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Molecular Classification of Breast Cancer

  • Maria Vidal
  • Laia Paré
  • Aleix PratEmail author
Chapter

Abstract

Breast cancer is a heterogeneous disease in terms of histology, therapeutic response, dissemination patterns to distant sites, and patient outcomes. To date, molecular characterization studies have started to elucidate the biology behind this heterogeneity. For example, 15 years of studies based on global gene expression analyses have helped identify 4 main intrinsic molecular subtypes of breast cancer (Luminal A, Luminal B, HER2-enriched, and basal-like). More recently, The Cancer Genome Atlas (TCGA) breast cancer project has further characterized this disease from a molecular perspective and provided important insights. In this chapter, we will describe the main molecular features of the intrinsic molecular subtypes and discuss how the combination of standard clinical–pathological markers with the information provided by these molecular entities might help further understand the biological complexity of this disease, increase the efficacy of current and novel therapies, and ultimately improve outcomes for breast cancer patients.

Keywords

Breast cancer Subtype PAM50 Gene expression Luminal A Luminal B HER2-enriched Basal-like Claudin-low Mutations PI3KCA Estrogen receptor 

Abbreviations

ER

Estrogen receptor

PR

Progesterone receptor

HER2

Human epidermal growth factor 2

IHC

Immunohistochemistry

5NP

5 Negative Profile

TN

Triple-negative

pCR

Pathologic complete response

qRT-PCR

Quantitative reverse transcriptase polymerase chain reaction

CNAs

Copy number aberrations

CDH1

E-cadherin

ILC

Invasive lobular carcinoma

IDC

Ductal

TCGA

The Cancer Genome Atlas

METABRIC

Molecular Taxonomy of Breast Cancer International Consortium

BL1

Basal-like 1

BL2

Basal-like 2

IM

Immunomodulatory

M

Mesenchymal

MSL

Mesenchymal stem-like

LAR

Luminal androgen receptor

BLIS

Basal-like immune-suppressed

BLIA

Basal-like immune-activated

IntClust

Integrative cluster

EMT

Epithelial-to-mesenchymal

References

  1. 1.
    La Vecchia C, Bosetti C, Lucchini F, Bertuccio P, Negri E, Boyle P, et al. Cancer mortality in Europe, 2000–2004, and an overview of trends since 1975. Ann Oncol. 2010;21(6):1323–60.PubMedCrossRefGoogle Scholar
  2. 2.
    Perou CM, Sorlie T, Eisen MB, van de Rijn M, Jeffrey SS, Rees CA, et al. Molecular portraits of human breast tumours. Nature. 2000;406(6797):747–52.PubMedCrossRefGoogle Scholar
  3. 3.
    Prat A, Perou CM. Deconstructing the molecular portraits of breast cancer. Mol Oncol. 2011;5(1):5–23.PubMedCrossRefGoogle Scholar
  4. 4.
    Prat A, Parker JS, Fan C, Perou CM. PAM50 assay and the three-gene model for identifying the major and clinically relevant molecular subtypes of breast cancer. Breast Cancer Res Treat. 2012;135(1):301–6.PubMedPubMedCentralCrossRefGoogle Scholar
  5. 5.
    Prat A, Parker JS, Karginova O, Fan C, Livasy C, Herschkowitz JI, et al. Phenotypic and molecular characterization of the claudin-low intrinsic subtype of breast cancer. Breast Cancer Res. 2010;12(5):R68.PubMedPubMedCentralCrossRefGoogle Scholar
  6. 6.
    Cancer Genome Atlas. N. Comprehensive molecular portraits of human breast tumours. Nature. 2012;490(7418):61–70.CrossRefGoogle Scholar
  7. 7.
    Sorlie T, Perou CM, Tibshirani R, Aas T, Geisler S, Johnsen H, et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci USA. 2001;98(19):10869–74.PubMedPubMedCentralCrossRefGoogle Scholar
  8. 8.
    Parker JS, Mullins M, Cheang MC, Leung S, Voduc D, Vickery T, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009;27(8):1160–7.PubMedPubMedCentralCrossRefGoogle Scholar
  9. 9.
    Liu S, Chapman JA, Burnell MJ, Levine MN, Pritchard KI, Whelan TJ, et al. Prognostic and predictive investigation of PAM50 intrinsic subtypes in the NCIC CTG MA.21 phase III chemotherapy trial. Breast Cancer Res Treat. 2015;149(2):439–48.PubMedCrossRefGoogle Scholar
  10. 10.
    Gnant M, Filipits M, Greil R, Stoeger H, Rudas M, Bago-Horvath Z, et al. Predicting distant recurrence in receptor-positive breast cancer patients with limited clinicopathological risk: using the PAM50 risk of recurrence score in 1478 postmenopausal patients of the ABCSG-8 trial treated with adjuvant endocrine therapy alone. Ann Oncol. 2014;25(2):339–45.PubMedCrossRefGoogle Scholar
  11. 11.
    Dowsett M, Sestak I, Lopez-Knowles E, Sidhu K, Dunbier AK, Cowens JW, et al. Comparison of PAM50 risk of recurrence score with oncotype DX and IHC4 for predicting risk of distant recurrence after endocrine therapy. J Clin Oncol. 2013;31(22):2783–90.PubMedCrossRefGoogle Scholar
  12. 12.
    Caan BJ, Sweeney C, Habel LA, Kwan ML, Kroenke CH, Weltzien EK, et al. Intrinsic subtypes from the PAM50 gene expression assay in a population-based breast cancer survivor cohort: prognostication of short- and long-term outcomes. Cancer Epidemiol Biomarkers Prev. 2014;23(5):725–34.PubMedPubMedCentralCrossRefGoogle Scholar
  13. 13.
    Sestak I, Cuzick J, Dowsett M, Lopez-Knowles E, Filipits M, Dubsky P, et al. Prediction of late distant recurrence after 5 years of endocrine treatment: a combined analysis of patients from the Austrian breast and colorectal cancer study group 8 and arimidex, tamoxifen alone or in combination randomized trials using the PAM50 risk of recurrence score. J Clin Oncol. 2015;33(8):916–22.PubMedCrossRefGoogle Scholar
  14. 14.
    Prat A, Galván P, Jimenez B, Buckingham W, Jeiranian HA, Schaper C, et al. Prediction of response to neoadjuvant chemotherapy using core needle biopsy samples with the Prosigna assay. Clin Cancer Res. 2016;22(3):560–6.PubMedCrossRefGoogle Scholar
  15. 15.
    Martin M, Prat A, Rodriguez-Lescure A, Caballero R, Ebbert MT, Munarriz B, et al. PAM50 proliferation score as a predictor of weekly paclitaxel benefit in breast cancer. Breast Cancer Res Treat. 2013;138(2):457–66.PubMedPubMedCentralCrossRefGoogle Scholar
  16. 16.
    Martín M, González-Rivera M, Morales S, de la Haba-Rodriguez J, González-Cortijo L, Manso L, et al. Prospective study of the impact of the Prosigna assay on adjuvant clinical decision-making in unselected patients with estrogen receptor positive, human epidermal growth factor receptor negative, node negative early-stage breast cancer. Curr Med Res Opin. 2015;31(6):1129–37.PubMedCrossRefGoogle Scholar
  17. 17.
    Jorgensen CL, Nielsen TO, Bjerre KD, Liu S, Wallden B, Balslev E, et al. PAM50 breast cancer intrinsic subtypes and effect of gemcitabine in advanced breast cancer patients. Acta Oncol. 2014;53(6):776–87.PubMedCrossRefGoogle Scholar
  18. 18.
    Filipits M, Nielsen TO, Rudas M, Greil R, Stoger H, Jakesz R, et al. The PAM50 risk-of-recurrence score predicts risk for late distant recurrence after endocrine therapy in postmenopausal women with endocrine-responsive early breast cancer. Clin Cancer Res. 2014;20(5):1298–305.PubMedCrossRefGoogle Scholar
  19. 19.
    Boccia RV. Translating Research into Practice: the Prosigna® (PAM50) Gene Signature Assay. Clin Adv Hematol Oncol. 2015;13(6 Suppl 6):3–13.PubMedGoogle Scholar
  20. 20.
    Prat A, Lluch A, Albanell J, Barry WT, Fan C, Chacon JI, et al. Predicting response and survival in chemotherapy-treated triple-negative breast cancer. Br J Cancer. 2014;111(8):1532–41.PubMedPubMedCentralCrossRefGoogle Scholar
  21. 21.
    Sikov W, Barry W, Hoadley K, Pitcher B, Singh B, Tolaney S, et al. Impact of intrinsic subtype by PAM50 and other gene signatures on pathologic complete response (pCR) rates in triple-negative breast cancer (TNBC) after neoadjuvant chemotherapy (NACT) +/− carboplatin (Cb) or bevacizumab (Bev): CALGB 40603/150709 (Alliance). San Antonio Breast Cancer Symp. 2014;2012:S4–05.Google Scholar
  22. 22.
    Bastien RR, Rodriguez-Lescure A, Ebbert MT, Prat A, Munarriz B, Rowe L, et al. PAM50 breast cancer subtyping by RT-qPCR and concordance with standard clinical molecular markers. BMC Med Genomics. 2012;5(1):44.PubMedPubMedCentralCrossRefGoogle Scholar
  23. 23.
    Prat A, Adamo B, Cheang MC, Anders CK, Carey LA, Perou CM. Molecular characterization of basal-like and non-basal-like triple-negative breast cancer. Oncologist. 2013;18(2):123–33.PubMedPubMedCentralCrossRefGoogle Scholar
  24. 24.
    Dunbier AK, Anderson H, Ghazoui Z, Salter J, Parker JS, Perou CM, et al. Association between breast cancer subtypes and response to neoadjuvant anastrozole. Steroids. 2011;76(8):736–40.PubMedCrossRefGoogle Scholar
  25. 25.
    Chia SK, Bramwell VH, Tu D, Shepherd LE, Jiang S, Vickery T, et al. A 50-Gene intrinsic subtype classifier for prognosis and prediction of benefit from adjuvant tamoxifen. Clin Cancer Res. 2012;18(16):4465–72.PubMedPubMedCentralCrossRefGoogle Scholar
