Skip to main content
SpringerLink
Log in

Molecular Classification of Breast Cancer

  • Chapter
  • First Online:
Precision Molecular Pathology of Breast Cancer

Part of the book series: Molecular Pathology Library ((MPLB,volume 10))

  • 1685 Accesses

Abstract

Breast cancer is a complex heterogeneous disease, encompassing a diverse spectrum of different subtypes with distinct histological, biological and clinical features. Traditional well-established classification systems utilising clinicopathological variables such as stage, grade and histological type have long been used in clinical management of breast cancer patients. However, compiling evidence indicates that these are insufficient to reflect the biological and clinical heterogeneity of breast cancer and tumours of similar clinicopathological features show different behaviour in terms of clinical outcome and response to specific therapy. Advances in molecular techniques and bioinformatics have contributed to the improved understanding of breast cancer biology and the development of molecular taxonomies and prognostic molecular assays for prediction of disease recurrence and therapeutic response. In this chapter, current molecular classification of breast cancer is discussed. Current limitations and challenges are also highlighted.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 119.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Elston CW, Ellis IO, Pinder SE. Pathological prognostic factors in breast cancer. Crit Rev Oncol Hematol. 1999;31(3):209–23.

    Article  CAS  PubMed  Google Scholar 

  2. Rakha EA, El-Sayed ME, Lee AH, Elston CW, Grainge MJ, Hodi Z, et al. Prognostic significance of Nottingham histologic grade in invasive breast carcinoma. J Clin Oncol. 2008;26(19):3153–8. PubMed PMID: 18490649. Epub 2008/05/21. eng.

    Google Scholar 

  3. Galea MH, Blamey RW, Elston CE, Ellis IO. The Nottingham Prognostic Index in primary breast-cancer. Breast Cancer Res Treat. 1992;22(3):207–19. PubMed PMID: ISI:A1992JQ41500005.

    Google Scholar 

  4. Sinn H-P, Kreipe H. A brief overview of the WHO classification of breast tumors, 4th edition, focusing on issues and updates from the 3rd edition. Breast Care. 2013;8(2):149–54. PubMed PMID: PMC3683948.

    Google Scholar 

  5. Rakha EA, El-Sayed ME, Menon S, Green AR, Lee AH, Ellis IO. Histologic grading is an independent prognostic factor in invasive lobular carcinoma of the breast. Breast Cancer Res Treat. 2008;111(1):121–7.

    Article  PubMed  Google Scholar 

  6. Cole BF, Gelber RD, Gelber S, Coates AS, Goldhirsch A. Polychemotherapy for early breast cancer: an overview of the randomised clinical trials with quality-adjusted survival analysis. The Lancet. 2001;358(9278):277–86.

    Article  CAS  Google Scholar 

  7. Feng Y, Sun B, Li X, Zhang L, Niu Y, Xiao C, et al. Differentially expressed genes between primary cancer and paired lymph node metastases predict clinical outcome of node-positive breast cancer patients. Breast Cancer Res Treat. 2007;103(3):319–29.

    Article  CAS  PubMed  Google Scholar 

  8. Peto R, Boreham J, Clarke M, Davies C, Beral V. UK and USA breast cancer deaths down 25 % in year 2000 at ages 20–69 years. Lancet. 2000;355(9217):1822.

    Article  CAS  PubMed  Google Scholar 

  9. Hayes DF, Bast RC, Desch CE, Fritsche H Jr, Kemeny NE, Jessup JM, et al. Tumor marker utility grading system: a framework to evaluate clinical utility of tumor markers. J Natl Cancer Inst. 1996;88(20):1456–66.

    Article  CAS  PubMed  Google Scholar 

  10. Wang DG, Fan JB, Siao CJ, Berno A, Young P, Sapolsky R, et al. Large-scale identification, mapping, and genotyping of single-nucleotide polymorphisms in the human genome. Science. 1998;280(5366):1077–82.

