66512 Alonso Curbelo Direna.Pdf

Contents

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 Contents

Contents

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 Contents

Contents

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

Contents

Dr. Jaime Millán Martínez, Head of group of Cell Biology of Inflammation at the Centro de Biología Molecular Severo Ochoa (CBMSO)

CERTIFIES:

I hereby issue this certification in Madrid on April 30st 2013.

Jaime Millán Martínez

PhD Thesis Tutor

Contents

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)

Contents

“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)

Contents

A mi padre del que tanto aprendí

Contents

Acknowledgements

Contents

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, Contents

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

Contents

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! Contents

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…

Contents

"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)

Contents

ABBREVIATIONS 7

SUMMARY 19

RESUMEN 23

INTRODUCTION 27

1. THE MELANOMA CHALLENGE: WHERE ARE WE NOW? 29

2. THE CELLULAR ORIGIN OF MELANOMA: THE MELANOCYTE 30

3. CLASSIFICATION OF CUTANEOUS MELANOCYTIC LESIONS 31

3.1 BENIGN MELANOCYTIC LESIONS: NEVI 32

3.2. MALIGNANT MELANOCYTIC LESIONS: MELANOMA 32

4. DEVELOPMENT AND PROGRESSION OF MELANOCYTIC TUMORS 34

4.1 HISTOLOGIC, BIOLOGIC AND GENETIC FEATURES ASSOCIATED WITH 34 MELANOMA PROGRESSION

4.2. INTRATUMOR HETEROGENEITY AND MELANOMA-CELL PLASTICITY 39

5. MELANOMA ONCOGENES AND “NON-ONCOGENE” DEPENDENCIES 41

5.1. MELANOMA ONCOGENES: “CLASSICAL” VERSUS “LINEAGE-SPECIFIC” FACTORS 41

5.2. NON-ONCOGENE DEPENDENCIES IN MELANOMA: AUTOPHAGY AND BEYOND 44

6. TREATMENT OF CUTANEOUS MELANOMA 48

OBJECTIVES 51

OBJETIVOS 55

MATERIALS AND METHODS 59

Contents

1. CELLS 61

2. GENE SET ENRICHMENT ANALYSIS (GSEA) IN MULTITUMOR DATASETS 61

3. OLIGONUCLEOTIDE ARRAY CGH (COMPARATIVE GENOMIC HYBRIDIZATION) 62

4. TISSUE MICROARRAYS (TMAS) AND IMMUNOHISTOCHEMISTRY (IHC) 62

5. KAPLAN-MEIER SURVIVAL ANALYSES 62

6. PROTEIN IMMUNOBLOTTING 63

7. IMMUNOFLUORESCENCE AND CONFOCAL-BASED SINGLE-CELL QUANTIFICATION IN 63 TISSUES

8. IMMUNOFLUORESCENCE IN FIXED CELLS 64

9. RAB7 EXPRESSION IN MELANOMA “INVASIVE” OR “PROLIFERATIVE” GENE 65 SIGNATURES

10. STABLE INHIBITION OF RAB7 FUNCTION 65

11. SITE-DIRECTED MUTAGENESIS AND RAB7 shRNA- RESCUE ASSAYS 66

12. siRNA-MEDIATED GENE SILENCING OF ATG7, RAB7, VPS34, SOX10 AND MITF 66

13. BECLIN1 STABLE RNA INTERFERENCE 67

14. CELL PROLIFERATION AND COLONY FORMATION ASSAYS 67

15. ANIMAL EXPERIMENTS: XENOGRAFT ASSAYS AND MELANOMA MODELS 68

16. MATRIGEL INVASION ASSAYS 68

17. ASSESSMENT OF LYSOSOMAL FUNCTION 69

18. GENERATION OF PEI-COMPLEXED PIC GENERATION OF PEI-COMPLEXED PIC 69

19. DRUG TREATMENTS AND VIABILITY ASSAYS 69

20. FLUID PHASE ENDOCYTOSIS ASSAYS 70

Contents

21. RNA EXTRACTION, RT-PCR AND HIGH THROUGHPUT RNA SEQUENCING 71

22. VISUALIZATION AND QUANTITATIVE ANALYSIS OF CYTOSKELETAL ALTERATIONS 72 (CYTOOCHIPS)

23. VIDEO AND FIXED-CELL FLUORESCENCE MICROSCOPY OF ENDOCYTIC AND 73 AUTOPHAGIC TRAFFICKING

24. TRANSMISSION ELECTRON MICROSCOPY 73

25. PROTEIN SECRETION ASSAYS 74

26. ONCOGENE-INDUCED SENESCENCE ASSAYS IN PRIMARY HUMAN MELANOCYTES 74

27. STATISTICAL ANALYSES 75

RESULTS 77

1. LINEAGE-RESTRICTED TRAITS ASSOCIATED WITH THE LYSOSOME IN MELANOMA 79

2. LINEAGE-RESTRICTED OVEREXPRESSION OF RAB7 IN MELANOMA 81

3. MITF-INDEPENDENT OVEREXPRESSION OF RAB7 IN MELANOMA 83

4. LINEAGE-ADDICTION OF MELANOMA CELLS TO RAB7 84

5. MELANOMA CELL MORPHOLOGY AND INVASIVE POTENTIAL CONTROLLED BY RAB7 87

6. RAB7 IS AN EARLY-INDUCED MELANOMA DRIVER TUNED DOWN AT INVASIVE 89 STAGES OF TUMOR PROGRESSION IN VIVO

7. HALTED DEGRADATION OF NON-CANONICAL AUTOPHAGOSOMES AND 91 MACROENDOSOMES IN RAB7-DEPLETED MELANOMA CELLS

8. DERAILED VESICLE TRAFFIC BY RAB7 DOWNREGULATION PROMOTES THE SECRETION 93 OF LYSOSOMAL PROTEASES

9. GLOBAL CHANGES IN GENE EXPRESSION AND PROTEIN SECRETION PROGRAMS BY 95 MODULATION OF RAB7 LEVELS

Contents

10. UPSTREAM REGULATION OF RAB7 BY MELANOCYTE DEVELOPMENTAL PATHWAYS 97

11. REGULATION OF RAB7 EXPRESSION AND FUNCTION BY ONCOGENIC SIGNALING 98 PATHWAYS IN MELANOMA CELLS

12. ACTIVATION OF ONCOGENIC SIGNALING IN NORMAL MELANOCYTES DEREGULATES 100 RAB7 AND ITS ASSOCIATED VESICLE TRAFFICKING PATHWAYS

13. ONCOGEN-DRIVEN ACTIVATION OF RAB7 IN VIVO 102

14. MODULATION OF RAB7-ASSOCIATED ENDOLYSOSOMAL VESICLE TRAFFICKING BY 103 TREATMENT WITH ds-RNA-BASED NANOCOMPLEXES

15. RAB7-MEDIATED VESICLE TRAFFICKING IS ACTIVELY INVOLVED IN THE ANTI- 104 MELANOMA ACTIVITY OF ds-RNA-BASED NANOCOMPLEXES

DISCUSSION 109

1. LESSONS FROM MULTITUMOR GSEA IN MELANOMA GENE DISCOVERY 111

2. BIOLOGICAL IMPLICATIONS OF MELANOMA-ASSOCIATED TRAITS IDENTIFIED BY GSEA 113

3. CELL LINEAGE AS A DETERMINANT OF RAB7 EXPRESSION AND FUNCTION IN CANCER 115

4. RAB7 EXPRESSION AND FUNCTION IN MELANOMA PROGRESSION 116

5. RAB7 VERSUS MITF AND OTHER LINEAGE-SPECIFIC MELANOMA DRIVERS 119

6. DOWNSTREAM EFFECTOR PATHWAYS OF RAB7 IN MELANOMA CELLS 119

7. ANTITUMOR THERAPEUTIC OPPORTUNITIES TARGETING ENDOLYSOSOMAL 122 PATHWAYS

8. PERSPECTIVES 125

CONCLUSIONS 127

CONCLUSIONES 131

Contents

REFERENCES 135

APPENDIX 161

1. SUPPLEMENTARY TABLES 163

2. SUPPLEMENTARY FIGURE 171

3. SUPPLEMENTARY VIDEO LEGENDS 172

4. PUBLICATIONS 173

5. PRESENTATIONS 173

Contents

Abbreviations

“Lo bueno, si breve, dos veces bueno”

Baltasar Gracián (1601-1658)

Contents

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 9

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

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

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

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

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

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

Abbreviations

WNT - Wingless‐type MMTV integration site family

WT - Wild Type

Summary

Abbreviations

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 type- selective 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 follow- up studies of patient prognosis. Finally, here we demonstrated that tumor-cell specific features of RAB7- dependent 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.

Summary

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

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.

Summary

Introduction

Resumen

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 drugs14- 16. 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, 25, 26 Fig. 1 Age-adjusted Melanoma Death Rates per Sex, are some of the main challenges that European Union, 1975 – 2006. Rates per 100,000 population. Source: Ref. 27 complicate the attainment of a cure for

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 Fig. 2. The skin of melanocytes. These cells are located primarily in architecture. At the top, the 1 28 the skin , the largest organ of the human body . As close-up shows melanocytes in depicted in Fig. 2, the skin is comprised of three main the basal layer of the epidermis, layers: i) the outer layer, the epidermis, mostly surrounded by composed of keratinocytes; ii) the middle layer, the keratinocytes (basal cells) dermis, containing fibroblasts, immunocompetent mast cells and macrophages, and structures such as blood and lymph vessels, hair roots and sweat glands; Source: National and (iii) the most inner layer, the subcutaneous layer, Cancer Institute website 29-31 mostly composed of fatty tissue . Specifically, (http://www.can cer.gov) melanocytes reside along the basal layer of the 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 membrane- bound 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

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, 43, mucosal surfaces from respiratory, gastrointestinal and genitourinary tracts44, and the heart45, 46. 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

Introduction

basis of the current World Health Clinicopathologic Most commonly Organization (WHO) classification of benign subtype of nevi mutated oncogene nevi, which recognizes different categories, such as common acquired nevi, congenital Common BRAF acquired nevi, spitz nevi and blue nevi, among others52 (see examples in Fig. 3). Importantly, it has Spitz HRAS been demonstrated that the clinicopathologic heterogeneity of nevi correlates with the NRAS presence of activating mutations in specific Congenital 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 Fig. 3. Representative subtypes of nevi and their most frequently mutated oncogene. Sources: Refs. 61-66 section 4) are thought to prevent malignant 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,

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 Clinicopathologic subtypes Commonly of melanoma mutated oncogenes entity23, 103, 104. However, as detailed Superficial spreading BRAF 59-78% below, classification schemes for melanoma NRAS 3-22% melanoma are currently being redefined BRAF 40-60% Lentigo maligna KIT 16-28% and are expected to gain significant melanoma NRAS 15-29% clinical relevance in the coming years. BRAF 12-23% Acral melanoma KIT 9-36% Emerging clinicogenetic classifications NRAS 8-15% Nodular melanoma BRAF 43-68% Comprehensive genomic studies11, 105-108 NRAS 12-31% GNAQ 50% have revealed that distinct genomic Uveal melanoma KIT 1-76% profiles do in fact associate well with the KIT 15-39% classical clinicopathological features Mucosal melanoma NRAS 5-15% BRAF 3-11% distinguished above; specifically, with the Fig. 4. Melanoma clinicopathologic subtypes and their most anatomical site of presentation and the frequently mutated oncogenes. Adapted from Ref. 109

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.

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 Dysplastic Bening Nevus 69, 124-128 signs of a pre-existing nevus . This has prompted the 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 non- pigment 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 Metastatic Melanoma 6, 123, 133 potential of melanocytic tumors . 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, and familial forms of melanoma67 also harbor genetic aberrations in these tumor suppressor pathways.

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 counteraparts. Adapted from Ref. 143

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.

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

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 pro- apoptotic 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 antigen- related 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 (FGF- 2), 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 tumor microenvironment189, 190.

Interestingly, several high-throughput

gene expression and tissue microarray

Skin Primary Metatasis Nevus RGP VGP Skin (TMA) analyses performed along the Nevus different stages of melanoma progression (Fig. 7) highlight the transition between thin and thick primary melanomas as the point of greatest molecular change180, 191-195. These studies have also been fundamental to identify the epithelial-to- mesenchymal (EMT) transition as a major determinant of melanoma progression196. However, the number of clinically validated biomarkers of disease Fig. 7. Examples of high-throughput gene expression (left) and progression is still limited83, 197. TMA (right) analyses at different stages of melanoma progression. Sources: Ref. 192 (left) and Ref. 195 (right)

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 VEGF- C202, 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 lineage- specification 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 hypoxia- dependent 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

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.

Introduction

Gene Alterations Frequency Pathway affected Kinases or signaling factors BRAF Point mutation 50% MAPK NRAS Point mutation 20% MAPK, PI3K ERBB4 Point mutation 15-20% MAPK, PI3K 1% overall (10% acral KIT Point mutation MAPK, PI3K lentiginous, 10% mucosal) AKT3 Amplification 25% PI3K CCND1 Amplification 10% Cell cycle Scaffold protein NEDD9 Amplification 50-60% (Integrin β3 and Src*) Point mutation or CDK4 5% Cell cycle amplification Transcription factors MITF Amplification 20% Melanocyte lineage ETV1 Amplification 15% MITF Tumor Suppressors PTEN Amplification 50-60% PI3K TP53 Amplification 5% Cell cycle Point mutation or CDKN2A/p16 30% Cell cycle deletion 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 antiapoptotic 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.

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, 255, 256, as it is commonly found to be downregulated in advanced melanomas257 (except in those in which MITF is amplified257, 258). In fact, these low-MITF expressing primary tumors214, 257 and melanoma cell lines216, 217 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. 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 Autolysosome

LC3 conjugation RAB7 PI3K ATGs SNAREs Inhibitors BECLIN1/VPS34 UVRAG Chloroquine Class III PI3K LAMP1/2 Bafilomycin A1 Damaged organelles or LYSOSOMAL proteins Amphisome Lysosome DEGRADATION Plasma Hydrolases membrane Permeases proteins

RAB7 RAB5 Early Late Endosomes Endosomes

Extracellular ENDOCYTOSIS material 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.

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 double- membrane 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

ElectronMicroscopy 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)

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 deprivation285- 288 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,

Introduction

there is a pending need to better understand the mechanisms that might underlie the context- dependency 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 signaling305- 307, 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 GTP- bound 'on' form and the GDP- bound '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 Fig. 11. Localization and function of Rab GTPases as coordinators of vesicle traffic. Each step of membrane traffic requires a specific RAB protein. nucleotide cycle311. The ability to Source: Ref. 308 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 epithelial- cell-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 Breslow 5-year Survival cutaneous melanoma initially depends on the stage at the time of diagnosis. (mm) Rates (%) The TNM classification (Table S2) and stage grouping of melanoma patients <1.0 95-100 1.0-2.0 80-96 (Table S3) is based on extensively revised clinical and histopathological 2.1-4 60-75% prognostic factors, included in American Joint Committee on Cancer (AJCC) >4.0 37-50% Melanoma Staging Database101. The depth of primary tumor invasion (or Fig. 12. Breslow thickness Breslow Thickness328) is one of the most relevant histological prognostic and patient prognosis. Source: Melanoma Research 5, 101 factor for metastatic disease and poor overall survival (Fig. 12) . Other Foundation website: http://www.melanoma.org/ clinically relevant predictors of poor prognosis included in the AJCC TNM system include: presence of ulceration and mitotic figures in the primary tumor; presence of melanoma

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

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.

Objetives

Objectives

Introduction

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

Introduction

Objetives

Objetivos

Introduction

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 pro- oncogénicos 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

Introduction

Objetives

“Ever tried. Ever failed. No matter.

Try again. Fail again. Fail better”.

Samuel Beckett (1906-1989)

Materials and Methods

Introduction

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), MBA- MD-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. 61

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

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; Ab- 1, 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). HRP- conjugated 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

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 TCS- SP5-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

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.

Materials and Methods

Unless otherwise indicated, cells were plated for expression and functional assays at day 6 post- infection, 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 used: forward primer 5´GGGAAACAAGATCGATCTTGAGAACAGACAAGTGGCCACAAAGCGG 3´, and reverse 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

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.

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 high- throughput 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.

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 CO2 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

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 TCS- SP5-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

351 with Ki,app 2.4, 94.1, 8.0 and 62.9nM for p110α, β, δ and δ, respectively) , or 0.5µM ETP-38 (a Class I 352 PI3K α,δ inhibitor with Ki,app 2.38 and 2.42 nM for p110α and δ, respectively) , to inhibit Class I PI3K- driven 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

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, dA- tailing, 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

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,

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.

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 activity- based 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. Senescence- associated 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 Kolmogorov- Smirnoff 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.

Materials and Methods

Objetives

“The experimenter who does not know what he is looking for will not understand what he finds”

Claude Bernard (1813-1878)

Results

Materials and Methods

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.

As expected, pigmentation and melanin a biosynthesis Gene Ontology (GO)-Biological

Processes (FDR<3.6x10-6) and the

Thyroid

Auton. gangliaAuton. Soft Tissue Soft

melanosome GO-Cellular Component SalivaryGland Pancreas -6 AerodigestiveTract

(FDR=1.8x10 ) were found to be Kidney

Stomach

Lung

Oesophagous

Endometrium

Ovary

andlymphoid

Hematopoietic

Intestine

Bone

MELANOMA

Pleura

Breast Liver

significantly enriched in melanoma (Table UrinaryTract

Central Nervous System NervousCentral Prostate S4 and results not shown). Interestingly, vacuole, lytic vacuoles, and lysosome GO gene sets scored even more significantly (FDR<1.0x10-8, Table S4). Within these

gene sets, a cluster of lysosome-associated (GO:0005764) factors was found to be uniquely co- regulated in melanoma cells (see heatmap for the CCLE dataset in Fig. 12a, separating LYSOSOME 55 melanoma cell lines from >750 examples of other tumor types, and Fig. b 12b for the corresponding enrichment LYSOSOME (GO:0005764) 0.6 0.5 plot). These genes code for lytic enzymes 0.4 0.3 (such as ACP5, cathepsins K, B and H, 0.2

0.1 Score (ES) Score among others) as well as for regulatory Enrichment 0.0 proteins involved in lysosome biogenesis Ranked gene list and function (such as LAMP2 and “Melanoma” “Melanoma” RAB7A)359, 360 (Fig. S1). postively correlated negatively correlated Fig 12. Lineage-specific enrichment of lysosomal factors in the Lysosomes share common precursor transcriptome of melanoma cells. (a) GSEA heat map showing a selective enrichment of the Lysosome Gene Ontology cluster organelles and constitutive factors with (GO:0005764) in melanoma cells compared to the rest of CCLE

361-370 tumor cell lines. The corresponding enrichment plot for lysosomal melanosomes . Therefore, although genes (GSEA FDR<0.05) is depicted in (b).

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 Chloroquine DQ-BSA- Early Melanosomes Bodipy-Green endosomes Bodipy-Green

Late Endosomes Lysosomes Melanoma cells Non-melanoma 1200 * cells b Melanosome 1000 800 600

Lysosome Green BSA

- 400 200

DQ 0

5 -

1246 (AU)IntensityMedian

128 62

28 29

145 19

- - -

103 143

133

- -

639V

HeLa

Mel

MCF7 U2OS

Mel Mel Mel

CAL62

1205Lu

- - -

Mel Mel

HCT116

- -

FTC

UACC

SK SK SK

SK SK LYSOSOME GENE SET (GO:0005764) WITHOUT MELANOSOMAL GENES d 0.5 100 0.4 NT) ***

0.3 to 80

0.2 cells 60 score (ES) score Enrichment Enrichment 0.1 40

0.0 relative

Vable 20 -0.1

(%, (%, 5

Ranked -

19 28 29

- - -

103 147

133

- -

gene list -

639V

HeLa

Mel

MCF7

BT549

CAL62

Mel Mel Mel

SW620

1205Lu

- - -

Mel Mel

HCT116

- -

“Melanoma” “Melanoma” FTC

UACC

SK SK SK SK postively correlated negatively correlated SK e

Melanoma cells Non-melanoma cells f

103

28 29

- - 62 SK-Mel- SK-Mel- UACC- SK-Mel- - FTC-133

639V HeLa CAL-62 Mel

Mel Mel

- -

103 147 62 19 -

SK 639V SK SK UACC HCT116 HeLa

- - + - + - + - + - + - + NT + CQ: LC3-I 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:0005764- lysosome 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.

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 non- melanoma 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 lysosome- associated 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, 378- 380, 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

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.

a b

+2 12 RAB7A – EntrezID:7879 Ratio Ratio

2 +1 (RNA) 11 0

-1 10 -2 expression

Normalized Log Normalized Chromosome 3q21.3

9 mRNA

Melanoma Non-Melanoma

c )

(10)

(

(16)

(28) (28)

(15) (15)

103 103 19 28 29

- - - -

all

Liver(28)

–

164

–

AML (34) AML

CML (15) CML

Mel

Mel Mel Mel Mel

Other (15) Other

other

Ovary (51) Ovary

- - - -

Breast (58) Breast

Kidney (34) Kidney

–

Prostate (7) Prostate

Glioma (62) Glioma

Thyroid (12) Thyroid

Bile Duct (8) Duct Bile

cell cell

Stomach (38) Stomach

SK WM RWP PC3 SK SK SK T98G U251 A549 MIAPaca SW1710 HeLa HCT116 HT29 BT549 UACC

Pancreas (44) Pancreas

UACC 639V

Colorectal (61) Colorectal

Melanoma

Meningioma (3) Meningioma T

Soft Tissue (21) Tissue Soft

Esophagus (25) Esophagus

LungNSC (131) LungNSC Urinary tract(27) Urinary

RAB7 (27) Endometrium

Mesothelioma (11) Mesothelioma

Other Leukemia(1) Other

Osteosarcoma

Neuroblastoma (17) Neuroblastoma

Lung Small Cell (53) Cell Small Lung

Medulloblastoma (4) (4) Medulloblastoma

Chondrosarcoma (4) Chondrosarcoma

Ewings Sarcoma (12) (12) Sarcoma Ewings Burkitt lymphoma (11) (11) lymphoma Burkitt

β-Actin (30) Myeloma Multiple

Lymphoma Lymphoma

Lymphoma DLBCL (18) DLBCL Lymphoma

Hodgkin Lymphoma (12) Lymphoma Hodgkin Upper Aerodigestive (32) Aerodigestive Upper d e Breast Colon Renal Cell Melanoma Lymphoma N = 121 High Low Negative Cancer Cancer Cancer 100% 80%

samples 60% of 40% Prostate Thyroid Neuroglial 20% Lung Cancer Sarcoma Cancer Cancer Tumor

0% Proportion

Fig. 14. The lysosome-asociated RAB7 small GTPase as a candidate lineage-specific cancer gene in melanoma. (a) Array- CGH 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).