  26. 26.
    Ellis MJ, Suman VJ, Hoog J, Lin L, Snider J, Prat A, et al. Randomized Phase II neoadjuvant comparison between letrozole, anastrozole, and exemestane for postmenopausal women with estrogen receptor-rich stage 2 to 3 breast cancer: clinical and biomarker outcomes and predictive value of the baseline PAM50-based intrinsic subtype—ACOSOG Z1031. J Clin Oncol. 2011;29(17):2342–9.PubMedPubMedCentralCrossRefGoogle Scholar
  27. 27.
    Gnant M, Filipits M, Greil R, Stoeger H, Rudas M, Bago-Horvath Z, et al. Predicting distant recurrence in receptor-positive breast cancer patients with limited clinicopathological risk: using the PAM50 risk of recurrence score in 1478 postmenopausal patients of the ABCSG-8 trial treated with adjuvant endocrine therapy alone. Ann Oncol. 2014;25(2):339–45.PubMedCrossRefGoogle Scholar
  28. 28.
    Martín M, González-Rivera M, Morales S, de la Haba J, González-Cortijo L, Manso L, et al. Prospective study of the impact of the Prosigna™ assay on adjuvant clinical decision-making in women with estrogen receptor-positive, HER2-negative, node-negative breast cancer: a GEICAM study. In: San Antonio Breast Cancer Symposium 2012; P6-08-10, 2014.Google Scholar
  29. 29.
    Nielsen TO, Parker JS, Leung S, Voduc D, Ebbert M, Vickery T, et al. A comparison of PAM50 intrinsic subtyping with immunohistochemistry and clinical prognostic factors in tamoxifen-treated estrogen receptor-positive breast cancer. Clin Cancer Res. 2010;16(21):5222–32.PubMedPubMedCentralCrossRefGoogle Scholar
  30. 30.
    Prat A, Cheang MC, Martin M, Parker JS, Carrasco E, Caballero R, et al. Prognostic significance of progesterone receptor-positive tumor cells within immunohistochemically defined luminal A breast cancer. J Clin Oncol. 2013;31(2):203–9.PubMedCrossRefGoogle Scholar
  31. 31.
    Prat A, Carey LA, Adamo B, Vidal M, Tabernero J, Cortés J, et al. Molecular features and survival outcomes of the intrinsic subtypes within HER2-positive breast cancer. J Natl Cancer Inst. 2014;106(8).Google Scholar
  32. 32.
    Curtis C, Shah SP, Chin S-F, Turashvili G, Rueda OM, Dunning MJ, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature. 2012;486(7403):346–52.PubMedPubMedCentralGoogle Scholar
  33. 33.
    Prat A, Bianchini G, Thomas M, Belousov A, Cheang MC, Koehler A, et al. Research-based PAM50 subtype predictor identifies higher responses and improved survival outcomes in HER2-positive breast cancer in the NOAH study. Clin Cancer Res. 2014;20(2):511–21.PubMedCrossRefGoogle Scholar
  34. 34.
    Carey L, Berry D, Ollila D, Harris L, Krop I, Weckstein D, et al. Clinical and translational results of CALGB 40601: a neoadjuvant phase III trial of weekly paclitaxel and trastuzumab with or without lapatinib for HER2-positive breast cancer. Proc Am Soc Clin Oncol: a500. 2013.Google Scholar
  35. 35.
    Prat A, Ellis MJ, Perou CM. Practical implications of gene-expression-based assays for breast oncologists. Nat Rev Clin Oncol. 2012;9(1):48–57.CrossRefGoogle Scholar
  36. 36.
    Dowsett M, Nielsen TO, A’Hern R, Bartlett J, Coombes RC, Cuzick J, et al. Assessment of Ki67 in breast cancer: recommendations from the international Ki67 in Breast Cancer Working Group. J Natl Cancer Inst. 2011.Google Scholar
  37. 37.
    Hammond MEH, Hayes DF, Dowsett M, Allred DC, Hagerty KL, Badve S, et al. American society of clinical oncology/college of american pathologists guideline recommendations for immunohistochemical testing of estrogen and progesterone receptors in breast cancer. J Clin Oncol. 2010;28(16):2784–95.PubMedPubMedCentralCrossRefGoogle Scholar
  38. 38.
    Wolff AC, Hammond MEH, Hicks DG, Dowsett M, McShane LM, Allison KH, et al. Recommendations for human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists Clinical practice guideline update. J Clin Oncol. 2013;31(31):3997–4013.PubMedCrossRefGoogle Scholar
  39. 39.
    McCullough A, Dell’Orto P, Reinholz M, Gelber R, Dueck A, Russo L, et al. Central pathology laboratory review of HER2 and ER in early breast cancer: an ALTTO trial [BIG 2-06/NCCTG N063D (Alliance)] ring study. Breast Cancer Res Treat. 2014;143(3):485–92.Google Scholar
  40. 40.
    Cheang MC, Chia SK, Voduc D, Gao D, Leung S, Snider J, et al. Ki67 index, HER2 status, and prognosis of patients with luminal B breast cancer. J Natl Cancer Inst. 2009;101(10):736–50.PubMedPubMedCentralCrossRefGoogle Scholar
