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Programa de Doctorado en Biociencias Moleculares

IDENTIFICATION OF MOLECULAR MECHANISMS OF ACQUIRED RESISTANCE TO TRASTUZUMAB

IN HER2+ BREAST CANCER

Doctoral Thesis

PAULA GONZÁLEZ ALONSO

Madrid, 2019

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UNIVERSIDAD AUTÓNOMA DE MADRID DOCTORAL SCHOOL

DEPARTMENT OF BIOCHEMISTRY

IDENTIFICATION OF MOLECULAR MECHANISMS OF ACQUIRED RESISTANCE TO TRASTUZUMAB

IN HER2+ BREAST CANCER

A doctoral dissertation submitted by Paula González Alonso

BSc in Biology, MSc in Biomolecular Sciences in partial fulfillment of the requirements for the degree of

Doctor of Philosophy in Molecular Biosciences

Supervisors:

Dr. Federico Rojo Todo Dr. Juan Madoz Gúrpide

Health Research Institute Fundación Jiménez Díaz Area of Cancer, Pathology Department

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The work for this PhD thesis was conducted in the Cancer Research Group of the Pathology De- partment at the Health Research Institute Fundación Jiménez Díaz (IIS-FJD, UAM), and was su- pervised by Dr. Federico Rojo Todo and Dr. Juan Madoz Gúrpide.

An international collaboration was started by the doctoral candidate and developed with the OncoProteomics Laboratory (OPL), headed by Prof. Dr. Connie R. Jimenez, at the VU University Medical Center - Cancer Center Amsterdam (VUmc-CCA), within the Amsterdam University Med- ical Centre (UMC).

The work was supported by grants from the Ministry of Economy and Competitiveness (MINECO) with European Regional Development Fund (FEDER) funding through the Institute of Health Carlos III (ISCIII) (Strategic Action for Health Research – AES – Program, grants PI12/01552 and PI15/00934; and CIBERONC, Biomedical Research Networking Centre for Cancer, grant CB16/12/00241). The doctoral candidate’s work was funded through a Fundación Conchita Rábago de Jiménez Díaz grant.

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Acknowledgments

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Acknowledgments

There are many people who so generously contributed to the work conducted during my PhD, and who made me feel supported and less lonely during this journey. I would like first to thank Dr. Federico Rojo, my supervisor, for all of the opportunities you gave me to conduct my research in your Cancer Biomarkers laboratory at the IIS-FJD in Madrid. You helped me develop my own ideas and think critically about my area of research; I have learned much and grown considerably through working under your supervision. I would also like to thank Dr. Juan Madoz Gúrpide, my co-supervisor, for providing me with an opportunity to join your research team as a predoctoral researcher. You introduced me to the world of proteomics and helped me to get the best from my enthusiasm for this field during my dissertation. Without the support that I have received from both of you I would not have been able to carry out this research.

Besides my supervisors at the IIS-FJD, I would like to express my sincere gratitude to Prof.

Connie R. Jimenez for your invaluable guidance and encouragement during my stay in your la- boratory, the OPL at the VUmc Cancer Center Amsterdam. You provided me with the tools that I needed to find the right way forward and to complete my dissertation successfully. It was en- riching to have the opportunity to carry out part of my research in your facilities.

I am also grateful to my tutor at UAM, Dr. Gema Moreno-Bueno, for your supervisory role;

I appreciate all your advice and assistance with the important administrative aspects of the work.

I gratefully acknowledge the funding received for my PhD from the Fundación Conchita Rábago de Jiménez Díaz; the institution is crucial to doctoral candidates like me being able to undertake our research.

I am most grateful to all the patients and families, health care professionals and adminis- trators who took part and made this research possible.

I thank Terese Winslow LLC, the American Association for Cancer Research, and Elsevier Ltd., for their permission to include copyrighted pictures as a part of my dissertation.

I would like to thank Phil Mason, for your very careful review of my manuscript, and for all your comments and suggestions.

To all my colleagues who participated in this project by the Cancer Biomarkers group at IIS- FJD in Madrid, thank you for wonderful collaboration and for always providing technical support.

With a special mention to my colleague and friend Cris, I appreciate you for mentoring me so

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Acknowledgments

willingly and for sharing with me your contagious enthusiasm for molecular biology and your passion for research (and for everything else), but especially for your words of wisdom and con- stant support, which have been ever-present during this important period of my life. Also, to my

‘little mushroom’, Rebeca, as you were always willing to help me and offer me the kindest advice to keep me thinking clearly. I really appreciate your friendship, your eagerness, and all the time we spent together in and outside the laboratory. I would also like to thank to Sandra, for your excellent cooperation, which helped me throughout doctoral studies and for your help with IHC and microscopy. Lina, you were always willing to share your great experience in pathology with me, and I deeply appreciate your friendship and great support with the clinical studies. Your sincere advice during the time we spent together was tremendously valuable. Raúl, thank you for sharing your experience as a PhD student with me during my first steps. It was a pleasure to work with you in the laboratory during that initial period; I really missed you after you left, and continue to be very grateful for your friendship. Ester and Ion, thank you for your constant sup- port and for always being willing to contribute to my growth as a researcher. Pedro, Olga and Blanca, thank you for the kindness of providing me your constant friendship, and for always being willing to help me. You were an enormous support to me. Melani and Marta, thank you both for your great and honest support for my project. Your contributions have also been es- sential to my achievements. It was a privilege to share a laboratory with all of you during these years. I would also like to thank Pablo, the bioinformatician at the IIS-FJD, for his sustained will- ingness to help me with data analysis when my skills were not sufficiently developed. In addition, I thank María, Nuria, Laura, Nerea, Virginia, Iván, Almudena, Raquel, Sandra, and all the mem- bers of the Pathology Department and the Oncohealth Institute at the FJD University Hospital (laboratory technicians, biologists and clinicians). Your support has made it easier, as well as a pleasure, to work and research over the years.

I also thank all my colleagues who were involved in this project as members of the group of Molecular Cancer Therapeutics, headed by Dr. Albanell at the IMIM in Barcelona, and the Breast Cancer Biology research group, headed by Dr. Lluch at the INCLIVA in Valencia. In particular, I would like to thank Ana and Pilar, respectively, for your topical and intellectual discussions about the research, which helped me come up with new ideas. To Oriol, thank you for your direct technical help and your immeasurable support with animal studies. To Ali and Cristina, thank you both for your indirect assistance and your support as PhD students undertaking projects in parallel to mine. Your kind effort and contributions were a strong and positive influence on the way my research and dissertation turned out.

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Acknowledgments

I greatly appreciate the support received through the collaborative work undertaken with the OPL at VUmc Cancer Center Amsterdam. I am very grateful to Sander, Thang, Jaco, and Alex for your participation in the project and for your help in getting the best quality results possible.

A special mention goes to Richard, for your kind help with sample preparation. I am very grateful to Tim, for your help in dealing with the practicalities of working in a research center and for always making me feel like a member of the team. To Franziska, Carolien, Robin, Irene, Tessa, Sanne, Iris, and Gosia, thank you for your feedback during our meetings. I am especially grateful to all my colleagues and friends at the OPL (or the CCA) in Amsterdam: Davide, Giulia, and Myr- iam, thank you for your support and for letting me share with you not only the moments of deepest anxiety but also those of greatest excitement; I would also like to thank Frank sincerely, for sharing your knowledge and expertise in dealing with phosphoproteomics data with me; a warm word goes to my great friends, Lety and Ayse, for your undeniable help in making me understand and apply all the scripts to my data, and for all the good times that we spent to- gether. Your presence and support were very important in a process that is otherwise often a tremendously solitary task.

Finally, I would like to thank my family, for your limitless patience and understanding, and for your practical and pragmatic support throughout my studies. Especially to my mother, Ana, for your wise counsel and guidance, and to my father, José Antonio, for your motivation and sympathetic ear. You are always there for me. Your dedication to my education, in so many ways, including your sincere words of encouragement and love have always given me so much strength.

This thesis is dedicated to the memory of my grandpa, Manolo, a truly outstanding person, who always believed in my ability to be successful in the academic world and gave me his bound- less support throughout my life. You are gone but your belief in me has made this thesis possible.

