Small Cell (53)
Medulloblastoma (4)
Ewings Sarcoma (12)
Burkitt lymphoma (11)
to
“gluttonous” behavior previously reported for
melanoma cells274, 445.
Finally, although this study focused on
AML (34)
Multiple Myeloma (30)
Melanoma (61)
Lymphoma –other- (28)
B-cell –all- (15)
CML (15)
Glioma (62)
Thyroid (12)
Hodgkin Lymphoma (12(
T-cell –all- (16)
Other Leukemia (1)
Chondrosarcoma (4)
Mesothelioma (11)
Lung NSC (131)
Kidney (34)
Liver (28)
Other (15)
Osteosarcoma (10)
Soft Tissue (21)
Pancreas (44)
Urinary tract (27)
Upper Aerodigestive (32)
Bile Duct (8)
Prostate (7)
Lung Small Cell (53)
Meningioma (3)
Endometrium (27)
Breast (58)
Esophagus (25)
Ovary (51)
Colorectal (61)
Lymphoma DLBCL (18)
Stomach (38)
Neuroblastoma (17)
Medulloblastoma (4)
Burkitt lymphoma (11)
Ewings Sarcoma (12)
to
cells
traits
investigated herein, as it is known that the
constituent parts of the cargo degraded at the
lysosome can be further metabolised to
Other Leuke mia (1)
B-cell –all- (15)
AML (34)
Thyroid (12)
CML (15)
Lymphoma DLBCL (18)
Lymphoma –other- (28)
Multiple Myeloma (30)
Meningioma (3)
T-cell –all- (16)
Burkitt lymphoma (11)
Prostate (7)
Soft Tissue (21)
Mesothelioma (11)
Bile Duct (8)
Kidney (34)
Colorectal (61)
Stomach (38)
Urinary tract (27)
Hodgkin Lymphoma (12)
Glioma (62)
Breast (58)
Osteosarcoma (10)
Other (15)
Upper Aerodigestive (32)
Ovary (51)
Pancreas (44)
Chondrosarcoma (4)
Lung Small Cell (53)
Endometrium (27)
Liver (28)
Melanoma (61)
Lung NSC (131)
Medulloblastoma (4)
Esophagus (25)
Neuroblastoma (17)
melanoma
mRNA expression (RNA)
Discussion
Secondly, an interesting finding that further
supported that the lysosome signature found
12
here by GSEA in melanoma cells was not a
11
mere reflection of a high load of melanosome10
related genes was the increased sensitivity of
12
also
12
related to mitochondrial metabolism and to
11
Golgi-associated trafficking (Table S4). These
10
functionally
metabolism gene expression signature has
114
RAB7A – EntrezID:7879
when
9
RAB27A – EntrezID:5873
10
8
6
RAB8A – EntrezID:4218
9
generate ATP or utilised for biosynthetic
Fig. 31. Relative mRNA expression of RAB7, RAB27 and RAB8
across different cancer types. Source:
http://www.broadinstitute.org/ccle/home
Discussion
been very recently reported in a subset of melanoma cells expressing MITF via its target PGC1α430, 431.
Thus, additional lineage-restricted signatures identified by GSEA in this study may represent novel
mediators of melanoma pathogenesis.
3. CELL LINEAGE AS A DETERMINANT OF RAB7 EXPRESSION AND FUNCTION IN CANCER
Perhaps one of the most unexpected findings of this PhD thesis was the identification of melanomaspecific functions of RAB7. This was surprising because RAB7 is a paradigm of trafficking modulators that
regulate different aspects of lysosome biogenesis and function in a variety of cell types266, 267, 360, 397, 447450
. Why, then the comparatively stronger dependency of melanoma cells on RAB7 for proliferation and
control of cell shape and motility? As indicated above, melanoma cells seem to be particularly
dependent on lysosomal activity. Secondly, they intrinsically express high levels of RAB7 via SOX10, a key
driver of melanocyte differentiation241,
249
and, consequently, not expressed by other tumor types.
Whether other networks linking developmental and vesicle trafficking pathways exist in non-melanoma
cells, making them dependent on alternative endolysosomal regulators (i.e. CUL3451), deserves further
investigation.
In cancer, studies on RAB7 expression are scarce, being limited to roles in thyroid hormone production
in thyroid cancer or to still unclear roles in mesothelioma386, 387. Studies on RAB7 function have involved
transient inactivation of this gene by siRNA or dominant negative mutants and/or have been limited to
very few cultured cell lines per tumor type analyzed. In fact, seemingly opposing functions have been
described for RAB7 in these studies. For example, RAB7 inactivation was seen to increase cellular
dendricity in neuronal cells452, whereas no morphological changes were reported in the case of A431
and MCF7 (breast cancer), HeLa (cervical carcinoma), or CHO (chicken hamster ovary) cells360, 450, 453.
Moreover, invasion and migration were found to be inhibited by RAB7 inactivation in HeLa and HT-1080
fibrosarcoma cells381, but favored in the DU145 prostate cell line383. Similarly, a pro-survival role has
been described for RAB7 in breast cancer cells grown in soft agar or treated with HSP90 inhibitor
geldanamycin382, in contrast to the tumor suppressor functions described for this GTPase in a murine
pro-B-cell lymphoid cell line and mouse embryonic fibroblasts (MEFs)385. Following this last study, a
Rab7 (flox/flox) CD4-Cre (+) mouse model lacking the RAB7 protein in both CD4 and CD8 T cells was
published. Curiously, different from the pro-death roles of RAB7 identified in murine pro-B-cell lymphoid
cell line and MEFs cultured in vitro385, these mice showed a defect in T cell proliferation that, according
to the authors, was not severe considering an efficient deletion of rab7 and inhibition of the autophagic
115
Discussion
flux. This lack of consensus on the specific roles reported for RAB7 in different studies might reflect
highly context-dependent functions of this GTPase. In addition, our data emphasize the importance of
performing expression and functional studies at early, intermediate and late stages of tumor
progression to assign pro- or anti-tumorigenic roles to RAB7 in particular tumor types. The fact that
equivalent studies have not been performed in other tumor types may therefore add to the confounding
results previously obtained in limited sets of cell lines.
4. RAB7 EXPRESSION AND FUNCTION IN MELANOMA PROGRESSION
This study has uncovered pro-oncogenic roles for RAB7 in melanoma. Interestingly, RAB7 had been
previously studied in melanocytic cells in the context of melanosome maturation and transport. In an
initial study, RAB7 was found to participate in melanosome maturation when antisense oligonucleotides
against this factor impaired the transport of melanosomes to the cell periphery in B16 melanoma
cells439. In a later study, GFP-RAB7 and GFP-RAB27 were transiently expressed in human epidermal
melanocytes in order to map the specific stage of the melanosome maturation process in which they
participated377. Finally, a third study further characterized the molecular mechanism by which RAB7
controls melanosome maturation, by inactivating RAB7 in MMAc human melanoma cell line440.
Curiously, none of these studies anticipated pro-oncogenic roles for RAB7 in melanoma (nor for RAB27,
which was later demonstrated to be required for melanoma cell proliferation251 and exosome
secretion200, 325). All three studies involved a transient inactivation of RAB function in culture, different
from our stable inactivation, long-term culture assays and the comprehensive studies in human
melanoma specimens and in mouse models. With this approach we have identified new roles and
mechanisms of regulation of RAB7, as described below.
1. Melanocytic
lineage
2. Oncogenic
transformation
SOX10
PI3K
RAB7
Dependency
Other lineages
Pluripotent
Neural Crest Progenitor
Melanocytes
Melanoma Cells
Fig. 32 Specific regulation of RAB7 in melanoma cells: a new link between melanocyte developmental pathways, oncogenic
signaling and vesicle trafficking via RAB7.
116
Discussion
We have found a dual action of SOX10 (a lineage-specifier) and PI3K-driven signaling cascades (a
classical event in tumor development) in the control of RAB7 (see model in Fig. 32), broadening the
spectrum of early drivers of melanoma initiation. However, a main conclusion of this thesis is that RAB7
is expressed in a distinct manner than “classical oncogenes” such as BRAF, MYC or DEK which are
sustained or progressively activated as melanoma progresses388, 390, 391. Instead, we found that RAB7 can
be partially tuned-down in invasive melanomas, and favoring metastatic progression. High RAB7
expression was found again in metastases, likely reflecting highly “proliferative” stages at these late
stages of the disease (Fig. 33). This is the first example of a RAB GTPase with this behavior in cancer.
Fig. 33. Model summarizing the multitumor GSEA, and histological and functional studies that led to the identification
of RAB7 as a novel lineage-dependent driver of melanoma progression. RAB7 is transactivated downstream the
melanocyte lineage specifier SOX10 (1) and hyperactivated in melanoma as an active response of these cells to counteract
a massive influx of vesicles resulting from oncogenic stress engaged already at early stages of tumor progression (2). The
oncogenic triggers involve, at least in part, PI3K Class I and Class III signals. In melanoma, RAB7 levels are, therefore,
higher than non-melanoma cells (and benign nevi) and are required to sustain high proliferative rates. Nevertheless RAB7
levels were not constant along progression. This protein can be downmodulated to favor the transition to invasive
phenotypes (3). Importantly, although RAB7 depletion compromises the survival of normal melanocytes, melanoma cells
become significantly more dependent on this protein for tumor maintenance. Moreover, macroendo-lysosomal trafficking
cascades are activated in melanoma but not in normal cells, representing a point of vulnerability that can be exploited for
therapeutic intervention (4).
A retrospective 10 year-follow up analysis of RAB7 expression in clinically-annotated primary
melanomas demonstrated RAB7 as an independent prognostic indicator of patient outcome,
117
Discussion
underscoring the physiological relevance of our findings. The molecular mechanisms underlying this
“oscillating” expression pattern of RAB7 in vivo needs further evaluation. However, it is tempting to
speculate that RAB7 may also be controlled by modulators of EMT-like transitions that have been
demonstrated to occur during melanoma progression194-196 . This hypothesis is supported by the parallel
regulation of RAB7 and CCDN1 (an EMT-like associated factor195), which we also studied by TMA.
It is also plausible that the dynamic modulation of RAB7 levels along the course of melanoma
progression is associated with its regulation by SOX10. SOX10 is required for terminal differentiation of
melanocytes454, and, in melanoma, de-differentiation has long been associated with increased
aggressiveness6,
melanoma248,
119
. However, while it is clear that SOX10 is required for the maintenance of
455
, its role in metastasis is unclear. Studies in cultured cells place SOX10 as a positive