  41. 41.
    Eroles P, Bosch A, Perez-Fidalgo JA, Lluch A. Molecular biology in breast cancer: intrinsic subtypes and signaling pathways. Cancer Treat Rev. 2012;38(6):698–707.PubMedCrossRefGoogle Scholar
  42. 42.
    Prat A, Cheang MCU, Martín M, Parker JS, Carrasco E, Caballero R, et al. Prognostic significance of progesterone receptor-positive tumor cells within immunohistochemically defined luminal A breast cancer. J Clin Oncol. 2013;31(2):203–9.PubMedCrossRefGoogle Scholar
  43. 43.
    Liu M, Pitcher B, Mardis E, Davies S, Snider J, Vickery T, et al. PAM50 gene signature is prognostic for breast cancer patients treated with adjuvant anthracycline and taxane based chemotherapy. In: San Antonio Breast Cancer Symposium 2012; P2-10-01.Google Scholar
  44. 44.
    Martín M, Prat A, Rodríguez-Lescure Á, Caballero R, Ebbert MW, Munárriz B, et al. PAM50 proliferation score as a predictor of weekly paclitaxel benefit in breast cancer. Breast Cancer Res Treat. 2013;138(2):457–66.PubMedPubMedCentralCrossRefGoogle Scholar
  45. 45.
    Cheang MC, Voduc KD, Tu D, Jiang S, Leung S, Chia SK, et al. Responsiveness of intrinsic subtypes to adjuvant anthracycline substitution in the NCIC.CTG MA.5 randomized trial. Clinical Cancer Res (an official journal of the American Association for Cancer Research). 2012;18(8):2402–12.CrossRefGoogle Scholar
  46. 46.
    Filipits M, Nielsen TO, Rudas M, Greil R, Stöger H, Jakesz R, et al. The PAM50 Risk-of-recurrence score predicts risk for late distant recurrence after endocrine therapy in postmenopausal women with endocrine-responsive early breast cancer. Clinical Cancer Res. 2014.Google Scholar
  47. 47.
    Sestak I, Cuzick J, Dowsett M, Lopez-Knowles E, Filipits M, Dubsky P, et al. Prediction of late distant recurrence after 5 years of endocrine treatment: a combined analysis of patients from the austrian breast and colorectal cancer study group 8 and arimidex, tamoxifen alone or in combination randomized trials using the PAM50 risk of recurrence score. J Clin Oncol. 2015;33(8):916–22.PubMedCrossRefGoogle Scholar
  48. 48.
    Sestak I, Dowsett M, Zabaglo L, Lopez-Knowles E, Ferree S, Cowens JW, et al. Factors predicting late recurrence for estrogen receptor–positive breast cancer. J Natl Cancer Inst. 2013.Google Scholar
  49. 49.
    Usary J, Zhao W, Darr D, Roberts PJ, Liu M, Balletta L, et al. Predicting drug responsiveness in human cancers using genetically engineered mice. Clin Cancer Res. 2013;19(17):4889–99.PubMedPubMedCentralCrossRefGoogle Scholar
  50. 50.
    von Minckwitz G, Blohmer JU, Costa SD, Denkert C, Eidtmann H, Eiermann W, et al. Response-guided neoadjuvant chemotherapy for breast cancer. J Clinl Oncol. 2013.Google Scholar
  51. 51.
    von Minckwitz G, Untch M, Blohmer J-U, Costa SD, Eidtmann H, Fasching PA, et al. Definition and impact of pathologic complete response on prognosis after neoadjuvant chemotherapy in various intrinsic breast cancer subtypes. J Clin Oncol. 2012;30(15):1796–804.CrossRefGoogle Scholar
  52. 52.
    Carey LA, Dees EC, Sawyer L, Gatti L, Moore DT, Collichio F, et al. The triple negative paradox: primary tumor chemosensitivity of breast cancer subtypes. Clin Cancer Res. 2007;13(8):2329–34.PubMedCrossRefGoogle Scholar
  53. 53.
    Cortazar P, Zhang L, Untch M, Mehta K, Costantino JP, Wolmark N, et al. Pathological complete response and long-term clinical benefit in breast cancer: the CTNeoBC pooled analysis. Lancet 384. 2014;(9938):164–72.Google Scholar
  54. 54.
    Roberts SA, Lawrence MS, Klimczak LJ, Grimm SA, Fargo D, Stojanov P, et al. An APOBEC cytidine deaminase mutagenesis pattern is widespread in human cancers. Nat Genet. 2013;45(9):970–6.PubMedPubMedCentralCrossRefGoogle Scholar
  55. 55.
    Kuong KJ, Loeb LA. APOBEC3B mutagenesis in cancer. Nat Genet. 2013;45(9):964–5.PubMedPubMedCentralCrossRefGoogle Scholar
  56. 56.
    Vaz-Luis I, Ottesen R, Hughes M, Marcom PK, Moy B, Rugo H, et al. Impact of hormone receptor status on patterns of recurrence and clinical outcomes among patients with human epidermal growth factor-2-positive breast cancer in the National Comprehensive Cancer Network: a prospective cohort study. Breast Cancer Res. 2012;14(5):R129.PubMedPubMedCentralCrossRefGoogle Scholar
  57. 57.