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Acknowledgments

“Nothing in life is to be feared, it is only to be understood. Now is the time to understand more, so that we may fear less.”

― Marie Skłodowska-Curie

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Abstract

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Abstract

Routine assessment of molecular biomarkers has been instrumental in determining the prognosis and treatment of breast cancer since the 1980s. HER2 is overexpressed in more than 20% of invasive breast cancers, and is associated with poor prognosis. The use of anti-HER2 ther- apies has significantly improved clinical outcomes in patients with HER2+ breast cancer, yet a notable proportion of those with metastatic disease acquire resistance after a period of treat- ment. This thesis aimed to understand the molecular mechanisms that operate after prolonged exposure to trastuzumab and that can modulate cancer proliferation and tumorigenicity pro- cesses, and those that arise after short exposure to treatment with trastuzumab, alone or com- bined with pertuzumab, in HER2+ breast cancer. Continued exposure to trastuzumab induced drug resistance in the BT-474 breast cancer cell line. Differences in signaling networks were an- alyzed using quantitative phosphoproteomics, and validated by data mining, immunoblotting and qPCR assays of the BT-474.r2T breast cancer cell model. This strategy identified potential biomarkers of trastuzumab resistance acquisition in BT-474.r2T cells, including decreased phos- phorylation of YAP1 at S109, and increased nuclear expression of YAP1/TAZ (active forms) and TEAD1-2. A novel dual treatment strategy targeting HER2 and YAP1-TEAD activity with trastuzumab and verteporfin restored sensitivity to trastuzumab in BT-474.r2T cellular and mu- rine xenograft models. The biological significance of YAP1 and TAZ expression was confirmed in a retrospective cohort study of HER2+ breast cancer patients. Nuclear YAP1 expression was highly positively correlated with nuclear TAZ expression, and a high level of nuclear expression of both biomarkers was associated with worse survival rates in HER2+ metastatic breast cancer.

Exposure to trastuzumab-based therapy increased nuclear YAP1 expression in early and ad- vanced HER2+ breast tumors, which was associated with poor clinical outcome in advanced HER2+ breast tumors.

Knowing the trastuzumab sensitivity of a given HER2+ breast tumor could significantly guide decision-making regarding the choice of treatment plans. Analysis of multiproteomic profiles allows differential signaling signatures to be identified, which improves our understanding of the biology of HER2+ breast cancer cells. Upon functional validation, the identified biomarkers may help improve the classification of HER2+ breast cancer cells as sensitive and resistant, and suggest potential new targets for directed therapy in HER2+ breast cancer cells and tumors with acquired resistance to trastuzumab. Based on the drug resistance biomarker signature, a scoring system can be developed to stratify patients by their expression profile, and to associate scores with clinical outcomes, thereby helping to improve prognosis and prediction of response to bi- omarker-directed therapy in HER2+ breast cancer.

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Resumen

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Resumen

La valoración rutinaria de marcadores moleculares ha sido clave para determinar el pronós- tico y tratamiento del cáncer de mama desde los años 1980. HER2 está sobreexpresado en más del 20% de los tumores de mama invasivos y se asocia con peor pronóstico. El uso de terapias anti-HER2 ha mejorado significativamente los resultados clínicos en pacientes con cáncer de mama HER2+, pero una notable proporción de pacientes con enfermedad metastásica pueden desarrollar resistencia tras un período de tratamiento. Esta tesis se centró en entender los me- canismos moleculares que operan tras la exposición prolongada a trastuzumab y que pueden modular procesos de proliferación celular y tumorigenicidad, y los que surgen tras una breve exposición a trastuzumab solo o combinado con pertuzumab en cáncer de mama HER2+. La ex- posición continuada a trastuzumab indujo resistencia en la línea celular BT-474. Las diferencias en redes de señalización se analizaron en las células BT-474.r2T usando técnicas de fosfoproteó- mica cuantitativa y se validaron mediante minería de datos y ensayos de inmunodetección y qPCR. Esta estrategia identificó biomarcadores potenciales de adquisición de resistencia a tras- tuzumab en las células BT-474.r2T, incluyendo la disminución de la fosforilación de YAP1 en S109 y el incremento de la expresión nuclear de YAP1/TAZ (formas activas) y TEAD1-2. Una nueva estrategia de doble bloqueo de la actividad de HER2 y YAP1-TEAD con trastuzumab y vertepor- fina restauró la sensibilidad a trastuzumab en modelos celulares y en xenoinjertos de BT- 474.r2T. El significado biológico de la expresión de YAP1 y TAZ se confirmó en una cohorte re- trospectiva de pacientes con cáncer de mama HER2+. La expresión nuclear de YAP1 correlacionó positivamente con la expresión nuclear de TAZ y los niveles elevados de expresión nuclear de ambos biomarcadores se asociaron con peores tasas de supervivencia en cáncer de mama HER2+ metastásico. La exposición a terapia basada en trastuzumab incrementó la expresión nu- clear de YAP1 en tumores de mama HER2+ tempranos y avanzados, y se asoció con peor resul- tado clínico en tumores de mama HER2+ avanzados.

Conocer la sensibilidad de cada tumor de mama HER2+ podría guiar la toma de decisiones para la elección del plan de tratamiento. El análisis de perfiles multiproteómicos permite la iden- tificación de firmas de señalización diferenciales, facilitando la comprensión de la biología de las células de cáncer de mama HER2+. Tras su validación funcional, los biomarcadores identificados permiten clasificar las células de cáncer de mama HER2+ en sensibles y resistentes y proponer nuevas dianas potenciales para terapia dirigida en células y tumores de cáncer de mama HRE2+

con resistencia adquirida a trastuzumab. La firma de expresión de biomarcadores de resistencia permite desarrollar un sistema de puntuación para clasificar los tumores según su perfil de ex- presión y asociar las puntuaciones con resultados clínicos, ayudando a mejorar el pronóstico y la predicción de respuesta a terapia dirigida en cáncer de mama HER2+.

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Table of contents

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Table of contents

List of abbreviations ... 11

1. Introduction ... 15

1.1. Breast cancer ... 17

1.1.1. Epidemiology of breast cancer... 17

1.1.2. Histological subtypes of breast cancer ... 18

1.1.3. Molecular characterization of breast cancer ... 19

1.1.4. Role of HER2 as a breast cancer biomarker ... 21

1.2. Emerging drugs for HER2-targeted therapy in breast cancer ... 24

1.2.1. Monoclonal antibodies targeting HER2: trastuzumab ... 24

1.2.2. Tyrosine kinase inhibitors (TKIs) ... 24

1.2.3. Other monoclonal antibodies targeting HER2: pertuzumab ... 25

1.2.4. Antibody-drug conjugates (ADCs): T-DM1 ... 26

1.2.5. Mechanism of action of trastuzumab ... 27

1.2.6. Resistance to anti-HER2-targeted therapy ... 27

1.2.6.1. Increased expression of ligands ... 29

1.2.6.2. Modification at the receptor level ... 29

1.2.6.3. Constitutive activation of HER2 downstream signaling pathway ... 30

1.3. Role of the major Hippo pathway downstream effectors in HER2+ breast cancer ... 31

1.3.1. Role of YAP/TAZ-TEAD in resistance to HER2-targeted therapy ... 34

1.4. Mass spectrometry (MS)-based phosphoproteomics in breast cancer ... 35

2. Objectives ... 37

3. Materials and methods ... 41

3.1. Cell culture methods and reagents ... 43

3.1.1. Generation of the trastuzumab-resistant breast cancer cell line (BCCL) ... 43

3.2. Cellular assays ... 44

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Table of contents

3.2.1. Drug-sensitivity assays ... 44

3.3. MS-based proteomics ... 45

3.3.1. Sample preparation and MS analysis ...45

3.3.1.1. Cell lysis and digestion ... 45

3.3.1.2. Immunoprecipitation of phosphotyrosine-containing peptides (pTyr-IP) and TiO2 enrichment (TiOx) of phosphoserine and phosphothreonine-containing peptides ... 46