regulator of pro-invasive genes246, 456, in contrast to expression studies of SOX10 in vivo showing that this
transcription factor is tuned-down in thick primary melanomas457. In agreement with this in vivo study,
here we have demonstrated that highly invasive (and dedifferentiated) melanoma cell lines express low
levels of RAB7 and SOX10. Further analyses are needed to fully understand the spatio-temporal
regulation of RAB7 and SOX10 in vivo. In this context, it would be interesting to explore whether
microenvironmental triggers217, 458, 459, EMT-inducing factors like TGF-β417, 460,
461
and/or epigenetics462
coordinately regulate these developmental and cancer biology pathways along melanoma progression.
Finally, this study suggests a possible pro-oncogenic role for RAB7 in melanoma initiation. We provided
in vitro and in vivo evidence that demonstrate the activation of RAB7-dependent macroendocytosis in
early stage melanomas. Moreover, we show that the characteristic cytosolic vacuoles that are induced
and accumulate in senescent RAS-expressing primary melanocytes143,
150
are, in fact, RAB7-positive
macroendosomes. This is consistent with the known roles of PI3K in macropinocytosis463-468. In addition,
we demonstrate that modulation of PI3K-associated macropinosomes, by upregulating or by inhibiting
RAB7 in normal primary melanocytes, is sufficient to delay or accelerate PI3K-driven OIS, respectively. Of
note, in other cell types, OIS is classically modulated by MAPK/ERK, not by PI3K137, and RAB7 blockade
has been shown to favor, not block, oncogenic transformation of mouse embryonic fibroblasts385.
Further analyses are needed to fully elucidate the specific mechanisms by which RAB7 might regulate
OIS and whether it does so in a cell-type dependent-manner. Similarly, it would be interesting to explore
putative cooperative interactions between RAB7 and frequently mutated melanomas drivers (e.g. BRAF,
NRAS, cKIT, etc.432).
118
Discussion
Finally, the pro-tumorigenic roles of RAB7 in melanoma may be relevant to the Charcot-Marie-Tooth
type 2B (CMT2B) disease, a hereditary neuropathy with axonal degeneration that has been linked to
activating mutations in the RAB7 gene469-471. Interestingly, a subset of patients with this disease has been
shown to develop cutaneous melanomas472-474, but it was unclear whether and how these mutations
could favor or mediate melanoma development. Our data offer a mechanistic framework to close the
gap from RAB7 to melanoma development in this CTM2B disease.
5. RAB7 VERSUS MITF AND OTHER LINEAGE-SPECIFIC MELANOMA DRIVERS
As mentioned before, MITF has been proposed as a master regulator of melanoma gene expression
profiles and tumor-cell phenotypic plasticity207, 214, 217. Therefore, one of the most interesting finding of
this study was that RAB7 is not another target or effector of the MITF program. This is different from
BCL2A1252, PGC1α430, 431, or RAB27236, 251, and places RAB7 as the first example of a non-transcriptional
regulator that, despite being overexpressed and acting in a melanocyte lineage-dependent manner, is
not controlled by MITF.
The regulation of RAB7 by SOX10 (independent of MITF and PAX3, both key in melanocyte
differentiation) illustrate that divergent routes exist within the hierarchy of melanocyte-lineage
transcription factors and, in contrast to the prevailing notion241,
418
, do not always lead to MITF.
Moreover, the fact that MITF-negative cells were still found to express SOX10 and RAB7, demonstrates
that even highly aggressive and poorly differentiated tumor cells can preserve a lineage memory that
reflects their developmental history. This is relevant because pigmented and amelanotic metastatic
melanomas both have an extremely poor prognosis, despite great progress in the implementation of
targeted therapies475.
6. DOWNSTREAM EFFECTOR PATHWAYS OF RAB7 IN MELANOMA CELLS
The ability of RAB7 to counteract the influx of both autophagosomes and endosomes via lysosomemediated degradation is a unique feature of this protein266,
267, 378, 380, 450
. Therefore, the impaired
autophaghic and endocytic flux found when downregulating RAB7 in melanocytic cells was consistent
with the literature. This defective autophagy could account for defects in melanoma cell proliferation as
previously described274, 288, 289. However, what was not obvious was that the autophagic vesicles that
119
Discussion
required RAB7 for degradation were generated independently of ATG7 and involved a recruitment of
LC3 into large macroendosomes instead of the standard double membrane autophagosomes476, 477 (Fig.
34). These results therefore point to non-canonical autophagy in melanoma cells, and broaden the
knowledge of self-degradative processes in cancer.
How, then, can derailed vesicle traffic impact on melanoma-cell phenotype? Here we have shown that a
trafficking regulator like RAB7 can impact a variety of cellular processes that are relevant in
tumorigenesis: localization of lysosomal proteases, gene expression programs, and cytoskeleton and
membrane dynamics. The key findings in this regard are discussed below.
LC3-II
RAB7
Class I PI3K
Class III PI3K
Class I PI3K
Class III PI3K
Late
Endosomes
Golgi
Early
Endosomes
?
Late
Endosomes
Golgi
Early
Endosomes
LYSOSOME
DEGRADATION
↑ RAB7
RAB5
Cathepsins
↓ RAB7
Lysosome
ER
Lysosome
ER
Phagophore Autophagosome (LC3)
Phagophore
ACTIVE LYSOSOMAL DEGRADATION
OF AUTOPHAGOSOMES AND ENDOSOMES
Autophagosome (LC3)
ENDOSOME-MEDIATED SECRETION
HALTED AUTOPHAGY
LOW RAB7
HIGH RAB7
Fig. 34. Proposed model illustrating RAB7-dependent vesicle traffic in melanoma cells and the impact of RAB7
downregulation on the fate of oncogene-driven cytoplasmic vesicles. Upon RAB7 downregulation, vesicles that were
being trafficked towards the lysosome for degradation accumulate and are redirected into secretory pathways.
The finding that lowering RAB7 levels induces the secretion of cathepsins has important implications.
Previous studies in melanoma had reported the presence of extracellular cathepsins in highly invasive
melanoma cell lines478 and, importantly, in the sera of melanoma patients with poor prognosis479.
Switching down RAB7 might therefore be a plausible way by which invasive melanomas secrete
cathepsins. Importantly, although RAB7 has been reported to favor the release of pro-cathepsin D in
HeLa cells480, our data showed that this feature is more extensive in melanoma cells (affecting more
120
Discussion
cathepsins, and promoting a selective enrichment in the extracellular compartment). Additional
differences with other systems refer to the distribution of lysosomes in RAB7 depleted cells. In prostate
tumor cells, lysosomes were found to be mispositioned towards the cell periphery383, but the release of
their cargo to the extracellular media was not investigated. This was not the case for melanoma cells, as
we visualized lysosomes still localized in the perinuclear area in RAB7-depleted cells. Instead, our results
demonstrated that “lysosomal proteins” (but not lysosomes themselves) are mislocalized towards the
cell periphery within endosomes prior to secretion to the extracellular space (Fig. 34).
Regarding the global consequences that RAB7 downregulation exerted on melanoma gene expression
profiles, we identified numerous genes and pathways to be modulated by this GTPase in a melanomaspecific manner. Proliferation promoting factors were found to be downregulated upon RAB7 knockdown, whereas genes and pathways involved in tumor cell invasiveness, membrane trafficking, protein
secretion and extracellular matrix remodelling were induced. We are particularly excited by these
results as they represent the first unbiased transcriptomic analysis of RAB7-controlled pathways in
cancer. A particularly relevant finding that stemmed from this analysis was the identification of RAB7 as
a negative regulator of CEACAM1, a pro-invasive factor412 with important clinical implications as a
marker of melanomas of poor prognosis183, 411, 413, 481, 482. The means by which RAB7 might impact gene
expression could be very complex and diverse, ranging from the direct deregulation of signaling factors
that shuttle from the plasma membrane to endosomes399, 483-486 to the alteration of nutrient sensing and
metabolic cascades385, 487. For example, RAS is known to signal not only from the plasma membrane, but
also from late endosomes enroute to lysosomes486. MAPK signaling is also spatio-temporally regulated
by late endocytic trafficking484 and RAB7485.
Finally, we also demonstrated that RAB7 function
determines the cytoskeleton architecture, probably reflecting the tight control that endocytic pathways
exert on integrins and/or cadherins400, 488-493. In this context, deregulated non-canonical macroendocytic
pathways, herein shown to be critically controlled by RAB7 in melanoma cells, are expected to have a
large impact on signaling and cytoskeleton dynamics463,
494
. Feedback loops may also be involved in
RAB7-mediated cellular functions. Particularly, RAB7 can regulate the activity of PI3K by complexing
with hVPS34495, which is important for endosomal trafficking and is shown here to regulate RAB7 levels.
These pleiotropic activities of RAB7, exerted without direct binding to DNA, distinguish this protein from
MITF and from other transcription factors like BRN2 and GLI2, which are proposed to modulate
melanoma-cell plasticity along tumor progression213, 216, 417. Thus, this study expands the horizon of the
121
Discussion
molecular switches that control melanoma-cell phenotype, placing the vesicle trafficking machinery
within this poorly understood aspect of melanoma pathogenesis.
7. ANTITUMOR THERAPEUTIC OPPORTUNITIES TARGETING ENDOLYSOSOMAL PATHWAYS
Melanomas accumulate a plethora of genetic and epigenetic alterations that contribute to the limited
efficacy of current anticancer treatments1, 496. However, here we show that melanoma cells retain a
particular wiring of endolysosomal pathways, independently of the mutational status of oncogenes
(BRAF or NRAS) and tumor suppressors (PTEN or p53), and that this feature can be exploited
therapeutically. In this context, we showed that mimetics of viral dsRNA (pIC-PEI complex [pIC]PEI) can
target endolysosomal pathways and engage tumor-cell selective cell death.
The antitumoral activity of [pIC]PEI and most importantly, its mode of action, were rather unanticipated.
pIC is a classical immunomodulator whose anticancer action has been primarily linked to IFN-driven
activation of immune effectors (e.g. dendritic cells, cytotoxic T cells, NK cells)497. However, in melanoma,
monotherapies based on pIC had failed in clinical trials498. Poor cellular uptake, degradation by cytosolic