    Perez EA, Romond EH, Suman VJ, Jeong J-H, Davidson NE, Geyer CE, et al. Four-year follow-up of trastuzumab plus adjuvant chemotherapy for operable human epidermal growth factor receptor 2–positive breast cancer: joint analysis of data from NCCTG N9831 and NSABP B-31. J Clin Oncol. 2011;29(25):3366–73.PubMedPubMedCentralCrossRefGoogle Scholar
  58. 58.
    de Azambuja E, Holmes AP, Piccart-Gebhart M, Holmes E, Di Cosimo S, Swaby RF, et al. Lapatinib with trastuzumab for HER2-positive early breast cancer (NeoALTTO): survival outcomes of a randomised, open-label, multicentre, phase 3 trial and their association with pathological complete response. Lancet Oncol. 2014;15(10):1137–46.PubMedCrossRefGoogle Scholar
  59. 59.
    Piccart-Gebhart M, Holmes A, Baselga J, De Azambuja D, Dueck A, Viale G, et al. First results from the phase III ALTTO trial (BIG 2-06; NCCTG [Alliance] N063D) comparing one year of anti-HER2 therapy with lapatinib alone (L), trastuzumab alone (T), their sequence (T → L), or their combination (T + L) in the adjuvant treatment of HER2-positive early breast cancer (EBC). Proc Am Soc Clin Oncol: LBA4. 2014.Google Scholar
  60. 60.
    Tolaney SM, Barry WT, Dang CT, Yardley DA, Moy B, Marcom PK, et al. Adjuvant paclitaxel and trastuzumab for node-negative, HER2-positive breast cancer. N Engl J Med. 2015;372(2):134–41.PubMedPubMedCentralCrossRefGoogle Scholar
  61. 61.
    Rimawi M, Niravath P, Wang T, Rexer B, Forero A, Wolff A, et al. TBCRC023: A randomized multicenter phase II neoadjuvant trial of lapatinib plus trastuzumab, with endcorine therapy and without chemotherapy, for 12 vs. 24 weeks in patients with HER2 overexpressing breast cancer. In: San Antonio Breast Cancer Symposium 2012;S6-02, 2014.Google Scholar
  62. 62.
    Prat A, Cruz C, Hoadley K, Díez O, Perou C, Balmaña J. Molecular features of the basal-like breast cancer subtype based on BRCA1 mutation status. Breast Cancer Res Treat. 2014;147(1):185–91.PubMedPubMedCentralCrossRefGoogle Scholar
  63. 63.
    Foulkes WD, Stefansson IM, Chappuis PO, Bégin LR, Goffin JR, Wong N, et al. Germline BRCA1 mutations and a basal epithelial phenotype in breast cancer. J Natl Cancer Inst. 2003;95(19):1482–5.PubMedCrossRefGoogle Scholar
  64. 64.
    Cheang MC, Voduc D, Bajdik C, Leung S, McKinney S, Chia SK, et al. Basal-like breast cancer defined by five biomarkers has superior prognostic value than triple-negative phenotype. Clin Cancer Res. 2008;14(5):1368–76.PubMedCrossRefGoogle Scholar
  65. 65.
    Schneider BP, Winer EP, Foulkes WD, Garber J, Perou CM, Richardson A, et al. Triple-negative breast cancer: risk factors to potential targets. Clin Cancer Res. 2008;14(24):8010–8.PubMedCrossRefGoogle Scholar
  66. 66.
    Prat A, Adamo B, Fan C, Peg V, Vidal M, Galvan P, et al. Genomic analyses across six cancer types identify basal-like breast cancer as a unique molecular entity. Sci Rep. 2013;3:3544.PubMedCrossRefGoogle Scholar
  67. 67.
    Hoadley KA, Yau C, Wolf DM, Cherniack AD, Tamborero D, Ng S, et al. Multiplatform analysis of 12 cancer types reveals molecular classification within and across tissues of origin. Cell. 2014;158(4):929–44.PubMedPubMedCentralCrossRefGoogle Scholar
  68. 68.
    Lim E, Vaillant F, Wu D, Forrest NC, Pal B, Hart AH, et al. Aberrant luminal progenitors as the candidate target population for basal tumor development in BRCA1 mutation carriers. Nat Med. 2009;15(8):907–13.PubMedCrossRefGoogle Scholar
  69. 69.
    Molyneux G, Geyer FC, Magnay F-A, McCarthy A, Kendrick H, Natrajan R, et al. BRCA1 basal-like breast cancers originate from luminal epithelial progenitors and not from basal stem cells. Cell Stem Cell. 2010;7(3):403–17.PubMedCrossRefGoogle Scholar
  70. 70.
    Keller PJ, Arendt LM, Skibinski A, Logvinenko T, Klebba I, Dong S, et al. Defining the cellular precursors to human breast cancer. Proc Natl Acad Sci. 2012;109(8):2772–7.PubMedCrossRefGoogle Scholar
  71. 71.
    Millikan R, Newman B, Tse C-K, Moorman P, Conway K, Smith L, et al. Epidemiology of basal-like breast cancer. Breast Cancer Res Treat. 2008;109(1):123–39.PubMedCrossRefGoogle Scholar
  72. 72.
    Iwamoto T, Booser D, Valero V, Murray JL, Koenig K, Esteva FJ, et al. Estrogen receptor (ER) mRNA and ER-related gene expression in breast cancers that Are 1 % to 10 % ER-positive by immunohistochemistry. J Clin Oncol. 2012;30(7):729–34.PubMedCrossRefGoogle Scholar
  73. 73.