3.3.1.3. Label-free analysis of protein expression and phosphorylation by liquid chromatography (LC)-MS/MS ... 47

3.3.2. Bioinformatic analysis ... 47

3.3.2.1. Protein, phosphopeptide and phosphorylation site (phosphosite) identification ... 47

3.3.2.2. Label-free quantitation ... 48

3.3.2.3. Signaling network analysis ... 49

3.4. Murine models ... 49

3.5. Gene expression analysis of The Cancer Genome Atlas (TCGA) database ... 50

3.6. HER2+ breast cancer patient samples ... 50

3.7. Molecular assays ... 51

3.7.1. Transient transfection of BCCLs ... 51

3.7.2. RNA acid isolation and lysis buffers ... 52

3.7.3. Primer design and quantitative real-time PCR (qPCR) ... 52

3.7.4. Protein extraction and analysis by immunoblotting ... 53

3.7.5. Protein expression analysis by IHC ... 54

3.7.5.1. Optimization of YAP1 and TAZ detection in HER2+ breast cancer... 55

3.8. Statistical analysis ... 56

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Table of contents

4. Results ... 59 4.1. Characterization of HER2+ BCCLs and assessment of HER2-targeted therapy-

induced effects ... 61 4.2. Multi-proteomic profiling of HER2+ BCCLs ... 62

4.2.1. pTyr-specific phosphoproteomics defines heterogeneity in HER family activity in parental and trastuzumab-resistant cells ... 64 4.2.1.1. Validation of expression and phosphorylation levels of HER family of

receptors in the acquired trastuzumab-resistant HER2+ cell line ... 65 4.2.2. Quantitative multi-proteomic workflow for the analysis of differential

(phospho-)protein expression profiles mediated by acquired trastuzumab

resistance and by response to anti-HER2-directed treatments ... 66 4.2.2.1. Identification of dysregulated (phospho-)proteins and pathways involved in

acquired resistance to trastuzumab in HER2+ BBCLs ... 67 4.2.2.2. YAP1 phosphorylation is downregulated after acquiring resistance to

trastuzumab and promoted by further exposure to trastuzumab ... 73 4.2.2.3. Identification of determinants of sensitivity to anti-HER2-directed drugs in

HER2+ BCCLs ... 77 4.3. Validation of YAP1 modulation in HER2+ BCCL with acquired trastuzumab

resistance ... 86 4.3.1. Effects of in vitro generation of trastuzumab resistance on the transcriptional

activity of Hippo pathway effectors ... 86 4.3.2. YAP1, TEAD1, and TEAD2 silencing restores sensitivity to trastuzumab in cells

with acquired trastuzumab resistance ... 89 4.4. Effect of combined therapy with trastuzumab and YAP1 inhibitors on trastuzumab-

resistant HER2+ breast cancer ... 91

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Table of contents

4.4.1. Effect of combined therapy with trastuzumab and dobutamine on in vitro cell

proliferation ... 91

4.4.2. Effect of combined therapy with trastuzumab and verteporfin on in vitro cell proliferation ... 92

4.4.3. Effect of combined therapy with trastuzumab and verteporfin on xenograft tumor growth ... 94

4.5. YAP1 and TAZ expression on HER2+ breast cancer. Clinical implications ... 96

4.5.1. Clinical value of YAP1/TAZ-TEAD expression in TCGA patients ... 96

4.5.2. YAP1 and TAZ expression profiles in HER2+ breast cancer tissue ... 97

4.5.3. Clinical significance of YAP1 and TAZ expression in HER2+ breast cancer ... 97

4.5.3.1. Neoadjuvant setting ... 99

4.5.3.2. Adjuvant setting ... 100

4.5.3.3. Metastatic setting ... 102

5. Discussion ... 107

5.1. Acquired resistance to trastuzumab and sensitivity to combined therapy with pertuzumab in HER2+ BCCLs ... 109

5.2. Proteome and phosphoproteome changes in acquired trastuzumab resistance and sensitivity to combined therapy with pertuzumab in HER2+ BCCLs ... 110

5.2.1. Label-free (phospho-)proteomics reveals signaling rewiring in HER2+ BCCLs with acquired trastuzumab resistance ... 111

5.2.2. YAP1 activity as a potential mediator of acquired resistance to trastuzumab ... 114

5.2.3. Key determinants of sensitivity to anti-HER2 therapy in BCCLs ... 115

5.3. Role of Hippo pathway downstream effectors in the acquisition of resistance to HER2-targeted therapy ... 117 5.3.1. Role of YAP1/TAZ-TEAD in acquired resistance to trastuzumab in HER2+ BCCLs .118

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Table of contents

5.3.2. Effect of combined therapy of trastuzumab with YAP1 inhibitors on growth of

acquired trastuzumab-resistant BCCLs and tumor xenografts ... 119

5.3.3. Clinical relevance of YAP1 and TAZ in HER2+ breast cancer ... 121

6. Conclusions ... 125

7. Conclusiones ... 129

8. References ... 133

9. Appendices ... 149

Appendix I – Supplementary material ... 151

Appendix II – Electronic supplementary tables ... 164

10. Annexes ... 165

Annex I – Ethical Committee Approval Forms ... 167

Annex II – List of publications ... 172

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List of abbreviations

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List of abbreviations

∩ Intersection

∪ Union

ACN Acetonitrile

ADAM A disintegrin and metalloprotease

ADC Antibody-drug conjugate

ADCC Antibody-dependent cell cytotoxicity

AHNAK Neuroblast differentiation-associated protein AHNAK AJCC American Joint Committee on Cancer

ANXA1/2 Annexin 1/2

AREG Amphiregulin

ARFGAP1 ADP-ribosylation factor GTPase-activating protein 1 ASCO American Society of Clinical Oncology

ATCC American Type Culture Collection ATP5E ATP synthase F1 subunit epsilon

AUC Area under the curve

BAIAP2 Brain-specific angiogenesis inhibitor 1-associated protein 2

BCA Bicinchoninic acid

BCCL Breast cancer cell line

bp Base pair

BT-474.r2T BT-474 cell line with acquired trastuzumab resistance

BTC Betacellulin

c-casp3 Cleaved caspase-3

CAP College of American Pathologists CBL E3 ubiquitin-protein ligase c-Cbl CBLB E3 ubiquitin-protein ligase Cbl-b

CC Creative Commons

CCA Cancer Center Amsterdam

cDNA Complimentary DNA

CGNL1 Cingulin-like protein 1

Cp Crossing point

CRC Colorectal cancer

CTGF Connective tissue growth factor

CTNNA1 Catenin alpha-1

CTNND1 Catenin delta-1

CYR61 Cysteine-rich angiogenic inducer 61

DAB 3,3′-diaminobenzidine

DCIS Ductal carcinoma in situ

DFS Disease-free survival

DLG3 Discs large homolog 3

DMEM Dulbecco’s modified Eagle medium

DMSO Dimethyl sulfoxide

DNA Deoxyribonucleic acid

DTT Dithiothreitol

EC50 Half maximal inhibitory concentration

ECD Extracellular domain

ECF Effective concentration of agonist/antagonist that gives a response F percent of the way between the bottom and top

EDTA Ethylenediaminetetraacetic acid EEA Ethical Committee for Animal Research

EFNB1 Ephrin-B1

EGF Epidermal growth factor

EGFR Epidermal growth factor receptor

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List of abbreviations

EIC Extracted ion chromatograms

EPG Epiregulin

EPHA Ephrin type-A receptor

ER Estrogen receptor

ER-/ER+ Estrogen receptor-negative/Estrogen receptor-positive FAM129B Niban-like protein 1

FBS Fetal bovine serum

FC Fold change

FDA Food and Drug Administration

FDR False discovery rate

FFPE Formalin-fixed and paraffin-embedded FISH Fluorescent in situ hybridization

FJD Fundación Jiménez Díaz

FW Forward

GAB1 GRB2-associated-binding protein 1

GAPDH Glyceraldehyde-3-phosphate dehydrogenase

GCO Global Cancer Observatory

GDC Genomic Data Commons

GO Gene ontology

GPCR G protein coupled receptor family H&E Hematoxylin and eosin

HB-EGF Heparin binding epidermal growth factor HER/ErbB Human epidermal growth factor receptor HER2-/HER2+ HER2-negative/HER2-positive