RNases and/or various mechanisms of immunotolerance were thought to account for this lack of
response in vivo499. Interestingly, these pitfalls could be overcome (at least in animal models) in the
presence of PEI. Moreover, [pIC]PEI was sufficient to inhibit melanoma growth in surrogate models of
lung metastasis, even in severely immunocompromised mice (in which signaling to NK, T or B cells is
defective) (results not shown).
Specifically, we demonstrated a complex of pIC and the polycationic carrier PEI as an unexpected
strategy that effectively promotes a marked mobilization of endosomal compartments in tumor cells.
This was visualized as large multivesicular structures by electron microscopy, and time-lapse imaging of
the distribution of RAB7. RAB7-decorated vesicles recruiting LC3 protein and lysosomes were found to
be mobilized as early as 2 hours upon treatment. However, the cellular collapse was significantly
delayed (>15h). It is therefore conceivable that autophagy is activated in response to [pIC]PEI as an initial
mechanism of protection, which is later shifted into a pro-death program (see model in Fig. 35500). Thus,
lysosomal degradation could be activated in order to resolve an exacerbated endocytosis driven by pIC
complexed to PEI501, 502. PEI can also induce fusion of late endosomes503, 504, and in this manner, it may
account, at least in part, for the large endocytic vesicles that can be visualized at early time points after
[pIC]PEI treatment. Importantly, the use of caspase inhibitors and visualization of caspase processing by
122
Discussion
immunoblotting, indicated a second death machinery activated by [pIC]PEI that involves classical
apoptotic programs, depending, at least in part, on activation of the pro-apoptotic factor NOXA via the
MDA-5 helicase (see model Fig. 35). Sustained waves of endosome generation, maturation and
resolution could lower the threshold for the activation of death programs (i.e. by depleting ATP and/or
key proteins or organelles required for cell maintenance) as described in other systems505.
Given the ability of melanoma cells to deactivate death programs506, it is interesting that lysosomal
activities can be harnessed for tumor-cell selective killing. This is particularly relevant because
autophagy has been abundantly linked to cytoprotection in innate and acquired immune responses 507509
, and this study has demonstrated the endolysosomal regulator RAB7 as a novel dependency in
melanoma. Thus, transforming trafficking pathways actively involved in tumor maintenance into an
Achilles’ heel is a possible and efficient strategy to fight against melanoma. Inhibition of
macroendocytosis significantly abrogated [pIC]PEI-induced melanoma cell death; its activation by
oncogenic signalling in melanocytes enhanced drug uptake. This is in agreement with studies showing
that PEI complexes can be uptaken by macropinocytosis510, although more than one uptake mechanism
might be involved511-513.
From a translational prospective, it is also relevant that the cell autonomous activity of [pIC] PEI can
bypass the dependency of classical IFN-activating immunomodulators on professional immune cells (i.e.
T cells, NK cells or B cells) for antitumoral activity in vivo. Thus, although the inhibition of localized and
disseminated melanoma growth by [pIC]PEI can be favored in the presence of an active immune system
(results not shown), [pIC]PEI is also highly efficient in severely immunocompromised mice . The response
to [pIC]PEI of autochthonous cutaneous melanomas generated in the NrasQ61K; Ink4a/Arf-/- model
(recapitulating the frequent melanoma-associated defects in the MAPK pathway and the p14ARF and
p16INK4a tumor suppressors), further emphasized the physiological relevance of our data.
Altogether, these results emphasize the potential of dsRNA mimics to overcome the traditional chemoand immuno-resistance of melanoma cells and reveal tractable points of crosstalk between innate
sensors of dsRNA, endo/lysosomal compartments and tumor cell death.
123
Discussion
a
mimic of viral
dsRNA (pIC)
b
Carrierfor
(PEI)
Carrier
cytosolic delivery (polycationic or lipidic)
Control
[pIC]PEI
1 Endosomal
Amphisomes
Autophagosomes
2
Lysosomes
Uptake, cytosolic
delivery and
activation of
immune sensors
Sustained
endosome mediated
autophagy
MDA-5
(inactive)
Lower threshold for
apoptosis
induction?
MDA-5
(active)
Melanoma lung metastases
(xenograft models)
Time course
Macroendosomes
Late
( macroe )endosomes
Control
[pIC]PEI
NOXA
Caspases
Progressive
destruction of
cellular
organelles?
TUMOR CELL DEATH
3
4
Activation of
apoptosis
Final cellular collapse
(by autophagic and
apoptotic cell death)
PET-CT
Tyr::Nras Q61K; Ink4a/Arf -/-
Fig. 35. Proposed model and efficacy in vivo of [pIC]PEI-induced antimelanoma activity. (a) dsRNA pIC complexed to the
carrier PEI is efficiently uptaked by the endosomal compartment of tumor cells for subsequent delivery to the cytosol (1).
The uptake of [pIC]PEI alters endosomal dynamics and induces sustained cycles of endosomes-autophaghosome-lysosome
fusions (2). Additionally, cytosolic pIC activates the helicase MDA-5 which favors the activation of the proapoptotic factor
NOXA with subsequent processing of apoptotic caspases (3). The convergence of sustained autophagy and the activation
of caspases synergizes in an efficient tumor self killing. Active MDA-5 can facilitate autophagosome formation, while
persistent endosome-mediated autophagy and the consequent autophagic damage may be lowering the threshold for the
entry to the apoptotic programme. Adapted from Ref. 500. (b) Representative examples illustrating the potent antitumor
activity of [pIC]PEI in vivo. The top panels show lungs of mice 14 days after intravenous inoculation of B16 melanoma cells
and treated as indicated. The bottom panels show coronal sections of PCT-CT fused images to assess metabolic activity
(18F-fluorodeoxyglucose incorporation) of representative examples of mice treated as indicated. The asterisk mark animal
hearts.
124
Discussion
8. PERSPECTIVES
This thesis has shed light on how melanoma cells exploit a lineage-specific wiring of the endolysomal
pathway to sustain and acquire cancer hallmarks. It has also demonstrated that the endolysosomal
pathway can be effectively targeted by dsRNA-based nanocomplexes, inducing tumor-cell selective cell
death. Still, future work directed at better understanding the mechanisms involved in the regulation
and function of the endolysosomal trafficking will extend our knowledge of the contribution of vesicle
trafficking regulators to human disease.
Regarding the upstream regulation of RAB7 expression by SOX10 and PI3K/PI3KC3, chromatin
immunoprecipitation and promoter activity assays are still necessary to distinguish between direct
versus indirect mechanisms. Computational analyses of the promoter of RAB7 anticipate binding sites
for additional transcriptional regulators, such as MYC, other melanoma-enriched transcription factors,
and EGR2, which is a SOX10-interacting partner514 (results not shown). In this manner we expect to
better characterize the cell- and context-dependent roles of this GTPase. Additionally, it would be also
interesting to address whether cell-intrinsic (EMT-inducers) and/or microenvironmental factors (e.g.
hypoxia, nutrient deprivation) that might impact on RAB7 independently or in cooperation with SOX10.
It should be noted that SOX10 is not only involved in melanocyte terminal differentiation from the
neural crest, but also in Schwann-cell development in the peripheral nervous system418; therefore, the
SOX10-RAB7 axis might have important basic and translational implications in demyelinating peripheral
neuropathies. Supporting this concept, SOX10 mutations have been associated with a number of neuralcrest-related
phenotypes,
including
demyelinating
peripheral
neuropathy
(CMT1),
central
dysmyelinating leukodystrophy, Waardenburg syndrome and Hirschsprung disease514. Similarly, and as
mentioned above, activating mutations in RAB7 are associated with the neuropathy CMT2B469-471. Some
of these patients develop melanoma472-474, although the underlying mechanisms are unknown. It would
be interesting to explore whether these RAB7 mutants favor malignant transformation of melanocytes
and/or play a driver role in the progression of melanoma in CMT2B patients. Finally, it would be also
interesting to check whether the treatments that are currently being investigated for CMT2B patients
with RAB7 mutations (i.e. the mood stabilizer valproic acid452) would have an effect on melanoma cells.
125
Discussion
Another area of research that deserves attention is to define whether the regulation of RAB7 activity by
GEFs and GAPs, or its interacting effector partners, could be a critical determinant of the functions of
this GTPase in melanoma development. HOPs515 and the mammalian TBC1D15516 have been
characterized as the GEF (in yeast) and GAP, respectively, for RAB7. Once activated, GTP-bound RAB7 is
known to interact with numerous partners to exert its particular molecular functions in vesicle
trafficking. These interacting partners include RILP, ORP1L, FYCO1, the retromer complex (VPS26–
VPS29–VPS35), Rabring7 and RAC1379. Interestingly, RAC1 has is found to be activated by somatic
mutations in melanoma13. Therefore, further analyses are needed to elucidate how these complex
functional networks, that have been associated with the activity of RAB7 in other cell types, are
interwired with developmental and oncogenic pathways in melanoma cells.
Regarding the cellular roles of RAB7 in vesicle trafficking, it would be very interesting to explore if RAB7
regulates exosome secretion, as these small vesicles are emerging as critical players in melanoma
metastasis200, 201 and are known to derive from RAB7-regulated late endosomes517450.
Finally, a better understanding of the variables that determine pro-death or pro-survival roles of the
endolysosomal pathways in the response of tumor cells to anti-cancer agents will aid in defining more
effective treatment strategies and circumventing mechanisms of chemoresistance.
In conclusion, we anticipate that untangling vesicle trafficking routes will be key to better understand
the mechanisms underlying human diseases, such as cancer and neurodegenerative diseases, in which
trafficking regulators are emerging as frequently altered drivers.
126
Objetives
"Anyone who has not made a mistake, has not tried anything new."
Albert Einstein (1879-1955)
Conclusions
127
Discussion
128
Conclusions
In light of the results presented here, the conclusions drawn from the study are:

