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.

13. Roy DM, Walsh LA, Chan TA. Driver mutations of cancer epigenomes. Protein Cell 2014;5:265-96.

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.

22. Wang JC, Dick JE. Cancer stem cells: lessons from leukemia. Trends Cell Biol 2005;15:494-501.

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.

75. Ogino S, Nowak JA, Hamada T, Milner DA Jr, Nishihara R. Insights into pathogenic interactions among environment, host, and tumor at the crossroads of molecular pathology and epidemiology. Annu Rev Pathol 2019;14:83-103.

Cancer Drug Resistance
ISSN 2578-532X (Online)
Follow Us


All published articles will preserved here permanently:


All published articles will preserved here permanently: