REFERENCES
1. Belizario JE. Cancer risks linked to the bad luck hypothesis and epigenomic mutational signatures. Epigenomes 2018;2:13.
2. Lawrence MS, Stojanov P, Mermel CH, Robinson JT, Garraway LA, et al. Discovery and saturation analysis of cancer genes across 21 tumour types. Nature 2014;505:495-501.
3. Vasaikar SV, Straub P, Wang J, Zhang B. LinkedOmics: analyzing multi-omics data within and across 32 cancer types. Nucleic Acids Res 2018;46:D956-63.
4. Kim YA, Cho DY, Przytycka TM. Understanding genotype - phenotype effects in cancer via network approaches. PLoS Comput Biol 2016;12:e1004747.
5. Barretina J, Caponigro G, Stransky N, Venkatesan K, Margolin AA, et al. The Cancer Cell Line Encyclopedia enables predictive modeling of anticancer drug sensitivity. Nature 2012;483:603-7.
6. Garnett MJ, Edelman J, Heidorn SJ, Greenman CD, Dastur A, et al. Systematic identification of genomic markers of drug sensitivity in cancer cells. Nature 2012;483:570-5.
7. Klijn C, Durinck S, Stawiski EW, Haverty PM, Jiang Z, et al. A comprehensive transcriptional portrait of human cancer cell lines. Nat Biotechnol 2015;33:306-12.
8. Campbell J, Ryan CJ, Brough R, Bajrami I, Pemberton HN, et al. Large-scale profiling of kinase dependencies in cancer cell lines. Cell Rep ;14:2490-501.
9. Polyak K, Haviv I, Campbell IG. Co-evolution of tumor cells and their microenvironment. Trends Genet 2008;25:30-8.
10. McGranahan N, Swanton C. Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. Cancer Cell 2015;27:15-26.
11. Belizario JE, Sangiuliano BA, Perez-Sosa M, Neyra JM, Moreira DF. Using pharmacogenomic databases for discovering patient-target genes and small molecule candidates to cancer therapy. Front Pharmacol 2016;7:312.
12. Feinberg AP, Koldobskiy MA, Göndör A. Epigenetic modulators, modifiers and mediators in cancer aetiology and progression. Nat Rev Genet 2016;17:284-99.
14. Jeggo PA, Pearl LH, Carr AM. DNA repair, genome stability and cancer: A historical perspective. Nat Rev Cancer 2016;16:35-42.
15. Stirzaker C, Taberlay PC, Statham AL, Clark SJ. Mining cancer methylomes: prospects and challenges. Trends Genet 2014;30:75-84.
16. Yao L, Shen H, Laird PW, Farnham PJ, Berman BP. Inferring regulatory element landscapes and transcription factor networks from cancer methylomes. Genome Biol 2015;16:105.
17. Widschwendter M, Jones A, Evans I, Reisel D, Dillner J, et al. Epigenome-based cancer risk prediction: rationale, opportunities and challenges. Nat Rev Clin Oncol 2018;15:292-309.
18. Mahoney KM, Rennert PD, Freeman GJ. Combination cancer immunotherapy and new immunomodulatory targets. Nat Rev Drug Discov 2015;14:561-84.
19. Blank CU, Haanen JB, Ribas A, Schumacher TN. Cancer Immunology. The cancer Immunogram. Science 2016;352:658-60.
20. Dumont N, Liu B, DeFilippis RA, Chang H, Rabban JT. Breast fibroblasts modulate early dissemination, tumorigenesis, and metastasis through alteration of extracellular matrix characteristics. Neoplasia 2013;15:249.
21. Thorsson V, Gibbs DL, Brown SD, Wolf D, Bortone DS, et al. The immune landscape of cancer. Immunity 2018;48:812-30.
23. Park SY, Lee HE, Li H, Shipitsin M, Gelman R, et al. Heterogeneity for stem cell-related markers according to tumor subtype and histologic stage in breast cancer. Clin Cancer Res 2010;16:876-87.
24. Kalluri R, Weinberg RA. The basics of epithelial-mesenchymal transition. J Clin Invest 2009;119:1420-8.
25. Aparicio S, Mardis E. Tumor heterogeneity: next-generation sequencing enhances the view from pathologist’s microscope. Genome Biol 2014;15:463.
26. Laskin J, Jones S, Aparicio S, Chia S, Ch’ng C, et al. Lessons learned from the application of whole-genome analysis to the treatment of patients with advanced cancers. Cold Spring Harb Mol Case Stud 2015;1:a000570.
27. Mertins P, Mani DR, Ruggles KV, Gillette MA, Clauser KR, et al. Proteogenomics connects somatic mutations to signaling in breast cancer. Nature 2016;534:55-62.