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 confocal- based 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.

a b c Fig. 15. MITF-independent expression of RAB7. (a)

24h 48h 72h

19 28 29 103

5 147

- - - -

- -

62 Relative levels of RAB7, MITF,

1366 164

- -

Mel Mel Mel Mel Mel

Mel and RAB27, assessed by WB in

- - - -

- - 361

- siRNA:

SK WM WM SK SK SK UACC Mel1

SK SK G

Control MITF MITF Control Control MITF

MITF MITF Control Control Control MITF Control siRNA: MITF - - - the indicated melanoma cell lines (b) Downregulation of MITF RAB7 MITF RAB27 but not RAB7 upon siRNA-mediated depletion of MITF RAB27 MITF in melanoma cells. (c) RAB27 Kinetics of the downregulation RAB27 RAB7 RAB7 of RAB27 but not RAB7 upon

β-Actin β-Actin α-Tubulin MITF siRNA-mediated depletion in UACC-62 cells. (d) Double IF staining of RAB7 d Melanoma specimens e Single-cell quantification (red) and MITF (green) in a Case # 90671 human melanoma specimens. Nuclei are counterstained with DAPI. The cases #90671 and

RAB7 #90601 exemplify melanomas with high RAB7 and MITF Case #90601 expression (compare to low levels of both proteins in the

stroma), whereas the case signal / cell(A.F.U) signal /

MITF #90603 shows positive RAB7

RAB7 Case # 90603 staining in a melanoma expressing negligible levels of Mean MITF. (e) Confocal-based quantification of the relative

Merge expression per cell of RAB7 and LN melanoma met Primary melanoma Primary melanoma Case #90671 Case #90601 Case #90603 MITF (in Arbitrary Fluorescence Mean MITF signal / cell (A.F.U)Units, A.F.U) of specimens shown in (d)

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 (β- Gal) 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 shControl shRAB7 (1) shRAB7 (2) a

UACC-62

Ctrl RAB7 (1) RAB7

shRNA: - (2) RAB7

Ctrl (1) RAB7 (2) RAB7 RAB7 β-Actin HCT116 UACC-62 HCT116

bb Melanoma UACC-62 WM-164 SK-Mel-103 SK-Mel-28 UACC-62 WM-164 SK-Mel-103 SK-Mel-28 shControl 12 6 4 2,5

shRAB7 2 Ctrl

- RAB7 - - -

Ctrl

RAB7 RAB7

Ctrl

RAB7 RAB7 Ctrl shRNA (3): RAB7 4 8 ** 1,5 2 RAB7 2 ** *** 1

(fold) 4 * *** *** 0,5 *** β-Actin 0 0 * Cell number Cell 0 0 1 2 3 4 1 2 3 4 Non-melanoma 1 2 3 4 1 2 3 4 HCT116 MiaPaca-2 639V A549 HCT116 MiaPaca-2 639V A549 16 8 15 10 12 6 10 8

- - - - 8 4 6

Ctrl Ctrl Ctrl

RAB7 RAB7 RAB7 RAB7 Ctrl shRNA (3): RAB7 * (fold) 4 2 5 4 RAB7 2 Cell number Cell 0 0 0 0 β-Actin 1 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 1 3 5 7

Days Days Days Days

103

103 28

- -

c 62

- 133

c 62

- -

62 133

Mel

- -

Mel Mel

- -

SK UACC

FTC HeLa CAL HCT116

SK SK UACC HeLa CAL FTC HCT116

shRNA (3): shControl

RAB7 RAB7 RAB7 RAB7 RAB7 RAB7 RAB7

Ctrl Ctrl Ctrl Ctrl Ctrl Ctrl Ctrl

RAB7 shRAB7 β-Actin

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.

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 Melanoma Non-melanoma

UACC-62 SK-Mel-147 WM-164SK-Mel-28 SK-Mel-103 HCT116 MiaPaca2 U251 A549 639V SK-Mel-147 HCT116

Vector

shControl

shRAB7 RAB7 T22N RAB7 b c d Empty GFP-RAB7GFP-RAB7 Empty GFP-RAB7GFP-RAB7 UACC-62 (BRAFV600E) SK-Mel-103 (NRASQ61R)

vector WT T22N vector WT MUT

103 ) - 2500

3 2000 shControl shControl

Mel 2000 - shRAB7 1500 shRAB7(3)

1500 SK

shControl 1000 1000 ***

143 *** - 500

500 **

Tumor vol(mm Tumor Mel

- 0 shRAB7 0 0 10 20 30 40 0 10 20 30

SK Days Days

WT WT

T22N T22N GFP- GFP- SK-Mel-147 (NRASQ61R) Empty

vector RAB7- RAB7-

RAB7 RAB7

vector )

- - - - 2000 WT MUT 3 2500 shControl Vector

2000 shRAB7(3) 1500 GFP-RAB7

Empty GFP Empty vector Empty GFP

GFP GFP

GFP-RAB7 - - - T22N

RAB7 RAB7 RAB7

Ctrl Ctrl shRNA: Ctrl 1500 * 1000 1000 GFP-RAB7 500 *** RAB7endog 500 ** RAB7endog vol(mm Tumor β-Actin 0 0 β-Actin 0 10 20 30 40 0 10 20 30 40 SK-Mel-103 SK-Mel-147 SK-Mel-103 Days 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 (blue) and non-melanoma (black) cell lines. Shown are (left) RAB7 and β-actin immunoblots of total cell extracts (right), and 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).

Fig. 18. Lineage-dependent expression a b Fibroblasts Melanocytes UACC-62 and function of RAB7 in normal skin Melanocytes Fibroblasts Keratinocytes

cells. (a) Expression of RAB7 and β-

RAB7 RAB7

Ctrl Ctrl RAB7 - - Ctrl - Skin biopsy: 1 2 3 1 2 3 1 2 3 shRNA: Actin WB in three sets of human RAB7 RAB7 primary skin cells isolated from the β-Actin β-Actin same donor. (b) Depletion of RAB7 by shRNA (3) in genetically matched

c ) d 1.2 Fibroblasts Melanocytes UACC-62 primary normal skin melanocytes and 1 fibroblasts, and in the melanoma cell shControl 0.8 line UACC-62. (c) Relative increase in

shRAB7

increase shControls

0.6 cell number (means ± SEM) for the

to shControl

0.4 indicated populations plated at equal number

0.2 cell numbers at day 6-post infection relative

Cell and cultured for four days. (d) Crystal

0 shRAB7 fold ( Fibroblasts Melanocytes UACC-62 violet staining of the indicated cell

Melanocytes Fibroblasts UACC-62 populations plated at equal cell e 100 f numbers at day 6-post infection and 80 shControl cultured for ten days. (e) Percentage shRAB7

60 of cells positive for lysosomal stress β- shControl 40 Galactosidase assay at acidic pH

20 (means ± SEM). Representative Gal positive cellspositive(%) Gal

- micrographs of the indicated cell β

0 shRAB7 Fibroblasts Melanocytes UACC-62 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

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

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 Melanoma tumor cells b SK-Mel-103 HCT116

SK-Mel-103* SK-Mel-147* Mel1* UACC-62 SK-Mel-28 WM-164 SK-Mel-29 SK-Mel-19 Melanocytes

shControl

shRAB7 shRAB7

Non-melanoma tumor cells c HCT116 A549 U251 MiaPaca2- 639V HeLa FTC-133 CAL-62 Fibroblasts SK-Mel-103 HCT116 Compact Loose Scattered 100 *** 100 80 80

shControl 60 60

40 40

Colonies(%) 20 20

shRAB7 0 0 shCtrl shRAB7 shCtrl shRAB7

d e f Melanoma cells g Melanoma Signatures

** RAB7 levels (Western Blot)

19 29 28 103 147

- - - - - “Invasive” “Proliferative” Invasiveness (Matrigel 80 62 2 ** 8 - 1E-23

Boyden Chambers) 1

Mel Mel Mel Mel Mel

- - - - 60 -

1.5 6 value

SK SK SK SK UACC Mel

SK 1E-18 in 24h (%) in24h 40 RAB7 1 4

cells 1E-13 20 RAB5 RAB7 0.5 2

RAB11 1E-08 Relative protein levelsproteinRelative

0 0 Invasive

Invading(fold)cells 0

62 29 19

28 RAB8

- - -

- 103

147 0.001

Adjustedcombinedp

Mel

Mel Mel

Mel RAB27

- -

Mel

- UACC

shControl -2.5 -1.5 -0.5 0.5 1.5 2.5

SK SK

shRAB7(2)

shRAB7(3) SK SK β-Actin 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).

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

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.

a BENIGN MALIGNANT b LESIONS MELANOMAS High Medium Low Dermal RGP VGP Skin Visceral *** *** Nevus (Non-invasive) (Invasive) Metastasis Metastasis 100 a b c d e * * 50 * * 0

80µm (%) samples TMA (22) * (48)

RAB7 a * * b c d e

Nevi

VGP (29) VGP Mets ’ ’ ’ ’ ’ (16) RGP * * (37) Mets Skin

80 µm Dermal Viscelral c e RAB7 signal / cell Low expression High expression N = (7) (7) (22) (40) (30) 100% 75% Maximum 50% Medium Low 25% Minimum 500 µm S100 negative cells (stroma) 0% d cases of Proportion RAB7

Breslow Depth f Kaplan-Meier survival estimates

1.001.00 High RAB7 expression

0.750.75 Free Free

0.500.50

CCND1 Survival 0.25 Disease 0.25 Low RAB7 expression P = 0.001

0.000.00 0 2 4 6 8 10 F 0 2 4analysis time6 8 10 Number at risk rab7 = No 64 52 42Years36 29 26 RAB7 rab7High = Si 48 64 3552 2242 1536 1229 926 rab7 = No rab7 = Si 500 µm RAB7 Low 48 35 22 15 12 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.

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 level- dependent 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 fluorescently- tagged 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 91

Results

a b c a DQ-Green-BSA Lysotracker-Red b c

shControl shBECLIN1

Ctrl RAB7 shControl shRNA:

RAB7 shControl shRAB7 LC3-I c

LC3-II shRAB7 α-Tubulin 20µm

d d e

GFP-LC3 GFP-LC3 Ctrl siRNA: RAB7 Non infected shRAB7 RAB7 siCtrl siATG7 18S

siRAB7 + siAtg7 RAB7

shControl shControl + siRAB7 siATG7+ siRAB7

ATG7+ ATG7+ ATG7 Rapamycin siRNA: Ctrl ATG7

RAB7 7.5 µm 7.5 µm 18S

f f g hh +0´ +5´ +10´ +15´ +20´ GFP-RAB5 Lucifer Yellow

GFP- h

RAB7

shCtrl shCtrl Cherry- LC3

LTR

blue

shRAB7 shRAB7 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.

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 RAB7- depleted 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 RAB7- depleted 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 93

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, non- melanoma 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.

a b RAB5 CTS-B Merge SK-Mel-28 UACC-62 SK-Mel-103 Fig.22. Mislocalization of CTS-B lysosomal proteases upon RAB7 downregulation. (a)

RAB5 (green) and cathepsin shControl

shControl (CTS)-B (red) double-IF in shControl and shRAB7 SK-Mel- 28 melanoma cells. (b) IF staining of CTS-B in the

shRAB7 indicated melanoma cell shRAB7 populations. Arrows mark the

enriched distribution of

- 62

c HCT116 SK-Mel-28 d - cathepsin B-positive large Mel

- vesicles towards the cell

SK HCT116

- - UACC

Ctrl RAB7 Ctrl shRNA: RAB7 periphery in RAB7-depleted

shRNA: cells. (c-e) Immunoblot

Ctrl

RAB7 RAB7 RAB7 Ctrl - - -Ctrl - analyses in conditioned media DCG-04 CM (CM) or total cell extracts from CTS-BCM

the indicated non-melanoma Extracellular PonceauCM CTS-DCM (black) and melanoma (blue) RAB7 cell lines, expressing control or CTS-XCM RAB7 shRNA, and probed with β-Actin Extracellular biotinylated DCG-04 or the CTS-SCM

Intracellular indicated antibodies. 28

- PonceauCM

- 133

- -

e Mel

UCC CAL SK HeLa FTC HCT116

CTS-B

Ctrl Ctrl Ctrl Ctrl

RAB7 RAB7 RAB7

Ctrl

RAB7 RAB7 Ctrl shRNA: RAB7

CTS-D CTS-BCM

CTS-X Extracellular

CTS-B Intracellular CTS-S

RAB7 RAB7 MITF

Intracellular α-Tubulin β-Actin

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 GO- categorization 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

Results

addition, we showed the induction of CEACAM1, a clinically relevant pro-metastatic melanoma gene410- 413, 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.

a c

shRNA:

Ctrl Ctrl Ctrl

RAB7 RAB7 RAB7

Ctrl Ctrl shRNA: Ctrl Downregulated Upregulated cell cycle cytokinesis RAB7 CEACAM1 chromosome segregation TDFP1 β-Actin cellular component organization Fibronectin cell communication CDC2 CM cell motion CDC6 Hsp70CM cell adhesion AURKB GAPDHCM

Nucleolin PonceauCM b d E2F PATHWAY MEMBRANE TRAFFICKING Phalloidin Paxillin 0.1 shControl 0.0 0.7 shRAB7 shControl shRAB7 -0.1 0.6 -0.2 0.5 -0.3 0.4 -0.4 0.3

-0.5 0.2 score score (ES) Enrichment -0.6 0.1 -0.7 0.0 Example Ranked gene list RAB7 KD RAB7 KD RAB7 KD RAB7 KD

Positively Negatively Positively Negatively 10 µm Average correlated correlated correlated correlated 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

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. SiRNA- mediated 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

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.

a b Fig. 24. SOX10-dependent regulation of RAB7 in melanoma cells. (a) qRT-PCR 1.2 RAB7 SOX10 PAX3 analyses of RAB7, SOX10 and PAX3 mRNA levels in UACC-62 melanoma cells expressing 1

) (siControl), SOX10 (siSOX10), or PAX3

siSOX10 siControl siControl siSOX10 levels 0.8 (siPAX3) siRNAs. (b) RT-PCR analyses of SOX10

0.6 SOX10, RAB7 and MITF mRNA levels in the

siControl mRNA

to indicated melanoma cell lines expressing 0.4 RAB7

fold control (siControl) or SOX10 (siSOX10) ( 0.2 Relative MITF siRNAs. (c) Impact of SOX10 siRNA (siSOX10) 0 on SOX10, RAB7 and MITF protein levels siControl siPAX3 siSOX10 18S analyzed by western blot in the indicated melanoma cell lines. α-Tubulin is shown as c d loading control. (d) Immunoblots of total

cell extracts isolated from indicated

147

19 28

103 melanoma cell lines and probed for basal

- - -

62 -

- RAB7, SOX10, and MITF. α-Tubulin is shown

Mel

Mel Mel Mel

Mel

- - -

- as loading control. Highly invasive melanoma

SK Mel

SK Sk UACC SK SK

siControl siSOX10

siSOX10 siControl

siControl siSOX10 siControl siSOX10 cell lines are highlighted in green. SOX10 RAB7

RAB7 SOX10

MITF MITF

β-Actin α-Tubulin

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

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).

a b c

SK-Mel-28 UACC-62 SK-Mel-103 NT LY294002 Non Treated LY294002 ETP-38 ETP-46992

RAB7 shRNA:

RAB7 RAB7 RAB7 RAB7 RAB7 RAB7

Ctrl Ctrl Ctrl Ctrl Ctrl Ctrl α-Tubulin LY294002: - - + + - - + + - - + +

SK-Mel-103 shControl CTS-B

RAB7 CTS-D

β-Actin shRAB7 Ponceau SK-Mel-28

d e ns f 5 Lucifer Yellow 70kD-Rhd-Dextran ** * 4 2.0 *** 2.0 ***

0 0 cells 3

1.0 1.0 2

0 0

siCtrl SIATG7 SIRAB7 + SIATG7 siCtrl siVPS34 + siRAB7 siVPS34 (fold increase) (fold

Vacuolized 1 siRAB7 siCtrl ATG7 VPS34 Uptake / cell (AFU) / cell Uptake 0.0 0.0 0 0 0 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). 99

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 RAS- driven 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.

100

Results

Fig. 26. Activation of RAB7- a b SK-Mel-103 UACC-62 dependent vesicle trafficking Melanocytes (NRASQ61R ) (BRAFV600E) Empty vector HRASG12V driven by PI3K signaling in primary human melanocytes expressing RAS oncogenes. (a)

Uptake of 70 kD Rhodamine-

103 -

Bright Field Bright Dextran in melanocytes and Mel - representative melanoma cell SK lines of the indicated genetic

backgrounds. (b) Bright field and Dextran - fluorescence micrographs Rdh showing the activation of 70kD 70K 70K Rhodamine(Rhd)-Dextran uptake in control and oncogenic RAS- cc HRASG12V dd ef Vector RAB7 WT RAB7 T22N expressing melanocytes. (c) RAB7 DMSO 30 LY294002 U0126 Confocal immunofluorescence

20 microscopy of RAB7-positive Vector

cells (%) cells 10

Vacuolized Vacuolized macropinocytic vesicles in 0 oncogenic RAS-expressing 80

60 melanocytes. (d) β-Gal-positive

Gal Gal V600E - 40

β and vacuolized cells in vector- or

- (%)

3µm 20 G12V SA

0 BRAF HRAS - expressing melanocytes 3.36 µm cells positive treated as indicated (see details in Materials and Methods). (e)

G12V Immunoblot analyses of total cell ee Vector BRAFV660E HRASG12V NRASQ61R NRASG12V extracts isolated from HRAS melanocytes co-expressing the indicated oncogenes and wild-

Q61R type (WT) or dominant negative

RAB7 WT RAB7 RAB7 T22N RAB7

RAB7 T22N RAB7 T22N RAB7 WT RAB7 WT RAB7 RAB7 WT RAB7 WT RAB7 T22N RAB7 T22N RAB7

- -

------

- (T22N) GFP-RAB7, or their

NRAS

GFP Vector GFP

GFP Vector GFP Vector GFP GFP Vector GFP GFP Vector GFP GFP corresponding empty vector BRAF controls, and probed for the Pan-RASectopic

Pan-RASendogenous G12V indicated antibodies. (f)

GFP-RAB7ectopic Representative micrographs NRAS

RAB7endogenous showing the effect of RAB7 wild- α-Tubulin type (WT) or dominant negative *** (T22N) overexpression on g hh > 12 *** senescence associated β- 30 pLV Vector GFP-RAB7 WT GFP-RAB7 T22N (%) 10 galactosidase staining and 25 cytoplasmic vacuolization in celss 20 8 primary melanocytes expressing 15 6 oncogenic mutants of BRAF, HRAS

10 and NRAS. The quantification of β- Gal positive Gal - 5

Β 4 - galactosidase positive cells is

0 SA 2 summarized in (g). (h) Dot plot Diametr of vacuoles Diametr vacuoles of (µm) showing the impact of RAB7 wild- Vector 0 type (WT) or dominant negative

RAB7

HRASG12V NRASG12V NRASQ61R RAB7 BRAFV600E Vector (T22N) overexpression in the size WT T22N of HRASG12V-induced vacuoles (vacuoles of ≥1µm in diameter were individually measured).

101

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).

a Tyr::CreERT2;BrafCA;Ptenfl/fl Tyr:NrasQ61K; Ink4a/Arf-/- Fig. 27. Confocal visualization of putative oncogene-driven RAB7- positive macropinosomes in vivo. (a,b) RAB7 Co-staining of RAB7 (red) and S100 S100+ S100 - S100+ S100 - (green) in paraffin-embedded sections of the indicated melanoma mouse models (a) of human melanocytic

S100 lesions (b). Melanocytic cells are marked by positive S100 staining. Note in (a) the differential levels and cytosolic

distribution of RAB7 in melanocytic Merge

5µm 1µm 1µm 5µm 1µm 1µm lesions (S100 positive, S100+) versus b stromal cells (S00 negative. S100-). In b PRIMARY MELANOMA NORMALSKIN (b), dotted lines separate melanocytic lesions from the stroma, negative for

1.59µm the melanocytic marker S100. The size RAB7 0.84µm of representative RAB7-coated 1.28µm macroendocytic vesicles visualized in lesions harbouring active PI3K signaling (i.e. melanomas and HRASG12V-Spitz S100 nevus) is also indicated.