HGS Hepatocyte growth factor-regulated tyrosine kinase substrate

HR Hormone receptor

HR-/HR+ Hormone receptor-negative/Hormone receptor-positive

HRP Horseradish peroxidase

IARC International Agency for Research on Cancer

ICD Intracellular domain

IDC Invasive ductal carcinoma

iDFS Invasive disease-free survival

IGF1R/IGF2R Insulin-like growth factor 1/2 receptor IGFBP5 Insulin-like growth factor-binding protein 5 IGHG1 Immunoglobulin heavy constant gamma 1

IGKC Immunoglobulin kappa constant

IHC Immunohistochemistry

ILC Invasive lobular carcinoma

IMIM Hospital del Mar Medical Research Institute INKA Inferred kinase activity

IP Immunoprecipitation

ITCH E3 ubiquitin-protein ligase Itchy homolog

ITGB2 β2-integrin

JAG1 Protein jagged-1

JAK Janus kinase

LAMA5 Laminin subunit alpha-5

LATS 1/2 Large tumor suppressor 1/2 LCIS Lobular carcinoma in situ

LMO7 LIM domain only protein 7

lncRNA Long noncoding RNA

MAPK Mitogen-activated protein kinase MERTK Tyrosine-protein kinase Mer

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List of abbreviations

MOB1A/MOB1B MOB kinase activator 1A/1B

mRNA Messenger ribonucleic acid

MS Mass spectrometry

MS/MS Tandem mass spectrometry

MST1/2 Mammalian STE20-like protein kinase 1/2

mTOR Mammalian target of rapamycin

MUC1-C/5AC Mucin-1/5AC

NC Non-commercial

NCCN National Comprehensive Cancer Network

NCD Noncommunicable disease

NCOR2 Nuclear receptor corepressor 2

ND No Derivatives

Neu Neuregulin

NK Natural killer

NOS Invasive ductal carcinoma, not otherwise specified

NRK Nik-related protein kinase

OPL OncoProteomics Laboratory

OS Overall survival

PARD3 Partitioning defective 3 homolog

PBS Phosphate-buffered saline

pCR Pathological complete response

PCR Polymerase chain reaction

PDT Photodynamic therapy

PFS Progression free survival

pH3 Phosphorylated histone-3-Ser10

PI3K Phosphatidylinositol 3 kinase

PIK3R1 phosphatidylinositol 3-kinase regulatory subunit alpha PKN2 Serine/threonine-protein kinase N2

PKP3 Plakophilin-3

PPI Protein-protein interaction

PR Progesterone receptor

PR-/PR+ Progesterone receptor-negative/Progesterone receptor-positive PRBB Barcelona Biomedical Research Park

Psite Phosphorylation site (phosphosite)

PTEN Phosphatidylinositol 3,4,5-trisphosphate 3-phosphatase and dual-spec- ificity protein phosphatase PTEN

PTK6 Protein-tyrosine kinase 6 PTM Posttranslational modification

qPCR Quantitative polymerase chain reaction

R-Dual Trastuzumab-resistant cells treated with dual therapy of trastuzumab and pertuzumab

R-T Trastuzumab-resistant cells treated with trastuzumab RC Untreated trastuzumab-resistant cells

RET proto-oncogene tyrosine-protein kinase receptor RET

RIN RNA integrity number

RIOK2 Serine/threonine-protein kinase RIO2

RIPA Radioimmunoprecipitation assay

RNA Ribonucleic acid

ROC Receiver operating curve

RR Response rate

RT Reverse transcriptase

RTK Receptor tyrosine kinase

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List of abbreviations

RV Reverse

S-Dual Trastuzumab-sensitive (parental) cells treated with dual therapy of trastuzumab and pertuzumab

S-T Trastuzumab-sensitive (parental) cells treated with trastuzumab

SAV1 Salvador homolog 1

SC Untreated trastuzumab-sensitive (parental) cells

SCID Severe combined immunodeficiency

SD Standard deviation

SDS-PAGE Sodium dodecyl sulfate polyacrylamide gel electrophoresis SEOM Spanish Society of Medical Oncology

SFN Stratifin (14-3-3 protein sigma; 14-3-3σ)

SHC2 Src homology 2 domain-containing-transforming protein 2 siRNA Small interfering ribonucleic acid

SPE Solid-phase extraction

SPTBN1 Spectrin beta chain, non-erythrocytic 1

STAT Signal transducer and activator of the transcription STK11 Serine/threonine-protein kinase STK11

TAZ Tafazzin

TCGA The Cancer Genome Atlas

TEAD1-4 Transcriptional enhancer factors 1-4

TFA Trifluoroacetic acid

TGF-α Transforming growth factor alpha

TiOx TiO2-based enrichment

TKI Tyrosine kinase inhibitor

TLN1 Talin-1

TMA Tissue microarray

TNBC Triple-negative breast cancer

TNM Tumor, node, metastasis

TNS1 Tensin-1

VEGFA Vascular endothelial growth factor A

VUmc VU University Medical Center

WHO World Health Organization

YAP1 Yes-associated protein 1

ZYX Zyxin

ΔGR Differential growth rate

THREE-LETTER AND ONE-LETTER CODES FOR AMINOACIDS

Alanine Ala, A Leucine Leu, L

Arginine Arg, R Lysine Lys, K

Aspartic acid Asp, D Methionine Met, M

Asparagine Asn, N Phenylalanine Phe, F

Cysteine Cys, C Proline Pro, P

Glutamic acid Glu, E Serine Ser, S

Glycine Gly, G Tyrosine Tyr, Y

Glutamine Gln, Q Threonine Thr, T

Histidine His, H Tryptophan Trp, W

Isoleucine Ile, I Valine Val, V

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1. Introduction

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1. Introduction

1.1. Breast cancer

1.1.1. Epidemiology of breast cancer

According World Health Organization (WHO) estimates, noncommunicable diseases (NCDs), such as cardiovascular diseases and cancer, are the leading cause of mortality in the world. In 2016, cancer was the second leading cause of deaths from NCDs (9.0 million; 22% of all NCD deaths) in most countries of the world (1). Cancer incidence and mortality are rapidly increasing in the developed countries, mainly due to population growth and aging, but also to the increasing prevalence of some causes of cancer linked to socioeconomic development (2, 3).

The recent GLOBOCAN 2018 database, produced by the International Agency for Research on Cancer (IARC) and available from the Global Cancer Observatory (GCO) (4), provides estimates of the incidence and mortality of 36 types of cancer in 185 countries by age and sex (5). Accord- ing to GLOBOCAN, the incidence of cancer in Spain in 2018 was 270,363 diagnosed cases, and the estimated incidence for 2025 was 301,777 cases. Colorectal cancer (CRC) was the most com- monly diagnosed cancer in Spain (13.7% of all cancer deaths), closely followed by breast cancer (12.1%). Moreover, lung cancer is the leading cause of cancer deaths in Spain (20.2% of all cases), followed by CRC (14.7%), pancreatic cancer (6.4%) and breast cancer (5.6%) (5) (Figure 1).

Figure 1. Estimated incidence and mortality of the ten main cancers in Spain, by sex. Bar graph produced with data from GLOBOCAN 2018 (Adapted from Global Cancer Observatory from the IARC; http://gco.iarc.fr/).

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Female breast cancer is the most frequent cancer diagnosis in women worldwide and the second most common cancer overall. 2,088,849 cases were diagnosed worldwide in 2018, caus- ing 626,679 deaths. Moreover, breast cancer is the most frequent cancer diagnosis in women in Spain, with an estimated 8% probability of developing breast cancer (6): of all cases of cancer in women in 2018, 38.7% (32,825 cases) were breast carcinomas, and accounted for 14.4% of all deaths due to cancer (6,421 cases) (5) (Figure 1). Although the incidence of breast cancer is rising, the early detection strategies and the advances in molecular diagnosis and therapeutics have led to a reduction in mortality and an increase in the 5-year survival rate to over 75% (6).

1.1.2. Histological subtypes of breast cancer

Breast cancer is a heterogeneous disease with a variable prognosis, depending on various histological and molecular characteristics that influence tumor behavior and determine the se- lection of the treatment provided to the patient (7). Most breast tumors are adenocarcinomas, which start as ductal carcinomas in situ (DCISs), or, less frequently, as lobular carcinomas in situ (LCISs) (Figure 2). 80% of invasive breast cancers spread into surrounding breast tissue as inva- sive ductal carcinomas (IDCs), also called not otherwise specified (NOS), and 10% of them spread as invasive lobular carcinomas (ILCs). The less common subtypes include tubular, cribriform, me- dullary, mucinous, neuroendocrine, papillary, micropapillary, apocrine, metaplastic, and inflam- matory carcinomas (8).