Gene Set Enrichment Analyses (GSEA) of multi-tumor gene expression datasets can be used to
identify lineage-specific cancer drivers. This strategy revealed a cluster of lysosome-associated
genes that distinguishes melanoma from over 35 different tumor types. This enrichment was
particularly significant for the small GTPase RAB7, and was found to reflect an intrinsic
dependency of melanomas on this protein, and ultimately, on lytic activities of lysosomes.

Despite the striking inter- and intra-tumor heterogeneity, even highly unstable and
dedifferentiated melanomas retain a particular wiring of vesicle trafficking pathways that trace
back to the cell of origin, the melanocytes. Consequently, melanoma specimens express RAB7 at
significantly higher levels than other tumor types and non-melanocytic surrounding stroma.

Downregulation of RAB7 compromises melanoma cell proliferation but increases the metastatic
potential of these tumor cells. This supports that conserved endolysosomal regulators can be
hijacked by melanoma cells in order to sustain tumor growth and cell plasticity in a tumor-type
dependent manner.

Functional roles of RAB7 in melanoma cells reflect the expression pattern of this protein in
clinical specimens. RAB7 levels are dynamically modulated during melanoma progression, being
induced at early stage radial growth phase melanomas, but undergoing partial downregulation
in invading melanomas. The levels of RAB7 in primary tumors are an independent predictive
factor of disease-free- and overall-survival of melanoma patients.

RAB7 is a critical mediator of the lysosomal turnover of autophagosomes, macroendosomes and
a newly identified class of non-canonical autophagosome-endosome hybrids. Deregulated
vesicle trafficking by downregulation of RAB7 has pleiotropic and melanoma-specific
consequences which involve, at least, (i) the relocalization of key mediators of intracellular
proteolysis and extracellular matrix remodeling, (ii) modulation of gene expression profiles, and
(iii) alteration of cytoskeleton dynamics. Thus, although RAB7 was considered a ubiquitous
endosomal trafficking mediator, this GTPase has specific roles in melanoma which are not
shared with other tumor types.

RAB7 expression is not controlled by MITF, the best characterized melanocyte lineage-specific
oncogene to date. Instead, RAB7 expression is driven by SOX10, a transcription factor known to
129
Conclusions
act in the earliest stage of differentiation of the melanocytic lineage, from neural crest
precursors. In addition, RAB7 expression and function is regulated by PI3K signaling. Therefore,
RAB7 links vesicle trafficking to oncogenic signals and developmental processes that are specific
for melanocytes.

Tumor cell-selective vesicle traffic controlled by RAB7 can be deregulated or exacerbated by
chemo- and immunomodulators.

Nanoparticles constituted by the dsRNA mimic polyinosine-polycytidylic acid (pIC) and the
carrier polyethyleneimine (PEI) promote tumor cell-selective cell death by a coordinated
activation of endolysosomal pathways and apoptotic cascades. This strategy may represent an
alternative to the current treatment of otherwise aggressive and chemoresistant melanomas.
130
Objetives
Conclusiones
131
Conclusions
132
Conclusiones
A la luz de los resultados que aquí se presentan, las conclusiones del estudio son:

El análisis de enriquecimiento de grupos de genes (GSEA) aplicado sobre bases de datos de
expresión génica de múltiples tipos de cáncer, es una estrategia eficaz para descubrir nuevos
mecanismos de iniciación y progresión específicos de tumores concretos. En particular, hemos
identificado un grupo de genes relacionados con la función lisosomal que distingue al melanoma
de entre más de 35 tipos tumorales.

Mientras estudios genéticos de alta densidad reflejan una extraordinaria variabilidad inter e
intratumoral en el melanoma, demostramos que incluso tumores altamente inestables y
desdiferenciados retienen una particular organización de las rutas endolisosomales que se
remontan a la célula de origen (los melanocitos). Estos estudios resultaron en la identificación
de un enriquecimiento y función específicos de RAB7 en melanoma. Estos datos son relevantes
porque describiendo un nuevo espectro de actividades pro-oncogénicas específicas de tumor de
esta proteína considerada hasta el momento como un factor ubicuo en células de mamífero.

Los melanomas dependen específicamente de RAB7 para mantener su capacidad proliferativa.
Sin embargo la reducción en la expresión de RAB7 favorece fenotipos pro-metastásicos. Estos
resultados revelan cómo las células de melanoma aprovechan factores intrínsecos de su linaje
celular para mantener la plasticidad y agresividad características de esta enfermedad.

Estudios de los niveles de RAB7 en biopsias clínicas aisladas de melanomas en distintos estadíos
de progresión permitieron determinar que ésta es una proteína que se activa de forma
temprana en este tumor. Sin embargo, los niveles de RAB7 no son constantes, si no que se
reducen en las fases invasivas del tumor. Este punto se demostró clínicamente relevante al
representar esta proteína un nuevo factor que determina un pronóstico desfavorable asociado a
un aumento del riesgo de desarrollo de metástasis.

RAB7 es esencial para la degradación lisosomal de endosomas, autofagosomas clásicos y un
nuevo tipo de autofagosomas no canónicos descritos aquí. La desregulación del tráfico vesicular
inducida tras la reducción en los niveles de RAB7 se traduce en efectos pleiotrópicos (pero
específicos de melanoma) que incluyen, al menos, cambios en los perfiles de expresión génica,
133
Conclusiones
reorganización de la arquitectura del citoesqueleto, y relocalización de factores prometastásicos implicados en degradación intracelular y de la matriz extracelular.

En enriquecimiento específico en la expresión de RAB7 en melanoma está determinado, al
menos en parte, por el factor transcripcional SOX10 (pero no por otros modulatores del linaje
melanocítico como MITF o PAX3). Un segundo nivel de regulación está mediado por la ruta PI3K,
clásicamente asociada a la transformación oncogénica de los melanocitos.

Desde un punto de vista terapéutico, se ha determinado que fármacos con distinto modo de
acción (desde inhibidores de proteínas apoptóticas hasta moduladores de MEK, entre otros) son
capaces de movilizar la maquinaria endolysosomal modulada por RAB7, generalmente (aunque
no necesariamente) para el favorecimiento de supervivencia celular.