Merge

25µm 7.5µm 25µm 7.5µm

SPITZ NEVUS (HRASG12V) COMPOUND NEVUS (BRAFV600E) 1.50µm

1.80µm

1.33µm

RAB7

S100 Merge 25µm 7.5µm 25µm 7.5µm

102

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 SK- Mel-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

[pIC]PEI U0126 TW-37 a a NT b (dsRNA mimmic) (MEK inh) (Mcl-1 inh) b Control [pIC]PEI

20 µm

[pIC]PEI

Bortezomib Cyclopamine Doxorubicin SB202190 (Proteasome inh) (Smo inhibitor) (DNA damaging) (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 RAB7- dependent 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

a GFP-RAB7 WT Lysotracker Merge b Lysotracker DQ-BSA Merged

Control

PEI

[pIC]

Chloroquine

PEI

PEI [pIC] 10 µm [pIC] 0s 5s 9s 27s 54s 81s 94s 97s c NT [pIC]PEI d [pIC]PEI

60+90’ +85’ +125’ 60+95’

+95’ +90’ +130’ GFPRAB7

+100’ +95’ +140’ +105’

LC3 -

+100’ +145’

+105’ Cherry

+110’ +105’ +150’ +130’ blue

+115 ’ +110’ +155’ - LTR

+120’ +115’ +160’ +150’ +5´ +25´

+120’ +170’

+125’ +45´ Merge

5 µm 5 µm 5 µm

Fig. 29. [pIC]PEI enhances RAB7-mediated macroendocytic trafficking. (a) SK-Mel-103 cells stably transfected with GFP- RAB7 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 Melanocytes SK-Mel-103 UACC-62 SK-Mel-28 100 NT [pIC]PEI

75 NT

Dead Cells (%) CellsDead 25

PEI

]

pIC [

Ctrl Bafil Chlor PEP

FG12 vector- HRASG12V- NT [pIC]PEI d b UACC-62 Melanocytes transduced expressing melanocytes melanocytes

DMSO Merge

LY294002

labeled

- Rhd

EIPA - PEI e [pIC]

Non infected FG12 vector HRASG12V BRAFV600E NRASQ61R NRASG12V

PEI

]

pIC [

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 lysosomal- associated 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, re- localizing 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 melanoma- restricted 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 co- deregulated 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

Discussion

Secondly, an interesting finding that further 12 supported that the lysosome signature found RAB7A – EntrezID:7879 here by GSEA in melanoma cells was not a 11 mere reflection of a high load of melanosome- 10 related genes was the increased sensitivity of 9

melanoma cells to chloroquine when

)

(

(15) (28)

compared to cells of other cancer types. (16)

all

–

CML (15)CML –

AML (34)AML

Liver(28)

Other(15)

Ovary (51)Ovary

Breast (58) other

Chloroquine is a lysosomotropic agent that, Kidney(34)

Glioma (62)Glioma

Prostate (7)

Thyroid (12)Thyroid

Bile Duct (8)Bile

–

cell

Stomach (38)Stomach

cell

Pancreas(44)

Colorectal(61)

LungNSC (131)

Esophagus (25)Esophagus

Soft Tissue (21)Soft

Melanoma

Meningioma (3)Meningioma Urinary tract(27)Urinary

although it exerts various effects on lysosomal Endometrium (27)

OtherLeukemia(1)

Osteosarcoma (10)

Mesothelioma (11)

Lung Small Small LungCell (53)

Neuroblastoma Neuroblastoma (17)

Chondrosarcoma (4)

Ewings Sarcoma Ewings (12)

Medulloblastoma Medulloblastoma (4)

Lymphoma DLBCL (18) Burkitt lymphoma lymphoma Burkitt (11)

295 Myeloma Multiple(30)

Lymphoma Lymphoma Hodgkin Lymphoma (12) function and on apoptosis , it is widely used AerodigestiveUpper (32) 12

to blunt autophagic and endocytic RAB27A – EntrezID:5873 (RNA) degradation288, 443, 444. The increased sensitivity 10 of melanoma cells to chloroquine might reflect 8 that these cancer cells are especially expression 6

“degradative”. This is consistent with the

mRNA

(15)

(10)

(34) (28) (28)

“gluttonous” behavior previously reported for (16)

all

–

CML (15)CML –

274, 445 (34)AML

Liver(28)

Other(15)

Ovary (51)Ovary

Breast (58)

other Kidney

melanoma cells . (62)Glioma

Prostate (7)

Thyroid (12)Thyroid

Bile Duct (8)Bile

–

cell

Stomach (38)Stomach

cell

Pancreas(44)

Colorectal(61)

Esophagus (25)Esophagus

Soft Tissue (21)Soft

Melanoma Melanoma (61)

Lung NSC NSC Lung (131)

Meningioma (3)Meningioma

Urinary tract tract Urinary (27)

Endometrium (27)

Osteosarcoma

Mesothelioma (11)

OtherLeukemia (1)

Lung Small Small LungCell (53)

Neuroblastoma (17)

Chondrosarcoma (4) Ewings Sarcoma Ewings (12)

Finally, although this study focused on Medulloblastoma (4)

Lymphoma DLBCLLymphoma (18)

Multiple Myeloma Multiple (30)

Burkitt lymphoma lymphoma Burkitt (11)

Lymphoma Lymphoma

Hodgkin Lymphoma (12( Upper AerodigestiveUpper (32) lysosome-associated genes, GSEA also RAB8A – EntrezID:4218 12 identified melanoma-enriched gene sets related to mitochondrial metabolism and to 11

Golgi-associated trafficking (Table S4). These 10

“metabolic” traits could be functionally 9

associated with the lysosomal traits

(4)

(15)

(16)

(28)

- all

investigated herein, as it is known that the all

–

CML (15)CML

AML (34)AML

Liver(28)

Other(15)

Ovary (51)Ovary

other

Breast (58)

Kidney(34)

Glioma (62)Glioma

Prostate (7)

Bile Duct (8)Bile

–

Thyroid (12)Thyroid

cell

Stomach (38)Stomach

cell

Pancreas(44)

Colorectal(61)

Esophagus (25)Esophagus

Soft Tissue (21)Soft

Lung NSC NSC Lung(131) Melanoma Melanoma (61)

constituent parts of the cargo degraded at the (3)Meningioma

Urinary tract tract Urinary (27)

Endometrium Endometrium (27)

Osteosarcoma (10)

Mesothelioma (11)

Lung Small Small LungCell (53)

OtherLeuke mia (1)

Neuroblastoma Neuroblastoma (17)

Chondrosarcoma (4)

Medulloblastoma

Lymphoma DLBCL (18) Burkitt lymphoma lymphoma Burkitt (11)

lysosome can be further metabolised to Myeloma Multiple (30)

Lymphoma Lymphoma

Hodgkin Lymphoma (12) Upper AerodigestiveUpper (32) generate ATP or utilised for biosynthetic

446 pathways . In agreement with our GSEA data, Fig. 31. Relative mRNA expression of RAB7, RAB27 and RAB8 a functionally relevant mitochondrial across different cancer types. Source: http://www.broadinstitute.org/ccle/home metabolism gene expression signature has

114

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 melanoma- specific 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, 447- 450. 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 2. Oncogenic lineage transformation RAB7 Dependency SOX10 PI3K Other lineages Pluripotent Melanocytes Melanoma Cells Neural Crest Progenitor

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, 119. However, while it is clear that SOX10 is required for the maintenance of melanoma248, 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 lysosome- mediated 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 RAB5 RAB7 Cathepsins Class I PI3K Class I PI3K Class III PI3K Class III PI3K

Late Golgi Late Endosomes Golgi Early Endosomes Endosomes Early ↑ RAB7 LYSOSOME Endosomes DEGRADATION ↓ RAB7 ? Lysosome ER Lysosome ER

Phagophore Autophagosome (LC3) Phagophore Autophagosome (LC3)

ACTIVE LYSOSOMAL DEGRADATION ENDOSOME-MEDIATED SECRETION OF AUTOPHAGOSOMES AND ENDOSOMES HALTED AUTOPHAGY HIGH RAB7 LOW 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 melanoma- specific 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 responses507- 509, 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 chemo- and 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

mimic of viral a dsRNA (pIC) b CarrierCarrierfor(PEI)cytosolic delivery (polycationic or lipidic)

Control [pIC]PEI

1 Endosomal LateMacroendosomes ( macroe )endosomes Uptake, cytosolic delivery and Amphisomes activation of immune sensors

Autophagosomes 2 Sustained endosome - Melanoma lung metastases mediated (xenograft models) autophagy Lysosomes

MDA-5 PEI (inactive) Control [pIC] MDA-5 Lower threshold for (active) apoptosis induction? course Time

NOXA Progressive 3 Caspases destruction of Activation of cellular apoptosis organelles?

Final cellular collapse PET-CT TUMOR CELL DEATH 4 (by autophagic and apoptotic cell death) Tyr::NrasQ61K; 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 neural- crest-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 pro- metastásicos 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 polyinosine- policitidílico 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

References

1. Chin, L., Garraway, L.A. & Fisher, D.E. Malignant melanoma: genetics and therapeutics in the genomic era. Genes Dev 20, 2149-2182 (2006). 2. Gupta, P.B. et al. The melanocyte differentiation program predisposes to metastasis after neoplastic transformation. Nat Genet 37, 1047-1054 (2005). 3. Scott, K.L. et al. Proinvasion metastasis drivers in early-stage melanoma are oncogenes. Cancer Cell 20, 92-103 (2011). 4. Soengas, M.S. & Lowe, S.W. Apoptosis and melanoma chemoresistance. Oncogene 22, 3138- 3151 (2003). 5. American Cancer Society in Atlanta, Ga: American Cancer Society; 20132013). 6. Miller, A.J. & Mihm, M.C., Jr. Melanoma. N Engl J Med 355, 51-65 (2006). 7. Siegel, R., Naishadham, D. & Jemal, A. Cancer statistics, 2013. CA Cancer J Clin 63, 11-30 (2013). 8. Liu, E.Y. & Ryan, K.M. Autophagy and cancer--issues we need to digest. J Cell Sci 125, 2349-2358 (2012). 9. Ferlay J, S.H., Bray F, Forman D, Mathers C and Parkin DM., Vol. 2013, Edn. 2010. (ed. V. 2.0) (Lyon, France: International Agency for Research on Cancer, 2010). 10. Tsao, H., Chin, L., Garraway, L.A. & Fisher, D.E. Melanoma: from mutations to medicine. Genes Dev 26, 1131-1155 (2012). 11. Berger, M.F. et al. Melanoma genome sequencing reveals frequent PREX2 mutations. Nature 485, 502-506 (2012). 12. Hodis, E. et al. A landscape of driver mutations in melanoma. Cell 150, 251-263 (2012). 13. Krauthammer, M. et al. Exome sequencing identifies recurrent somatic RAC1 mutations in melanoma. Nat Genet 44, 1006-1014 (2012). 14. Hodi, F.S. et al. Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med 363, 711-723 (2010). 15. Chapman, P.B. et al. Improved survival with vemurafenib in melanoma with BRAF V600E mutation. N Engl J Med 364, 2507-2516 (2011). 16. Khattak, M., Fisher, R., Turajlic, S. & Larkin, J. Targeted therapy and immunotherapy in advanced melanoma: an evolving paradigm. Ther Adv Med Oncol 5, 105-118 (2013). 17. Baade, P. & Coory, M. Trends in melanoma mortality in Australia: 1950-2002 and their implications for melanoma control. Aust N Z J Public Health 29, 383-386 (2005). 18. Desmond, R.A. & Soong, S.J. Epidemiology of malignant melanoma. Surg Clin North Am 83, 1-29 (2003). 19. de Vries, E., Bray, F.I., Coebergh, J.W. & Parkin, D.M. Changing epidemiology of malignant cutaneous melanoma in Europe 1953-1997: rising trends in incidence and mortality but recent stabilizations in western Europe and decreases in Scandinavia. Int J Cancer 107, 119-126 (2003). 20. Tas, F. Metastatic behavior in melanoma: timing, pattern, survival, and influencing factors. J Oncol 2012, 647684 (2012). 21. Gogas, H.J., Kirkwood, J.M. & Sondak, V.K. Chemotherapy for metastatic melanoma: time for a change? Cancer 109, 455-464 (2007). 22. Sondak, V.K. & Flaherty, L.E. Targeted therapies: Improved outcomes for patients with metastatic melanoma. Nat Rev Clin Oncol 8, 513-515 (2011). 23. Whiteman, D.C., Pavan, W.J. & Bastian, B.C. The melanomas: a synthesis of epidemiological, clinical, histopathological, genetic, and biological aspects, supporting distinct subtypes, causal pathways, and cells of origin. Pigment Cell Melanoma Res 24, 879-897 (2011). 24. Quintana, E. et al. Phenotypic heterogeneity among tumorigenic melanoma cells from patients that is reversible and not hierarchically organized. Cancer Cell 18, 510-523 (2010).

137

References

25. Johnson, D.B. & Sosman, J.A. Update on the Targeted Therapy of Melanoma. Curr Treat Options Oncol (2013). 26. Smalley, K.S. & Sondak, V.K. Melanoma--an unlikely poster child for personalized cancer therapy. N Engl J Med 363, 876-878 (2010). 27. Cabanes, A., Pérez-Gómez, B., Aragonés, N., Pollán, M. & López-Abente, G. La situación del cáncer en España, 1975-2006. Instituto de Salud Carlos III, Madrid (2009). 28. Tortora, G.J. & Derrickson, B.H. Principles of Anatomy and Physiology Edn. 11th Edition. (Chichester; 2006). 29. Kierszenbaum A, T.L. (ed.) Histology and Cell Biology: An Introduction to Pathology, Edn. 3rd edition. (2012). 30. Young, B.a. & J.W., H. (eds.) Wheater's Functional Histology: A Text and Colour Atlas, Edn. 4th Edition. (2000). 31. Mapunya, M.B. & Lall, N. in Breakthroughs in Melanoma Research. (ed. Y. Tanaka) (InTech, Croatia; 2011). 32. Kawakami, A. & Fisher, D.E. Key discoveries in melanocyte development. J Invest Dermatol 131, E2-4 (2011). 33. Fitzpatrick, T.B. & Breathnach, A.S. [the Epidermal Melanin Unit System]. Dermatol Wochenschr 147, 481-489 (1963). 34. Dupin, E. & Le Douarin, N.M. Development of melanocyte precursors from the vertebrate neural crest. Oncogene 22, 3016-3023 (2003). 35. D’Orazio, J., Marsch, A., Lagrew, J.a. & Veith, W.-B. in Advances in Malignant Melanoma - Clinical and Research Perspectives. (ed. D.A. Armstrong) (InTech, 2011). 36. Lin, J.Y. & Fisher, D.E. Melanocyte biology and skin pigmentation. Nature 445, 843-850 (2007). 37. Brenner, M. & Hearing, V.J. The protective role of melanin against UV damage in human skin. Photochem Photobiol 84, 539-549 (2008). 38. Kondo, T. & Hearing, V.J. Update on the regulation of mammalian melanocyte function and skin pigmentation. Expert Rev Dermatol 6, 97-108 (2008). 39. Park, H., Kosmadaki, M., Pongpudpunth, M., Lee, J. & Yaar, M. in Fitzpatrick's Dermatology in General Medicine. (eds. L. Goldsmith et al.)2012). 40. Mintz, B. & Klein-Szanto, A.J. Malignancy of eye melanomas originating in the retinal pigment epithelium of transgenic mice after genetic ablation of choroidal melanocytes. Proc Natl Acad Sci U S A 89, 11421-11425 (1992). 41. Goldgeier, M.H., Klein, L.E., Klein-Angerer, S., Moellmann, G. & Nordlund, J.J. The distribution of melanocytes in the leptomeninges of the human brain. J Invest Dermatol 82, 235-238 (1984). 42. Lin, C.S. & Zak, F.G. Studies on melanocytes. VI. Melanocytes in the middle ear. Arch Otolaryngol 108, 489-490 (1982). 43. Steel, K.P. & Barkway, C. Another role for melanocytes: their importance for normal stria vascularis development in the mammalian inner ear. Development 107, 453-463 (1989). 44. Barrett, A.W. & Scully, C. Human oral mucosal melanocytes: a review. J Oral Pathol Med 23, 97- 103 (1994). 45. Brito, F.C. & Kos, L. Timeline and distribution of melanocyte precursors in the mouse heart. Pigment Cell Melanoma Res 21, 464-470 (2008). 46. Yajima, I. & Larue, L. The location of heart melanocytes is specified and the level of pigmentation in the heart may correlate with coat color. Pigment Cell Melanoma Res 21, 471-476 (2008). 47. Hussein, M.R. Extracutaneous malignant melanomas. Cancer Invest 26, 516-534 (2008). 48. Laver, N.V., McLaughlin, M.E. & Duker, J.S. Ocular melanoma. Arch Pathol Lab Med 134, 1778- 1784 (2010).

138

References

49. Liubinas, S.V., Maartens, N. & Drummond, K.J. Primary melanocytic neoplasms of the central nervous system. J Clin Neurosci 17, 1227-1232 (2010). 50. Carvajal, R.D., Spencer, S.A. & Lydiatt, W. Mucosal melanoma: a clinically and biologically unique disease entity. J Natl Compr Canc Netw 10, 345-356 (2012). 51. Mihajlovic, M., Vlajkovic, S., Jovanovic, P. & Stefanovic, V. Primary mucosal melanomas: a comprehensive review. Int J Clin Exp Pathol 5, 739-753 (2012). 52. LeBoit, P., Burg, G., Weedon, D. & Sarasain, A. Pathology and genetics of skin tumours. World Health Organization classification of tumours. Lyon: IARC Press (2006). 53. Clark, W.H., From, L., Bernardino, E.A. & Mihm, M.C. The histogenesis and biological behavior of primary human malignant melanomas of the skin. Cancer Research 29, 707-727 (1969). 54. Argenziano, G., Zalaudek, I., Ferrara, G., Hofmann-Wellenhof, R. & Soyer, H.P. Proposal of a new classification system for melanocytic naevi. Br J Dermatol 157, 217-227 (2007). 55. Grossman, D. Failure to compare dermoscopy findings of pigmented lesions on your patient: Comment on "Dermoscopy of patients with multiple nevi". Arch Dermatol 147, 50 (2011). 56. Argenziano, G. et al. Dermoscopy of patients with multiple nevi: Improved management recommendations using a comparative diagnostic approach. Arch Dermatol 147, 46-49 (2011). 57. Kincannon, J. & Boutzale, C. The physiology of pigmented nevi. Pediatrics 104, 1042-1045 (1999). 58. Zayour, M. & Lazova, R. Congenital melanocytic nevi. Clin Lab Med 31, 267-280 (2011). 59. McKee, P., Calonje, E. & Granter, S. in Melanocytic Nevi, Edn. 3rd ed. (Mosby, Philadelphia, PA; 2005). 60. Farber, M.J., Heilman, E.R. & Friedman, R.J. Dysplastic nevi. Dermatol Clin 30, 389-404 (2012). 61. Pollock, P.M. et al. High frequency of BRAF mutations in nevi. Nat Genet 33, 19-20 (2003). 62. Indsto, J.O. et al. Low prevalence of RAS-RAF-activating mutations in Spitz melanocytic nevi compared with other melanocytic lesions. J Cutan Pathol 34, 448-455 (2007). 63. Ichii-Nakato, N. et al. High frequency of BRAFV600E mutation in acquired nevi and small congenital nevi, but low frequency of mutation in medium-sized congenital nevi. J Invest Dermatol 126, 2111-2118 (2006). 64. Bauer, J., Curtin, J.A., Pinkel, D. & Bastian, B.C. Congenital melanocytic nevi frequently harbor NRAS mutations but no BRAF mutations. J Invest Dermatol 127, 179-182 (2007). 65. Bastian, B.C., LeBoit, P.E. & Pinkel, D. Mutations and copy number increase of HRAS in Spitz nevi with distinctive histopathological features. Am J Pathol 157, 967-972 (2000). 66. Ross, A.L., Sanchez, M.I. & Grichnik, J.M. Molecular nevogenesis. Dermatol Res Pract 2011, 463184 (2011). 67. Bennett, D.C. Human melanocyte senescence and melanoma susceptibility genes. Oncogene 22, 3063-3069 (2003). 68. Elder, D.E. Dysplastic naevi: an update. Histopathology 56, 112-120 (2010). 69. Naeyaert, J.M. & Brochez, L. Clinical practice. Dysplastic nevi. N Engl J Med 349, 2233-2240 (2003). 70. Shah, K.N. The risk of melanoma and neurocutaneous melanosis associated with congenital melanocytic nevi. Semin Cutan Med Surg 29, 159-164 (2010). 71. Crowson, A.N., Magro, C.M., Sanchez-Carpintero, I. & Mihm, M.C., Jr. The precursors of malignant melanoma. Recent Results Cancer Res 160, 75-84 (2002). 72. Elder, D.E. Precursors to melanoma and their mimics: nevi of special sites. Mod Pathol 19 Suppl 2, S4-20 (2006). 73. Gandini, S. et al. Meta-analysis of risk factors for cutaneous melanoma: I. Common and atypical naevi. Eur J Cancer 41, 28-44 (2005).

139

References

74. Watt, A.J., Kotsis, S.V. & Chung, K.C. Risk of melanoma arising in large congenital melanocytic nevi: a systematic review. Plast Reconstr Surg 113, 1968-1974 (2004). 75. Bauer, J. & Garbe, C. Acquired melanocytic nevi as risk factor for melanoma development. A comprehensive review of epidemiological data. Pigment Cell Res 16, 297-306 (2003). 76. Rigel, D.S. et al. Dysplastic nevi. Markers for increased risk for melanoma. Cancer 63, 386-389 (1989). 77. Greene, M.H. et al. High risk of malignant melanoma in melanoma-prone families with dysplastic nevi. Ann Intern Med 102, 458-465 (1985). 78. Zhang, G. & Herlyn, M. Human nevi: no longer precursors of melanomas? J Invest Dermatol 132, 2133-2134 (2012). 79. Troxel, D.B. Error in surgical pathology. Am J Surg Pathol 28, 1092-1095 (2004). 80. Veenhuizen, K.C. et al. Quality assessment by expert opinion in melanoma pathology: experience of the pathology panel of the Dutch Melanoma Working Party. J Pathol 182, 266-272 (1997). 81. Troxel, D.B. Pitfalls in the diagnosis of malignant melanoma: findings of a risk management panel study. Am J Surg Pathol 27, 1278-1283 (2003). 82. Brenn, T. Pitfalls in the evaluation of melanocytic lesions. Histopathology 60, 690-705 (2012). 83. Bougnoux, A.C. & Solassol, J. The contribution of proteomics to the identification of biomarkers for cutaneous malignant melanoma. Clin Biochem 46, 518-523 (2013). 84. Kashani-Sabet, M. et al. A multi-marker assay to distinguish malignant melanomas from benign nevi. Proc Natl Acad Sci U S A 106, 6268-6272 (2009). 85. Zhang, G. & Li, G. Novel multiple markers to distinguish melanoma from dysplastic nevi. PLoS ONE 7, e45037 (2012). 86. Roguin, A. Rene Theophile Hyacinthe Laennec (1781-1826): the man behind the stethoscope. Clin Med Res 4, 230-235 (2006). 87. Laennec, R. Sur les melanoses. Bulletin de Faculte de Medecine Paris 1 (1806). 88. Kabbarah, O. & Chin, L. Revealing the genomic heterogeneity of melanoma. Cancer Cell 8, 439- 441 (2005). 89. Scolyer, R.A., Long, G.V. & Thompson, J.F. Evolving concepts in melanoma classification and their relevance to multidisciplinary melanoma patient care. Mol Oncol 5, 124-136 (2011). 90. Arrington, J.H., 3rd, Reed, R.J., Ichinose, H. & Krementz, E.T. Plantar lentiginous melanoma: a distinctive variant of human cutaneous malignant melanoma. Am J Surg Pathol 1, 131-143 (1977). 91. Clark, W.H., Jr., From, L., Bernardino, E.A. & Mihm, M.C. The histogenesis and biologic behavior of primary human malignant melanomas of the skin. Cancer Res 29, 705-727 (1969). 92. Mihm, M.C., Jr., Clark, W.H., Jr. & From, L. The clinical diagnosis, classification and histogenetic concepts of the early stages of cutaneous malignant melanomas. N Engl J Med 284, 1078-1082 (1971). 93. McGovern, V.J. The classification of melanoma and its relationship with prognosis. Pathology 2, 85-98 (1970). 94. McGovern, V.J. et al. The classification of malignant melanoma and its histologic reporting. Cancer 32, 1446-1457 (1973). 95. Jain, S. & Allen, P.W. Desmoplastic malignant melanoma and its variants. A study of 45 cases. Am J Surg Pathol 13, 358-373 (1989). 96. Blessing, K. et al. Small cell malignant melanoma: a variant of naevoid melanoma. Clinicopathological features and histological differential diagnosis. J Clin Pathol 53, 591-595 (2000).