28. Guerin M, Gonçalves A, Toiron Y, Baudelet E, Audebert S, et al. How may targeted proteomics complement genomic data in breast cancer? Expert Rev Proteomics 2017;14:43-54.
29. Shipitsin M, Campbell LL, Argani P, Weremowicz S, Bloushtain-Qimron N, et al. Molecular definition of breast tumor heterogeneity. Cancer Cell 2007;11:259-73.
30. Reis-Filho J, Pusztai L. Gene expression profiling in breast cancer: classification, prognostication, and prediction. Lancet 2011;378:1812-23.
31. Gudjonsson T, Adriance MC, Sternlicht MD, Petersen OW, Bissel MJ. Myoepithelial cells: their origin and function in breast morphogenesis and neoplasia. J Mammary Gland Biol Neoplasia 2005;10:261-72.
32. Stephens PJ, Tarpey PS, Davies H, Van Loo P, Greenman C, et al. The landscape of cancer genes and mutational processes in breast cancer. Nature 2012;486:400-4.
33. Sorlie T, Tibshirani R, Parker J, Hastie H, Marron JS, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci U S A 2003;100:8418-23.
34. Curtis CSP, Shah SF, Chin G, Turashvili OM, Rueda MJ, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature 2012;486:346-52.
35. Perou CM, Sørlie T, Eisen MB, van de Rijn M, Jeffrey SS, et al. Molecular portraits of human breast tumours. Nature 2000;406:747-52.
36. De Mattos-Arruda L, Ng CKY, Piscuoglio S, Gonzalez-Cao M, Lim RS, et al. Genetic heterogeneity and actionable mutations in HER2-positive primary breast cancers and their brain metastases. Oncotarget 2018;9:20617-30.
37. Turner NC, Reis-Filho JS. Basal-like breast cancer and the BRCA1 phenotype. Oncogene 2006;25:5846-53.
38. Gonzalez-Angulo AM, Morales-Vasquez F, Hortobagyi GN. Overview of resistance to systemic therapy in patients with breast cancer. Adv Exp Med Biol 2007;608:1-22.
39. Razavi P, Chang MT, Xu G, Bandlamudi C, Ross DS, et al. The genomic landscape of endocrine-resistant advanced breast cancers. Cancer Cell 2018;34:427-38.
40. Arteaga CL, Sliwkowski MX, Osborne CK, Perez EA, Puglisi F, et al. Treatment of HER2-positive breast cancer: current status and future perspectives. Nat Rev Clin Oncol 2012;9:16-32.
41. Pareja F, Reis-Filho JS. Triple-negative breast cancers - a panoply of cancer types. Nat Rev Clin Oncol 2018;15:347-8.
42. Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature 2012;490:61-70.
43. Alexandrov LB, Nik-Zainal S, Wedge DC, Aparicio AS, Behjati S, et al. Signatures of mutational processes in human cancer. Nature 2013;500:415-21.
44. Mundim FG, Pasini FS, Nonogaki S, Rocha RM, Soares FA, et al. Breast carcinoma-associated fibroblasts share similar biomarker profiles in matched lymph node metastasis. Appl Immunohistochem Mol Morphol 2016;24:712-20.
45. Harris LN, Ismaila N, McShane LM, Andre F, Collyar DE, et al. Use of biomarkers to guide decisions on adjuvant systemic therapy for women with early-stage Invasive breast cancer: American Society of Clinical Oncology Clinical Practice Guideline. J Clin Oncol 2016;34:1134-50.
46. Weaver DL, Ashikaga T, Krag DN, Skelly JM, Anderson SJ, et al. Effect of occult metastases on survival in node-negative breast cancer. N Engl J Med 2011;364:412-21.
47. Liu MC, Pitcher BN, Mardis ER, Davies SR, Friedman PN, et al. PAM50 gene signatures and breast cancer prognosis with adjuvant anthracycline- and taxane-based chemotherapy: correlative analysis of C9741 (Alliance). NPJ Breast Cancer 2016;2:15023.
48. Li WX, He K, Tang L, Dai SX, Li GH, et al. Comprehensive tissue-specific gene set enrichment analysis and transcription factor analysis of breast cancer by integrating 14 gene expression datasets. Oncotarget 2017;8:6775-86.
49. Bancovik J, Moreira D, Porter D, Carrasco D, Yao J, et al. Dermcidin exerts its oncogenic effects in breast cancer via modulation ERBB signaling. BMC Cancer 2015;15:70.
50. Wilhelm M, Schlegl J, Hahne H, Gholami AM, Lieberenz M, et al. Mass-spectrometry-based draft of the human proteome. Nature 2014;509:582-7.
51. Scaltriti M, Nuciforo P, Bradbury I, Sperinde J, Agbor-Tarh D, et al. High HER2 expression correlates with response to the combination of lapatinib and trastuzumab. J. Clin Cancer Res 2015;21:569-76.