Nanopartículas constituidas por ARNs de doble cadena miméticos de ácido polyinosinepolicitidílico y el portador catiónico polietilenimina (PEI), promueven la muerte de células
tumorales mediante una movilización masiva del tráfico endolisosomal y la posterior activación
de cascadas apoptóticas. Esta estrategia puede representar una opción terapéutica para el
tratamiento de los melanomas, intrínsicamente agresivos y resistentes a la quimio- e
inmunoterapia convencionales.
134
Objetives
References
135
Conslusions
136
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Appendix
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162
Appendix
Degree of
sun damage
Common
anatomic
site
Superficial
spreanding
melanoma
70% of all melanomas in
light-skinned individuals.
Frequently diagnosed in
middle-aged people
Acute
intermittent
sun exposure
Trunk of
men and
legs of
women
Lentigo
maligna
melanoma
<1 % of cutaneous
melanomas.
Frequently diagnosed in
the seventh decade of life
Chronic sun
exposure
Head and
neck
Not related
to sun
damage
Palms,
soles,
nails
Intermittent
sun exposure
Trunk,
head,
neck and
lower legs
Subtypes
Epidemiology and age of
patient
Acrallentiginous
melanoma
Nodular
melanoma
2% and 80% of cutaneous
melanomas in Caucasian
and dark-skinned
individuals respectively.
Frequently diagnosed in
the seventh decade of life
10-15% of all melanomas
in Caucasian individuals.
Frequently diagnosed in
the sixth decade of life
Key histophatological features
RGP in which enlarged atypical
melanocytes display a marked
upward scatter within the
epidermis ("pagetoid" spread). At
later stages, dermal invasion
(VGP) can be observed
RGP characterized by linear or
nested proliferation of atypical
melanocytes along the basal
epidermis ("lentiginous"
hyperplasia, or Lentigo Maligna).
When dermal invasion (VGP) is
observed, the term lentigo
maligna melanoma is used
RGP in which atypical
melanocytes exhibit a
"lentiginous" proliferation along
the basal epidermis. At later
stages, dermal invasion (VGP) can
be observed
VGP in which atypical
melancoytes form one or more
solid nodules within the dermis.
No significant RGP
Table S1. Major Clinicopathological Subtypes of Cutaneous Melanomas. Information extracted from ref. 52
163
Appendix
T
Tis
Thickness (mm)
in situ
Ulceration Status/Mitoses
Not applicable
T1
≤ 1.00
a: Without ulceration and mitosis < 1/mm 2
T2
T3
T4
N
N0
N1
N2
N3
M
M0
M1a
M1b
M1c
b: With ulceration and mitosis ≥ 1/mm2
1.01-2.00
a: Without ulceration
b: With ulceration
2.01-4.00
a: Without ulceration
b: With ulceration
> 4.00
a: Without ulceration
b: With ulceration
Number of Metastatic Nodes
Nodal Metastatic
0
Not applicable
1
a: Micrometastasis
b: Macrometastasis
2
a: Micrometastasis
b: Macrometastasis
c: In transit metastases/satellites without
metatatic nodes
4 + metastatic nodes, or
matted nodes, or in transit
metastases/satellites with
metastatic nodes
Site
Serum LDH
No distant metatases
Not applicable
Distant skin, subcutaneous,
Normal
or nodal metastases
Lung metastases
Normal
All other visceral metastases
Normal
Any distant metastasis
Elevated
Table S2. TNM Staging Categories for Cutaneous Melanoma. AJCC Melanoma Staging and
Classification. Adapted from ref. 101
Stage
0
IA
IB
IIA
IIB
IIC
III
Clinical Staging
T
N
Tis
N0
T1a
N0
T1b
N0
T2a
N0
T2b
N0
T3a
N0
T3b
N0
T4a
N0
T4b
N0
Any T
N>N0
M
M0
M0
M0
M0
M0
M0
M0
M0
M0
M0
Stage
0
IA
IB
IIA
IIB
IIC
IIIA
IIIB
IIIC
IV
Any T
Any N
M1
IV
Pathologic Staging
T
N
Tis
N0
T1a
N0
T1b
N0
T2a
N0
T2b
N0
T3a
N0
T3b
N0
T4a
N0
T4b
N0
T1-4a
N1a or N2a
T1-4b
N1a or N2a
T1-4a
Nib or N2b or N2c
T1-4b
Nib or N2b or N2c
Any T
N3
Any T
Any N
M
M0
M0
M0
M0
M0
M0
M0
M0
M0
M0
M0
M0
M0
M0
M1
Table S3. Anatomic Stage Grouping for Cutaneous Melanoma. AJCC Melanoma Staging and
Classification Adapted from ref. 101
164
Appendix
GO Term and Description
term_size adj_pvalue
GO:0005773
vacuole
212
6,66344E-10
GO:0000323
GO:0005764
GO:0005739
GO:0044429
GO:0031090
GO:0042470
GO:0031966
GO:0005740
GO:0031988
GO:0016023
GO:0043218
GO:0031410
GO:0031982
GO:0043209
GO:0005743
GO:0019866
GO:0042613
GO:0030529
GO:0005770
GO:0005794
GO:0045177
GO:0044433
GO:0005741
GO:0030173
GO:0031228
GO:0030424
GO:0016471
GO:0005774
GO:0019867
GO:0034045
GO:0005594
GO:0000307
lytic vacuole
lysosome
mitochondrion
mitochondrial part
organelle membrane
melanosome
mitochondrial membrane
mitochondrial envelope
membrane-bounded vesicle
cytoplasmic membrane-bounded vesicle
compact myelin
cytoplasmic vesicle
vesicle
myelin sheath
mitochondrial inner membrane
organelle inner membrane
MHC class II protein complex
ribonucleoprotein complex
late endosome
Golgi apparatus
apical part of cell
cytoplasmic vesicle part
mitochondrial outer membrane
integral to Golgi membrane
intrinsic to Golgi membrane
axon
vacuolar proton-transporting V-type ATPase complex
vacuolar membrane
outer membrane
pre-autophagosomal structure membrane
collagen type IX
cyclin-dependent protein kinase holoenzyme complex
179
1,00219E-08
179
1,00219E-08
813
1,44277E-06
468
4,75902E-06
825
5,36687E-06
105
8,17296E-06
324
4,88567E-05
341
4,88567E-05
469
8,02254E-05
450
8,07733E-05
10
0,000124617
535
0,000365405
565
0,000365405
23
0,000455941
266
0,000467785
282
0,00105986
23
0,00161817
431
0,00655529
57
0,00716068
694
0,0113744
172
0,0146773
160
0,0152588
82
0,0154928
48
0,0258355
51
0,0297121
167
0,0301226
13
0,0412011
52
0,0412011
104
0,0412011
10
0,042695
10
0,042695
19
0,0469011
Table S4. Gene-Ontology Gene Sets (Cellular component) significantly enriched in melanoma cells (GSEA FDR <
0.05). Genome-wide analysis using “Cellular Component” Gene Ontology (GO) terms were evaluated by GSEA in
the multi-cancer NCI-60 cell line dataset (GSE5720GO)2. Shown are the statistically significant GO terms
(FDR<0.05) selectively enriched in the melanoma samples. Lysosomal-related gene sets are marked in red. The
expected melanoma-specific term “melanosome” is marked in brown.
165
Appendix
CELL LINE
BRAF
(EXON 15)
NRAS
(EXON 3)
PTEN
(PROTEIN)
p53
MITF (PROTEIN /
LEVELS)
RAB7A GENE IN GAINED
3q21.3 REGION (CGH)
SK-Mel-103
wt
mutant
(Q61R)
+
wt R
No
Yes
wt
-
wt
Yes / High
Yes
wt
+
mutant
Yes / High
Yes
wt
-
wt
Yes / High
Yes
mutant
(Q61R)
+
wt R
No
No
wt
-
wt
Yes / Low
Yes
wt
+
wt R
Yes / Low
ND
wt
-
wt R
Yes / High
No
SK-Mel-19
SK-Mel-28
SK-Mel-29
SK-Mel-147
mutant
(V600E)
mutant
(V600E)
mutant
(V600E)
wt
mutant
(V600E)
mutant
(V600E)
wt/mutant
(V600E)
UACC-62
SK-Mel-5
G-361
SK-Mel-173
wt
NRAS
(Q61K)
-/+
wt R
ND
No
WM-164
mutant
(V600E)
wt
+
mutant
Yes / High
ND
Mel-1
wt
mutant
(Q61R)
ND
ND
No
ND
Table S5. Characterization of the human melanoma cell lines used for functional assays in this study
166
Appendix
DISEASE FREE SURVIVAL
OVERALL SURVIVAL
5 YEARS FOLLOW UP
5 YEARS FOLLOW UP
HR
95%CI
p
RAB7 Expression
2.52
1.39 - 4.60
0.002
Adjusted by Breslow
(mm)
2.17
1.18 - 4.00
0.013
10 YEARS FOLLOW UP
HR
95%CI
p
RAB7 Expression
2.98
1.35 - 6.59
0.007
Adjusted by Breslow
(mm)
2.36
1.06 - 5.26
0.036
10 YEARS FOLLOW UP
HR
95%CI
p
RAB7 Expression
2.43
1.41 - 4.19
0.001
Adjusted by Breslow
(mm)
2.06
1.19 - 3.59
0.010
HR
95%CI
p
RAB7 Expression
2.01
1.07 - 3.76
0.030
Adjusted by Breslow
(mm)
1.53