Figure 2. Breast adenocarcinomas originate in the glandular tissue. (From Ductal Carcinoma In Situ (DCIS) [A] and Lobular Carcinoma In Situ (LCIS) [B], The National Cancer Institute. Used with permission under Copyright © license from Terese Winslow LLC, 2012; National Institutes of Health (NIH); https://www.cancer.gov/).

A B

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According to the American Joint Committee on Cancer (AJCC), histological grade can be defined according to the Nottingham grading system, which is based on the quantification of three aspects of tumor differentiation: the percentage of tubule formation in the tumor, the degree of nuclear pleomorphism, and the mitotic count and rate (9). Tumor classification can be completed using the tumor, node, metastasis (TNM) staging classification system, by which tu- mor stage is assessed based on tumor size, regional lymph node affectation, and the presence of distant metastases. Breast cancer stage is determined based on the TNM classification, whereby the disease is considered to be early (Stage I and Stage II), locally advanced (Stage IIIA and Stage IIIB), or advanced or metastatic (Stage IIIC and Stage IV) (10). It is essential to classify the morphology, determine the histological grade and assess the clinical stage of the tumor to provide an initial diagnosis and prognosis of breast cancer, but these activities have a limited capacity to predict the response to treatment and the risk of long-term recurrence (11). Thus, morphological breast cancer subtypes can be further subdivided into classifications based on their molecular signatures (e.g., gene expression profiles and expression of protein biomarkers).

1.1.3. Molecular characterization of breast cancer

In recent decades, molecular classification of breast tumor subtypes based on the assess- ment of prognostic and predictive biomarkers has been decisive in determining the prognosis and treatment strategy (12). Prognostic factors are clinical or biological characteristics of the tumor that identify subgroups of untreated patients having different outcomes in terms of over- all survival (OS) and disease-free survival (DFS). However, predictive factors are clinical or bio- logical characteristics of the tumor that identify subgroups of treated patients with different outcomes as a consequence of such treatment (13).

Gene expression profiling has provided a useful approach to describe the taxonomy of breast carcinomas that has enabled tumors to be classified with respect to intrinsic molecular subtypes (14). The current molecular classification of breast cancer is based on the determina- tion of four prognostic and/or predictive biomarkers by immunohistochemistry (IHC) in human tumors: estrogen receptor (ER) and progesterone receptor (PR) (collectively known as hormone receptors, HRs), Human Growth Factor Receptor 2 (HER2) and the proliferation marker protein Ki-67. Accordingly, breast carcinomas are classified into four major molecular subtypes, Luminal A and Luminal B, basal-like, and HER2-positive (HER2+), which facilitate treatment discrimina- tion. As the list of molecular targets being evaluated continues to lengthen due to the molecular heterogeneity of the disease, breast cancer classification evolves year by year.

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The basal-like (mostly ER-negative, ER-) and HER2+ (mostly HER2-amplified and ER-) tumors had the shortest relapse-free survival and OS, whereas the luminal-type (ER-positive, ER+) sub- group generally had the best prognosis (14–17). Molecular characterization of breast cancer also defined a highly aggressive subtype with reduced therapeutic options called triple-negative breast cancer (TNBC) (ER-, PR-negative [PR-], HER2-negative [HER2-]) (18, 19). A claudin-low subtype has recently been defined, which exhibits its own molecular characteristics (20). Clinical designation by IHC and/or fluorescent in situ hybridization (FISH) can be used to identify breast cancer molecular subtypes, yet the classic pathological markers used in the clinic for tumor clas- sification do not fully correlate with the intrinsic molecular subtypes in a significant number of cases (21). Those cases should be therefore considered different and unique (22). According to this designation, all the intrinsic subtypes may be identified as types of HER2+ breast cancer and, conversely, HER2-overexpressing tumors may also be identified as types of HER2- tumors (23) (Figure 3).

Figure 3. Correspondence between immunohistochemical and molecular classification of breast cancer. (Adapted from Molecular and cellular heterogeneity in breast cancer: chal- lenges for personalized medicine, by Rivenbark, O’Connor and Coleman, 2013, under a Crea- tive Commons Attribution-NonCommercial-NoDerivatives 4.0 International license [CC BY-NC- ND 4.0] from Elsevier) (21).

The currently implemented microarray technologies allow the simultaneous analysis of can- cer-specific gene expression signatures associated with clinical outcomes. Several breast cancer multigene assays have emerged, such as Oncotype DX (Genomic Health), 50-gene prediction analysis of microarray (PAM50) (commercialized as Prosigna; NanoString Technologies), and MammaPrint (Agendia), which have led to improvements in diagnosis, prognosis and prediction of therapeutic responses (24). Although not approved by the US Food and Drug Administration (FDA), Oncotype DX is a widely used prognostic gene-expression signature in clinical practice.

The Prosigna and MammaPrint assays were approved by the FDA in 2013 and 2007, respectively, and by European Union regulators as a prognostic tool for predicting distant recurrence for early stage breast tumors (25–27).

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In summary, recent advances in molecular biology have allowed the identification of prog- nostic and predictive biomarkers in breast cancer, enabling the molecular subtyping of breast tumors and the selection of the most appropriate therapy for each subtype.

1.1.4. Role of HER2 as a breast cancer biomarker

The HER2 (HER2/neu, c-erbB-2) gene is located in chromosome 17, where it encodes a transmembrane tyrosine kinase receptor protein (28). HER2 belongs to the human epidermal growth factor (EGFR) or HER family of receptor tyrosine kinases (RTKs), which also includes EGFR (HER1, ERBB1), HER3 (ERBB3) and HER4 (ERBB4). These receptors are highly homologous, and consist of a cysteine-rich N-terminal extracellular domain (ECD) with a ligand-binding region, a transmembrane domain and a C-terminal intracellular domain (ICD) with tyrosine-kinase activ- ity. However, HER3 exhibits impaired kinase activity. Specific ligand binding leads to conforma- tional changes that are required for homodimerization or heterodimerization, and subsequent activation of the HER receptors (29). EGFR-specific ligands include transforming growth factor alpha (TGF-α), epidermal growth factor (EGF), epiregulin (EPG), betacellulin (BTC), amphiregulin (AREG), and heparin binding (HB)-EGF. HER3-specific ligands include neuregulin-1 (NRG-2) and neuregulin-2 (NRG-2), while neuregulin-3 (NRG-3) and neuregulin-4 (NRG-4) are HER4-specific ligands. So far, no ligand for the HER2 receptor has been identified, although the HER2 ECD exists in a constitutive open conformation in the absence of a ligand, inducing the spontaneous ho- modimerization and favoring the preference for HER2 as the dimerization partner of the other HER receptors. This thereby confers more stability on HER2 heterodimers than homodimers, and their signaling is more potent than that of other receptor combinations. Ligand binding re- sults in phosphorylation and activation of HER receptors, and their binding to many proteins initiates different downstream signaling pathways. HER2-mediated signaling is ultimately asso- ciated with cell proliferation, motility, invasiveness, resistance to apoptosis and angiogenesis (30, 31) (Figure 4).

HER transmembrane receptors are involved in cell–cell and cell–stroma communications, mainly through signal transduction induced by external ligands and subsequently propagated through phosphorylating or dephosphorylating transmembrane proteins and intracellular sig- naling intermediates. Some of them have kinase activity and signal propagation occurs thereby as the enzymatic activity of one protein activates or inhibits the enzymatic activity of the next protein in the pathway, ultimately affecting the transcription of various genes (32). The biologi- cal response is determined by the presence of regulators, the specific combination of ligand and receptor dimer components, and the diverse range of proteins that associate with the tyrosine

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phosphorylated receptors (33, 34). For instance, major pathways involved in HER2 downstream signal transduction include the phosphatidylinositol 3 kinase (PI3K)/Akt/mammalian target of rapamycin (mTOR) pathway, the Ras/mitogen-activated protein kinase (MAPK) pathway, and the Janus kinase (JAK)/signal transducer and activator of the transcription (STAT) pathway (Fig- ure 5) (30, 32). Consequently, HER2 amplification induces an increased activation of crucial sig- naling pathways that ultimately affect cell proliferation, survival, migration, and angiogenesis.