    Cheang M, Martin M, Nielsen T, Prat A, Rodriguez-Lescure A, Ruiz A, et al. Quantitative hormone receptors, triple-negative breast cancer (TNBC), and molecular subtypes: a collaborative effort of the BIG-NCI NABCG. Proc Am Soc Clin Oncol: a1008. 2012.Google Scholar
  74. 74.
    Prat A, Parker JS, Fan C, Cheang MCU, Miller LD, Bergh J, et al. Concordance among gene expression-based predictors for ER-positive breast cancer treated with adjuvant tamoxifen. Ann Oncol. 2012;23(11):2866–73.PubMedPubMedCentralCrossRefGoogle Scholar
  75. 75.
    Lehmann BD, Bauer JA, Chen X, Sanders ME, Chakravarthy AB, Shyr Y, et al. Identification of human triple-negative breast cancer subtypes and preclinical models for selection of targeted therapies. J Clin Invest. 2011;121(7):2750–67.PubMedPubMedCentralCrossRefGoogle Scholar
  76. 76.
    Lehmann BD, Pietenpol JA. Identification and use of biomarkers in treatment strategies for triple-negative breast cancer subtypes. J Pathol. 2014;232(2):142–50.PubMedPubMedCentralCrossRefGoogle Scholar
  77. 77.
    Burstein MD, Tsimelzon A, Poage GM, Covington KR, Contreras A, Fuqua S, et al. Comprehensive genomic analysis identifies novel subtypes and targets of triple-negative breast cancer. Clinical Cancer Res. 2014.Google Scholar
  78. 78.
    Masuda H, Baggerly KA, Wang Y, Zhang Y, Gonzalez-Angulo AM, Meric-Bernstam F, et al. Differential response to neoadjuvant chemotherapy among 7 triple-negative breast cancer molecular subtypes. Clinical Cancer Res (An Official Journal of the American Association for Cancer Research). 2013;19(19):5533–40.CrossRefGoogle Scholar
  79. 79.
    Loi S, Michiels S, Salgado R, Sirtaine N, Jose V, Fumagalli D, et al. Tumor infiltrating lymphocytes are prognostic in triple negative breast cancer and predictive for trastuzumab benefit in early breast cancer: results from the FinHER trial. Ann Oncol. 2014;25(8):1544–50.PubMedCrossRefGoogle Scholar
  80. 80.
    Ali HR, Provenzano E, Dawson S-J, Blows FM, Liu B, Shah M, et al. Association between CD8+ T-cell infiltration and breast cancer survival in 12 439 patients. Ann Oncol. 2014;25(8):1536–43.PubMedCrossRefGoogle Scholar
  81. 81.
    Rody A, Karn T, Liedtke C, Pusztai L, Ruckhaeberle E, Hanker L, et al. A clinically relevant gene signature in triple negative and basal-like breast cancer. Breast Cancer Res. 2011;13(5):R97.PubMedPubMedCentralCrossRefGoogle Scholar
  82. 82.
    Herschkowitz JI, Simin K, Weigman VJ, Mikaelian I, Usary J, Hu Z, et al. Identification of conserved gene expression features between murine mammary carcinoma models and human breast tumors. Genome Biol. 2007;8(5):R76.PubMedPubMedCentralCrossRefGoogle Scholar
  83. 83.
    Lim E, Vaillant F, Wu D, Forrest NC, Pal B, Hart AH, et al. Aberrant luminal progenitors as the candidate target population for basal tumor development in BRCA1 mutation carriers. Nat Med. 2009;15(8):907–13.PubMedCrossRefGoogle Scholar
  84. 84.
    Taube JH, Herschkowitz JI, Komurov K, Zhou AY, Gupta S, Yang J, et al. Core epithelial-to-mesenchymal transition interactome gene-expression signature is associated with claudin-low and metaplastic breast cancer subtypes. Proc Natl Acad Sci USA. 2010;107(35):15449–54.PubMedPubMedCentralCrossRefGoogle Scholar
  85. 85.
    Phillips JE, Petrie TA, Creighton FP, Garcia AJ. Human mesenchymal stem cell differentiation on self-assembled monolayers presenting different surface chemistries. Acta Biomater. 2010;6(1):12–20.PubMedCrossRefGoogle Scholar
  86. 86.
    Hennessy BT, Gonzalez-Angulo AM, Stemke-Hale K, Gilcrease MZ, Krishnamurthy S, Lee JS, et al. Characterization of a naturally occurring breast cancer subset enriched in epithelial-to-mesenchymal transition and stem cell characteristics. Cancer Res. 2009;69(10):4116–24.PubMedPubMedCentralCrossRefGoogle Scholar
  87. 87.
    Hennessy BT, Krishnamurthy S, Giordano S, Buchholz TA, Kau SW, Duan Z, et al. Squamous cell carcinoma of the breast. J Clin Oncol. 2005;23(31):7827–35.PubMedCrossRefGoogle Scholar
  88. 88.
    Vu-Nishino H, Tavassoli FA, Ahrens WA, Haffty BG. Clinicopathologic features and long-term outcome of patients with medullary breast carcinoma managed with breast-conserving therapy (BCT). Int J Radiat Oncol Biol Phys. 2005;62(4):1040–7.PubMedCrossRefGoogle Scholar
  89. 89.
    Hess KR, Anderson K, Symmans WF, Valero V, Ibrahim N, Mejia JA, et al. Pharmacogenomic predictor of sensitivity to preoperative chemotherapy with paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide in breast cancer. J Clin Oncol. 2006;24(26):4236–44.PubMedCrossRefGoogle Scholar