0.81 - 2.90
0.193
Table S6. RAB7 and patient prognosis. Kaplan-Meier, log-rank test (P), and Cox regression univariate and Breswlowadjusted analyses of Disease Free Survival (DSF) (left) and Overall survival (OS) (right) following resection of primary
melanomas, analyzed as a function of high vs low RAB7 protein levels. Hazard ratios (HR); 95% confidence intervals (95%CI).
167
Appendix
TABLE S7. Significantly up- or down-regulated pathways identified by GSEA upon RAB7 downregulation in representative
melanoma and non-melanoma cell lines. GSEA was performed using annotations from whole-genome KEGG, Reactome and NCI
pathway databases in RNA sequencing data (GSE42735) from melanoma (UACC-62) and non-melanoma (HCT116) cells stably
SIGNIFICANTLY UP- OR DOWN-REGULATED PATHWAYS IDENTIFIED BY GSEA UPON RAB7
expressing scrambled shRNA or RAB7 shRNA (shRNA 3) and harvested at day 3 after lentiviral infection. Shown are the pathways
DOWNREGULATION
IN REPRESENTATIVE
MELANOMA
AND NON-MELANOMA
CELL
LINES
significantly
enriched in RAB7-downregulated
cells (FDR<0.25).
Top scoring pathways
(FDR<0.05) are marked
in bold.
1. DOWNREGULATED PATHWAYS (UACC-62 MELANOMA CELL LINE)
NCI
KEGG
REACTOME
DATABASE
NAME
REACTOME__M PHASE
REACTOME__CELL CYCLE, MITOTIC
REACTOME__MITOTIC PROMETAPHASE
REACTOME__G2/M CHECKPOINTS
REACTOME__DNA STRAND ELONGATION
REACTOME__ACTIVATION OF ATR IN RESPONSE TO REPLICATION STRESS
REACTOME__CELL CYCLE CHECKPOINTS
REACTOME__DNA REPLICATION
REACTOME__G1/S TRANSITION
REACTOME__ACTIVATION OF THE PRE-REPLICATIVE COMPLEX
REACTOME__DNA REPLICATION PRE-INITIATION
REACTOME__ELONGATION OF INTRON-CONTAINING TRANSCRIPTS AND CO-TRANSCRIPTIONAL MRNA SPLICING
REACTOME__ELONGATION AND PROCESSING OF CAPPED TRANSCRIPTS
REACTOME__DNA REPAIR
REACTOME__EXTENSION OF TELOMERES
REACTOME__FORMATION AND MATURATION OF MRNA TRANSCRIPT
REACTOME__E2F MEDIATED REGULATION OF DNA REPLICATION
REACTOME__INTERACTIONS OF REV WITH HOST CELLULAR PROTEINS
REACTOME__LAGGING STRAND SYNTHESIS
REACTOME__METABOLISM OF NON-CODING RNA
REACTOME__ASSEMBLY OF THE PRE-REPLICATIVE COMPLEX
REACTOME__HIV LIFE CYCLE
REACTOME__M/G1 TRANSITION
REACTOME__APC/C-MEDIATED DEGRADATION OF CELL CYCLE PROTEINS
REACTOME__INTERACTIONS OF VPR WITH HOST CELLULAR PROTEINS
REACTOME__NUCLEAR IMPORT OF REV PROTEIN
REACTOME__DOUBLE-STRAND BREAK REPAIR
REACTOME__GAP-FILLING DNA REPAIR SYNTHESIS AND LIGATION IN GG-NER
REACTOME__APC-CDC20 MEDIATED DEGRADATION OF NEK2A
REACTOME__LATE PHASE OF HIV LIFE CYCLE
REACTOME__GAP-FILLING DNA REPAIR SYNTHESIS AND LIGATION IN TC-NER
DNA_REPLICATION_-_HOMO_SAPIENS_(HUMAN)
CELL_CYCLE_-_HOMO_SAPIENS_(HUMAN)
PYRIMIDINE_METABOLISM_-_HOMO_SAPIENS_(HUMAN)
FANCONI_PATHWAY:FANCONI ANEMIA PATHWAY
AURORA_B_PATHWAY:AURORA B SIGNALING
PLK1_PATHWAY:PLK1 SIGNALING EVENTS
ATR_PATHWAY:ATR SIGNALING PATHWAY
E2F_PATHWAY:E2F TRANSCRIPTION FACTOR NETWORK
BARD1PATHWAY:BARD1 SIGNALING EVENTS
FOXM1PATHWAY:FOXM1 TRANSCRIPTION FACTOR NETWORK
AURORA_A_PATHWAY:AURORA A SIGNALING
ATM_PATHWAY:ATM PATHWAY
MYC_ACTIVPATHWAY:VALIDATED TARGETS OF C-MYC TRANSCRIPTIONAL ACTIVATION
TOLL_ENDOGENOUS_PATHWAY:ENDOGENOUS TLR SIGNALING
SIZE
FDR q-val
86
<0.0001
277
<0.0001
82
<0.0001
34
<0.0001
30
<0.0001
30
<0.0001
101
<0.0001
85
<0.0001
88
<0.0001
23
<0.0001
66
<0.0001
121
<0.0001
121
<0.0001
95
<0.0001
23
<0.0001
139
0.003
21
0.005
30
0.016
19
0.025
20
0.028
52
0.035
99
0.035
52
0.048
72
0.046
33
0.055
28
0.087
18
0.087
15
0.125
22
0.137
88
0.153
15
0.191
34
<0.0001
104
0.007
88
0.186
44
<0.0001
38
<0.0001
42
<0.0001
38
1.01E-04
71
5.48E-04
29
6.60E-04
38
0.0109909
30
0.01218575
34
0.01694113
79
0.04611067
24
0.08515701
2. UPREGULATED PATHWAYS (UACC-62 MELANOMA CELL LINE)
REACTOME
DATABASE
NAME
REACTOME__CLASSICAL ANTIBODY-MEDIATED COMPLEMENT ACTIVATION
REACTOME__FORMATION OF PLATELET PLUG
REACTOME__INTEGRIN CELL SURFACE INTERACTIONS
REACTOME__NEF-MEDIATES DOWN MODULATION OF CELL SURFACE RECEPTORS BY RECRUITING THEM TO CLATHRIN ADAPTERS
REACTOME__HEMOSTASIS
REACTOME__GLYCOLYSIS
REACTOME__MEMBRANE TRAFFICKING
REACTOME__INTEGRIN ALPHAIIBBETA3 SIGNALING
REACTOME__EXOCYTOSIS OF ALPHA GRANULE
REACTOME__IMMUNOREGULATORY INTERACTIONS BETWEEN A LYMPHOID AND A NON-LYMPHOID CELL
REACTOME__CELL SURFACE INTERACTIONS AT THE VASCULAR WALL
REACTOME__INTRINSIC PATHWAY
REACTOME__BASIGIN INTERACTIONS
REACTOME__PI3K/AKT SIGNALLING
REACTOME__NCAM1 INTERACTIONS
REACTOME__FORMATION OF FIBRIN CLOT (CLOTTING CASCADE)
REACTOME__CLASS B/2 (SECRETIN FAMILY RECEPTORS)
REACTOME__CREATION OF C4 AND C2 ACTIVATORS
REACTOME__OLFACTORY SIGNALING PATHWAY
REACTOME__PEPTIDE CHAIN ELONGATION
REACTOME__NEURORANSMITTER RECEPTOR BINDING AND DOWNSTREAM TRANSMISSION IN THE POSTSYNAPTIC CELL
REACTOME__GLUTAMATE BINDING, ACTIVATION OF AMPA RECEPTORS AND SYNAPTIC PLASTICITY
REACTOME__PI3K CASCADE
REACTOME__DIABETES PATHWAYS
REACTOME__ELECTRON TRANSPORT CHAIN
REACTOME__METABOLISM OF BILE ACIDS AND BILE SALTS
REACTOME__GLUCOSE REGULATION OF INSULIN SECRETION
REACTOME__NCAM SIGNALING FOR NEURITE OUT-GROWTH
REACTOME__G(S)-ALPHA MEDIATED EVENTS IN GLUCAGON SIGNALLING
REACTOME__INTEGRATION OF ENERGY METABOLISM
REACTOME__AXON GUIDANCE
REACTOME__COMPLEMENT CASCADE
REACTOME__APOPTOTIC CLEAVAGE OF CELLULAR PROTEINS
168
SIZE
FDR q-val
15
0.00838841
103
0.01967726
76
0.01936138
20
0.01901494
210
0.01646517
20
0.01851544
40
0.01608925
21
0.0253362
56
0.02482065
73
0.02508278
84
0.03821398
15
0.03860102
23
0.11686838
29
0.10913188
25
0.11578983
24
0.1443846
28
0.15163149
18
0.18257278
253
0.19473417
100
0.19209401
27
0.19213723
27
0.1851637
21
0.18657506
251
0.21221207
74
0.20692673
23
0.20272683
146
46
24
204
46
29
33
0.1970926
0.20521082
0.20030124
0.20510356
0.21086268
0.23172796
0.23814444
Appendix
2. UPREGULATED PATHWAYS (UACC-62 MELANOMA CELL LINE)
NCI
KEGG
DATABASE
NAME
GLYCAN_STRUCTURES_-_BIOSYNTHESIS_1_-_HOMO_SAPIENS_(HUMAN)
CELL_ADHESION_MOLECULES_(CAMS)_-_HOMO_SAPIENS_(HUMAN)
GLYCAN_STRUCTURES_-_DEGRADATION_-_HOMO_SAPIENS_(HUMAN)
LEUKOCYTE_TRANSENDOTHELIAL_MIGRATION_-_HOMO_SAPIENS_(HUMAN)
ECM-RECEPTOR_INTERACTION_-_HOMO_SAPIENS_(HUMAN)
ANTIGEN_PROCESSING_AND_PRESENTATION_-_HOMO_SAPIENS_(HUMAN)
FOCAL_ADHESION_-_HOMO_SAPIENS_(HUMAN)
AMINOSUGARS_METABOLISM_-_HOMO_SAPIENS_(HUMAN)
CHONDROITIN_SULFATE_BIOSYNTHESIS_-_HOMO_SAPIENS_(HUMAN)
HEMATOPOIETIC_CELL_LINEAGE_-_HOMO_SAPIENS_(HUMAN)
GLYCAN_STRUCTURES_-_BIOSYNTHESIS_2_-_HOMO_SAPIENS_(HUMAN)
JAK-STAT_SIGNALING_PATHWAY_-_HOMO_SAPIENS_(HUMAN)
AUTOIMMUNE_THYROID_DISEASE_-_HOMO_SAPIENS_(HUMAN)
TYPE_I_DIABETES_MELLITUS_-_HOMO_SAPIENS_(HUMAN)
KERATAN_SULFATE_BIOSYNTHESIS_-_HOMO_SAPIENS_(HUMAN)
GALACTOSE_METABOLISM_-_HOMO_SAPIENS_(HUMAN)
FRUCTOSE_AND_MANNOSE_METABOLISM_-_HOMO_SAPIENS_(HUMAN)
TIGHT_JUNCTION_-_HOMO_SAPIENS_(HUMAN)
REGULATION_OF_ACTIN_CYTOSKELETON_-_HOMO_SAPIENS_(HUMAN)
GAP_JUNCTION_-_HOMO_SAPIENS_(HUMAN)
OXIDATIVE_PHOSPHORYLATION_-_HOMO_SAPIENS_(HUMAN)
N-GLYCAN_BIOSYNTHESIS_-_HOMO_SAPIENS_(HUMAN)
GLYCOSPHINGOLIPID_BIOSYNTHESIS_-_GANGLIOSERIES_-_HOMO_SAPIENS_(HUMAN)
ALZHEIMER'S_DISEASE_-_HOMO_SAPIENS_(HUMAN)
APOPTOSIS_-_HOMO_SAPIENS_(HUMAN)
CHRONIC_MYELOID_LEUKEMIA_-_HOMO_SAPIENS_(HUMAN)
NATURAL_KILLER_CELL_MEDIATED_CYTOTOXICITY_-_HOMO_SAPIENS_(HUMAN)
SMALL_CELL_LUNG_CANCER_-_HOMO_SAPIENS_(HUMAN)