140

References

97. Martin, R.C. et al. So-called "malignant blue nevus": a clinicopathologic study of 23 patients. Cancer 115, 2949-2955 (2009). 98. Hendrickson, M.R. & Ross, J.C. Neoplasms arising in congenital giant nevi: morphologic study of seven cases and a review of the literature. Am J Surg Pathol 5, 109-135 (1981). 99. Jen, M., Murphy, M. & Grant-Kels, J.M. Childhood melanoma. Clin Dermatol 27, 529-536 (2009). 100. Kemp, S., Gallagher, G., Kabani, S. & Moskal, R. Persistent melanoma in situ: case report and review. J Oral Maxillofac Surg 66, 1945-1948 (2008). 101. Balch, C.M. et al. Final version of 2009 AJCC melanoma staging and classification. J Clin Oncol 27, 6199-6206 (2009). 102. Balch, C.M. et al. A new American Joint Committee on Cancer staging system for cutaneous melanoma. Cancer 88, 1484-1491 (2000). 103. National Comprehensive Cancer Network 2013). 104. Dickson, P.V. & Gershenwald, J.E. Staging and prognosis of cutaneous melanoma. Surg Oncol Clin N Am 20, 1-17 (2011). 105. Greenwald, H.S., Friedman, E.B. & Osman, I. Superficial spreading and nodular melanoma are distinct biological entities: a challenge to the linear progression model. Melanoma Res 22, 1-8 (2012). 106. Curtin, J.A. et al. Distinct sets of genetic alterations in melanoma. N Engl J Med 353, 2135-2147 (2005). 107. Lee, J.H., Choi, J.W. & Kim, Y.S. Frequencies of BRAF and NRAS mutations are different in histological types and sites of origin of cutaneous melanoma: a meta-analysis. Br J Dermatol 164, 776-784 (2010). 108. Saldanha, G., Potter, L., Daforno, P. & Pringle, J.H. Cutaneous melanoma subtypes show different BRAF and NRAS mutation frequencies. Clin Cancer Res 12, 4499-4505 (2006). 109. Pacheco, I., Buzea, C. & Tron, V. Towards new therapeutic approaches for malignant melanoma. Expert Rev Mol Med 13, e33 (2011). 110. Pfeifer, G.P. & Hainaut, P. Next-generation sequencing: emerging lessons on the origins of human cancer. Curr Opin Oncol 23, 62-68 (2011). 111. Whiteman, D.C. et al. Melanocytic nevi, solar keratoses, and divergent pathways to cutaneous melanoma. J Natl Cancer Inst 95, 806-812 (2003). 112. Viros, A. et al. Improving melanoma classification by integrating genetic and morphologic features. PLoS Med 5, e120 (2008). 113. Thompson, J.F., Scolyer, R.A. & Kefford, R.F. Cutaneous melanoma in the era of molecular profiling. Lancet 374, 362-365 (2009). 114. Ferrara, G., Senetta, R., Paglierani, M. & Massi, D. Main clues in the pathologic diagnosis of melanoma: is molecular genetics helping? Dermatol Ther 25, 423-431 (2012). 115. Tremante, E. et al. Melanoma molecular classes and prognosis in the postgenomic era. Lancet Oncol 13, e205-211 (2012). 116. Helmbold, P., Altrichter, D., Klapperstuck, T. & Marsch, W. Intratumoral DNA stem-line heterogeneity in superficial spreading melanoma. J Am Acad Dermatol 52, 803-809 (2005). 117. Diaz-Cano, S.J. Tumor heterogeneity: mechanisms and bases for a reliable application of molecular marker design. Int J Mol Sci 13, 1951-2011 (2012). 118. Gerlinger, M. et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N Engl J Med 366, 883-892 (2012). 119. Kuzel, P. & A.J., C. (ed. InTech)2011). 120. Marusyk, A., Almendro, V. & Polyak, K. Intra-tumour heterogeneity: a looking glass for cancer? Nat Rev Cancer 12, 323-334 (2012).

141

References

121. Hanahan, D. & Weinberg, R.A. Hallmarks of cancer: the next generation. Cell 144, 646-674 (2011). 122. Clark, W.H., Jr. et al. A study of tumor progression: the precursor lesions of superficial spreading and nodular melanoma. Hum Pathol 15, 1147-1165 (1984). 123. Elder, D.E. Pathology of melanoma. Clin Cancer Res 12, 2308s-2311s (2006). 124. Bevona, C., Goggins, W., Quinn, T., Fullerton, J. & Tsao, H. Cutaneous melanomas associated with nevi. Arch Dermatol 139, 1620-1624; discussion 1624 (2003). 125. Marks, R., Dorevitch, A.P. & Mason, G. Do all melanomas come from "moles"? A study of the histological association between melanocytic naevi and melanoma. Australas J Dermatol 31, 77- 80 (1990). 126. Crucioli, V. & Stilwell, J. The histogenesis of malignant melanoma in relation to pre-existing pigmented lesions. J Cutan Pathol 9, 396-404 (1982). 127. Sagebiel, R.W. Melanocytic nevi in histologic association with primary cutaneous melanoma of superficial spreading and nodular types: effect of tumor thickness. J Invest Dermatol 100, 322S- 325S (1993). 128. Takata, M., Murata, H. & Saida, T. Molecular pathogenesis of malignant melanoma: a different perspective from the studies of melanocytic nevus and acral melanoma. Pigment Cell Melanoma Res 23, 64-71 (2010). 129. Lomas, J., Martin-Duque, P., Pons, M. & Quintanilla, M. The genetics of malignant melanoma. Front Biosci 13, 5071-5093 (2008). 130. Chin, L. The genetics of malignant melanoma: lessons from mouse and man. Nat Rev Cancer 3, 559-570 (2003). 131. Hoerter, J.D. et al. Does melanoma begin in a melanocyte stem cell? J Skin Cancer 2012, 571087 (2012). 132. Zabierowski, S.E., Fukunaga-Kalabis, M., Li, L. & Herlyn, M. Dermis-derived stem cells: a source of epidermal melanocytes and melanoma? Pigment Cell Melanoma Res 24, 422-429 (2011). 133. Herlyn, M. et al. Characteristics of cultured human melanocytes isolated from different stages of tumor progression. Cancer Res 45, 5670-5676 (1985). 134. Michaloglou, C., Vredeveld, L.C., Mooi, W.J. & Peeper, D.S. BRAF(E600) in benign and malignant human tumours. Oncogene 27, 877-895 (2008). 135. Mooi, W.J. & Peeper, D.S. Oncogene-induced cell senescence--halting on the road to cancer. N Engl J Med 355, 1037-1046 (2006). 136. Collado, M. & Serrano, M. Senescence in tumours: evidence from mice and humans. Nat Rev Cancer 10, 51-57 (2010). 137. Serrano, M., Lin, A.W., McCurrach, M.E., Beach, D. & Lowe, S.W. Oncogenic ras provokes premature cell senescence associated with accumulation of p53 and p16INK4a. Cell 88, 593-602 (1997). 138. Lowe, S.W. & Sherr, C.J. Tumor suppression by Ink4a-Arf: progress and puzzles. Curr Opin Genet Dev 13, 77-83 (2003). 139. Sharpless, E. & Chin, L. The INK4a/ARF locus and melanoma. Oncogene 22, 3092-3098 (2003). 140. Vredeveld, L.C., Rowland, B.D., Douma, S., Bernards, R. & Peeper, D.S. Functional identification of LRF as an oncogene that bypasses RASV12-induced senescence via upregulation of CYCLIN E. Carcinogenesis 31, 201-207 (2010). 141. Drost, J. et al. BRD7 is a candidate tumour suppressor gene required for p53 function. Nat Cell Biol 12, 380-389 (2010). 142. Collado, M. & Serrano, M. The power and the promise of oncogene-induced senescence markers. Nat Rev Cancer 6, 472-476 (2006).

142

References

143. Denoyelle, C. et al. Anti-oncogenic role of the endoplasmic reticulum differentially activated by mutations in the MAPK pathway. Nat Cell Biol 8, 1053-1063 (2006). 144. Gray-Schopfer, V.C. et al. Cellular senescence in naevi and immortalisation in melanoma: a role for p16? Br J Cancer 95, 496-505 (2006). 145. Michaloglou, C. et al. BRAFE600-associated senescence-like cell cycle arrest of human naevi. Nature 436, 720-724 (2005). 146. Healy, E. et al. Prognostic significance of allelic losses in primary melanoma. Oncogene 16, 2213- 2218 (1998). 147. Keller-Melchior, R., Schmidt, R. & Piepkorn, M. Expression of the tumor suppressor gene product p16INK4 in benign and malignant melanocytic lesions. J Invest Dermatol 110, 932-938 (1998). 148. Prieur, A. & Peeper, D.S. Cellular senescence in vivo: a barrier to tumorigenesis. Curr Opin Cell Biol 20, 150-155 (2008). 149. Maldonado, J.L., Timmerman, L., Fridlyand, J. & Bastian, B.C. Mechanisms of cell-cycle arrest in Spitz nevi with constitutive activation of the MAP-kinase pathway. Am J Pathol 164, 1783-1787 (2004). 150. Bansal, R. & Nikiforov, M.A. Pathways of oncogene-induced senescence in human melanocytic cells. Cell Cycle 9, 2782-2788 (2010). 151. Wang, S. & Kaufman, R.J. The impact of the unfolded protein response on human disease. J Cell Biol 197, 857-867 (2012). 152. Bianchi-Smiraglia, A. & Nikiforov, M.A. Controversial aspects of oncogene-induced senescence. Cell Cycle 11, 4147-4151 (2012). 153. Cotter, M.A., Florell, S.R., Leachman, S.A. & Grossman, D. Absence of senescence-associated beta-galactosidase activity in human melanocytic nevi in vivo. J Invest Dermatol 127, 2469-2471 (2007). 154. Gray-Schopfer, V.C., Soo, J.K. & Bennett, D.C. Comment on "Absence of senescence-associated beta-galactosidase activity in human melanocytic nevi in vivo". J Invest Dermatol 128, 1581; author reply 1583-1584 (2008). 155. Michaloglou, C., Soengas, M.S., Mooi, W.J. & Peeper, D.S. Comment on "Absence of senescence- associated beta-galactosidase activity in human melanocytic nevi in vivo". J Invest Dermatol 128, 1582-1583; author reply 1583-1584 (2008). 156. Tran, S.L. et al. Absence of distinguishing senescence traits in human melanocytic nevi. J Invest Dermatol 132, 2226-2234 (2012). 157. Omholt, K., Platz, A., Kanter, L., Ringborg, U. & Hansson, J. NRAS and BRAF mutations arise early during melanoma pathogenesis and are preserved throughout tumor progression. Clin Cancer Res 9, 6483-6488 (2003). 158. Easty, D.J., Gray, S.G., O'Byrne, K.J., O'Donnell, D. & Bennett, D.C. Receptor tyrosine kinases and their activation in melanoma. Pigment Cell Melanoma Res 24, 446-461 (2011). 159. Palmieri, G. et al. Main roads to melanoma. J Transl Med 7, 86 (2009). 160. Flaherty, K.T., Hodi, F.S. & Fisher, D.E. From genes to drugs: targeted strategies for melanoma. Nat Rev Cancer 12, 349-361 (2012). 161. Bennett, D.C. How to make a melanoma: what do we know of the primary clonal events? Pigment Cell Melanoma Res 21, 27-38 (2008). 162. Chin, L. et al. Cooperative effects of INK4a and ras in melanoma susceptibility in vivo. Genes Dev 11, 2822-2834 (1997). 163. Sharpless, N.E., Kannan, K., Xu, J., Bosenberg, M.W. & Chin, L. Both products of the mouse Ink4a/Arf locus suppress melanoma formation in vivo. Oncogene 22, 5055-5059 (2003).

143

References

164. Vredeveld, L.C. et al. Abrogation of BRAFV600E-induced senescence by PI3K pathway activation contributes to melanomagenesis. Genes Dev 26, 1055-1069 (2012). 165. Dankort, D. et al. Braf(V600E) cooperates with Pten loss to induce metastatic melanoma. Nat Genet 41, 544-552 (2009). 166. Kim, M. Cooperative interactions of PTEN deficiency and RAS activation in melanoma metastasis. Small Gtpases 1, 161-164 (2010). 167. Dovey, M., White, R.M. & Zon, L.I. Oncogenic NRAS cooperates with p53 loss to generate melanoma in zebrafish. Zebrafish 6, 397-404 (2009). 168. Bardeesy, N. et al. Dual inactivation of RB and p53 pathways in RAS-induced melanomas. Mol Cell Biol 21, 2144-2153 (2001). 169. Maertens, O. et al. Elucidating Distinct Roles for NF1 in Melanomagenesis. Cancer Discov 3, 338- 349 (2012). 170. Cheung, M., Sharma, A., Madhunapantula, S.V. & Robertson, G.P. Akt3 and mutant V600E B-Raf cooperate to promote early melanoma development. Cancer Res 68, 3429-3439 (2008). 171. Garraway, L.A. et al. Integrative genomic analyses identify MITF as a lineage survival oncogene amplified in malignant melanoma. Nature 436, 117-122 (2005). 172. Dong, J. et al. BRAF oncogenic mutations correlate with progression rather than initiation of human melanoma. Cancer Res 63, 3883-3885 (2003). 173. Colombino, M. et al. BRAF/NRAS mutation frequencies among primary tumors and metastases in patients with melanoma. J Clin Oncol 30, 2522-2529 (2012). 174. Greene, V.R., Johnson, M.M., Grimm, E.A. & Ellerhorst, J.A. Frequencies of NRAS and BRAF mutations increase from the radial to the vertical growth phase in cutaneous melanoma. J Invest Dermatol 129, 1483-1488 (2009). 175. Wu, H., Goel, V. & Haluska, F.G. PTEN signaling pathways in melanoma. Oncogene 22, 3113-3122 (2003). 176. Hwang, P.H. et al. Suppression of tumorigenicity and metastasis in B16F10 cells by PTEN/MMAC1/TEP1 gene. Cancer Lett 172, 83-91 (2001). 177. Nogueira, C. et al. Cooperative interactions of PTEN deficiency and RAS activation in melanoma metastasis. Oncogene 29, 6222-6232 (2010). 178. Lin, W.M. et al. Modeling genomic diversity and tumor dependency in malignant melanoma. Cancer Res 68, 664-673 (2008). 179. Mirmohammadsadegh, A. et al. Epigenetic silencing of the PTEN gene in melanoma. Cancer Res 66, 6546-6552 (2006). 180. Jensen, E.H. et al. Down-regulation of pro-apoptotic genes is an early event in the progression of malignant melanoma. Ann Surg Oncol 14, 1416-1423 (2007). 181. Mueller, D.W. & Bosserhoff, A.K. Role of miRNAs in the progression of malignant melanoma. Br J Cancer 101, 551-556 (2009). 182. Bonazzi, V.F., Stark, M.S. & Hayward, N.K. MicroRNA regulation of melanoma progression. Melanoma Res 22, 101-113 (2012). 183. Thies, A. et al. CEACAM1 expression in cutaneous malignant melanoma predicts the development of metastatic disease. J Clin Oncol 20, 2530-2536 (2002). 184. Redondo, P., Lloret, P., Idoate, M. & Inoges, S. Expression and serum levels of MMP-2 and MMP- 9 during human melanoma progression. Clin Exp Dermatol 30, 541-545 (2005). 185. Matarrese, P. et al. Cathepsin B inhibition interferes with metastatic potential of human melanoma: an in vitro and in vivo study. Mol Cancer 9, 207 (2010). 186. Mahabeleshwar, G.H. & Byzova, T.V. Angiogenesis in melanoma. Semin Oncol 34, 555-565 (2007).

144

References

187. van Kempen, L.C., van Muijen, G.N. & Ruiter, D.J. Melanoma progression in a changing environment. Eur J Cell Biol 86, 65-67 (2007). 188. Brychtova, S. et al. ( InTech, DO, 2011). 189. Postow, M.A., Harding, J. & Wolchok, J.D. Targeting immune checkpoints: releasing the restraints on anti-tumor immunity for patients with melanoma. Cancer J 18, 153-159 (2012). 190. Karagiannis, P. et al. IgG4 subclass antibodies impair antitumor immunity in melanoma. J Clin Invest (2013). 191. Hoek, K.S. DNA microarray analyses of melanoma gene expression: a decade in the mines. Pigment Cell Res 20, 466-484 (2007). 192. Haqq, C. et al. The gene expression signatures of melanoma progression. Proc Natl Acad Sci U S A 102, 6092-6097 (2005). 193. Smith, A.P., Hoek, K. & Becker, D. Whole-genome expression profiling of the melanoma progression pathway reveals marked molecular differences between nevi/melanoma in situ and advanced-stage melanomas. Cancer Biol Ther 4, 1018-1029 (2005). 194. Riker, A.I. et al. The gene expression profiles of primary and metastatic melanoma yields a transition point of tumor progression and metastasis. BMC Med Genomics 1, 13 (2008). 195. Alonso, S.R. et al. Progression in cutaneous malignant melanoma is associated with distinct expression profiles: a tissue microarray-based study. Am J Pathol 164, 193-203 (2004). 196. Alonso, S.R. et al. A high-throughput study in melanoma identifies epithelial-mesenchymal transition as a major determinant of metastasis. Cancer Res 67, 3450-3460 (2007). 197. Gould Rothberg, B.E. & Rimm, D.L. Biomarkers: the useful and the not so useful--an assessment of molecular prognostic markers for cutaneous melanoma. J Invest Dermatol 130, 1971-1987 (2010). 198. Bourgault-Villada, I. et al. Current Insight Into the Metastatic Process and Melanoma Cell Dissemination. (2011). 199. Damsky, W.E., Resenbaum, L.E. & Bosenberg, M. Decoding melanoma metastasis. Cancers, 126- 163 (2010). 200. Peinado, H. et al. Melanoma exosomes educate bone marrow progenitor cells toward a pro- metastatic phenotype through MET. Nat Med 18, 883-891 (2012). 201. Hood, J.L., San, R.S. & Wickline, S.A. Exosomes released by melanoma cells prepare sentinel lymph nodes for tumor metastasis. Cancer Res 71, 3792-3801 (2011). 202. Rinderknecht, M. & Detmar, M. Tumor lymphangiogenesis and melanoma metastasis. J Cell Physiol 216, 347-354 (2008). 203. Liersch, R., Hirakawa, S., Berdel, W.E., Mesters, R.M. & Detmar, M. Induced lymphatic sinus hyperplasia in sentinel lymph nodes by VEGF-C as the earliest premetastatic indicator. Int J Oncol 41, 2073-2078 (2012). 204. Peinado, H., Lavotshkin, S. & Lyden, D. The secreted factors responsible for pre-metastatic niche formation: old sayings and new thoughts. Semin Cancer Biol 21, 139-146 (2011). 205. Weinberg, R., Fisher, D.E. & Rich, J. Dynamic and transient cancer stem cells nurture melanoma. Nat Med 16, 758 (2010). 206. Hoek, K.S. & Goding, C.R. Cancer stem cells versus phenotype-switching in melanoma. Pigment Cell Melanoma Res 23, 746-759 (2010). 207. Widmer, D.S. et al. Hypoxia contributes to melanoma heterogeneity by triggering HIF1alpha- dependent phenotype switching. J Invest Dermatol (2013). 208. Hoek, K.S. et al. In vivo switching of human melanoma cells between proliferative and invasive states. Cancer Res 68, 650-656 (2008).