  90. 90.
    Nielsen TO, Hsu FD, Jensen K, Cheang M, Karaca G, Hu Z, et al. Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma. Clin Cancer Res. 2004;10(16):5367–74.PubMedCrossRefGoogle Scholar
  91. 91.
    Curtis C, Shah SP, Chin SF, Turashvili G, Rueda OM, Dunning MJ, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature. 2012;486(7403):346–52.PubMedPubMedCentralGoogle Scholar
  92. 92.
    Dawson SJ, Rueda OM, Aparicio S, Caldas C. A new genome-driven integrated classification of breast cancer and its implications. EMBO J. 2013;32(5):617–28.PubMedPubMedCentralCrossRefGoogle Scholar
  93. 93.
    Comprehensive molecular portraits of human breast tumours. Nature. 2012;490(7418):61–70.CrossRefGoogle Scholar
  94. 94.
    Robinson DR, Wu Y-M, Vats P, Su F, Lonigro RJ, Cao X, et al. Activating ESR1 mutations in hormone-resistant metastatic breast cancer. Nat Genet. 2013;45(12):1446–51.PubMedPubMedCentralCrossRefGoogle Scholar
  95. 95.
    Liu Y, Colditz GA, Gehlert S, Goodman M. Racial disparities in risk of second breast tumors after ductal carcinoma in situ. Breast Cancer Res Treat. 2014;148(1):163–73.PubMedPubMedCentralCrossRefGoogle Scholar
  96. 96.
    Jeselsohn R, Yelensky R, Buchwalter G, Frampton G, Meric-Bernstam F, Gonzalez-Angulo AM, et al. Emergence of constitutively active estrogen receptor-α mutations in pretreated advanced estrogen receptor-positive breast cancer. Clin Cancer Res. 2014;20(7):1757–67.PubMedPubMedCentralCrossRefGoogle Scholar
  97. 97.
    Segal CV, Dowsett M. Estrogen receptor mutations in breast cancer–new focus on an old target. Clin Cancer Res. 2014;20(7):1724–6.PubMedCrossRefGoogle Scholar
  98. 98.
    de Dueñas E, Hernández A, Zotano Á, Carrión R, López-Muñiz J, Novoa S, et al. Prospective evaluation of the conversion rate in the receptor status between primary breast cancer and metastasis: results from the GEICAM 2009-03 ConvertHER study. Breast Cancer Res Treat. 2014;143(3):507–15.PubMedPubMedCentralCrossRefGoogle Scholar
  99. 99.
    Parker JS, Mullins M, Cheang MCU, Leung S, Voduc D, Vickery T, et al. Supervised risk predictor of breast cancer based on intrinsic subtypes. J Clin Oncol. 2009;27(8):1160–7.PubMedPubMedCentralCrossRefGoogle Scholar
  100. 100.
    Prat A, Maggie C, Galván P, Nuciforo P, Paré L, Adamo B, Muñoz M, Viladot M, Press F, Gagnon R, Ellis C, Johnston S. Intrinsic subtype, prognosis, and benefit of lapatinib therapy in first line hormone-receptor positive metastatic breast cancer treated with letrozole. JAMA Oncol. 2016;2(10).Google Scholar
  101. 101.
    Johnston S, Pippen J, Pivot X, Lichinitser M, Sadeghi S, Dieras V, et al. Lapatinib combined with letrozole versus letrozole and placebo as first-line therapy for postmenopausal hormone receptor-positive metastatic breast cancer. J Clin Oncol. 2009;27(33):5538–46.PubMedCrossRefGoogle Scholar
  102. 102.
    Malkin D, Li FP, Strong LC, Fraumeni JF Jr, Nelson CE, Kim DH, et al. Germ line p53 mutations in a familial syndrome of breast cancer, sarcomas, and other neoplasms. Science. 1990;250(4985):1233–8.PubMedCrossRefGoogle Scholar
  103. 103.
    Davidoff AM, Kerns BJ, Pence JC, Marks JR, Iglehart JD. p53 alterations in all stages of breast cancer. J Surg Oncol. 1991;48(4):260–7.PubMedCrossRefGoogle Scholar
  104. 104.
    Gasco M, Shami S, Crook T. The p53 pathway in breast cancer. Breast Cancer Res. 2002;4(2):70–6.PubMedPubMedCentralCrossRefGoogle Scholar
  105. 105.
    Bose R. A neu view of invasive lobular breast cancer. Clin Cancer Res. 2013;19(13):3331–3.PubMedPubMedCentralCrossRefGoogle Scholar
  106. 106.
    Shah SP, Morin RD, Khattra J, Prentice L, Pugh T, Burleigh A, et al. Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution. Nature. 2009;461(7265):809–13.PubMedCrossRefGoogle Scholar
  107. 107.
    Foote FW Jr, Stewart FW. A histologic classification of carcinoma of the breast. Surgery. 1946;19:74–99.PubMedGoogle Scholar
  108. 108.
    Dabbs DJ, Schnitt SJ, Geyer FC, Weigelt B, Baehner FL, Decker T, et al. Lobular neoplasia of the breast revisited with emphasis on the role of E-cadherin immunohistochemistry. Am J Surg Pathol. 2013;37(7):e1–11.PubMedCrossRefGoogle Scholar
  109. 109.
