Genomic profiling of breast cancers

Current Opinion in Obstetrics and Gynecology

Volumn 27, Issue 1, 2015, Pages 34-39

  Curtis, Christina ^a  

^a STANFORD UNIVERSITY SCHOOL OF MEDICINE   (United States)

Author keywords

breast cancer; genomics; heterogeneity; molecular subtype; somatic alteration

Indexed keywords

BIOLOGICAL MARKER; EPIDERMAL GROWTH FACTOR RECEPTOR 2; TUMOR MARKER;

BREAST CANCER; BREAST TUMOR; CANCER PROGNOSIS; CIRCULATING TUMOR CELL; GENETIC HETEROGENEITY; HIGH THROUGHPUT SCREENING; HUMAN; PRIORITY JOURNAL; REVIEW; TREATMENT RESPONSE; BREAST NEOPLASMS; DNA SEQUENCE; FEMALE; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION; GENETICS; HIGH THROUGHPUT SEQUENCING; MOLECULARLY TARGETED THERAPY; PREDICTIVE VALUE; PROCEDURES; PROGNOSIS; TRENDS;

BIOMARKERS, TUMOR; BREAST NEOPLASMS; FEMALE; GENE EXPRESSION PROFILING; GENE EXPRESSION REGULATION, NEOPLASTIC; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; HUMANS; MOLECULAR TARGETED THERAPY; PREDICTIVE VALUE OF TESTS; PROGNOSIS; SEQUENCE ANALYSIS, DNA;

EID: 84920766414     PISSN: 1040872X     EISSN: 1473656X     Source Type: Journal    
DOI: 10.1097/GCO.0000000000000145     Document Type: Review

References (42)