52. Kirouac DC, Du J, Lahdenranta J, Onsum MD, Nielsen UB, et al. HER2+ cancer cell dependence on PI3K vs. MAPK signaling axes is determined by expression of EGFR, ERBB3 and CDKN1B. PLoS Comput Biol 2016;12:e1004827.
53. Osmanbeyoglu HU, Pelossof R, Bromberg JF, Leslie CS. Linking signaling pathways to transcriptional programs in breast cancer. Genome Res 2014;24:1869-80.
54. Osmanbeyoglu HU, Toska E, Chan C, Baselga J, Leslie CS. Pancancer modelling predicts the context-specific impact of somatic mutations on transcriptional programs. Nature Commun 2017;8:14249.
55. Fackler MJ, Umbricht CB, Williams D, Argani P, Cruz LA, et al. Genome-wide methylation analysis identifies genes specific to breast cancer hormone receptor status and risk of recurrence. Cancer Res 2011;71:6195-207.
56. Su Y, Subedee A, Bloushtain-Qimron N, Savova V, Krzystanek M, et al. Somatic cell fusions reveal extensive heterogeneity in basal-like breast cancer. Cell Rep 2015;11:1549-63.
57. Droog M, Mensink M, Zwart W. The estrogen receptor α-cistrome beyond breast cancer. Mol Endocrinol 2016;30:1046-58.
58. Mei S, Meyer CA, Zheng R, Qin Q, Wu Q, et al. Cistrome Cancer: a web resource for integrative gene regulation modeling in cancer. Cancer Res 2017;77:19-22.
59. Fleischer T, Tekpli X, Mathelier A, Wang S, Nebdal D, et al. DNA methylation at enhancers identifies distinct breast cancer lineages. Nat Commun 2017;8:1379.
60. Garrido-Castro AC, Goel S. CDK4/6 Inhibition in breast cancer: mechanisms of response and treatment failure. Curr Breast Cancer Rep 2017;9:26-33.
61. Goel S, DeCristo MJ, Watt AC, BrinJones H, Sceneay J, et al. CDK4/6 inhibition triggers anti-tumour immunity. Nature 2017;548:471-5.
62. Fiegl H, Millinger S, Goebel G, Müller-Holzner E, Marth C, et al. Breast cancer DNA methylation profiles in cancer cells and tumor stroma: association with HER-2/neu status in primary breast cancer. Cancer Res 2006;66:29-33.
63. Costa A, Kieffer Y, Scholer-Dahirel A, Pelon F, Bourachot B, et al. Fibroblast heterogeneity and immunosuppressive environment in human breast cancer. Cancer Cell 2018;33:463-79.
64. Force J, Leal JHS, McArthur HL. Checkpoint blockade strategies in the treatment of breast cancer: where we are and where we are heading. Curr Treat Options Oncol 2019;20:35.
65. Mori H, Kubo M, Yamaguchi R, Nishimura R, Osako T, et al. The combination of PD-L1 expression and decreased tumor-infiltrating lymphocytes is associated with a poor prognosis in triple-negative breast cancer. Oncotarget 2017;8:15584-92.
66. Yeong J, Lim JCT, Lee B, Li H, Ong CCH, et al. Prognostic value of CD8+ PD-1+ immune infiltrates and PDCD1 gene expression in triple negative breast cancer. J Immunother Cancer 2019;7:34.
67. Dzutsev A, Badger JH, Perez-Chanona E, Roy S, Salcedo R, et al. Microbes and cancer. Annu Rev Immunol 2017;35:199-228.
68. Thompson KJ, Ingle JN, Tang X, Chia N, Jeraldo PR, et al. A comprehensive analysis of breast cancer microbiota and host gene expression. PLoS One 2017;12:e0188873.
69. Routy B, Le Chatelier E, Derosa L, Duong CPM, Alou MT, et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 2018;359:91-7.
70. D’Abreo N, Adams S. Immune-checkpoint inhibition for metastatic triple-negative breast cancer: safety first? Nat Rev Clin Oncol 2019;16:399-400.
71. Rojas K, Stuckey A. Breast cancer epidemiology and risk factors. Clin Obstet Gynecol 2016;59:651-72.
72. Safe S, Li X. Endocrine disruption: relevance of experimental studies in female animals to human studies. Curr Opin Toxicol 2017;3:12-9.
73. Reid G. Can breast microbiota provide protective effects against cancer? Future Microbiol 2016;11:987-99.
74. Hamada T, Keum N, Nishihara R, Ogino S. Molecular pathological epidemiology: new developing frontiers of big data science to study etiologies and pathogenesis. J Gastroenterol 2017;52:265-75.