145

References

209. Hoek, K.S. et al. Metastatic potential of melanomas defined by specific gene expression profiles with no BRAF signature. Pigment Cell Res 19, 290-302 (2006). 210. Hendrix, M.J., Seftor, E.A., Hess, A.R. & Seftor, R.E. Vasculogenic mimicry and tumour-cell plasticity: lessons from melanoma. Nat Rev Cancer 3, 411-421 (2003). 211. Jeffs, A.R. et al. A gene expression signature of invasive potential in metastatic melanoma cells. PLoS ONE 4, e8461 (2009). 212. Tap, W.D. et al. Pharmacodynamic characterization of the efficacy signals due to selective BRAF inhibition with PLX4032 in malignant melanoma. Neoplasia 12, 637-649 (2010). 213. Pinner, S. et al. Intravital imaging reveals transient changes in pigment production and Brn2 expression during metastatic melanoma dissemination. Cancer Res 69, 7969-7977 (2009). 214. Eichhoff, O.M. et al. The immunohistochemistry of invasive and proliferative phenotype switching in melanoma: a case report. Melanoma Res 20, 349-355 (2010). 215. Danen, E.H. et al. E-cadherin expression in human melanoma. Melanoma Res 6, 127-131 (1996). 216. Javelaud, D. et al. GLI2 and M-MITF transcription factors control exclusive gene expression programs and inversely regulate invasion in human melanoma cells. Pigment Cell Melanoma Res 24, 932-943 (2011). 217. Cheli, Y. et al. Hypoxia and MITF control metastatic behaviour in mouse and human melanoma cells. Oncogene (2011). 218. Larue, L. & Davidson, I. Front seat and back seat drivers of melanoma metastasis. Pigment Cell Melanoma Res 24, 898-901 (2011). 219. Visvader, J.E. & Lindeman, G.J. Cancer stem cells in solid tumours: accumulating evidence and unresolved questions. Nat Rev Cancer 8, 755-768 (2008). 220. Shackleton, M., Quintana, E., Fearon, E.R. & Morrison, S.J. Heterogeneity in cancer: cancer stem cells versus clonal evolution. Cell 138, 822-829 (2009). 221. Schatton, T. et al. Identification of cells initiating human melanomas. Nature 451, 345-349 (2008). 222. Boiko, A.D. et al. Human melanoma-initiating cells express neural crest nerve growth factor receptor CD271. Nature 466, 133-137 (2010). 223. Strizzi, L. et al. The significance of a Cripto-1 positive subpopulation of human melanoma cells exhibiting stem cell-like characteristics. Cell Cycle 12 (2013). 224. Quintana, E. et al. Efficient tumour formation by single human melanoma cells. Nature 456, 593- 598 (2008). 225. La Porta, C.A. & Zapperi, S. Human breast and melanoma cancer stem cells biomarkers. Cancer Lett (2012). 226. Roesch, A. et al. A temporarily distinct subpopulation of slow-cycling melanoma cells is required for continuous tumor growth. Cell 141, 583-594 (2010). 227. Redi, C.A. Human embryonic stem cells handbook. Eur J Histochem 57, ejh 2013 br2012 (2013). 228. Kumar, S.M. et al. Acquired cancer stem cell phenotypes through Oct4-mediated dedifferentiation. Oncogene 31, 4898-4911 (2012). 229. Held, M. & Bosenberg, M. A role for the JARID1B stem cell marker for continuous melanoma growth. Pigment Cell Melanoma Res 23, 481-483 (2010). 230. Somasundaram, R., Villanueva, J. & Herlyn, M. Intratumoral heterogeneity as a therapy resistance mechanism: role of melanoma subpopulations. Adv Pharmacol 65, 335-359 (2012). 231. Wilmott, J.S. et al. Intratumoral molecular heterogeneity in a BRAF-mutant, BRAF inhibitor- resistant melanoma: a case illustrating the challenges for personalized medicine. Mol Cancer Ther 11, 2704-2708 (2012). 232. Greaves, M. & Maley, C.C. Clonal evolution in cancer. Nature 481, 306-313 (2012).

146

References

233. Luo, J., Solimini, N.L. & Elledge, S.J. Principles of cancer therapy: oncogene and non-oncogene addiction. Cell 136, 823-837 (2009). 234. Garraway, L.A. & Sellers, W.R. Lineage dependency and lineage-survival oncogenes in human cancer. Nat Rev Cancer 6, 593-602 (2006). 235. Garraway, L.A. et al. "Lineage addiction" in human cancer: lessons from integrated genomics. Cold Spring Harb Symp Quant Biol 70, 25-34 (2005). 236. Chiaverini, C. et al. Microphthalmia-associated transcription factor regulates RAB27A gene expression and controls melanosome transport. J Biol Chem 283, 12635-12642 (2008). 237. Levy, C., Khaled, M. & Fisher, D.E. MITF: master regulator of melanocyte development and melanoma oncogene. Trends Mol Med 12, 406-414 (2006). 238. Widlund, H.R. & Fisher, D.E. Microphthalamia-associated transcription factor: a critical regulator of pigment cell development and survival. Oncogene 22, 3035-3041 (2003). 239. Vachtenheim, J. & Ondru ova, L. (ed. D.L. Davids) (InTech,, 2013). 240. Goding, C.R. Mitf from neural crest to melanoma: signal transduction and transcription in the melanocyte lineage. Genes Dev 14, 1712-1728 (2000). 241. Hou, L. & Pavan, W.J. Transcriptional and signaling regulation in neural crest stem cell-derived melanocyte development: do all roads lead to Mitf? Cell Res 18, 1163-1176 (2008). 242. Webster, M.R. & Weeraratna, A.T. A Wnt-er Migration: The Confusing Role of beta-Catenin in Melanoma Metastasis. Sci Signal 6, pe11 (2013). 243. Curtin, J.A., Busam, K., Pinkel, D. & Bastian, B.C. Somatic activation of KIT in distinct subtypes of melanoma. J Clin Oncol 24, 4340-4346 (2006). 244. Pavey, S. et al. Microarray expression profiling in melanoma reveals a BRAF mutation signature. Oncogene 23, 4060-4067 (2004). 245. Medic, S., Rizos, H. & Ziman, M. Differential PAX3 functions in normal skin melanocytes and melanoma cells. Biochem Biophys Res Commun 411, 832-837 (2011). 246. Mascarenhas, J.B. et al. PAX3 and SOX10 activate MET receptor expression in melanoma. Pigment Cell Melanoma Res 23, 225-237 (2010). 247. Scholl, F.A. et al. PAX3 is expressed in human melanomas and contributes to tumor cell survival. Cancer Res 61, 823-826 (2001). 248. Shakhova, O. et al. Sox10 promotes the formation and maintenance of giant congenital naevi and melanoma. Nat Cell Biol 14, 882-890 (2012). 249. Harris, M.L., Baxter, L.L., Loftus, S.K. & Pavan, W.J. Sox proteins in melanocyte development and melanoma. Pigment Cell Melanoma Res 23, 496-513 (2010). 250. Hocker, T.L., Singh, M.K. & Tsao, H. Melanoma genetics and therapeutic approaches in the 21st century: moving from the benchside to the bedside. J Invest Dermatol 128, 2575-2595 (2008). 251. Akavia, U.D. et al. An integrated approach to uncover drivers of cancer. Cell 143, 1005-1017 (2010). 252. Haq, R. et al. BCL2A1 is a lineage-specific antiapoptotic melanoma oncogene that confers resistance to BRAF inhibition. Proc Natl Acad Sci U S A 110, 4321-4326 (2013). 253. Tachibana, M. Evidence to suggest that expression of MITF induces melanocyte differentiation and haploinsufficiency of MITF causes Waardenburg syndrome type 2A. Pigment Cell Res 10, 25- 33 (1997). 254. Opdecamp, K. et al. Melanocyte development in vivo and in neural crest cell cultures: crucial dependence on the Mitf basic-helix-loop-helix-zipper transcription factor. Development 124, 2377-2386 (1997).

147

References

255. Thurber, A.E. et al. Inverse expression states of the BRN2 and MITF transcription factors in melanoma spheres and tumour xenografts regulate the NOTCH pathway. Oncogene 30, 3036- 3048 (2011). 256. Bell, R.E. & Levy, C. The three M's: melanoma, microphthalmia-associated transcription factor and microRNA. Pigment Cell Melanoma Res 24, 1088-1106 (2011). 257. Salti, G.I. et al. Micropthalmia transcription factor: a new prognostic marker in intermediate- thickness cutaneous malignant melanoma. Cancer Res 60, 5012-5016 (2000). 258. Selzer, E. et al. The melanocyte-specific isoform of the microphthalmia transcription factor affects the phenotype of human melanoma. Cancer Res 62, 2098-2103 (2002). 259. Chien, P.K.a.A.J. (ed.) The role of cellular differentiation and cell fate in malignant melanoma, Research on melanoma - A glimpse into current directions and future trends. (InTech, 2011). 260. Yang, Z. & Klionsky, D.J. Eaten alive: a history of macroautophagy. Nat Cell Biol 12, 814-822 (2010). 261. Kroemer, G., Marino, G. & Levine, B. Autophagy and the integrated stress response. Mol Cell 40, 280-293 (2010). 262. Xie, Z. & Klionsky, D.J. Autophagosome formation: core machinery and adaptations. Nat Cell Biol 9, 1102-1109 (2007). 263. Mizushima, N., Yoshimori, T. & Ohsumi, Y. The role of Atg proteins in autophagosome formation. Annu Rev Cell Dev Biol 27, 107-132 (2011). 264. Funderburk, S.F., Wang, Q.J. & Yue, Z. The Beclin 1-VPS34 complex--at the crossroads of autophagy and beyond. Trends Cell Biol 20, 355-362 (2010). 265. Mehrpour, M., Esclatine, A., Beau, I. & Codogno, P. Overview of macroautophagy regulation in mammalian cells. Cell Res 20, 748-762 (2010). 266. Jager, S. et al. Role for Rab7 in maturation of late autophagic vacuoles. J Cell Sci 117, 4837-4848 (2004). 267. Gutierrez, M.G., Munafo, D.B., Beron, W. & Colombo, M.I. Rab7 is required for the normal progression of the autophagic pathway in mammalian cells. J Cell Sci 117, 2687-2697 (2004). 268. Liang, C., Feng, P., Ku, B., Oh, B.H. & Jung, J.U. UVRAG: a new player in autophagy and tumor cell growth. Autophagy 3, 69-71 (2007). 269. Saftig, P., Beertsen, W. & Eskelinen, E.L. LAMP-2: a control step for phagosome and autophagosome maturation. Autophagy 4, 510-512 (2008). 270. Tokarev, A.A., Alfonso, A. & Segev, N. in Trafficking Inside Cells: Pathways, Mechanisms and Regulation. (ed. E. Nava Segev, with Associate Editors: Aixa Alfonso, Gregory Payne and Julie Donaldson.) (Landes Bioscience and Springer Science+Business Media, 2009). 271. Kim, J., Kundu, M., Viollet, B. & Guan, K.L. AMPK and mTOR regulate autophagy through direct phosphorylation of Ulk1. Nat Cell Biol 13, 132-141 (2011). 272. Shigemitsu, K. et al. Regulation of translational effectors by amino acid and mammalian target of rapamycin signaling pathways. Possible involvement of autophagy in cultured hepatoma cells. J Biol Chem 274, 1058-1065 (1999). 273. Tasdemir, E. et al. Methods for assessing autophagy and autophagic cell death. Methods Mol Biol 445, 29-76 (2008). 274. Checinska, A. & Soengas, M.S. The gluttonous side of malignant melanoma: basic and clinical implications of macroautophagy. Pigment Cell Melanoma Res 24, 1116-1132 (2011). 275. Shen, S. et al. Cyclodepsipeptide toxin promotes the degradation of Hsp90 client proteins through chaperone-mediated autophagy. J Cell Biol 185, 629-639 (2009).

148

References

276. Chan, S.H., Kikkawa, U., Matsuzaki, H., Chen, J.H. & Chang, W.C. Insulin receptor substrate-1 prevents autophagy-dependent cell death caused by oxidative stress in mouse NIH/3T3 cells. J Biomed Sci 19, 64 (2012). 277. Degenhardt, K. et al. Autophagy promotes tumor cell survival and restricts necrosis, inflammation, and tumorigenesis. Cancer Cell 10, 51-64 (2006). 278. White, E. & Lowe, S.W. Eating to exit: autophagy-enabled senescence revealed. Genes Dev 23, 784-787 (2009). 279. Ryan, K.M. p53 and autophagy in cancer: guardian of the genome meets guardian of the proteome. Eur J Cancer 47, 44-50 (2010). 280. Levy, J.M. & Thorburn, A. Targeting autophagy during cancer therapy to improve clinical outcomes. Pharmacol Ther 131, 130-141 (2011). 281. Bursch, W. The autophagosomal-lysosomal compartment in programmed cell death. Cell Death Differ 8, 569-581 (2001). 282. Kroemer, G. & Jaattela, M. Lysosomes and autophagy in cell death control. Nat Rev Cancer 5, 886-897 (2005). 283. Flemming, A. Cancer: Autophagy presents Achilles heel in melanoma. Nat Rev Drug Discov 10, 491 (2011). 284. Marino, M.L. et al. Autophagy is a protective mechanism for human melanoma cells under acidic stress. J Biol Chem 287, 30664-30676 (2012). 285. Kuo, M.T., Savaraj, N. & Feun, L.G. Targeted cellular metabolism for cancer chemotherapy with recombinant arginine-degrading enzymes. Oncotarget 1, 246-251 (2010). 286. Diaz-Meco, M.T. Targeting leucine addiction and autophagy in melanoma. Pigment Cell Melanoma Res 24, 588-589 (2012). 287. Savaraj, N. et al. Arginine deprivation, autophagy, apoptosis (AAA) for the treatment of melanoma. Curr Mol Med 10, 405-412 (2010). 288. Sheen, J.H., Zoncu, R., Kim, D. & Sabatini, D.M. Defective regulation of autophagy upon leucine deprivation reveals a targetable liability of human melanoma cells in vitro and in vivo. Cancer Cell 19, 613-628 (2011). 289. Ma, X.H. et al. Measurements of tumor cell autophagy predict invasiveness, resistance to chemotherapy, and survival in melanoma. Clin Cancer Res 17, 3478-3489 (2011). 290. Fernandez-Barral, A. et al. Hypoxia negatively regulates antimetastatic PEDF in melanoma cells by a hypoxia inducible factor-independent, autophagy dependent mechanism. PLoS ONE 7, e32989 (2012). 291. Lazova, R., Klump, V. & Pawelek, J. Autophagy in cutaneous malignant melanoma. J Cutan Pathol 37, 256-268 (2009). 292. Miracco, C. et al. Beclin 1 and LC3 autophagic gene expression in cutaneous melanocytic lesions. Hum Pathol 41, 503-512 (2010). 293. Sivridis, E. et al. Beclin-1 and LC3A expression in cutaneous malignant melanomas: a biphasic survival pattern for beclin-1. Melanoma Res 21, 188-195 (2011). 294. Giammarioli, A.M. et al. Differential effects of the glycolysis inhibitor 2-deoxy-D-glucose on the activity of pro-apoptotic agents in metastatic melanoma cells, and induction of a cytoprotective autophagic response. Int J Cancer 131, E337-347 (2012). 295. Lakhter, A.J. et al. Chloroquine Promotes Apoptosis in Melanoma Cells by Inhibiting BH3 Domain-Mediated PUMA Degradation. J Invest Dermatol (2013). 296. Davids, L.M., Kleemann, B., Cooper, S. & Kidson, S.H. Melanomas display increased cytoprotection to hypericin-mediated cytotoxicity through the induction of autophagy. Cell Biol Int 33, 1065-1072 (2009).

149

References

297. Xie, X., White, E.P. & Mehnert, J.M. Coordinate autophagy and mTOR pathway inhibition enhances cell death in melanoma. PLoS ONE 8, e55096 (2013). 298. Hammerova, J., Uldrijan, S., Taborska, E., Vaculova, A.H. & Slaninova, I. Necroptosis modulated by autophagy is a predominant form of melanoma cell death induced by sanguilutine. Biol Chem 393, 647-658 (2012). 299. Chen, Y., Liersch, R. & Detmar, M. The miR-290-295 cluster suppresses autophagic cell death of melanoma cells. Sci Rep 2, 808 (2012). 300. Kroemer, G. & Levine, B. Autophagic cell death: the story of a misnomer. Nat Rev Mol Cell Biol 9, 1004-1010 (2008). 301. Selimovic, D. et al. Bortezomib/proteasome inhibitor triggers both apoptosis and autophagy- dependent pathways in melanoma cells. Cell Signal 25, 308-318 (2013). 302. Tomic, T. et al. Metformin inhibits melanoma development through autophagy and apoptosis mechanisms. Cell Death Dis 2, e199 (2011). 303. Li, B. et al. Autophagy facilitates major histocompatibility complex class I expression induced by IFN-gamma in B16 melanoma cells. Cancer Immunol Immunother 59, 313-321 (2010). 304. Yan, J. et al. Timing is critical for an effective anti-metastatic immunotherapy: the decisive role of IFNgamma/STAT1-mediated activation of autophagy. PLoS ONE 6, e24705 (2011). 305. El Andaloussi, S., Mager, I., Breakefield, X.O. & Wood, M.J. Extracellular vesicles: biology and emerging therapeutic opportunities. Nat Rev Drug Discov (2013). 306. Mosesson, Y., Mills, G.B. & Yarden, Y. Derailed endocytosis: an emerging feature of cancer. Nat Rev Cancer 8, 835-850 (2008). 307. Thery, C., Ostrowski, M. & Segura, E. Membrane vesicles as conveyors of immune responses. Nat Rev Immunol 9, 581-593 (2009). 308. Stenmark, H. Rab GTPases as coordinators of vesicle traffic. Nat Rev Mol Cell Biol 10, 513-525 (2009). 309. Segev, N. Ypt and Rab GTPases: insight into functions through novel interactions. Curr Opin Cell Biol 13, 500-511 (2001). 310. Pfeffer, S.R. Rab GTPases: specifying and deciphering organelle identity and function. Trends Cell Biol 11, 487-491 (2001). 311. Grosshans, B.L., Ortiz, D. & Novick, P. Rabs and their effectors: achieving specificity in membrane traffic. Proc Natl Acad Sci U S A 103, 11821-11827 (2006). 312. Zerial, M. & McBride, H. Rab proteins as membrane organizers. Nat Rev Mol Cell Biol 2, 107-117 (2001). 313. Yin, Y.X. et al. Increased expression of Rab25 in breast cancer correlates with lymphatic metastasis. Tumour Biol 33, 1581-1587 (2012). 314. Fan, Y., Xin, X.Y., Chen, B.L. & Ma, X. Knockdown of RAB25 expression by RNAi inhibits growth of human epithelial ovarian cancer cells in vitro and in vivo. Pathology 38, 561-567 (2006). 315. Cheng, K.W. et al. The RAB25 small GTPase determines aggressiveness of ovarian and breast cancers. Nat Med 10, 1251-1256 (2004). 316. Cheng, K.W. et al. Rab25 increases cellular ATP and glycogen stores protecting cancer cells from bioenergetic stress. EMBO Mol Med 4, 125-141 (2012). 317. Cao, C., Lu, C., Xu, J., Zhang, J. & Li, M. Expression of Rab25 correlates with the invasion and metastasis of gastric cancer. Chin J Cancer Res 25, 192-199 (2013). 318. Amornphimoltham, P. et al. Rab25 regulates invasion and metastasis in head and neck cancer. Clin Cancer Res 19, 1375-1388 (2013). 319. Tong, M. et al. Rab25 is a tumor suppressor gene with antiangiogenic and anti-invasive activities in esophageal squamous cell carcinoma. Cancer Res 72, 6024-6035 (2012).

150

References

320. Tang, B.L. Is Rab25 a tumor promoter or suppressor--context dependency on RCP status? Tumour Biol 31, 359-361 (2010). 321. Nam, K.T. et al. Loss of Rab25 promotes the development of intestinal neoplasia in mice and is associated with human colorectal adenocarcinomas. J Clin Invest 120, 840-849 (2010). 322. Goldenring, J.R. & Nam, K.T. Rab25 as a tumour suppressor in colon carcinogenesis. Br J Cancer 104, 33-36 (2010). 323. Cheng, J.M., Ding, M., Aribi, A., Shah, P. & Rao, K. Loss of RAB25 expression in breast cancer. Int J Cancer 118, 2957-2964 (2006). 324. Sato, T. et al. The Rab8 GTPase regulates apical protein localization in intestinal cells. Nature 448, 366-369 (2007). 325. Ostrowski, M. et al. Rab27a and Rab27b control different steps of the exosome secretion pathway. Nat Cell Biol 12, 19-30; sup pp 11-13 (2010). 326. Goueli, B.S., Powell, M.B., Finger, E.C. & Pfeffer, S.R. TBC1D16 is a Rab4A GTPase activating protein that regulates receptor recycling and EGF receptor signaling. Proc Natl Acad Sci U S A 109, 15787-15792 (2012). 327. Alderton, G.K. Genomics: driving cancer biology. Nat Rev Cancer 11, 79 (2011). 328. Breslow, A. Thickness, cross-sectional areas and depth of invasion in the prognosis of cutaneous melanoma. Ann Surg 172, 902-908 (1970). 329. Garbe, C. et al. Diagnosis and treatment of melanoma. European consensus-based interdisciplinary guideline--Update 2012. Eur J Cancer 48, 2375-2390 (2012). 330. Kirkwood, J.M. et al. Interferon alfa-2b adjuvant therapy of high-risk resected cutaneous melanoma: the Eastern Cooperative Oncology Group Trial EST 1684. J Clin Oncol 14, 7-17 (1996). 331. National Cancer Institute and the National Institutes of Health, Vol. 20132013). 332. Davar, D., Tarhini, A. & Kirkwood, J.M. Adjuvant therapy: melanoma. J Skin Cancer 2011, 274382 (2011). 333. Robert, C. et al. Ipilimumab plus dacarbazine for previously untreated metastatic melanoma. N Engl J Med 364, 2517-2526 (2011). 334. Zarour, H.M. & Kirkwood, J.M. Melanoma vaccines: early progress and future promises. Semin Cutan Med Surg 22, 68-75 (2003). 335. Slingluff, C.L., Jr. et al. Helper T-cell responses and clinical activity of a melanoma vaccine with multiple peptides from MAGE and melanocytic differentiation antigens. J Clin Oncol 26, 4973- 4980 (2008). 336. Kazaks, A., Balmaks, R., Voronkova, T., Ose, V. & Pumpens, P. Melanoma vaccine candidates from chimeric hepatitis B core virus-like particles carrying a tumor-associated MAGE-3 epitope. Biotechnol J 3, 1429-1436 (2008). 337. Schatton, T. & Frank, M.H. Cancer stem cells and human malignant melanoma. Pigment Cell Melanoma Res 21, 39-55 (2008). 338. Pennock, G.K., Waterfield, W. & Wolchok, J.D. Patient responses to ipilimumab, a novel immunopotentiator for metastatic melanoma: how different are these from conventional treatment responses? Am J Clin Oncol 35, 606-611 (2012). 339. Valyi-Nagy, I.T. et al. Undifferentiated keratinocytes control growth, morphology, and antigen expression of normal melanocytes through cell-cell contact. Lab Invest 69, 152-159 (1993). 340. Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A 102, 15545-15550 (2005). 341. Shankavaram, U.T. et al. Transcript and protein expression profiles of the NCI-60 cancer cell panel: an integromic microarray study. Mol Cancer Ther 6, 820-832 (2007).