INSULIN_SIGNALING_PATHWAY_-_HOMO_SAPIENS_(HUMAN)
AXON_GUIDANCE_-_HOMO_SAPIENS_(HUMAN)
GLYCOLYSIS_/_GLUCONEOGENESIS_-_HOMO_SAPIENS_(HUMAN)
INOSITOL_PHOSPHATE_METABOLISM_-_HOMO_SAPIENS_(HUMAN)
O-GLYCAN_BIOSYNTHESIS_-_HOMO_SAPIENS_(HUMAN)
EPITHELIAL_CELL_SIGNALING_IN_HELICOBACTER_PYLORI_INFECTION_-_HOMO_SAPIENS_(HUMAN)
COMPLEMENT_AND_COAGULATION_CASCADES_-_HOMO_SAPIENS_(HUMAN)
ERBB_SIGNALING_PATHWAY_-_HOMO_SAPIENS_(HUMAN)
GLYCEROLIPID_METABOLISM_-_HOMO_SAPIENS_(HUMAN)
CYTOKINE-CYTOKINE_RECEPTOR_INTERACTION_-_HOMO_SAPIENS_(HUMAN)
MELANOMA_-_HOMO_SAPIENS_(HUMAN)
SIZE FDR
113
115
27
102
85
76
186
27
20
71
58
138
46
37
17
31
37
122
197
85
117
40
15
27
81
74
116
86
128
124
57
47
29
64
62
85
45
225
67
q-val
<0.0001
0.01128041
0.04056513
0.04269259
0.0432842
0.04394831
0.04950933
0.07179534
0.07282304
0.07333832
0.07801138
0.07842021
0.08743946
0.0880243
0.08975697
0.08988976
0.09018355
0.09094558
0.09114642
0.09158529
0.09356262
0.09765068
0.10406436
0.12694243
0.12932102
0.13115391
0.16281699
0.16349994
0.16410345
0.16636552
0.17005293
0.19285673
0.19408289
0.20235842
0.22344443
0.22548513
0.22696957
0.22995618
0.23285107
PPAR_SIGNALING_PATHWAY_-_HOMO_SAPIENS_(HUMAN)
60
0.23577489
INTEGRIN_CS_PATHWAY:INTEGRIN FAMILY CELL SURFACE INTERACTIONS
24
0.01262245
ARF6_TRAFFICKINGPATHWAY:ARF6 TRAFFICKING EVENTS
48
0.01976676
LYSOPHOSPHOLIPID_PATHWAY:LPA RECEPTOR MEDIATED EVENTS
64
0.03868764
IGF1_PATHWAY:IGF1 PATHWAY
28
0.04400015
IL6_7PATHWAY:IL6-MEDIATED SIGNALING EVENTS
45
0.04896526
A6B1_A6B4_INTEGRIN_PATHWAY:A6B1 AND A6B4 INTEGRIN SIGNALING
43
0.05006161
CXCR4_PATHWAY:CXCR4-MEDIATED SIGNALING EVENTS
97
0.05018903
ECADHERIN_NASCENTAJ_PATHWAY:E-CADHERIN SIGNALING IN THE NASCENT ADHERENS JUNCTION
38
0.05030787
46
49
42
60
34
63
54
25
21
66
48
72
51
124
31
63
44
57
25
35
46
24
51
50
39
49
76
24
19
40
17
25
58
24
26
59
37
103
17
43
43
30
0.05168133
0.0524029
0.05249197
0.05251113
0.05502375
0.09599881
0.1002318
0.10785396
0.12341514
0.12517372
0.12831745
0.1296601
0.13114354
0.13248943
0.14232591
0.14390154
0.14599414
0.14841408
0.1512948
0.15236078
0.15469341
0.15510428
0.15837726
0.16307765
0.1635841
0.16704606
0.17017573
0.17049243
0.17246254
0.17291948
0.18491796
0.1972177
0.19961236
0.19996001
0.20215957
0.21128222
0.21195725
0.21226509
0.2123452
0.2371342
0.24791914
0.24983431
HEDGEHOG_GLIPATHWAY:HEDGEHOG SIGNALING EVENTS MEDIATED BY GLI PROTEINS
TAP63PATHWAY:VALIDATED TRANSCRIPTIONAL TARGETS OF TAP63 ISOFORMS
THROMBIN_PAR1_PATHWAY:PAR1-MEDIATED THROMBIN SIGNALING EVENTS
MYC_REPRESSPATHWAY:VALIDATED TARGETS OF C-MYC TRANSCRIPTIONAL REPRESSION
UPA_UPAR_PATHWAY:UROKINASE-TYPE PLASMINOGEN ACTIVATOR (UPA) AND UPAR-MEDIATED SIGNALING
HIF1_TFPATHWAY:HIF-1-ALPHA TRANSCRIPTION FACTOR NETWORK
TGFBRPATHWAY:TGF-BETA RECEPTOR SIGNALING
WNT_SIGNALING_PATHWAY:WNT SIGNALING NETWORK
RXR_VDR_PATHWAY:RXR AND RAR HETERODIMERIZATION WITH OTHER NUCLEAR RECEPTOR
P75NTRPATHWAY:P75(NTR)-MEDIATED SIGNALING
ANGIOPOIETINRECEPTOR_PATHWAY:ANGIOPOIETIN RECEPTOR TIE2-MEDIATED SIGNALING
AVB3_INTEGRIN_PATHWAY:INTEGRINS IN ANGIOGENESIS
NFAT_3PATHWAY:ROLE OF CALCINEURIN-DEPENDENT NFAT SIGNALING IN LYMPHOCYTES
PDGFRBPATHWAY:PDGFR-BETA SIGNALING PATHWAY
SYNDECAN_4_PATHWAY:SYNDECAN-4-MEDIATED SIGNALING EVENTS
INTEGRIN1_PATHWAY:BETA1 INTEGRIN CELL SURFACE INTERACTIONS
CERAMIDE_PATHWAY:CERAMIDE SIGNALING PATHWAY
FAK_PATHWAY:SIGNALING EVENTS MEDIATED BY FOCAL ADHESION KINASE
IL27PATHWAY:IL27-MEDIATED SIGNALING EVENTS
PI3KPLCTRKPATHWAY:TRK RECEPTOR SIGNALING MEDIATED BY PI3K AND PLC-GAMMA
SYNDECAN_1_PATHWAY:SYNDECAN-1-MEDIATED SIGNALING EVENTS
HDAC_CLASSIII_PATHWAY:SIGNALING EVENTS MEDIATED BY HDAC CLASS III
KITPATHWAY:SIGNALING EVENTS MEDIATED BY STEM CELL FACTOR RECEPTOR (C-KIT)
TXA2PATHWAY:THROMBOXANE A2 RECEPTOR SIGNALING
TCPTP_PATHWAY:SIGNALING EVENTS MEDIATED BY TCPTP
PTP1BPATHWAY:SIGNALING EVENTS MEDIATED BY PTP1B
MET_PATHWAY:SIGNALING EVENTS MEDIATED BY HEPATOCYTE GROWTH FACTOR RECEPTOR (C-MET)
INTEGRIN_A9B1_PATHWAY:ALPHA9 BETA1 INTEGRIN SIGNALING EVENTS
ARF_3PATHWAY:ARF1 PATHWAY
ECADHERIN_STABILIZATION_PATHWAY:STABILIZATION AND EXPANSION OF THE E-CADHERIN ADHERENS JUNCTION
EPHA2_FWDPATHWAY:EPHA2 FORWARD SIGNALING
ALK1PATHWAY:ALK1 SIGNALING EVENTS
ENDOTHELINPATHWAY:ENDOTHELINS
LYMPHANGIOGENESIS_PATHWAY:VEGFR3 SIGNALING IN LYMPHATIC ENDOTHELIUM
NECTIN_PATHWAY:NECTIN ADHESION PATHWAY
IL4_2PATHWAY:IL4-MEDIATED SIGNALING EVENTS
RET_PATHWAY:SIGNALING EVENTS REGULATED BY RET TYROSINE KINASE
ERBB1_DOWNSTREAM_PATHWAY:ERBB1 DOWNSTREAM SIGNALING
BETACATENIN_DEG_PATHWAY:DEGRADATION OF BETA CATENIN
INSULIN_PATHWAY:INSULIN PATHWAY
ERBB2ERBB3PATHWAY:ERBB2/ERBB3 SIGNALING EVENTS
INTEGRIN_A4B1_PATHWAY:ALPHA4 BETA1 INTEGRIN SIGNALING EVENTS
169
Appendix
3. DOWNREGULATED PATHWAYS (HCT116 COLON CANCER CELL LINE)
KEGG
REACTOME
DATABASE
NAME
REACTOME__EXOCYTOSIS OF ALPHA GRANULE
REACTOME__FORMATION OF PLATELET PLUG
REACTOME__HEMOSTASIS
REACTOME__INTEGRIN CELL SURFACE INTERACTIONS
REACTOME__APOPTOTIC CLEAVAGE OF CELLULAR PROTEINS
REACTOME__NCAM SIGNALING FOR NEURITE OUT-GROWTH
REACTOME__AXON GUIDANCE
REACTOME__APC/C:CDC20 MEDIATED DEGRADATION OF MITOTIC PROTEINS
REACTOME__FURTHER PLATELET RELEASATE
REACTOME__G1/S DNA DAMAGE CHECKPOINTS
REACTOME__NCAM1 INTERACTIONS
REACTOME__APOPTOTIC EXECUTION PHASE
REACTOME__MUSCLE CONTRACTION
REACTOME__CDC20:PHOSPHO-APC/C MEDIATED DEGRADATION OF CYCLIN A
REACTOME__ACTIVATION OF APC/C AND APC/C:CDC20 MEDIATED DEGRADATION OF MITOTIC PROTEINS
REACTOME__APC/C:CDC20 MEDIATED DEGRADATION OF SECURIN
REACTOME__AUTODEGRADATION OF CDH1 BY CDH1:APC/C
REACTOME__CELL SURFACE INTERACTIONS AT THE VASCULAR WALL
REACTOME__GLUCOSE METABOLISM
REACTOME__CDK-MEDIATED PHOSPHORYLATION AND REMOVAL OF CDC6
REACTOME__GLYCOLYSIS
REACTOME__PHASE 1 - FUNCTIONALIZATION OF COMPOUNDS
REACTOME__CELL DEATH SIGNALLING VIA NRAGE, NRIF AND NADE
REACTOME__GLUCONEOGENESIS
REACTOME__BASIGIN INTERACTIONS
REACTOME__G(S)-ALPHA MEDIATED EVENTS IN GLUCAGON SIGNALLING
ECM-RECEPTOR_INTERACTION_-_HOMO_SAPIENS_(HUMAN)
ALZHEIMER'S_DISEASE_-_HOMO_SAPIENS_(HUMAN)
PPAR_SIGNALING_PATHWAY_-_HOMO_SAPIENS_(HUMAN)
SPHINGOLIPID_METABOLISM_-_HOMO_SAPIENS_(HUMAN)
GLUTATHIONE_METABOLISM_-_HOMO_SAPIENS_(HUMAN)
PROTEASOME_-_HOMO_SAPIENS_(HUMAN)
CELL_ADHESION_MOLECULES_(CAMS)_-_HOMO_SAPIENS_(HUMAN)
ANTIGEN_PROCESSING_AND_PRESENTATION_-_HOMO_SAPIENS_(HUMAN)
AXON_GUIDANCE_-_HOMO_SAPIENS_(HUMAN)
CARBON_FIXATION_-_HOMO_SAPIENS_(HUMAN)
POLYUNSATURATED_FATTY_ACID_BIOSYNTHESIS_-_HOMO_SAPIENS_(HUMAN)
PYRUVATE_METABOLISM_-_HOMO_SAPIENS_(HUMAN)
SIZE
51
97
207
77
32
44
44
63
20
50
23
38
27
61
64
59
58
86
74
44
20
57
23
31
25
24
85
27
60
35
37
21
114
78
120
21
15
39
FDR q-val
0.00539583
0.01474072
0.04375368
0.10112921
0.14367585
0.1724425
0.1871709
0.19323502
0.19445132
0.19954892
0.20022282
0.2021108
0.20359442
0.204563
0.21012999
0.21391934
0.21625
0.21701321
0.22160994
0.22272432
0.23832981
0.24262054
0.24464706
0.24813245
0.2486531
0.24909715
0.06163346
0.09436793
0.19583198
0.19969407
0.20419754
0.20671786
0.21696399
0.21856105
0.23966669
0.24837023
0.24879314
0.2495452
4. UPREGULATED PATHWAYS (HCT116 COLON CANCER CELL LINE)
REACTOME
DATABASE
KEGG
NCI
NAME
REACTOME__EUKARYOTIC TRANSLATION ELONGATION
REACTOME__3 -UTR-MEDIATED TRANSLATIONAL REGULATION