    Article  CAS  PubMed  Google Scholar 

  11. Pinkel D, Segraves R, Sudar D, Clark S, Poole I, Kowbel D, et al. High resolution analysis of DNA copy number variation using comparative genomic hybridization to microarrays. Nat Genet. 1998;20(2):207–11.

    Article  CAS  PubMed  Google Scholar 

  12. Schweiger MR, Kerick M, Timmermann B, Albrecht MW, Borodina T, Parkhomchuk D, et al. Genome-wide massively parallel sequencing of formaldehyde fixed-paraffin embedded (FFPE) tumor tissues for copy-number- and mutation-analysis. PLoS ONE. 2009;4(5):e5548.

    Article  PubMed Central  PubMed  Google Scholar 

  13. Liang P, Pardee AB. Differential display of eukaryotic messenger RNA by means of the polymerase chain reaction. Science. 1992;257(5072):967–71.

    Article  CAS  PubMed  Google Scholar 

  14. Velculescu VE, Zhang L, Vogelstein B, Kinzler KW. Serial analysis of gene expression. Science. 1995;270(5235):484–7.

    Article  CAS  PubMed  Google Scholar 

  15. Brown PO, Botstein D. Exploring the new world of the genome with DNA microarrays. Nat Genet. 1999;21(1 Suppl):33–7.

    Article  CAS  PubMed  Google Scholar 

  16. Torres TT, Metta M, Ottenwalder B, Schlotterer C. Gene expression profiling by massively parallel sequencing. Genome Res. 2008;18(1):172–7. PubMed PMID: 18032722. Pubmed Central PMCID: 2134766.

    Google Scholar 

  17. Rakha EA, Pinder SE, Bartlett JM, Ibrahim M, Starczynski J, Carder PJ, et al. Updated UK recommendations for HER2 assessment in breast cancer. J Clin Pathol. 2015;68(2):93–9. PubMed PMID: 25488926. Pubmed Central PMCID: 4316916.

    Google Scholar 

  18. Pathology reporting of breast disease. A Joint Document Incorporating the Third Edition of the NHS Breast Screening Programme’s Guidelines for Pathology Reporting in Breast Cancer Screening and the Second Edition of The Royal College of Pathologists’ Minimum Dataset for Breast Cancer Histopathology, Jan 2005. NHSBSP Pub. No 58 p.

    Google Scholar 

  19. Hammond ME, 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.

    Article  PubMed Central  PubMed  Google Scholar 

  20. Goldhirsch A, Glick JH, Gelber RD, Coates AS, Thurlimann B, Senn HJ. Meeting highlights: international expert consensus on the primary therapy of early breast cancer 2005. Ann Oncol. 2005;16(10):1569–83.

    Article  CAS  PubMed  Google Scholar 

  21. Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet. 2005;365(9472):1687–717. PubMed PMID: 15894097.

    Google Scholar 

  22. Effects of adjuvant tamoxifen and of cytotoxic therapy on mortality in early breast cancer. An overview of 61 randomized trials among 28,896 women. Early Breast Cancer Trialists’ Collaborative Group. N Engl J Med. 1988;319(26):1681–92. PubMed PMID: 3205265.

    Google Scholar 

  23. Tamoxifen for early breast cancer: an overview of the randomised trials. Early Breast Cancer Trialists’ Collaborative Group. Lancet. 1998;351(9114):1451–67. PubMed PMID: 9605801.

    Google Scholar 

  24. Fisher B, Dignam J, Bryant J, DeCillis A, Wickerham DL, Wolmark N, et al. Five versus more than five years of tamoxifen therapy for breast cancer patients with negative lymph nodes and estrogen receptor-positive tumors. J Natl Cancer Inst. 1996;88(21):1529–42.

    Article  CAS  PubMed  Google Scholar 

  25. Bardou VJ, Arpino G, Elledge RM, Osborne CK, Clark GM. Progesterone receptor status significantly improves outcome prediction over estrogen receptor status alone for adjuvant endocrine therapy in two large breast cancer databases. J Clin Oncol. 2003;21(10):1973–9.