Figure 4. The HER receptor family and HER ligands. A. The figure shows the structure of the HER receptors, including the four domains within the ECD, the ICD with kinase activity and the extracellular ligands specific for each receptor. EGFR, HER3, and HER4 are shown in the un- liganded closed conformation. HER2 has no activating ligands and HER3 lacks a functional ty- rosine kinase domain. B. The conformational change associated with ligand binding is de- picted, and the formation of an allosteric kinase domain dimer. (Adapted from The Under- Appreciated Promiscuity of the Epidermal Growth Factor Receptor Family, by Kennedy et al., 2016, under a Creative Commons Attribution 4.0 International license [CC BY 4.0] by Frontiers) (31).

In the 1980s, HER2 gene amplification was described as an independent prognostic factor that is associated with a shorter DFS for patients with breast cancer (35, 36). Over 20% of inva- sive breast cancers exhibit HER2 amplification or HER2 overexpression, which enables self-suffi- ciency in growth signals and constitutive activation of growth factor signaling pathways, increas- ing cell proliferation capability and invasiveness. HER2+ breast cancer is more aggressive and is

A EGFR

B

HER2 HER3 HER4

No Tyrosine kinase Activity

Asymmetric kinase domain dimer Tyrosine kinase Domain

TGF-α EGF EPG BTC AREG HB-EGF

No known ligand Neu-1 EPG

HB-EGF Neu 1, 2, 3, 4

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associated with factors predicting poor clinical outcome (37). In addition, HER2 receptor status is a predictive marker of response to HER2-targeted treatments in all patients with breast cancer (30, 38). Thus, one of the main challenges of using HER2 receptor as a prognostic and predictive marker in breast cancer has been to establish a gold standard of HER2 status assessment in clin- ical practice that guarantees high degrees of reproducibility and reliability of the diagnoses.

Figure 5. HER2 signaling pathway. Receptor homodimerization or heterodimerization in- duces HER2 activation, triggering a variety of downstream signaling cascades. PI3K/Akt/mTOR are the best studied pathways activated by HER2. In addition, HER2 activation can activate the Ras/Raf, MEK, and JAK/STAT pathways. (Reused from Trastuzumab: updated mechanisms of action and resistance in breast cancer, by Vu T and Claret FX, 2012, under a Creative Commons Attribution-NonCommercial 3.0 Unported License [CC BY-NC 3.0] by Frontiers) (39).

HER-2 status in breast cancer is now widely and routinely tested for, mostly by IHC, to de- termine HER2 protein expression levels, and by fluorescent in situ hybridization (FISH) to deter- mine HER2 gene amplification levels. HER2 status should be assessed exclusively in the tumor component and requires the performance of the technique and the interpretation of the results to be standardized, according to the American Society of Clinical Oncology (ASCO) and the Col- lege of American Pathologists (CAP) guidelines, published in 2007 (40) and updated in 2013 (41).

In line with this, in 2009, the Spanish Society of Medical Oncology (SEOM) and the Spanish Soci- ety of Pathology (SEAP) determined the Spanish Recommendations for HER2 assessment in breast cancer (42). Appropriate identification of the HER2+ breast cancer subtype in clinical prac- tice significantly improved the treatment of this subset of patients, since amplification and/or overexpression of HER2 are associated with a considerable benefit from HER2-targeted therapy in breast cancer.

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1.2. Emerging drugs for HER2-targeted therapy in breast cancer

Since the 1990s, a variety of anti-HER2 directed therapies have been developed that, in combination with chemotherapy, have become the current therapeutic regimens for HER2+

breast cancer in early and advanced settings. Current anti-HER2 therapies include humanized monoclonal antibodies, tyrosine kinase inhibitors (TKIs), and antibody-drug conjugates (ADCs).

1.2.1. Monoclonal antibodies targeting HER2: trastuzumab

In 1995, Genentech developed the first HER2-targeted therapy, the humanized IgG1 mon- oclonal antibody trastuzumab (Herceptin®), which selectively binds to domain IV of HER2 ECD and blocks the formation of HER2–HER2 homodimers and ligand-independent heterodimers with other HER family members (43) (Figure 6). Analysis of clinical trials performed in patients with HER2+ metastatic breast cancer revealed that trastuzumab increased PFS and produced a greater overall response rate (RR) in HER2+ metastatic breast cancer patients who are receiving chemotherapy (44–46). When combined with chemotherapy for early-stage breast cancers, ne- oadjuvant treatment with trastuzumab significantly increases pCR rate (47). These results were further supported by the analysis of adjuvant trials including HERA, NSABP B-31, NCCTG N9831, and BCIRG-006, which showed improved DFS and OS for patients receiving trastuzumab in com- bination with chemotherapy (48–51). In 1998, the FDA approved trastuzumab in combination with chemotherapy for use in patients with metastatic HER2+ breast tumors, and HER2-status determination is considered an essential predictive variable for the selection of anti-HER2 ther- apy. Trastuzumab is currently an integral part of HER2+ breast cancer therapy from the early to the advanced stages of the disease. However, the initial success of trastuzumab was limited by the emergence of resistance phenotypes in HER2+ breast cancers. This is discussed in greater detail below.

1.2.2. Tyrosine kinase inhibitors (TKIs)

In recent years, more comprehensive analyses of molecular events occurring in HER2+

breast cancer cells have emerged (52), leading to the development of additional HER2-targeted therapies to complement trastuzumab activity. In line with this, lapatinib (Tykerb®, Glax- oSmithKline) is an oral reversible dual HER2 and EGFR TKI (53). Lapatinib was approved by the FDA in 2007 as a treatment in combination with capecitabine for HER2+ metastatic breast cancer patients who had progressed to first-line treatment with trastuzumab, after phase III trials re- vealed significantly higher PFS relative to capecitabine alone (54).

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Neratinib (Nerlynx®, Pfizer) is an oral irreversible TKI of HER1, HER2 and HER4 that was developed to overcome to initial anti-HER2 resistance by targeting the HER signaling pathway.

The NEfERT-T trial revealed that neratinib, in combination with taxanes, was very effective as a first-line treatment in the metastatic setting (55). Neratinib was approved in 2017 by the FDA as an additional adjuvant therapy to prevent recurrence in early-stage HER2+ breast cancer pa- tients who had received at least one year of trastuzumab therapy. Its approval was based on the preliminary analysis after a 2-year follow-up of the ExteNET phase III trial, which revealed signif- icantly better invasive-DFS (iDFS) after 12-months of neratinib administration compared with placebo after 1 year of trastuzumab-based adjuvant therapy (56). More recently, this was con- firmed by the 5-year analysis of the ExteNEt trial, although the effect on OS has not so far been analyzed (57).

1.2.3. Other monoclonal antibodies targeting HER2: pertuzumab

Advances in basic and translational research and clinical trials to identify new options for inhibiting HER2 and other HER receptors have been successful in improving cancer outcomes in HER2+ breast cancer patients. The humanized monoclonal antibody pertuzumab (Perjeta®, Genentech) is one of these additional HER2-targeted therapies. Pertuzumab binds to domain II of HER2 ECD, preventing the spontaneous formation of homodimers HER2–HER2 and the for- mation of heterodimers, mainly HER2–HER3 (58) (Figure 6). The combination with pertuzumab provides a mechanism of action that is complementary to trastuzumab due to the more potent blockade of HER signaling (59).