151

References

342. Scherf, U. et al. A gene expression database for the molecular pharmacology of cancer. Nat Genet 24, 236-244 (2000). 343. Barretina, J. et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 483, 603-607. 344. Widmer, D.S. et al. Systematic classification of melanoma cells by phenotype-specific gene expression mapping. Pigment Cell Melanoma Res (2012). 345. Feng, Y., Press, B. & Wandinger-Ness, A. Rab 7: an important regulator of late endocytic membrane traffic. J Cell Biol 131, 1435-1452 (1995). 346. Giuliano, S. et al. Microphthalmia-associated transcription factor controls the DNA damage response and a lineage-specific senescence program in melanomas. Cancer Res 70, 3813-3822. 347. Dhomen, N. et al. Oncogenic Braf induces melanocyte senescence and melanoma in mice. Cancer Cell 15, 294-303 (2009). 348. Tormo, D. et al. Targeted activation of innate immunity for therapeutic induction of autophagy and apoptosis in melanoma cells. Cancer Cell 16, 103-114 (2009). 349. Dharmawardhane, S. et al. Regulation of macropinocytosis by p21-activated kinase-1. Mol Biol Cell 11, 3341-3352 (2000). 350. Lanzetti, L., Palamidessi, A., Areces, L., Scita, G. & Di Fiore, P.P. Rab5 is a signalling GTPase involved in actin remodelling by receptor tyrosine kinases. Nature 429, 309-314 (2004). 351. Martinez Gonzalez, S. et al. Rapid identification of ETP-46992, orally bioavailable PI3K inhibitor, selective versus mTOR. Bioorg Med Chem Lett 22, 5208-5214. 352. Martinez Gonzalez, S. et al. Identification of ETP-46321, a potent and orally bioavailable PI3K alpha, delta inhibitor. Bioorg Med Chem Lett 22, 3460-3466. 353. Trapnell, C. et al. Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nat Protoc 7, 562-578. 354. Langmead, B., Trapnell, C., Pop, M. & Salzberg, S.L. Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10, R25 (2009). 355. Li, H. et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics 25, 2078-2079 (2009). 356. Thery, M. et al. Anisotropy of cell adhesive microenvironment governs cell internal organization and orientation of polarity. Proc Natl Acad Sci U S A 103, 19771-19776 (2006). 357. Greenbaum, D. et al. Chemical approaches for functionally probing the proteome. Mol Cell Proteomics 1, 60-68 (2002). 358. Barretina, J. et al. The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity. Nature 483, 603-607 (2012). 359. Eskelinen, E.L. et al. Role of LAMP-2 in lysosome biogenesis and autophagy. Mol Biol Cell 13, 3355-3368 (2002). 360. Bucci, C., Thomsen, P., Nicoziani, P., McCarthy, J. & van Deurs, B. Rab7: a key to lysosome biogenesis. Mol Biol Cell 11, 467-480 (2000). 361. Marks, M.S. & Seabra, M.C. The melanosome: membrane dynamics in black and white. Nat Rev Mol Cell Biol 2, 738-748 (2001). 362. Raposo, G. & Marks, M.S. The dark side of lysosome-related organelles: specialization of the endocytic pathway for melanosome biogenesis. Traffic 3, 237-248 (2002). 363. Dell'Angelica, E.C. Melanosome biogenesis: shedding light on the origin of an obscure organelle. Trends Cell Biol 13, 503-506 (2003). 364. Nakatsu, F. & Ohno, H. Adaptor protein complexes as the key regulators of protein sorting in the post-Golgi network. Cell Struct Funct 28, 419-429 (2003).

152

References

365. Hearing, V.J. Biogenesis of pigment granules: a sensitive way to regulate melanocyte function. J Dermatol Sci 37, 3-14 (2005). 366. Schiaffino, M.V. Signaling pathways in melanosome biogenesis and pathology. Int J Biochem Cell Biol 42, 1094-1104 (2010). 367. Yamaguchi, Y. & Hearing, V.J. Physiological factors that regulate skin pigmentation. Biofactors 35, 193-199 (2009). 368. Kondo, T. & Hearing, V.J. Update on the regulation of mammalian melanocyte function and skin pigmentation. Expert Rev Dermatol 6, 97-108 (2011). 369. Sitaram, A. & Marks, M.S. Mechanisms of protein delivery to melanosomes in pigment cells. Physiology (Bethesda) 27, 85-99 (2012). 370. Raposo, G. & Marks, M.S. Melanosomes--dark organelles enlighten endosomal membrane transport. Nat Rev Mol Cell Biol 8, 786-797 (2007). 371. Hu, Z.Z. et al. Comparative Bioinformatics Analyses and Profiling of Lysosome-Related Organelle Proteomes. Int J Mass Spectrom 259, 147-160 (2007). 372. Sameni, M., Moin, K. & Sloane, B.F. Imaging proteolysis by living human breast cancer cells. Neoplasia 2, 496-504 (2000). 373. Yates, R.M. & Russell, D.G. Real-time spectrofluorometric assays for the lumenal environment of the maturing phagosome. Methods Mol Biol 445, 311-325 (2008). 374. Wattiaux, R., Jadot, M., Misquith, S. & Wattiaux-de Coninck, S. Characterization of endocytic components of liver nonparenchymal cells. Subcell Biochem 19, 163-194 (1993). 375. Limet, J.N., Quintart, J., Schneider, Y.J. & Courtoy, P.J. Receptor-mediated endocytosis of polymeric IgA and galactosylated serum albumin in rat liver. Evidence for intracellular ligand sorting and identification of distinct endosomal compartments. Eur J Biochem 146, 539-548 (1985). 376. Seglen, P.O., Grinde, B. & Solheim, A.E. Inhibition of the lysosomal pathway of protein degradation in isolated rat hepatocytes by ammonia, methylamine, chloroquine and leupeptin. Eur J Biochem 95, 215-225 (1979). 377. Jordens, I. et al. Rab7 and Rab27a control two motor protein activities involved in melanosomal transport. Pigment Cell Res 19, 412-423 (2006). 378. Zhang, M., Chen, L., Wang, S. & Wang, T. Rab7: roles in membrane trafficking and disease. Biosci Rep 29, 193-209 (2009). 379. Wang, T., Ming, Z., Xiaochun, W. & Hong, W. Rab7: role of its protein interaction cascades in endo-lysosomal traffic. Cell Signal 23, 516-521 (2011). 380. Hyttinen, J.M., Niittykoski, M., Salminen, A. & Kaarniranta, K. Maturation of autophagosomes and endosomes: a key role for Rab7. Biochim Biophys Acta 1833, 503-510 (2013). 381. Williams, K.C. & Coppolino, M.G. Phosphorylation of membrane type 1-matrix metalloproteinase (MT1-MMP) and its vesicle-associated membrane protein 7 (VAMP7)- dependent trafficking facilitate cell invasion and migration. J Biol Chem 286, 43405-43416 (2011). 382. Wang, T. et al. A role of Rab7 in stabilizing EGFR-Her2 and in sustaining Akt survival signal. J Cell Physiol (2011). 383. Steffan, J.J., Williams, B.C., Welbourne, T. & Cardelli, J.A. HGF-induced invasion by prostate tumor cells requires anterograde lysosome trafficking and activity of Na+-H+ exchangers. J Cell Sci 123, 1151-1159 (2010). 384. Steffan, J.J. & Cardelli, J.A. Thiazolidinediones induce Rab7-RILP-MAPK-dependent juxtanuclear lysosome aggregation and reduce tumor cell invasion. Traffic 11, 274-286.

153

References

385. Edinger, A.L., Cinalli, R.M. & Thompson, C.B. Rab7 prevents growth factor-independent survival by inhibiting cell-autonomous nutrient transporter expression. Dev Cell 5, 571-582 (2003). 386. Davidson, B. et al. Gene expression signatures differentiate ovarian/peritoneal serous carcinoma from diffuse malignant peritoneal mesothelioma. Clin Cancer Res 12, 5944-5950 (2006). 387. Croizet-Berger, K., Daumerie, C., Couvreur, M., Courtoy, P.J. & van den Hove, M.F. The endocytic catalysts, Rab5a and Rab7, are tandem regulators of thyroid hormone production. Proc Natl Acad Sci U S A 99, 8277-8282 (2002). 388. Davies, H. et al. Mutations of the BRAF gene in human cancer. Nature 417, 949-954 (2002). 389. Wang, H. et al. c-Myc depletion inhibits proliferation of human tumor cells at various stages of the cell cycle. Oncogene 27, 1905-1915 (2008). 390. Zhuang, D. et al. C-MYC overexpression is required for continuous suppression of oncogene- induced senescence in melanoma cells. Oncogene 27, 6623-6634 (2008). 391. Khodadoust, M.S. et al. Melanoma proliferation and chemoresistance controlled by the DEK oncogene. Cancer Res 69, 6405-6413 (2009). 392. Kallunki, T., Olsen, O.D. & Jaattela, M. Cancer-associated lysosomal changes: friends or foes? Oncogene 32, 1995-2004 (2013). 393. Chang, S.H. et al. Beclin1-induced autophagy abrogates radioresistance of lung cancer cells by suppressing osteopontin. J Radiat Res 53, 422-432 (2012). 394. Tassa, A., Roux, M.P., Attaix, D. & Bechet, D.M. Class III phosphoinositide 3-kinase--Beclin1 complex mediates the amino acid-dependent regulation of autophagy in C2C12 myotubes. Biochem J 376, 577-586 (2003). 395. Juenemann, K. & Reits, E.A. Alternative macroautophagic pathways. Int J Cell Biol 2012, 189794 (2012). 396. Bucci, C. et al. The small GTPase rab5 functions as a regulatory factor in the early endocytic pathway. Cell 70, 715-728 (1992). 397. Rink, J., Ghigo, E., Kalaidzidis, Y. & Zerial, M. Rab conversion as a mechanism of progression from early to late endosomes. Cell 122, 735-749 (2005). 398. Kumari, S., Mg, S. & Mayor, S. Endocytosis unplugged: multiple ways to enter the cell. Cell Res 20, 256-275 (2010). 399. Dobrowolski, R. & De Robertis, E.M. Endocytic control of growth factor signalling: multivesicular bodies as signalling organelles. Nat Rev Mol Cell Biol (2011). 400. Caswell, P.T., Vadrevu, S. & Norman, J.C. Integrins: masters and slaves of endocytic transport. Nat Rev Mol Cell Biol 10, 843-853 (2009). 401. Guha, S. & Padh, H. Cathepsins: fundamental effectors of endolysosomal proteolysis. Indian J Biochem Biophys 45, 75-90 (2008). 402. Mason, S.D. & Joyce, J.A. Proteolytic networks in cancer. Trends Cell Biol 21, 228-237 (2011). 403. Linke, M., Herzog, V. & Brix, K. Trafficking of lysosomal cathepsin B-green fluorescent protein to the surface of thyroid epithelial cells involves the endosomal/lysosomal compartment. J Cell Sci 115, 4877-4889 (2002). 404. Andrews, N.W. Regulated secretion of conventional lysosomes. Trends Cell Biol 10, 316-321 (2000). 405. Victor, B.C., Anbalagan, A., Mohamed, M.M., Sloane, B.F. & Cavallo-Medved, D. Inhibition of cathepsin B activity attenuates extracellular matrix degradation and inflammatory breast cancer invasion. Breast Cancer Res 13, R115 (2011). 406. Cavallo-Medved, D. et al. Live-cell imaging demonstrates extracellular matrix degradation in association with active cathepsin B in caveolae of endothelial cells during tube formation. Exp Cell Res 315, 1234-1246 (2009).

154

References

407. Agola, J.O., Jim, P.A., Ward, H.H., Basuray, S. & Wandinger-Ness, A. Rab GTPases as regulators of endocytosis, targets of disease and therapeutic opportunities. Clin Genet 80, 305-318 (2011). 408. Halaban, R., Cheng, E., Smicun, Y. & Germino, J. Deregulated E2F transcriptional activity in autonomously growing melanoma cells. J Exp Med 191, 1005-1016. (2000). 409. Shan, B., Farmer, A.A. & Lee, W.H. The molecular basis of E2F-1/DP-1-induced S-phase entry and apoptosis. Cell Growth Differ 7, 689-697 (1996). 410. Markel, G. et al. Systemic dysregulation of CEACAM1 in melanoma patients. Cancer Immunol Immunother 59, 215-230 (2010). 411. Sivan, S. et al. Serum CEACAM1 Correlates with Disease Progression and Survival in Malignant Melanoma Patients. Clin Dev Immunol 2012, 290536 (2012). 412. Ebrahimnejad, A. et al. CEACAM1 enhances invasion and migration of melanocytic and melanoma cells. Am J Pathol 165, 1781-1787 (2004). 413. Thies, A., Mauer, S., Fodstad, O. & Schumacher, U. Clinically proven markers of metastasis predict metastatic spread of human melanoma cells engrafted in scid mice. Br J Cancer 96, 609- 616 (2007). 414. Gradilone, A. et al. Fibronectin and laminin expression in sentinel lymph nodes of patients with malignant melanoma. Br J Dermatol 157, 398-401 (2007). 415. Kaariainen, E. et al. Switch to an invasive growth phase in melanoma is associated with tenascin- C, fibronectin, and procollagen-I forming specific channel structures for invasion. J Pathol 210, 181-191 (2006). 416. Ren, Z. et al. Intratumor injection of oncolytic adenovirus expressing HSP70 prolonged survival in melanoma B16 bearing mice by enhanced immune response. Cancer Biol Ther 7, 191-195 (2008). 417. Pierrat, M.J., Marsaud, V., Mauviel, A. & Javelaud, D. Expression of microphthalmia-associated transcription factor (MITF), which is critical for melanoma progression, is inhibited by both transcription factor GLI2 and transforming growth factor-beta. J Biol Chem 287, 17996-18004 (2012). 418. Potterf, S.B., Furumura, M., Dunn, K.J., Arnheiter, H. & Pavan, W.J. Transcription factor hierarchy in Waardenburg syndrome: regulation of MITF expression by SOX10 and PAX3. Hum Genet 107, 1-6 (2000). 419. Bondurand, N. et al. Interaction among SOX10, PAX3 and MITF, three genes altered in Waardenburg syndrome. Hum Mol Genet 9, 1907-1917 (2000). 420. Falasca, M. & Maffucci, T. Rethinking phosphatidylinositol 3-monophosphate. Biochim Biophys Acta 1793, 1795-1803 (2009). 421. Ackermann, J. et al. Metastasizing melanoma formation caused by expression of activated N- RasQ61K on an INK4a-deficient background. Cancer Res 65, 4005-4011 (2005). 422. Chen, J.K., Taipale, J., Cooper, M.K. & Beachy, P.A. Inhibition of Hedgehog signaling by direct binding of cyclopamine to Smoothened. Genes Dev 16, 2743-2748 (2002). 423. Wenzel, J., Tormo, D. & Tuting, T. Toll-like receptor-agonists in the treatment of skin cancer: history, current developments and future prospects. Handb Exp Pharmacol, 201-220 (2008). 424. Bieber, T., Meissner, W., Kostin, S., Niemann, A. & Elsasser, H.P. Intracellular route and transcriptional competence of polyethylenimine-DNA complexes. J Control Release 82, 441-454 (2002). 425. Delgado, M.A., Elmaoued, R.A., Davis, A.S., Kyei, G. & Deretic, V. Toll-like receptors control autophagy. Embo J 27, 1110-1121 (2008). 426. Mercer, J. & Helenius, A. Vaccinia virus uses macropinocytosis and apoptotic mimicry to enter host cells. Science 320, 531-535 (2008).

155

References

427. Berger, M.F. et al. Integrative analysis of the melanoma transcriptome. Genome Res 20, 413-427 (2010). 428. Ryu, B., Kim, D.S., Deluca, A.M. & Alani, R.M. Comprehensive expression profiling of tumor cell lines identifies molecular signatures of melanoma progression. PLoS ONE 2, e594 (2007). 429. Wang, E. et al. Melanoma-restricted genes. J Transl Med 2, 34 (2004). 430. Vazquez, F. et al. PGC1alpha expression defines a subset of human melanoma tumors with increased mitochondrial capacity and resistance to oxidative stress. Cancer Cell 23, 287-301 (2013). 431. Haq, R. et al. Oncogenic BRAF regulates oxidative metabolism via PGC1alpha and MITF. Cancer Cell 23, 302-315 (2013). 432. Dutton-Regester, K. & Hayward, N.K. Reviewing the somatic genetics of melanoma: from current to future analytical approaches. Pigment Cell Melanoma Res 25, 144-154 (2012). 433. Xia, L. et al. ACP5, a direct transcriptional target of FoxM1, promotes tumor metastasis and indicates poor prognosis in hepatocellular carcinoma. Oncogene (2013). 434. Le Gall, C. et al. A cathepsin K inhibitor reduces breast cancer induced osteolysis and skeletal tumor burden. Cancer Res 67, 9894-9902 (2007). 435. Quintanilla-Dieck, M.J., Codriansky, K., Keady, M., Bhawan, J. & Runger, T.M. Cathepsin K in melanoma invasion. J Invest Dermatol 128, 2281-2288 (2008). 436. Podgorski, I. & Sloane, B.F. Cathepsin B and its role(s) in cancer progression. Biochem Soc Symp, 263-276 (2003). 437. Borovansky, J. & Elleder, M. Melanosome degradation: fact or fiction. Pigment Cell Res 16, 280- 286 (2003). 438. Ohbayashi, N. & Fukuda, M. Role of Rab family GTPases and their effectors in melanosomal logistics. J Biochem 151, 343-351 (2012). 439. Gomez, P.F. et al. Identification of rab7 as a melanosome-associated protein involved in the intracellular transport of tyrosinase-related protein 1. J Invest Dermatol 117, 81-90 (2001). 440. Kawakami, A. et al. Rab7 regulates maturation of melanosomal matrix protein gp100/Pmel17/Silv. J Invest Dermatol 128, 143-150 (2008). 441. Hume, A.N., Ushakov, D.S., Tarafder, A.K., Ferenczi, M.A. & Seabra, M.C. Rab27a and MyoVa are the primary Mlph interactors regulating melanosome transport in melanocytes. J Cell Sci 120, 3111-3122 (2007). 442. Chakraborty, A.K., Funasaka, Y., Araki, K., Horikawa, T. & Ichihashi, M. Evidence that the small GTPase Rab8 is involved in melanosome traffic and dendrite extension in B16 melanoma cells. Cell Tissue Res 314, 381-388 (2003). 443. Bevan, A.P. et al. Chloroquine extends the lifetime of the activated insulin receptor complex in endosomes. J Biol Chem 272, 26833-26840 (1997). 444. Amaravadi, R.K. et al. Principles and current strategies for targeting autophagy for cancer treatment. Clin Cancer Res 17, 654-666 (2011). 445. Lugini, L. et al. Potent phagocytic activity discriminates metastatic and primary human malignant melanomas: a key role of ezrin. Lab Invest 83, 1555-1567 (2003). 446. Ryan, K.M. p53 and autophagy in cancer: guardian of the genome meets guardian of the proteome. Eur J Cancer 47, 44-50 (2011). 447. Vitelli, R. et al. Role of the small GTPase Rab7 in the late endocytic pathway. J Biol Chem 272, 4391-4397 (1997). 448. Cantalupo, G., Alifano, P., Roberti, V., Bruni, C.B. & Bucci, C. Rab-interacting lysosomal protein (RILP): the Rab7 effector required for transport to lysosomes. Embo J 20, 683-693 (2001).

156

References

449. Lebrand, C. et al. Late endosome motility depends on lipids via the small GTPase Rab7. Embo J 21, 1289-1300 (2002). 450. Vanlandingham, P.A. & Ceresa, B.P. Rab7 regulates late endocytic trafficking downstream of multivesicular body biogenesis and cargo sequestration. J Biol Chem 284, 12110-12124 (2009). 451. Huotari, J. et al. Cullin-3 regulates late endosome maturation. Proc Natl Acad Sci U S A 109, 823- 828 (2012). 452. Yamauchi, J. et al. The mood stabilizer valproic acid improves defective neurite formation caused by Charcot-Marie-Tooth disease-associated mutant Rab7 through the JNK signaling pathway. J Neurosci Res 88, 3189-3197 (2010). 453. Spinosa, M.R. et al. Functional characterization of Rab7 mutant proteins associated with Charcot-Marie-Tooth type 2B disease. J Neurosci 28, 1640-1648 (2008). 454. Sauka-Spengler, T. & Bronner-Fraser, M. A gene regulatory network orchestrates neural crest formation. Nat Rev Mol Cell Biol 9, 557-568 (2008). 455. Loftus, S.K. Decreased melanoma proliferation and cell survival: turn down your SOX10. Pigment Cell Melanoma Res 26, 3-4 (2013). 456. Seong, I. et al. Sox10 controls migration of B16F10 melanoma cells through multiple regulatory target genes. PLoS ONE 7, e31477 (2012). 457. Bakos, R.M. et al. Nestin and SOX9 and SOX10 transcription factors are coexpressed in melanoma. Exp Dermatol 19, e89-94 (2010). 458. Feige, E. et al. Hypoxia-induced transcriptional repression of the melanoma-associated oncogene MITF. Proc Natl Acad Sci U S A 108, E924-933 (2011). 459. Olbryt, M. et al. Melanoma-associated genes, MXI1, FN1, and NME1, are hypoxia responsive in murine and human melanoma cells. Melanoma Res 21, 417-425 (2011). 460. Javelaud, D., Alexaki, V.I. & Mauviel, A. Transforming growth factor-beta in cutaneous melanoma. Pigment Cell Melanoma Res 21, 123-132 (2008). 461. Busse, A. & Keilholz, U. Role of TGF-beta in melanoma. Curr Pharm Biotechnol 12, 2165-2175 (2011). 462. van den Hurk, K. et al. Genetics and epigenetics of cutaneous malignant melanoma: a concert out of tune. Biochim Biophys Acta 1826, 89-102 (2012). 463. Swanson, J.A. Shaping cups into phagosomes and macropinosomes. Nat Rev Mol Cell Biol 9, 639- 649 (2008). 464. Overmeyer, J.H., Kaul, A., Johnson, E.E. & Maltese, W.A. Active ras triggers death in glioblastoma cells through hyperstimulation of macropinocytosis. Mol Cancer Res 6, 965-977 (2008). 465. Amyere, M. et al. Constitutive macropinocytosis in oncogene-transformed fibroblasts depends on sequential permanent activation of phosphoinositide 3-kinase and phospholipase C. Mol Biol Cell 11, 3453-3467 (2000). 466. Araki, N., Egami, Y., Watanabe, Y. & Hatae, T. Phosphoinositide metabolism during membrane ruffling and macropinosome formation in EGF-stimulated A431 cells. Exp Cell Res 313, 1496- 1507 (2007). 467. Porat-Shliom, N., Kloog, Y. & Donaldson, J.G. A unique platform for H-Ras signaling involving clathrin-independent endocytosis. Mol Biol Cell 19, 765-775 (2008). 468. Veithen, A., Cupers, P., Baudhuin, P. & Courtoy, P.J. v-Src induces constitutive macropinocytosis in rat fibroblasts. J Cell Sci 109 ( Pt 8), 2005-2012 (1996). 469. BasuRay, S., Mukherjee, S., Romero, E., Wilson, M.C. & Wandinger-Ness, A. Rab7 mutants associated with Charcot-Marie-Tooth disease exhibit enhanced NGF-stimulated signaling. PLoS ONE 5, e15351 (2010).