REACTOME__PEPTIDE CHAIN ELONGATION
REACTOME__FORMATION OF A POOL OF FREE 40S SUBUNITS
REACTOME__GTP HYDROLYSIS AND JOINING OF THE 60S RIBOSOMAL SUBUNIT
REACTOME__L13A-MEDIATED TRANSLATIONAL SILENCING OF CERULOPLASMIN EXPRESSION
REACTOME__EUKARYOTIC TRANSLATION TERMINATION
REACTOME__INFLUENZA VIRAL RNA TRANSCRIPTION AND REPLICATION
REACTOME__CAP-DEPENDENT TRANSLATION INITIATION
REACTOME__EUKARYOTIC TRANSLATION INITIATION
REACTOME__ACTIVATION OF THE MRNA UPON BINDING OF THE CAP-BINDING COMPLEX AND EIFS, AND SUBSEQUENT BINDING TO 43S
REACTOME__INFLUENZA LIFE CYCLE
REACTOME__INFLUENZA INFECTION
REACTOME__FORMATION OF THE TERNARY COMPLEX, AND SUBSEQUENTLY, THE 43S COMPLEX
REACTOME__METABOLISM OF PROTEINS
REACTOME__G2/M CHECKPOINTS
REACTOME__M PHASE
REACTOME__ELONGATION OF INTRON-CONTAINING TRANSCRIPTS AND CO-TRANSCRIPTIONAL MRNA SPLICING
REACTOME__GENE EXPRESSION
REACTOME__ELONGATION AND PROCESSING OF CAPPED TRANSCRIPTS
REACTOME__MITOTIC PROMETAPHASE
REACTOME__ACTIVATION OF THE PRE-REPLICATIVE COMPLEX
REACTOME__ACTIVATION OF ATR IN RESPONSE TO REPLICATION STRESS
REACTOME__CLEAVAGE OF GROWING TRANSCRIPT IN THE TERMINATION REGION
REACTOME__FORMATION AND MATURATION OF MRNA TRANSCRIPT
RIBOSOME_-_HOMO_SAPIENS_(HUMAN)
NAPHTHALENE_AND_ANTHRACENE_DEGRADATION_-_HOMO_SAPIENS_(HUMAN)
PLK1_PATHWAY:PLK1 SIGNALING EVENTS
170
SIZE FDR q-val
104
<0.0001
121
<0.0001
100
<0.0001
110
<0.0001
122
<0.0001
121
<0.0001
100
<0.0001
152
<0.0001
129
<0.0001
129
1.18E-04
64
2.92E-04
156
3.16E-04
161
3.45E-04
55
0.00134256
207
0.09879488
34
0.10528342
86
0.13186814
121
0.13790113
346
0.14086446
121
0.14316013
82
0.14367956
23
0.1830022
30
0.1976846
23
0.20171253
139
0.20955685
66
<0.0001
18
0.19851044
42
0.1614753
Renal
Prostate
Ovarian
NSLC
Leukemia
Colon
CNS
Breast
MELANOMA
Appendix
LYSOSOME
*
Figure S1. The melanoma-enriched lysosome cluster. GSEA heat map showing the relative
enrichment of genes from the Gene Ontology – Lysosome gene set in melanoma cells compared
to the rest of the NCI-60 cell lines. Dataset (GSE5720GO)2
171
Appendix
SUPPLEMENTARY VIDEO LEGENDS
Video S1. Time-lapse imaging of control and RAB7-depleted SK-Mel-28 melanoma cells to show the impact of
this GTPase on cellular morphology and motility. Imaging by optical microscopy (bright field images) of SK-Mel-28
cells (BRAF-mutated) stably expressing scrambled shRNA (left) or RAB7 shRNA2 (right). Images were captured at 10
min intervals in a Leica DMI6000 B fluorescence microscope coupled to a CO2 and temperature-controlled
incubation chamber. Note the active emission and retraction of cellular extensions in highly dendritic SK-Mel-28
cells expressing RAB7 shRNA.
Video S2. Dynamic morphological changes in RAB7-depleted melanoma cells. Time lapse bright field imaging of
SK-Mel-103 cells (NRAS-mutated, MITF negative) stably expressing dominant-negative RAB7 (T22N). Images were
captured at 10 min intervals in a Delta Vision RT microscope coupled to a CO2 and temperature-controlled
incubation chamber. Note the prominent cytosolic vacuolization and the dynamic assembly and disassembly of
cell-cell contacts.
Video S3. Real time imaging of the recruitment of LC3 to large single-membrane RAB7-positive endosomes
generated from the plasma membrane. Real-time imaging of control SK-Mel-103 melanoma cells stably expressing
GFP-RAB7 (green) and the autophagy protein LC3 labeled in red by fusion to the cherry protein. Images were
captured at 10-minute intervals in a Delta Vision RT fluorescence microscope, coupled to a CO2 and temperaturecontrolled incubation chamber. Note the recruitment of the autophagosomal marker LC3 to RAB7-coated
endocytic vesicles (>1µm diameter) once they reach the perinuclear region.
Video S4. Activation of macropinocytosis in melanocytes expressing oncogenic RAS. Time lapse bright field
imaging of primary foreskin melanocytes expressing HRASG12V (right) or empty vector (left). Cells were imaged at
day 3 after lentiviral-mediated transduction, after the acquisition of features of oncogene-induced senescence in
HRASG12V-expressing melanocytes. Images were captured at 10 min intervals in a Delta Vision RT microscope
coupled to a CO2 and temperature-controlled incubation chamber. Note active generation of macropinosomes and
a dynamic motile behaviour in senescent HRASG12V-expressing melanocytes.
172
Appendix
PUBLICATIONS
Alonso-Curbelo D, Riveiro-Falkenbach E, Pérez-Guijarro E, Megías D, Gómez-López G, Olmeda D,
Calvo TG, Osterloh L, Cifdaloz M, Cañón E, Pisano DG, Ortíz-Romero P, Tormo D, Hoek K, RodríguezPeralto JL and Soengas MS (2013). RAB7 controls melanoma progression by exploiting a lineagespecific wiring of the endolysomal pathway. (Submitted to Cancer Cell)
Alonso-Curbelo D, Soengas MS (2010). Self-killing of melanoma cells by cytosolic delivery of dsRNA:
Wiring innate immunity for a coordinated mobilization of endosomes, autophagosomes and the
apoptotic machinery in tumor cells. Autophagy 6, 148-150. Review
Tormo D, Alonso-Curbelo D, Soengas MS (2009). Cytosolic delivery of dsRNA triggers MDA-5 mediated
autonomous cell death in aggressive melanomas. Clin Transl Oncol 11, 39-41. Review
Tormo D, Checinska A, Alonso-Curbelo D, Pérez-Guijarro E, Cañón E, Riveiro-Falkenbach E, Calvo TG,
Larribere L, Megías D, Mulero F, Piris MA, Dash R, Barral PM, Rodríguez-Peralto JL, Ortíz-Romero P,
Tüting T, Fisher PB, Soengas MS (2009). Targeted activation of innate immunity for therapeutic
induction of autophagy and apoptosis in melanoma cells. Cancer Cell 16, 103-114.
PRESENTATIONS
Alonso-Curbelo D, Riveiro-Fakenbach E, Pérez-Guijarro E, Gómez-López G, Megías D, Olmeda D, Pisano
D, Joyce J, Rodríguez-Peralto JL, Soengas MS. Oral presentation: Addiction of melanoma cells to the
GTPase RAB7 imposed by a lineage dependent wiring of endolysosomal pathways. Cell Symposia:
Hallmarks of Cancer (San Francisco, USA), 2012.
Alonso-Curbelo D, Pérez-Guijarro E, Olmeda D, Riveiro-Falkenbach E, Osterloh L and Soengas MS. Poster
presentation: RAB7-dependent endo/lysosomal vesicle trafficking in melanoma progression. CHSL
Meeting on Cell Death (Cold Spring Harbor, NY, USA), 2011.
Alonso-Curbelo D, Olmeda D, Pérez-Guijarro E, Calvo TG and Soengas MS. Poster presentation: RABdependent endo/lysosomal vesicle trafficking in melanoma progression. IDIBELL Cancer Conferences on
Metastasis and Angiogenesis (Barcelona, Spain), 2011.
Alonso-Curbelo D, Olmeda D, Pérez-Guijarro E, Calvo TG and Soengas MS. Poster presentation: RAB7dependent endo/lysosomal vesicle trafficking in melanoma. 1st Prize Award. “CNIO PhD Student Lab
Day” (Madrid, Spain), 2011.
Alonso-Curbelo D, Riveiro-Falkenbach E, Rodríguez-Peralto JL and Soengas MS. Poster presentation:
Intracellular protein degradation pathways in melanoma progression and drug response. 7th Annual
International Melanoma Congress of the Society for Melanoma Research (Sydney, Australia), 2010.
Alonso-Curbelo D, Tormo D, Megías D and Soengas MS. Poster presentation: Membrane trafficking in
melanoma progression and chemoresistance. 6th Annual International Melanoma Congress of the
Society for Melanoma Research (Boston, USA), 2009.
173
Appendix
174