    Ciriello G, Gatza ML, Beck AH, Wilkerson MD, Rhie SK, Pastore A, et al. Comprehensive molecular portraits of invasive lobular breast cancer. Cell. 2015;163(2):506–19.PubMedPubMedCentralCrossRefGoogle Scholar
  110. 110.
    cBioportal for Cancer Genomics.Google Scholar
  111. 111.
    Cerami E, Gao J, Dogrusoz U, Gross BE, Sumer SO, Aksoy BA, et al. The cBio cancer genomics portal: an open platform for exploring multidimensional cancer genomics data. Cancer Discov. 2012;2(5):401–4.PubMedCrossRefGoogle Scholar
  112. 112.
    Gao J, Aksoy BA, Dogrusoz U, Dresdner G, Gross B, Sumer SO, et al. Integrative analysis of complex cancer genomics and clinical profiles using the cBioPortal. Sci Signal. 2013;6(269):pl1.Google Scholar
  113. 113.
    Bos PD, Zhang XH, Nadal C, Shu W, Gomis RR, Nguyen DX, et al. Genes that mediate breast cancer metastasis to the brain. Nature. 2009;459(7249):1005–9.PubMedPubMedCentralCrossRefGoogle Scholar
  114. 114.
    Silver DP, Richardson AL, Eklund AC, Wang ZC, Szallasi Z, Li Q, et al. Efficacy of neoadjuvant Cisplatin in triple-negative breast cancer. J Clin Oncol. 2010;28(7):1145–53.PubMedPubMedCentralCrossRefGoogle Scholar
  115. 115.
    Li Y, Zou L, Li Q, Haibe-Kains B, Tian R, Li Y, et al. Amplification of LAPTM4B and YWHAZ contributes to chemotherapy resistance and recurrence of breast cancer. Nat Med. 2010;16(2):214–8.PubMedPubMedCentralCrossRefGoogle Scholar
  116. 116.
    Juul N, Szallasi Z, Eklund AC, Li Q, Burrell RA, Gerlinger M, et al. Assessment of an RNA interference screen-derived mitotic and ceramide pathway metagene as a predictor of response to neoadjuvant paclitaxel for primary triple-negative breast cancer: a retrospective analysis of five clinical trials. Lancet Oncol. 2010;11(4):358–65.PubMedCrossRefGoogle Scholar
  117. 117.
    Buffa FM, Camps C, Winchester L, Snell CE, Gee HE, Sheldon H, et al. microRNA-associated progression pathways and potential therapeutic targets identified by integrated mRNA and microRNA expression profiling in breast cancer. Cancer Res. 2011;71(17):5635–45.PubMedCrossRefGoogle Scholar
  118. 118.
    Hatzis C, Pusztai L, Valero V, Booser DJ, Esserman L, Lluch A, et al. A genomic predictor of response and survival following taxane-anthracycline chemotherapy for invasive breast cancer. JAMA. 2011;305(18):1873–81.PubMedCrossRefGoogle Scholar
  119. 119.
    Itoh M, Iwamoto T, Matsuoka J, Nogami T, Motoki T, Shien T, et al. Estrogen receptor (ER) mRNA expression and molecular subtype distribution in ER-negative/progesterone receptor-positive breast cancers. Breast Cancer Res Treat. 2014;143(2):403–9.PubMedCrossRefGoogle Scholar
  120. 120.
    Minn AJ, Gupta GP, Siegel PM, Bos PD, Shu W, Giri DD, et al. Genes that mediate breast cancer metastasis to lung. Nature. 2005;436(7050):518–24.PubMedPubMedCentralCrossRefGoogle Scholar
  121. 121.
    Sotiriou C, Wirapati P, Loi S, Harris A, Fox S, Smeds J, et al. Gene expression profiling in breast cancer: understanding the molecular basis of histologic grade to improve prognosis. J Natl Cancer Inst. 2006;98(4):262–72.PubMedCrossRefGoogle Scholar
  122. 122.
    Ivshina AV, George J, Senko O, Mow B, Putti TC, Smeds J, et al. Genetic reclassification of histologic grade delineates new clinical subtypes of breast cancer. Cancer Res. 2006;66(21):10292–301.PubMedCrossRefGoogle Scholar
  123. 123.
    Desmedt C, Piette F, Loi S, Wang Y, Lallemand F, Haibe-Kains B, et al. Strong time dependence of the 76-gene prognostic signature for node-negative breast cancer patients in the TRANSBIG multicenter independent validation series. Clin Cancer Res. 2007;13(11):3207–14.PubMedCrossRefGoogle Scholar
  124. 124.
    Patil G, Valliyodan B, Deshmukh R, Prince S, Nicander B, Zhao M, et al. Soybean (Glycine max) SWEET gene family: insights through comparative genomics, transcriptome profiling and whole genome re-sequence analysis. BMC Genom. 2015;16:520.CrossRefGoogle Scholar
  125. 125.
    Anders CK, Acharya CR, Hsu DS, Broadwater G, Garman K, Foekens JA, et al. Age-specific differences in oncogenic pathway deregulation seen in human breast tumors. PLoS ONE. 2008;3(1):e1373.PubMedPubMedCentralCrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Medical OncologyHospital Clinic of BarcelonaBarcelonaSpain
  2. 2.Translational Genomics and Targeted Therapeutics in Solid Tumors LabAugust Pi I Sunyer Biomedical Research Institute (IDIBAPS)BarcelonSpain

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