After Cortés et al. described that combination therapy with trastuzumab and pertuzumab showed a greater clinical benefit rate than trastuzumab monotherapy in HER2+ breast cancer patients who had progressed during trastuzumab therapy (60), the efficacy of complementing trastuzumab with pertuzumab has been analyzed in several studies. Analysis of the CLEOPATRA trial revealed better PFS and OS in HER2+ metastatic breast cancer patients treated with per- tuzumab, trastuzumab and chemotherapy than those yielded by either agent alone (61). As a consequence, since 2013, pertuzumab has been widely used in association with trastuzumab and chemotherapy for HER2+ breast cancer patients (62, 63). This regimen has also produced improved outcomes in the adjuvant and neoadjuvant settings, as revealed by the analysis of NeoSphere trial (improved pCR rate in the neoadjuvant setting) (64) and the APHINITY trial (im- proved iDFS in the adjuvant setting) (65). It is worth noting that pertuzumab may be offered as third-line treatment if the patient has not received it previously, according to the National

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Comprehensive Cancer Network (NCCN) Clinical Practice Guidelines in Oncology for Breast Can- cer (66).

Figure 6. The mechanism of action of pertuzumab and trastuzumab. Trastuzumab binds to the ECD IV of the HER2 receptor, blocking the spontaneous formation of homodimers and ligand-independent heterodimers. Pertuzumab binds to the ECD II of the HER2 receptor, blocking the formation of ligand-induced HER2 heterodimers. (Reused from Pertuzumab: Op- timizing HER2 Blockade by Metzger-Filho O, Winer EP and Krop I, 2013, under a Copyright © 2013 license, with permission from the American Association for Cancer Research) (58).

1.2.4. Antibody-drug conjugates (ADCs): T-DM1

The recently approved trastuzumab emtansine (T-DM1; Kadcyla®, Genentech) is an ADC that consists of trastuzumab conjugated to the microtubule inhibitor emtansine and is an opti- mal second-line treatment for advanced HER2+ breast cancer with superior OS and a better ad- verse event profile compared with the combination of lapatinib and capecitabine (67). The TDM4258g trial aimed to assess the safety and efficacy of T-DM1 in HER2+ metastatic breast cancer patients who had tumor progression after prior treatment with trastuzumab. Analysis of this trial highlighted the robust antitumor activity of T-DM1, and the higher RR in patients with higher HER2 expression levels (68). The phase III trials EMILIA and TR3RESA have shown that T- DM1 significantly improves PFS and OS in HER2+ early and metastatic patients that had previ- ously been treated with other anti-HER2-based regimens (69–72). Recently, primary results from the MARIANNE study revealed similar PFS and RR for T-DM1 with or without pertuzumab, and for trastuzumab with taxanes for first-line treatment in HER2+ advanced breast cancer patients, although an increased tolerability was described in the T-DM1 arms (73).

Currently, the treatment of choice for HER2+ breast cancer is based on the consideration of multiple factors, including the HR status of the tumor and previous exposure to treatments.

HR status mainly dictates the need to administer endocrine therapy for patients with HR-positive (HR+) tumors, while the combination of chemotherapy and HER2-directed therapy is

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recommended for HR+ and HR-negative (HR-) tumors (66). Treatment with both trastuzumab and pertuzumab is indicated for women with higher-risk, early-stage HER2+ tumors, beginning before or after surgery. In patients with advanced disease, previous exposure to therapies and possible resistance mechanisms that may have emerged from previous treatments are consid- ered. This need for individualized treatment makes treatment selection for HER2+ breast cancer particularly challenging in clinical practice, but allows rapid and personalized evolution of ther- apies targeting HER2+ breast cancers. However, the emergence of trastuzumab-resistant HER2+

breast cancers makes it crucial to understand the mechanisms of action and resistance to trastuzumab to enable us to develop new therapeutic strategies.

1.2.5. Mechanism of action of trastuzumab

As previously mentioned, the ECD of HER2 resembles a ligand-activated state and it can be blocked by selective trastuzumab binding, which impairs receptor homodimerization (43, 74).

Upon binding to HER2, the main mechanisms of action of trastuzumab include HER2 internaliza- tion and degradation through recruiting the E3 ubiquitin-protein ligase c-Cbl (CBL) to its docking site, Tyr1112, where CBL ubiquitinates HER2 and leads to its degradation (75). Trastuzumab also activates of the immune response via the antibody-dependent cell-mediated cytotoxicity (ADCC) (76), involving natural killer (NK) cells, neutrophils and macrophages. Blocking HER2 homodi- merization reduces activation of the HER2 tyrosine kinase domain and further downregulates the HER2 downstream signaling pathways, PI3K and MAPK (77). This reduces the activity of cel- lular processes mediated by the trastuzumab-downregulated pathways, such as trastuzumab- mediated PI3K inhibition, which causes an accumulation of the cyclin-dependent kinase inhibitor p27, leading to G1 cell cycle arrest and reduced cell proliferation (78).

1.2.6. Resistance to anti-HER2-targeted therapy

Despite the development and use of HER2-targeted therapeutics, resistance to trastuzumab remains a challenge in the clinical milieu. In terms of treatment resistance, we can differentiate primary and acquired forms.

Primary resistance is defined by the presence of molecular alterations at diagnosis that in- duce tumor cells to evade anti-HER2 therapy and to avoid the treatment effect (Figure 7B-C).

According to the intratumor heterogeneity and branched evolution hypothesis, primary re- sistant tumors can respond differently to treatments: 1) if all tumor cells within a tumor have a molecular alteration that confers resistance to therapy (monoclonal tumor), disease progression will be observed during therapy administration or shortly after treatment has finished (up to 6

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months); or 2) if only a small subpopulation of cells within a tumor exhibit primary resistance (polyclonal tumor), partial response to treatment may occur during exposure to the therapy or shortly after the end of treatment, by the elimination of sensitive cells and persistence of the resistant cells (79).

The acquired-resistance model is defined by the evolution of a primary tumor that is initially sensitive and responsive to treatment (as revealed by a reduced infiltrating tumor component);

yet new tumor clones with adapted molecular alterations emerge after prolonged exposure to treatment, which allow tumors to evade the mechanisms of action of anti-HER2 therapy, leading to relapse and non-response to treatment (Figure 7D-E) (79, 80).

Figure 7. Models of primary and acquired trastuzumab resistance. A. HER2+ breast cancer tumor sensitive to anti-HER2 treatment, exhibiting pCR after anti-HER2 therapy. B. Anti-HER2 therapy refractory tumor. In this model, HER2+ breast cancer tumor consists mainly of anti- HER2 primary resistant cells. There is progression during the treatment, as resistant cells con- tinue to expand upon treatment. C. Heterogeneous HER2+ breast tumor, consisting of sensi- tive cells and primary resistant cells, and exhibiting partial response to treatment and relapse.

D. Monoclonal HER2+ breast tumor exhibiting pCR after treatment and relapse due to acqui- sition of novel molecular alterations upon prolonged exposure to anti-HER2 treatment that confer tumor resistance to treatment. E. Heterogeneous primary HER2+ breast tumor, con- sisting of sensitive cells and primary resistant cells, exhibiting partial response to anti-HER2 treatment and relapse due to additional molecular alterations occurring upon prolonged ex- posure to anti-HER2 treatment and conferring acquired resistance to therapy (Adapted from Platinum-Sensitive Recurrence in Ovarian Cancer: The Role of Tumor Microenvironment, by

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Chien J et al., 2013, under a Creative Commons Attribution 3.0 Unported License [CC BY 3.0]

by Frontiers) (79).

In the context of HER2+ breast cancer, treatment with trastuzumab exhibits a 25% non- response rate in patients with early tumors due to intrinsic or primary resistance (81). Moreover, 70% of patients with metastatic disease whose tumors are initially responsive to trastuzumab eventually progress to therapy after several months of exposure to the drug due to acquired resistance (82). For these reasons, developing a more effective treatment of trastuzumab-re- sistant HER2+ breast cancer patients requires a deeper understanding of intratumor heteroge- neity and acquired resistance mechanisms, including by the identification of the molecular bi- omarkers that mediate these phenotypes.

Targeting novel biomarkers involved in resistance with different agents may allow reversion of trastuzumab resistance and is essential for managing patients with HER2+ breast cancer. Sev- eral mechanisms have been proposed to explain the acquisition of trastuzumab resistance in patients with HER2+ breast cancer (83). Major molecular adaptations that have been described as resistance mechanisms can be classified as those involving increased expression of HER lig- ands, modification at the receptor level, or constitutive activation of HER2-downstream signal- ing pathways. Moreover, the source of potential targetable molecular adaptations is increasing and more predictive biomarkers that can be used in directed therapy are being identified (84).