1. King CR, Kraus MH, Aaronson SA. Amplification of a novel v-erbB-related gene in a human mammary carcinoma. Science 1985; 229:974-976.
2. Slamon DJ, Godolphin W, Jones LA, et al. Studies of the HER-2/neu protooncogene in human breast and ovarian cancer. Science 1989; 244:707-712.
3. Banerji S, Cibulskis K, Rangel-Escareno C, et al. Sequence analysis of mutations and translocations across breast cancer subtypes. Nature 2012; 486:405-409.
4. Curtis C, Shah SP, Chin SF, et al. The genomic and transcriptomic architecture of 2000 breast tumours reveals novel subgroups. Nature 2012; 486:346-352.
5. Ellis MJ, Ding L, Shen D, et al. Whole-genome analysis informs breast cancer response to aromatase inhibition. Nature 2012; 486:353-360.
6. Nik-Zainal S, Alexandrov LB, Wedge DC, et al. Mutational processes molding the genomes of 21 breast cancers. Cell 2012; 149:979-993.
7. Nik-Zainal S, Van Loo P, Wedge DC, et al. The life history of 21 breast cancers. Cell 2012; 149:994-1007.
8. Shah SP, Roth A, Goya R, et al. The clonal and mutational evolution spectrum of primary triple-negative breast cancers. Nature 2012; 486:395-399.
9. Stephens PJ, Tarpey PS, Davies H, et al. The landscape of cancer genes and mutational processes in breast cancer. Nature 2012; 486:400-404.
10. Cancer Genome Atlas Network. Comprehensive molecular portraits of human breast tumours. Nature 2012; 490:61-70.
11. Bose R, Kavuri SM, Searleman AC, et al. Activating HER2 mutations in HER2 gene amplification negative breast cancer. Cancer Discov 2013; 3:224-237.
12. Kadoch C, Hargreaves DC, Hodges C, et al. Proteomic and bioinformatic analysis of mammalian SWI/SNF complexes identifies extensive roles in human malignancy. Nat Genet 2013; 45:592-601.
13. Wiegand KC, Shah SP, Al-Agha OM, et al. ARID1A mutations in endometriosis- associated ovarian carcinomas. N Engl J Med 2010; 363:1532-1543.
14. WiegandKC, Lee AF, Al-AghaOM, et al. Loss ofBAF250a (ARID1A) is frequent in high-grade endometrial carcinomas. J Pathol 2011; 224:328-333.
15. Lichner Z, Scorilas A, White NMA, et al. The chromatin remodeling gene ARID1A is a new prognostic marker in clear cell renal cell carcinoma. Am J Pathol 2013; 182:1163-1170.
16. VireE, Curtis C, Davalos V, et al. The breast cancer oncogene EMSY represses transcription of antimetastatic microRNAmiR-31. MolCell 2014; 53:806-818.
17. Yamamoto S, Wu Z, Russnes HG, et al. JARID1B is a luminal lineage-driving oncogene in breast cancer. Cancer Cell 2014; 25:762-777.
18. Perou CM, Sorlie T, Eisen MB, et al. Molecular portraits of human breast tumours. Nature 2000; 406:747-752.
19. Chia SK, Bramwell VH, Tu D, et al. A 50-gene intrinsic subtype classifier for prognosis and prediction of benefit from adjuvant tamoxifen. Clin Cancer Res 2012; 18:4465-4472.
20. Dawson S-J, Rueda OM, Aparicio S, Caldas C. A new genome-driven integrated classification of breast cancer and its implications. EMBO J 2013; 32:617-628.
21. Ali H, Rueda OM, Chin S-F, et al. Genome-driven integrated classification of breast cancer validated in over 7500 samples. Genome Biol 2014; 15:431.
22. Chen X, Li J, Gray WH, et al. TNBC type: a subtyping tool for triple-negative breast cancer. Cancer Inform 2012; 11:147-156.
23. Lehmann BD, Bauer JA, Chen X, et al. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest 2011; 121:2750-2767.
24. Mayer IA, Abramson VG, Lehmann BD, Pietenpol JA. New strategies for triplenegative breast cancer: deciphering the heterogeneity. Clin Cancer Res 2014; 20:782-790.
25. Yu K-D, Zhu R, Zhan M, et al. Identification of prognosis-relevant subgroups in patients with chemoresistant triple-negative breast cancer. Clin Cancer Res 2013; 19:2723-2733.
26. Balko JM, Giltnane JM, Wang K, et al. Molecular profiling of the residual disease of triple-negative breast cancers after neoadjuvant chemotherapy identifies actionable therapeutic targets. Cancer Discov 2014; 4:232-245.
27. Almendro V, Cheng Y-K, Randles A, et al. Inference of tumor evolution during chemotherapy by computational modeling and in situ analysis of genetic and phenotypic cellular diversity. Cell Rep 2014; 6:514-527.
28. Almendro V, Kim HJ, Cheng Y-K, et al. Genetic and phenotypic diversity in breast tumor metastases. Cancer Res 2014; 74:1338-1348.
29. Wang Y, Waters J, Leung ML, et al. Clonal evolution in breast cancer revealed by single nucleus genome sequencing. Nature 2014; 512:155-160.
30. Crockford A, Jamal-Hanjani M, Hicks J, Swanton C. Implications of intratumour heterogeneity for treatment stratification. J Pathol 2014; 232:264-273.
31. Parker JS, Mullins M, Cheang MCU, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol 2009; 27:1160-1167.
32. Silwal-Pandit L, Vollan HKM, Chin S-F, et al. TP53 mutation spectrum in breast cancer is subtype specific and has distinct prognostic relevance. Clin Cancer Res 2014; 20:3569-3580.
33. Russnes HG, Vollan HKM, Lingjaerde OC, et al. Genomic architecture characterizes tumor progression paths and fate in breast cancer patients. Sci Transl Med 2010; 2:38ra47.
34. Vollan HKM, Rueda OM, Chin S-F, et al. A tumor DNA complex aberration index is an independent predictor of survival in breast and ovarian cancer. Mol Oncol 2014. pii: S1574-7891(14)00174-4.
35. Abdel-Fatah TMA, Russell R, Albarakati N, et al. Genomic and protein expression analysis reveals flap endonuclease 1 (FEN1) as a key biomarker in breast and ovarian cancer. Mol Oncol 2014; 8:1326-1338.
36. De Mattos-Arruda L, Cortes J, Santarpia L, et al. Circulating tumour cells and cell-free DNA as tools for managing breast cancer. Nat Rev Clin Oncol 2013; 10:377-389.
37. Bettegowda C, Sausen M, Leary RJ, et al. Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci Transl Med 2014; 6:224ra24.
38. Newman AM, Bratman SV, To J, et al. An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage. NatMed 2014; 20:548-554.
39. Dawson S-J, Tsui DWY, Murtaza M, et al. Analysis of circulating tumor DNA to monitor metastatic breast cancer. N Engl J Med 2013; 368:1199-1209.
40. Murtaza M, Dawson S-J, Tsui DWY, et al. Noninvasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature 2013; 497:108-112.
41. Wallwiener M, Hartkopf AD, Baccelli I, et al. The prognostic impact of circulating tumor cells in subtypes of metastatic breast cancer. Breast Cancer Res Treat 2013; 137:503-510.
42. Bidard F-C, Peeters DJ, Fehm T, et al. Clinical validity of circulating tumour cells in patients with metastatic breast cancer: a pooled analysis of individual patient data. Lancet Oncol 2014; 15:406-414.