157

References

470. McCray, B.A., Skordalakes, E. & Taylor, J.P. Disease mutations in Rab7 result in unregulated nucleotide exchange and inappropriate activation. Hum Mol Genet 19, 1033-1047 (2010). 471. Verhoeven, K. et al. Mutations in the small GTP-ase late endosomal protein RAB7 cause Charcot- Marie-Tooth type 2B neuropathy. Am J Hum Genet 72, 722-727 (2003). 472. Greene, M.H., Mead, G.D., Reimer, R.R., Bergfeld, W.F. & Fraumeni, J.F., Jr. Malignant melanoma and Charcot-Marie-Tooth disease. Am J Med Genet 5, 69-71 (1980). 473. Manoukian, S., Briscioli, V. & Lalatta, F. Malignant melanoma and Charcot-Marie-Tooth disease: a further case. Am J Med Genet 68, 242 (1997). 474. Saini, R., Lehrhoff, S. & Sarnoff, D.S. Charcot-Marie-tooth disease and multiple malignant melanomas: a case report. J Drugs Dermatol 9, 164-166 (2010). 475. Flaherty, K.T., Hodi, F.S. & Fisher, D.E. From genes to drugs: targeted strategies for melanoma. Nat Rev Cancer (2012). 476. Florey, O., Kim, S.E., Sandoval, C.P., Haynes, C.M. & Overholtzer, M. Autophagy machinery mediates macroendocytic processing and entotic cell death by targeting single membranes. Nat Cell Biol 13, 1335-1343 (2011). 477. Fader, C.M. & Colombo, M.I. Autophagy and multivesicular bodies: two closely related partners. Cell Death Differ 16, 70-78 (2009). 478. Klose, A., Zigrino, P., Dennhofer, R., Mauch, C. & Hunzelmann, N. Identification and discrimination of extracellularly active cathepsins B and L in high-invasive melanoma cells. Anal Biochem 353, 57-62 (2006). 479. Kos, J. et al. Cathepsins B, H, and L and their inhibitors stefin A and cystatin C in sera of melanoma patients. Clin Cancer Res 3, 1815-1822 (1997). 480. Rojas, R. et al. Regulation of retromer recruitment to endosomes by sequential action of Rab5 and Rab7. J Cell Biol 183, 513-526 (2008). 481. Sapoznik, S., Ortenberg, R., Schachter, J. & Markel, G. CEACAM1 in malignant melanoma: a diagnostic and therapeutic target. Curr Top Med Chem 12, 3-10 (2012). 482. Khatib, N. et al. Carcinoembryonic antigen cell adhesion molecule-1 (CEACAM1) in posterior uveal melanoma: correlation with clinical and histological survival markers. Invest Ophthalmol Vis Sci 52, 9368-9372 (2011). 483. Skorobogata, O. & Rocheleau, C.E. RAB-7 antagonizes LET-23 EGFR signaling during vulva development in Caenorhabditis elegans. PLoS ONE 7, e36489 (2012). 484. Taub, N., Teis, D., Ebner, H.L., Hess, M.W. & Huber, L.A. Late endosomal traffic of the epidermal growth factor receptor ensures spatial and temporal fidelity of mitogen-activated protein kinase signaling. Mol Biol Cell 18, 4698-4710 (2007). 485. Ceresa, B.P. & Bahr, S.J. rab7 activity affects epidermal growth factor:epidermal growth factor receptor degradation by regulating endocytic trafficking from the late endosome. J Biol Chem 281, 1099-1106 (2006). 486. Lu, A. et al. A clathrin-dependent pathway leads to KRas signaling on late endosomes en route to lysosomes. J Cell Biol 184, 863-879 (2009). 487. Flinn, R.J., Yan, Y., Goswami, S., Parker, P.J. & Backer, J.M. The late endosome is essential for mTORC1 signaling. Mol Biol Cell 21, 833-841 (2010). 488. Frasa, M.A. et al. Armus is a Rac1 effector that inactivates Rab7 and regulates E-cadherin degradation. Curr Biol 20, 198-208 (2010). 489. Anitei, M. & Hoflack, B. Bridging membrane and cytoskeleton dynamics in the secretory and endocytic pathways. Nat Cell Biol 14, 11-19 (2011). 490. Yang, C., Hoelzle, M., Disanza, A., Scita, G. & Svitkina, T. Coordination of membrane and actin cytoskeleton dynamics during filopodia protrusion. PLoS ONE 4, e5678 (2009).

158

References

491. Kawauchi, T. Regulation of cell adhesion and migration in cortical neurons: Not only Rho but also Rab family small GTPases. Small Gtpases 2, 36-40 (2011). 492. Kawauchi, T. et al. Rab GTPases-dependent endocytic pathways regulate neuronal migration and maturation through N-cadherin trafficking. Neuron 67, 588-602 (2010). 493. Kasahara, K., Nakayama, Y. & Yamaguchi, N. v-Src and c-Src, nonpalmitoylated Src-family kinases, induce perinuclear accumulation of lysosomes through Rab7 in a kinase activity- independent manner. Cancer Lett 262, 19-27 (2008). 494. Gu, Z., Noss, E.H., Hsu, V.W. & Brenner, M.B. Integrins traffic rapidly via circular dorsal ruffles and macropinocytosis during stimulated cell migration. J Cell Biol 193, 61-70 (2011). 495. Stein, M.P., Feng, Y., Cooper, K.L., Welford, A.M. & Wandinger-Ness, A. Human VPS34 and p150 are Rab7 interacting partners. Traffic 4, 754-771 (2003). 496. Soengas, M.S. & Lowe, S.W. Apoptosis and melanoma chemoresistance. Oncogene 22, 3138- 3151 (2003). 497. Field, A.K., Tytell, A.A., Lampson, G.P. & Hilleman, M.R. Inducers of interferon and host resistance. II. Multistranded synthetic polynucleotide complexes. Proc Natl Acad Sci U S A 58, 1004-1010 (1967). 498. Robinson, R.A. et al. A phase I-II trial of multiple-dose polyriboinosic-polyribocytidylic acid in patieonts with leukemia or solid tumors. J Natl Cancer Inst 57, 599-602 (1976). 499. Levine, A.S., Sivulich, M., Wiernik, P.H. & Levy, H.B. Initial clinical trials in cancer patients of polyriboinosinic-polyribocytidylic acid stabilized with poly-L-lysine, in carboxymethylcellulose [poly(ICLC)], a highly effective interferon inducer. Cancer Res 39, 1645-1650 (1979). 500. Alonso-Curbelo, D. & Soengas, M.S. 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 (2010). 501. Boussif, O. et al. A versatile vector for gene and oligonucleotide transfer into cells in culture and in vivo: polyethylenimine. Proc Natl Acad Sci U S A 92, 7297-7301 (1995). 502. Kopatz, I., Remy, J.S. & Behr, J.P. A model for non-viral gene delivery: through syndecan adhesion molecules and powered by actin. J Gene Med 6, 769-776 (2004). 503. Godbey, W.T., Wu, K.K. & Mikos, A.G. Tracking the intracellular path of poly(ethylenimine)/DNA complexes for gene delivery. Proc Natl Acad Sci U S A 96, 5177-5181 (1999). 504. Remy-Kristensen, A., Clamme, J.P., Vuilleumier, C., Kuhry, J.G. & Mely, Y. Role of endocytosis in the transfection of L929 fibroblasts by polyethylenimine/DNA complexes. Biochim Biophys Acta 1514, 21-32 (2001). 505. Eisenberg-Lerner, A., Bialik, S., Simon, H.U. & Kimchi, A. Life and death partners: apoptosis, autophagy and the cross-talk between them. Cell Death Differ 16, 966-975 (2009). 506. Gray-Schopfer, V., Wellbrock, C. & Marais, R. Melanoma biology and new targeted therapy. Nature 445, 851-857 (2007). 507. Levine, B. & Deretic, V. Unveiling the roles of autophagy in innate and adaptive immunity. Nat Rev Immunol 7, 767-777 (2007). 508. Sanjuan, M.A. & Green, D.R. Eating for good health: linking autophagy and phagocytosis in host defense. Autophagy 4, 607-611 (2008). 509. Virgin, H.W. & Levine, B. Autophagy genes in immunity. Nat Immunol 10, 461-470 (2009). 510. Grosse, S. et al. Potocytosis and cellular exit of complexes as cellular pathways for gene delivery by polycations. J Gene Med 7, 1275-1286 (2005). 511. Huth, S. et al. Insights into the mechanism of magnetofection using PEI-based magnetofectins for gene transfer. J Gene Med 6, 923-936 (2004).

159

References

512. Rejman, J., Conese, M. & Hoekstra, D. Gene transfer by means of lipo- and polyplexes: role of clathrin and caveolae-mediated endocytosis. J Liposome Res 16, 237-247 (2006). 513. Rejman, J., Bragonzi, A. & Conese, M. Role of clathrin- and caveolae-mediated endocytosis in gene transfer mediated by lipo- and polyplexes. Mol Ther 12, 468-474 (2005). 514. Jones, E.A. et al. Interactions of Sox10 and Egr2 in myelin gene regulation. Neuron Glia Biol 3, 377-387 (2007). 515. Wurmser, A.E., Sato, T.K. & Emr, S.D. New component of the vacuolar class C-Vps complex couples nucleotide exchange on the Ypt7 GTPase to SNARE-dependent docking and fusion. J Cell Biol 151, 551-562 (2000). 516. Zhang, X.M., Walsh, B., Mitchell, C.A. & Rowe, T. TBC domain family, member 15 is a novel mammalian Rab GTPase-activating protein with substrate preference for Rab7. Biochem Biophys Res Commun 335, 154-161 (2005). 517. Hurley, J.H. & Odorizzi, G. Get on the exosome bus with ALIX. Nat Cell Biol 14, 654-655 (2012).

160

References

Appendix

161

References

162

Appendix

Common Epidemiology and age of Degree of Subtypes anatomic Key histophatological features patient sun damage site RGP in which enlarged atypical 70% of all melanomas in Trunk of melanocytes display a marked Superficial Acute light-skinned individuals. men and upward scatter within the spreanding intermittent Frequently diagnosed in legs of epidermis ("pagetoid" spread). At melanoma sun exposure middle-aged people women later stages, dermal invasion (VGP) can be observed RGP characterized by linear or nested proliferation of atypical <1 % of cutaneous melanocytes along the basal Lentigo melanomas. Chronic sun Head and epidermis ("lentiginous" maligna Frequently diagnosed in exposure neck hyperplasia, or Lentigo Maligna). melanoma the seventh decade of life When dermal invasion (VGP) is observed, the term lentigo maligna melanoma is used 2% and 80% of cutaneous RGP in which atypical melanomas in Caucasian melanocytes exhibit a Acral- Not related Palms, and dark-skinned "lentiginous" proliferation along lentiginous to sun soles, individuals respectively. the basal epidermis. At later melanoma damage nails Frequently diagnosed in stages, dermal invasion (VGP) can the seventh decade of life be observed 10-15% of all melanomas Trunk, VGP in which atypical Nodular in Caucasian individuals. Intermittent head, melancoytes form one or more melanoma Frequently diagnosed in sun exposure neck and solid nodules within the dermis. the sixth decade of life lower legs No significant RGP Table S1. Major Clinicopathological Subtypes of Cutaneous Melanomas. Information extracted from ref. 52

163

Appendix

T Thickness (mm) Ulceration Status/Mitoses Tis in situ Not applicable T1 ≤ 1.00 a: Without ulceration and mitosis < 1/mm2 b: With ulceration and mitosis ≥ 1/mm2 T2 1.01-2.00 a: Without ulceration b: With ulceration T3 2.01-4.00 a: Without ulceration b: With ulceration T4 > 4.00 a: Without ulceration b: With ulceration N Number of Metastatic Nodes Nodal Metastatic N0 0 Not applicable N1 1 a: Micrometastasis

b: Macrometastasis N2 2 a: Micrometastasis b: Macrometastasis c: In transit metastases/satellites without metatatic nodes N3 4 + metastatic nodes, or matted nodes, or in transit metastases/satellites with metastatic nodes M Site Serum LDH M0 No distant metatases Not applicable Distant skin, subcutaneous, M1a Normal or nodal metastases M1b Lung metastases Normal M1c 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

Clinical Staging Pathologic Staging Stage T N M Stage T N M 0 Tis N0 M0 0 Tis N0 M0 IA T1a N0 M0 IA T1a N0 M0 IB T1b N0 M0 IB T1b N0 M0 T2a N0 M0 T2a N0 M0 IIA T2b N0 M0 IIA T2b N0 M0 T3a N0 M0 T3a N0 M0 IIB T3b N0 M0 IIB T3b N0 M0 T4a N0 M0 T4a N0 M0 IIC T4b N0 M0 IIC T4b N0 M0 III Any T N>N0 M0 IIIA T1-4a N1a or N2a M0 IIIB T1-4b N1a or N2a M0 T1-4a Nib or N2b or N2c M0 IIIC T1-4b Nib or N2b or N2c M0 Any T N3 M0 IV Any T Any N M1 IV Any T Any N 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 lytic vacuole 179 1,00219E-08 GO:0005764 lysosome 179 1,00219E-08 GO:0005739 mitochondrion 813 1,44277E-06 GO:0044429 mitochondrial part 468 4,75902E-06 GO:0031090 organelle membrane 825 5,36687E-06 GO:0042470 melanosome 105 8,17296E-06 GO:0031966 mitochondrial membrane 324 4,88567E-05 GO:0005740 mitochondrial envelope 341 4,88567E-05 GO:0031988 membrane-bounded vesicle 469 8,02254E-05 GO:0016023 cytoplasmic membrane-bounded vesicle 450 8,07733E-05 GO:0043218 compact myelin 10 0,000124617 GO:0031410 cytoplasmic vesicle 535 0,000365405 GO:0031982 vesicle 565 0,000365405 GO:0043209 myelin sheath 23 0,000455941 GO:0005743 mitochondrial inner membrane 266 0,000467785 GO:0019866 organelle inner membrane 282 0,00105986 GO:0042613 MHC class II protein complex 23 0,00161817 GO:0030529 ribonucleoprotein complex 431 0,00655529 GO:0005770 late endosome 57 0,00716068 GO:0005794 Golgi apparatus 694 0,0113744 GO:0045177 apical part of cell 172 0,0146773 GO:0044433 cytoplasmic vesicle part 160 0,0152588 GO:0005741 mitochondrial outer membrane 82 0,0154928 GO:0030173 integral to Golgi membrane 48 0,0258355 GO:0031228 intrinsic to Golgi membrane 51 0,0297121 GO:0030424 axon 167 0,0301226 GO:0016471 vacuolar proton-transporting V-type ATPase complex 13 0,0412011 GO:0005774 vacuolar membrane 52 0,0412011 GO:0019867 outer membrane 104 0,0412011 GO:0034045 pre-autophagosomal structure membrane 10 0,042695 GO:0005594 collagen type IX 10 0,042695 GO:0000307 cyclin-dependent protein kinase holoenzyme complex 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

BRAF NRAS PTEN MITF (PROTEIN / RAB7A GENE IN GAINED CELL LINE p53 (EXON 15) (EXON 3) (PROTEIN) LEVELS) 3q21.3 REGION (CGH)

mutant SK-Mel-103 wt + wtR No Yes (Q61R) mutant SK-Mel-19 wt - wt Yes / High Yes (V600E) mutant SK-Mel-28 wt + mutant Yes / High Yes (V600E) mutant SK-Mel-29 wt - wt Yes / High Yes (V600E) mutant SK-Mel-147 wt + wtR No No (Q61R) mutant UACC-62 wt - wt Yes / Low Yes (V600E) mutant SK-Mel-5 wt + wtR Yes / Low ND (V600E) wt/mutant G-361 wt - wtR Yes / High No (V600E) NRAS SK-Mel-173 wt -/+ wtR ND No (Q61K) mutant WM-164 wt + mutant Yes / High ND (V600E) mutant Mel-1 wt ND ND No ND (Q61R)

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 HR 95%CI p RAB7 Expression 2.52 1.39 - 4.60 0.002 RAB7 Expression 2.98 1.35 - 6.59 0.007 Adjusted by Breslow Adjusted by Breslow 2.17 1.18 - 4.00 0.013 2.36 1.06 - 5.26 0.036 (mm) (mm) 10 YEARS FOLLOW UP 10 YEARS FOLLOW UP HR 95%CI p HR 95%CI p RAB7 Expression 2.43 1.41 - 4.19 0.001 RAB7 Expression 2.01 1.07 - 3.76 0.030 Adjusted by Breslow Adjusted by Breslow 2.06 1.19 - 3.59 0.010 1.53 0.81 - 2.90 0.193 (mm) (mm)

Table S6. RAB7 and patient prognosis. Kaplan-Meier, log-rank test (P), and Cox regression univariate and Breswlow- adjusted 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

pathwaySIGNIFICANTLY databases in RNA UPsequencing- OR DOWN data -(REGULATEDGSE42735) from PATHWAYS melanoma (UACC IDENTIFIED-62) and non BY-melanoma GSEA UPON (HCT116) RAB7 cells stably expressing scrambled shRNA or RAB7 shRNA (shRNA 3) and harvested at day 3 after lentiviral infection. Shown are the pathways significantlyDOWNREGULATION enriched in RAB7-downregulated IN REPRESENTATIVE cells (FDR<0.25). MELANOMA Top scoring pathways AND NON (FDR<0.05)-MELANOMA are marked CELL in bold. LINES

1. DOWNREGULATED PATHWAYS (UACC-62 MELANOMA CELL LINE)

DATABASE NAME SIZE FDR q-val REACTOME__M PHASE 86 <0.0001 REACTOME__CELL CYCLE, MITOTIC 277 <0.0001 REACTOME__MITOTIC PROMETAPHASE 82 <0.0001 REACTOME__G2/M CHECKPOINTS 34 <0.0001 REACTOME__DNA STRAND ELONGATION 30 <0.0001 REACTOME__ACTIVATION OF ATR IN RESPONSE TO REPLICATION STRESS 30 <0.0001 REACTOME__CELL CYCLE CHECKPOINTS 101 <0.0001 REACTOME__DNA REPLICATION 85 <0.0001 REACTOME__G1/S TRANSITION 88 <0.0001 REACTOME__ACTIVATION OF THE PRE-REPLICATIVE COMPLEX 23 <0.0001 REACTOME__DNA REPLICATION PRE-INITIATION 66 <0.0001 REACTOME__ELONGATION OF INTRON-CONTAINING TRANSCRIPTS AND CO-TRANSCRIPTIONAL MRNA SPLICING 121 <0.0001 REACTOME__ELONGATION AND PROCESSING OF CAPPED TRANSCRIPTS 121 <0.0001 REACTOME__DNA REPAIR 95 <0.0001 REACTOME__EXTENSION OF TELOMERES 23 <0.0001 REACTOME__FORMATION AND MATURATION OF MRNA TRANSCRIPT 139 0.003 REACTOME__E2F MEDIATED REGULATION OF DNA REPLICATION 21 0.005 REACTOME REACTOME__INTERACTIONS OF REV WITH HOST CELLULAR PROTEINS 30 0.016 REACTOME__LAGGING STRAND SYNTHESIS 19 0.025 REACTOME__METABOLISM OF NON-CODING RNA 20 0.028 REACTOME__ASSEMBLY OF THE PRE-REPLICATIVE COMPLEX 52 0.035 REACTOME__HIV LIFE CYCLE 99 0.035 REACTOME__M/G1 TRANSITION 52 0.048 REACTOME__APC/C-MEDIATED DEGRADATION OF CELL CYCLE PROTEINS 72 0.046 REACTOME__INTERACTIONS OF VPR WITH HOST CELLULAR PROTEINS 33 0.055 REACTOME__NUCLEAR IMPORT OF REV PROTEIN 28 0.087 REACTOME__DOUBLE-STRAND BREAK REPAIR 18 0.087 REACTOME__GAP-FILLING DNA REPAIR SYNTHESIS AND LIGATION IN GG-NER 15 0.125 REACTOME__APC-CDC20 MEDIATED DEGRADATION OF NEK2A 22 0.137 REACTOME__LATE PHASE OF HIV LIFE CYCLE 88 0.153 REACTOME__GAP-FILLING DNA REPAIR SYNTHESIS AND LIGATION IN TC-NER 15 0.191 DNA_REPLICATION_-_HOMO_SAPIENS_(HUMAN) 34 <0.0001 CELL_CYCLE_-_HOMO_SAPIENS_(HUMAN) 104 0.007 KEGG PYRIMIDINE_METABOLISM_-_HOMO_SAPIENS_(HUMAN) 88 0.186 FANCONI_PATHWAY:FANCONI ANEMIA PATHWAY 44 <0.0001 AURORA_B_PATHWAY:AURORA B SIGNALING 38 <0.0001 PLK1_PATHWAY:PLK1 SIGNALING EVENTS 42 <0.0001 ATR_PATHWAY:ATR SIGNALING PATHWAY 38 1.01E-04 E2F_PATHWAY:E2F TRANSCRIPTION FACTOR NETWORK 71 5.48E-04