In recent years, evidence has emerged about the role of a range of signaling pathways and po- tential biomarkers of trastuzumab resistance that could be targeted, thereby boosting the effi- cacy of current anti-HER2 therapy in breast cancer.

1.2.6.1. Increased expression of ligands

Studies have shown that resistant cancer cells can reactivate the HER2 pathway by secret- ing HER-specific ligands or ligands of other families of RTKs as a compensatory signaling mecha- nism. For instance, overexpression of the HER3 ligand neuregulin was described as an important mechanism of resistance, inducing activation of HER2/HER3 dimerization and activating HER4 (85, 86). Moreover, increased IGF (IGF-R ligand) induces overactivation of the RAS/MAPK PI3K/Akt/mTOR signaling pathways, which mediates activation of proliferation and invasion pro- cesses upon HER2 receptor blockade (87).

1.2.6.2. Modification at the receptor level

Truncation of the ECD of HER2 by the A disintegrin and metalloprotease 10 (ADAM10) or by alternative initiation or translation of the mRNA-encoding HER2 produces a variant called

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p95HER2 which lacks ECD. The presence of this truncated form prevents binding of trastuzumab and blocking of tyrosine kinase activity, but is associated with the non-response to monoclonal antibodies and with a worse prognosis in HER2+ patients (88, 89).

Breast cancer genome sequencing has facilitated the identification of HER2-activating mu- tations in cancers that are found to be HER2- by IHC or FISH (90, 91). Activating HER2 mutations can induce oncogenic transformation of breast cancer cells in culture and breast tumors in xen- ograft models (91, 92). Moreover, HER2 mutations in exons 19-21 encoding tyrosine kinase do- mains and affecting fewer than 5% of patients were associated with worse prognosis and lapa- tinib resistance (93). Thus, these HER2 mutations can mediate resistance to anti-HER2 treat- ments and are proposed as emerging targets in various solid cancers (94, 95). There have been studies additionally reporting the role of a splice variant that eliminates exon 16 (Δ16HER2) in the HER2 ECD, which interacts directly with Src tyrosine kinase and confers resistance to trastuzumab in HER2+ breast cancer (96, 97).

Breast cancer cells can also overcome trastuzumab inhibition by crosstalk of HER2 with HER family receptors EGFR, HER3 and HER4 (98–100). In addition, several molecular mechanisms of anti-HER2-resistance involve signaling crosstalk via other receptors that mediate signaling by HER2-downstream pathways. There is evidence of activation of PI3K/Akt/mTOR signaling path- way by c-MET overexpression (101, 102), whereas increased levels of insulin-like growth factor 1 receptor (IGF1R) signaling (103, 104) and mucin-1 (MUC1-C) overexpression (105) were de- scribed as activating RAS/MAPK and PI3K/Akt/mTOR signaling pathways, contributing to trastuzumab resistance. Amplified FGFR signaling was associated with the acquisition of re- sistance to dual HER2-targeting with lapatinib and trastuzumab (106). Moreover, overexpression of the ephrin type-A receptor 2 (EPHA2) was associated with reduced DFS and OS in a cohort of HER2+ breast cancer patients. The same study described how cell lines that had acquired re- sistance to trastuzumab exhibited increased Src-mediated activation of EPHA2, leading to the amplification of PI3K/Akt and MAPK signaling (107).

1.2.6.3. Constitutive activation of HER2 downstream signaling pathways

Many molecular mechanisms involved in the constitutive modification of RAS/MAPK and PI3K/Akt/mTOR pathways can activate proliferation and invasion processes upon HER2 receptor blockade. One of the main alterations inducing this effect in HER2+ breast cancer is the loss of the phosphatidylinositol 3,4,5-trisphosphate 3-phosphatase and dual-specificity protein phos- phatase PTEN (PTEN), which induces constitutive activation of Akt, and blocks trastuzumab-me- diated cell-cycle arrest and inhibition of apoptosis (108–110). Mutations of PIK3CA that activate

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PI3K/Akt pathway have been associated with trastuzumab resistance (111, 112). PIK3CA is the gene that encodes the catalytic subunit of p100α of PI3K and is mutated in 26% of breast cancer cases (113).

In clinical practice, trastuzumab treatment is continued in patients beyond first-line disease progression, mainly due to its favorable safety profile (114). This, along with the heterogeneity of the disease, may favor the development of resistance mechanisms that involve different sig- naling pathways during therapy with trastuzumab in HER2+ breast cancers. Emerging evidence is revealing potential biomarkers of trastuzumab resistance that can be targeted, thereby im- proving the efficacy in of anti-HER2 breast cancer therapy. Among other signaling events, acti- vation of the major Hippo pathway downstream effectors has been strongly implicated in breast cancer development and progression, and, in more recently, linked to anti-HER2 drug resistance, as discussed in the next section.

1.3. Role of the major Hippo pathway downstream effectors in HER2+ breast cancer

The Hippo tumor suppressor pathway is an evolutionarily conserved signaling pathway that controls organ size and cells through the regulation of cell proliferation and apoptosis (115, 116).

It responds to various upstream regulators, including mechanical signals, cellular stress, extracellular signals, polarity, and cell adhesion contacts. These upstream regulators promote the activation of the Hippo kinase cascade, which consists of serine/threonine kinases mammalian STE20-like protein kinase 1/2 (MST1/MST2), the large tumor suppressors, LATS1 and LATS2, and the adaptor proteins Salvador homolog 1 (SAV1) and MOB kinase activators (MOB1A/MOB1B) (117). Major downstream effectors of the Hippo kinase cascade are the paralogs and transcriptional coactivators Yes-associated protein (YAP) and tafazzin (TAZ).

The Hippo kinase module is the main regulator of YAP/TAZ, which functions by phosphorylating and promoting either the cytoplasmic retention of YAP and TAZ via a 14-3-3 interaction, or the degradation of YAP/TAZ. When the Hippo pathway is active, the Hippo kinase cascade phosphorylates YAP/TAZ, which interacts with 14-3-3 proteins, resulting in cytoplasmic retention and protein degradation. However, when the Hippo pathway is inactive or negatively regulated, YAP/TAZ are dephosphorylated and translocate to the nucleus where they interact with transcriptional enhancer factors TEAD1–4. This induces transcription of various genes that combine modulation of different cellular processes, such as cell proliferation, differentiation, growth, and death (118, 119) (Figure 8). A known mechanism of negative regulation of the Hippo pathway involves the E3 ubiquitin-protein ligase Itchy homolog (ITCH), which mediates LATS1

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1. Introduction

ubiquitination and proteasomal degradation, leading to stabilization of dephosphorylated YAP/TAZ, and associating with tumorigenesis in several preclinical models including those of breast tumors (120, 121).

The critical role of major Hippo pathway downstream effectors under diverse physiological and pathological conditions, such as development, tissue homeostasis, and tumorigenesis, has been increasingly recognized (122, 123). It has been proposed that YAP promotes metastasis through its interaction with TEAD in melanoma and breast carcinoma (124), and formation of the YAP/TAZ-TEAD complex leads to transcription of tissue development and growth-promoting genes (122, 125, 126), while disrupting the interactions of the complex reduces cell proliferation (127). In summary, dysregulated signaling by the Hippo pathway has been reported in several cancer types such as breast, liver, lung, prostate, stomach, and colorectal tumors (123).

Figure 8. The core Hippo pathway. MST1/2 phosphorylates Sav, Lats1/2, and Mob; Lats1/2 phosphorylates YAP/TAZ; phosphorylated YAP/TAZ interacts with 14-3-3 proteins, resulting in cytoplasmic retention and protein degradation. However, when the Hippo pathway is inactive, YAP/TAZ are dephosphorylated and translocate to the nucleus, where they interact with tran- scription factors TEAD1–4. This induces transcription of genes that combine modulation of different cellular processes, such as cell proliferation, differentiation, growth, and death.

(Adapted from YAP and TAZ: a nexus for Hippo signaling and beyond by Hansen CG, et al. 2015, under a Copyright © 2015 license, with permission from Elsevier) (118).

Recent research has assessed the complexity of YAP/TAZ more comprehensively, identifying new upstream regulatory components and revealing their crosslinks with transmembrane receptors and proteins involved in different signaling pathways (Figure 9), such

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