BARD1PATHWAY:BARD1 SIGNALING EVENTS 29 6.60E-04 NCI FOXM1PATHWAY:FOXM1 TRANSCRIPTION FACTOR NETWORK 38 0.0109909 AURORA_A_PATHWAY:AURORA A SIGNALING 30 0.01218575 ATM_PATHWAY:ATM PATHWAY 34 0.01694113 MYC_ACTIVPATHWAY:VALIDATED TARGETS OF C-MYC TRANSCRIPTIONAL ACTIVATION 79 0.04611067 TOLL_ENDOGENOUS_PATHWAY:ENDOGENOUS TLR SIGNALING 24 0.08515701

2. UPREGULATED PATHWAYS (UACC-62 MELANOMA CELL LINE)

DATABASE NAME SIZE FDR q-val REACTOME__CLASSICAL ANTIBODY-MEDIATED COMPLEMENT ACTIVATION 15 0.00838841 REACTOME__FORMATION OF PLATELET PLUG 103 0.01967726 REACTOME__INTEGRIN CELL SURFACE INTERACTIONS 76 0.01936138 REACTOME__NEF-MEDIATES DOWN MODULATION OF CELL SURFACE RECEPTORS BY RECRUITING THEM TO CLATHRIN ADAPTERS 20 0.01901494 REACTOME__HEMOSTASIS 210 0.01646517 REACTOME__GLYCOLYSIS 20 0.01851544 REACTOME__MEMBRANE TRAFFICKING 40 0.01608925 REACTOME__INTEGRIN ALPHAIIBBETA3 SIGNALING 21 0.0253362 REACTOME__EXOCYTOSIS OF ALPHA GRANULE 56 0.02482065 REACTOME__IMMUNOREGULATORY INTERACTIONS BETWEEN A LYMPHOID AND A NON-LYMPHOID CELL 73 0.02508278 REACTOME__CELL SURFACE INTERACTIONS AT THE VASCULAR WALL 84 0.03821398 REACTOME__INTRINSIC PATHWAY 15 0.03860102 REACTOME__BASIGIN INTERACTIONS 23 0.11686838 REACTOME__PI3K/AKT SIGNALLING 29 0.10913188 REACTOME__NCAM1 INTERACTIONS 25 0.11578983 REACTOME__FORMATION OF FIBRIN CLOT (CLOTTING CASCADE) 24 0.1443846 REACTOME__CLASS B/2 (SECRETIN FAMILY RECEPTORS) 28 0.15163149 REACTOME__CREATION OF C4 AND C2 ACTIVATORS 18 0.18257278

REACTOME REACTOME__OLFACTORY SIGNALING PATHWAY 253 0.19473417 REACTOME__PEPTIDE CHAIN ELONGATION 100 0.19209401 REACTOME__NEURORANSMITTER RECEPTOR BINDING AND DOWNSTREAM TRANSMISSION IN THE POSTSYNAPTIC CELL 27 0.19213723 REACTOME__GLUTAMATE BINDING, ACTIVATION OF AMPA RECEPTORS AND SYNAPTIC PLASTICITY 27 0.1851637 REACTOME__PI3K CASCADE 21 0.18657506 REACTOME__DIABETES PATHWAYS 251 0.21221207 REACTOME__ELECTRON TRANSPORT CHAIN 74 0.20692673 REACTOME__METABOLISM OF BILE ACIDS AND BILE SALTS 23 0.20272683 REACTOME__GLUCOSE REGULATION OF INSULIN SECRETION 146 0.1970926 REACTOME__NCAM SIGNALING FOR NEURITE OUT-GROWTH 46 0.20521082 REACTOME__G(S)-ALPHA MEDIATED EVENTS IN GLUCAGON SIGNALLING 24 0.20030124 REACTOME__INTEGRATION OF ENERGY METABOLISM 204 0.20510356 REACTOME__AXON GUIDANCE 46 0.21086268 REACTOME__COMPLEMENT CASCADE 168 29 0.23172796 REACTOME__APOPTOTIC CLEAVAGE OF CELLULAR PROTEINS 33 0.23814444 Appendix

2. UPREGULATED PATHWAYS (UACC-62 MELANOMA CELL LINE) DATABASE NAME SIZE FDR q-val GLYCAN_STRUCTURES_-_BIOSYNTHESIS_1_-_HOMO_SAPIENS_(HUMAN) 113 <0.0001 CELL_ADHESION_MOLECULES_(CAMS)_-_HOMO_SAPIENS_(HUMAN) 115 0.01128041 GLYCAN_STRUCTURES_-_DEGRADATION_-_HOMO_SAPIENS_(HUMAN) 27 0.04056513 LEUKOCYTE_TRANSENDOTHELIAL_MIGRATION_-_HOMO_SAPIENS_(HUMAN) 102 0.04269259 ECM-RECEPTOR_INTERACTION_-_HOMO_SAPIENS_(HUMAN) 85 0.0432842 ANTIGEN_PROCESSING_AND_PRESENTATION_-_HOMO_SAPIENS_(HUMAN) 76 0.04394831 FOCAL_ADHESION_-_HOMO_SAPIENS_(HUMAN) 186 0.04950933 AMINOSUGARS_METABOLISM_-_HOMO_SAPIENS_(HUMAN) 27 0.07179534 CHONDROITIN_SULFATE_BIOSYNTHESIS_-_HOMO_SAPIENS_(HUMAN) 20 0.07282304 HEMATOPOIETIC_CELL_LINEAGE_-_HOMO_SAPIENS_(HUMAN) 71 0.07333832 GLYCAN_STRUCTURES_-_BIOSYNTHESIS_2_-_HOMO_SAPIENS_(HUMAN) 58 0.07801138 JAK-STAT_SIGNALING_PATHWAY_-_HOMO_SAPIENS_(HUMAN) 138 0.07842021 AUTOIMMUNE_THYROID_DISEASE_-_HOMO_SAPIENS_(HUMAN) 46 0.08743946 TYPE_I_DIABETES_MELLITUS_-_HOMO_SAPIENS_(HUMAN) 37 0.0880243 KERATAN_SULFATE_BIOSYNTHESIS_-_HOMO_SAPIENS_(HUMAN) 17 0.08975697 GALACTOSE_METABOLISM_-_HOMO_SAPIENS_(HUMAN) 31 0.08988976 FRUCTOSE_AND_MANNOSE_METABOLISM_-_HOMO_SAPIENS_(HUMAN) 37 0.09018355 TIGHT_JUNCTION_-_HOMO_SAPIENS_(HUMAN) 122 0.09094558 REGULATION_OF_ACTIN_CYTOSKELETON_-_HOMO_SAPIENS_(HUMAN) 197 0.09114642

GAP_JUNCTION_-_HOMO_SAPIENS_(HUMAN) 85 0.09158529 KEGG OXIDATIVE_PHOSPHORYLATION_-_HOMO_SAPIENS_(HUMAN) 117 0.09356262 N-GLYCAN_BIOSYNTHESIS_-_HOMO_SAPIENS_(HUMAN) 40 0.09765068 GLYCOSPHINGOLIPID_BIOSYNTHESIS_-_GANGLIOSERIES_-_HOMO_SAPIENS_(HUMAN) 15 0.10406436 ALZHEIMER'S_DISEASE_-_HOMO_SAPIENS_(HUMAN) 27 0.12694243 APOPTOSIS_-_HOMO_SAPIENS_(HUMAN) 81 0.12932102 CHRONIC_MYELOID_LEUKEMIA_-_HOMO_SAPIENS_(HUMAN) 74 0.13115391 NATURAL_KILLER_CELL_MEDIATED_CYTOTOXICITY_-_HOMO_SAPIENS_(HUMAN) 116 0.16281699 SMALL_CELL_LUNG_CANCER_-_HOMO_SAPIENS_(HUMAN) 86 0.16349994 INSULIN_SIGNALING_PATHWAY_-_HOMO_SAPIENS_(HUMAN) 128 0.16410345 AXON_GUIDANCE_-_HOMO_SAPIENS_(HUMAN) 124 0.16636552 GLYCOLYSIS_/_GLUCONEOGENESIS_-_HOMO_SAPIENS_(HUMAN) 57 0.17005293 INOSITOL_PHOSPHATE_METABOLISM_-_HOMO_SAPIENS_(HUMAN) 47 0.19285673 O-GLYCAN_BIOSYNTHESIS_-_HOMO_SAPIENS_(HUMAN) 29 0.19408289 EPITHELIAL_CELL_SIGNALING_IN_HELICOBACTER_PYLORI_INFECTION_-_HOMO_SAPIENS_(HUMAN) 64 0.20235842 COMPLEMENT_AND_COAGULATION_CASCADES_-_HOMO_SAPIENS_(HUMAN) 62 0.22344443 ERBB_SIGNALING_PATHWAY_-_HOMO_SAPIENS_(HUMAN) 85 0.22548513 GLYCEROLIPID_METABOLISM_-_HOMO_SAPIENS_(HUMAN) 45 0.22696957 CYTOKINE-CYTOKINE_RECEPTOR_INTERACTION_-_HOMO_SAPIENS_(HUMAN) 225 0.22995618 MELANOMA_-_HOMO_SAPIENS_(HUMAN) 67 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 HEDGEHOG_GLIPATHWAY:HEDGEHOG SIGNALING EVENTS MEDIATED BY GLI PROTEINS 46 0.05168133 TAP63PATHWAY:VALIDATED TRANSCRIPTIONAL TARGETS OF TAP63 ISOFORMS 49 0.0524029 THROMBIN_PAR1_PATHWAY:PAR1-MEDIATED THROMBIN SIGNALING EVENTS 42 0.05249197 MYC_REPRESSPATHWAY:VALIDATED TARGETS OF C-MYC TRANSCRIPTIONAL REPRESSION 60 0.05251113 UPA_UPAR_PATHWAY:UROKINASE-TYPE PLASMINOGEN ACTIVATOR (UPA) AND UPAR-MEDIATED SIGNALING 34 0.05502375 HIF1_TFPATHWAY:HIF-1-ALPHA TRANSCRIPTION FACTOR NETWORK 63 0.09599881 TGFBRPATHWAY:TGF-BETA RECEPTOR SIGNALING 54 0.1002318 WNT_SIGNALING_PATHWAY:WNT SIGNALING NETWORK 25 0.10785396 RXR_VDR_PATHWAY:RXR AND RAR HETERODIMERIZATION WITH OTHER NUCLEAR RECEPTOR 21 0.12341514 P75NTRPATHWAY:P75(NTR)-MEDIATED SIGNALING 66 0.12517372 ANGIOPOIETINRECEPTOR_PATHWAY:ANGIOPOIETIN RECEPTOR TIE2-MEDIATED SIGNALING 48 0.12831745 AVB3_INTEGRIN_PATHWAY:INTEGRINS IN ANGIOGENESIS 72 0.1296601 NFAT_3PATHWAY:ROLE OF CALCINEURIN-DEPENDENT NFAT SIGNALING IN LYMPHOCYTES 51 0.13114354 PDGFRBPATHWAY:PDGFR-BETA SIGNALING PATHWAY 124 0.13248943 SYNDECAN_4_PATHWAY:SYNDECAN-4-MEDIATED SIGNALING EVENTS 31 0.14232591 INTEGRIN1_PATHWAY:BETA1 INTEGRIN CELL SURFACE INTERACTIONS 63 0.14390154 CERAMIDE_PATHWAY:CERAMIDE SIGNALING PATHWAY 44 0.14599414 NCI FAK_PATHWAY:SIGNALING EVENTS MEDIATED BY FOCAL ADHESION KINASE 57 0.14841408 IL27PATHWAY:IL27-MEDIATED SIGNALING EVENTS 25 0.1512948 PI3KPLCTRKPATHWAY:TRK RECEPTOR SIGNALING MEDIATED BY PI3K AND PLC-GAMMA 35 0.15236078 SYNDECAN_1_PATHWAY:SYNDECAN-1-MEDIATED SIGNALING EVENTS 46 0.15469341 HDAC_CLASSIII_PATHWAY:SIGNALING EVENTS MEDIATED BY HDAC CLASS III 24 0.15510428 KITPATHWAY:SIGNALING EVENTS MEDIATED BY STEM CELL FACTOR RECEPTOR (C-KIT) 51 0.15837726 TXA2PATHWAY:THROMBOXANE A2 RECEPTOR SIGNALING 50 0.16307765 TCPTP_PATHWAY:SIGNALING EVENTS MEDIATED BY TCPTP 39 0.1635841 PTP1BPATHWAY:SIGNALING EVENTS MEDIATED BY PTP1B 49 0.16704606 MET_PATHWAY:SIGNALING EVENTS MEDIATED BY HEPATOCYTE GROWTH FACTOR RECEPTOR (C-MET) 76 0.17017573 INTEGRIN_A9B1_PATHWAY:ALPHA9 BETA1 INTEGRIN SIGNALING EVENTS 24 0.17049243 ARF_3PATHWAY:ARF1 PATHWAY 19 0.17246254 ECADHERIN_STABILIZATION_PATHWAY:STABILIZATION AND EXPANSION OF THE E-CADHERIN ADHERENS JUNCTION 40 0.17291948 EPHA2_FWDPATHWAY:EPHA2 FORWARD SIGNALING 17 0.18491796 ALK1PATHWAY:ALK1 SIGNALING EVENTS 25 0.1972177 ENDOTHELINPATHWAY:ENDOTHELINS 58 0.19961236 LYMPHANGIOGENESIS_PATHWAY:VEGFR3 SIGNALING IN LYMPHATIC ENDOTHELIUM 24 0.19996001 NECTIN_PATHWAY:NECTIN ADHESION PATHWAY 26 0.20215957 IL4_2PATHWAY:IL4-MEDIATED SIGNALING EVENTS 59 0.21128222 RET_PATHWAY:SIGNALING EVENTS REGULATED BY RET TYROSINE KINASE 37 0.21195725 ERBB1_DOWNSTREAM_PATHWAY:ERBB1 DOWNSTREAM SIGNALING 103 0.21226509 BETACATENIN_DEG_PATHWAY:DEGRADATION OF BETA CATENIN 17 0.2123452 INSULIN_PATHWAY:INSULIN PATHWAY 43 0.2371342 ERBB2ERBB3PATHWAY:ERBB2/ERBB3 SIGNALING EVENTS 43 0.24791914 INTEGRIN_A4B1_PATHWAY:ALPHA4 BETA1 INTEGRIN SIGNALING EVENTS 30 0.24983431

169

Appendix

3. DOWNREGULATED PATHWAYS (HCT116 COLON CANCER CELL LINE)

DATABASE NAME SIZE FDR q-val REACTOME__EXOCYTOSIS OF ALPHA GRANULE 51 0.00539583 REACTOME__FORMATION OF PLATELET PLUG 97 0.01474072 REACTOME__HEMOSTASIS 207 0.04375368 REACTOME__INTEGRIN CELL SURFACE INTERACTIONS 77 0.10112921 REACTOME__APOPTOTIC CLEAVAGE OF CELLULAR PROTEINS 32 0.14367585 REACTOME__NCAM SIGNALING FOR NEURITE OUT-GROWTH 44 0.1724425 REACTOME__AXON GUIDANCE 44 0.1871709 REACTOME__APC/C:CDC20 MEDIATED DEGRADATION OF MITOTIC PROTEINS 63 0.19323502 REACTOME__FURTHER PLATELET RELEASATE 20 0.19445132 REACTOME__G1/S DNA DAMAGE CHECKPOINTS 50 0.19954892 REACTOME__NCAM1 INTERACTIONS 23 0.20022282 REACTOME__APOPTOTIC EXECUTION PHASE 38 0.2021108 REACTOME__MUSCLE CONTRACTION 27 0.20359442 REACTOME__CDC20:PHOSPHO-APC/C MEDIATED DEGRADATION OF CYCLIN A 61 0.204563

REACTOME REACTOME__ACTIVATION OF APC/C AND APC/C:CDC20 MEDIATED DEGRADATION OF MITOTIC PROTEINS 64 0.21012999 REACTOME__APC/C:CDC20 MEDIATED DEGRADATION OF SECURIN 59 0.21391934 REACTOME__AUTODEGRADATION OF CDH1 BY CDH1:APC/C 58 0.21625 REACTOME__CELL SURFACE INTERACTIONS AT THE VASCULAR WALL 86 0.21701321 REACTOME__GLUCOSE METABOLISM 74 0.22160994 REACTOME__CDK-MEDIATED PHOSPHORYLATION AND REMOVAL OF CDC6 44 0.22272432 REACTOME__GLYCOLYSIS 20 0.23832981 REACTOME__PHASE 1 - FUNCTIONALIZATION OF COMPOUNDS 57 0.24262054 REACTOME__CELL DEATH SIGNALLING VIA NRAGE, NRIF AND NADE 23 0.24464706 REACTOME__GLUCONEOGENESIS 31 0.24813245 REACTOME__BASIGIN INTERACTIONS 25 0.2486531 REACTOME__G(S)-ALPHA MEDIATED EVENTS IN GLUCAGON SIGNALLING 24 0.24909715 ECM-RECEPTOR_INTERACTION_-_HOMO_SAPIENS_(HUMAN) 85 0.06163346 ALZHEIMER'S_DISEASE_-_HOMO_SAPIENS_(HUMAN) 27 0.09436793 PPAR_SIGNALING_PATHWAY_-_HOMO_SAPIENS_(HUMAN) 60 0.19583198 SPHINGOLIPID_METABOLISM_-_HOMO_SAPIENS_(HUMAN) 35 0.19969407 GLUTATHIONE_METABOLISM_-_HOMO_SAPIENS_(HUMAN) 37 0.20419754 PROTEASOME_-_HOMO_SAPIENS_(HUMAN) 21 0.20671786

KEGG CELL_ADHESION_MOLECULES_(CAMS)_-_HOMO_SAPIENS_(HUMAN) 114 0.21696399 ANTIGEN_PROCESSING_AND_PRESENTATION_-_HOMO_SAPIENS_(HUMAN) 78 0.21856105 AXON_GUIDANCE_-_HOMO_SAPIENS_(HUMAN) 120 0.23966669 CARBON_FIXATION_-_HOMO_SAPIENS_(HUMAN) 21 0.24837023 POLYUNSATURATED_FATTY_ACID_BIOSYNTHESIS_-_HOMO_SAPIENS_(HUMAN) 15 0.24879314 PYRUVATE_METABOLISM_-_HOMO_SAPIENS_(HUMAN) 39 0.2495452

4. UPREGULATED PATHWAYS (HCT116 COLON CANCER CELL LINE)

DATABASE NAME SIZE FDR q-val REACTOME__EUKARYOTIC TRANSLATION ELONGATION 104 <0.0001 REACTOME__3 -UTR-MEDIATED TRANSLATIONAL REGULATION 121 <0.0001 REACTOME__PEPTIDE CHAIN ELONGATION 100 <0.0001 REACTOME__FORMATION OF A POOL OF FREE 40S SUBUNITS 110 <0.0001 REACTOME__GTP HYDROLYSIS AND JOINING OF THE 60S RIBOSOMAL SUBUNIT 122 <0.0001 REACTOME__L13A-MEDIATED TRANSLATIONAL SILENCING OF CERULOPLASMIN EXPRESSION 121 <0.0001 REACTOME__EUKARYOTIC TRANSLATION TERMINATION 100 <0.0001 REACTOME__INFLUENZA VIRAL RNA TRANSCRIPTION AND REPLICATION 152 <0.0001 REACTOME__CAP-DEPENDENT TRANSLATION INITIATION 129 <0.0001 REACTOME__EUKARYOTIC TRANSLATION INITIATION 129 1.18E-04 REACTOME__ACTIVATION OF THE MRNA UPON BINDING OF THE CAP-BINDING COMPLEX AND EIFS, AND SUBSEQUENT BINDING TO 43S 64 2.92E-04 REACTOME__INFLUENZA LIFE CYCLE 156 3.16E-04 REACTOME__INFLUENZA INFECTION 161 3.45E-04 REACTOME__FORMATION OF THE TERNARY COMPLEX, AND SUBSEQUENTLY, THE 43S COMPLEX 55 0.00134256 REACTOME REACTOME__METABOLISM OF PROTEINS 207 0.09879488 REACTOME__G2/M CHECKPOINTS 34 0.10528342 REACTOME__M PHASE 86 0.13186814 REACTOME__ELONGATION OF INTRON-CONTAINING TRANSCRIPTS AND CO-TRANSCRIPTIONAL MRNA SPLICING 121 0.13790113 REACTOME__GENE EXPRESSION 346 0.14086446 REACTOME__ELONGATION AND PROCESSING OF CAPPED TRANSCRIPTS 121 0.14316013 REACTOME__MITOTIC PROMETAPHASE 82 0.14367956 REACTOME__ACTIVATION OF THE PRE-REPLICATIVE COMPLEX 23 0.1830022 REACTOME__ACTIVATION OF ATR IN RESPONSE TO REPLICATION STRESS 30 0.1976846 REACTOME__CLEAVAGE OF GROWING TRANSCRIPT IN THE TERMINATION REGION 23 0.20171253 REACTOME__FORMATION AND MATURATION OF MRNA TRANSCRIPT 139 0.20955685 RIBOSOME_-_HOMO_SAPIENS_(HUMAN) 66 <0.0001 KEGG NAPHTHALENE_AND_ANTHRACENE_DEGRADATION_-_HOMO_SAPIENS_(HUMAN) 18 0.19851044 NCI PLK1_PATHWAY:PLK1 SIGNALING EVENTS 42 0.1614753

170

Appendix

MELANOMA

Colon NSLC Renal

Prostate Ovarian

Leukemia

Breast CNS

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 temperature- controlled 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, Rodríguez- Peralto JL and Soengas MS (2013). RAB7 controls melanoma progression by exploiting a lineage- specific 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: RAB- dependent 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: RAB7- dependent 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