    Article  CAS  PubMed  Google Scholar 

  26. Rakha EA, El-Sayed ME, Green AR, Paish EC, Powe DG, Gee J, et al. Biologic and clinical characteristics of breast cancer with single hormone receptor positive phenotype. J Clin Oncol. 2007;25(30):4772–8.

    Article  PubMed  Google Scholar 

  27. Ravdin PM, Green S, Dorr TM, McGuire WL, Fabian C, Pugh RP, et al. Prognostic significance of progesterone receptor levels in estrogen receptor-positive patients with metastatic breast cancer treated with tamoxifen: results of a prospective Southwest Oncology Group study. J Clin Oncol. 1992;10(8):1284–91.

    CAS  PubMed  Google Scholar 

  28. Colomer R, Beltran M, Dorcas J, Cortes-Funes H, Hornedo J, Valentin V, et al. It is not time to stop progesterone receptor testing in breast cancer. J Clin Oncol. 2005;23(16):3868–9; author reply 9–70. PubMed PMID: 15923595.

    Google Scholar 

  29. Stendahl M, Ryden L, Nordenskjold B, Jonsson PE, Landberg G, Jirstrom K. High progesterone receptor expression correlates to the effect of adjuvant tamoxifen in premenopausal breast cancer patients. Clin Cancer Res. 2006;12(15):4614–8.

    Article  CAS  PubMed  Google Scholar 

  30. Regan MM, Viale G, Mastropasqua MG, Maiorano E, Golouh R, Carbone A, et al. Re-evaluating adjuvant breast cancer trials: assessing hormone receptor status by immunohistochemical versus extraction assays. J Natl Cancer Inst. 2006;98(21):1571–81.

    Article  CAS  PubMed  Google Scholar 

  31. Slamon DJ, Clark GM, Wong SG, Levin WJ, Ullrich A, McGuire WL. Human breast cancer: correlation of relapse and survival with amplification of the HER-2/neu oncogene. Science. 1987;235(4785):177–82.

    Article  CAS  PubMed  Google Scholar 

  32. Dandachi N, Dietze O, Hauser-Kronberger C. Chromogenic in situ hybridization: a novel approach to a practical and sensitive method for the detection of HER2 oncogene in archival human breast carcinoma. Lab Invest. 2002;82(8):1007–14.

    Article  CAS  PubMed  Google Scholar 

  33. Wolff AC, Hammond ME, Schwartz JN, Hagerty KL, Allred DC, Cote RJ, et al. American Society of Clinical Oncology/College of American Pathologists guideline recommendations for human epidermal growth factor receptor 2 testing in breast cancer. J Clin Oncol. 2007;25(1):118–45.

    Article  CAS  PubMed  Google Scholar 

  34. Bartlett J, Mallon E, Cooke T. The clinical evaluation of HER-2 status: which test to use? J Pathol. 2003;199(4):411–7.

    Article  CAS  PubMed  Google Scholar 

  35. Kaufmann M, von Minckwitz G, Bear HD, Buzdar A, McGale P, Bonnefoi H, et al. Recommendations from an international expert panel on the use of neoadjuvant (primary) systemic treatment of operable breast cancer: new perspectives 2006. Ann Oncol. 2007;18(12):1927–34.

    Article  CAS  PubMed  Google Scholar 

  36. Ward S, Pilgrim H, Hind D. Trastuzumab for the treatment of primary breast cancer in HER2-positive women: a single technology appraisal. Health Technol Assess. 2009;13(Suppl 1):1–6.

    Article  PubMed  Google Scholar 

  37. Rakha EA, Reis-Filho JS, Ellis IO. Combinatorial biomarker expression in breast cancer. Breast Cancer Res Treat. 2010;120(2):293–308. PubMed PMID: 20107892. Epub 2010/01/29. eng.

    Google Scholar 

  38. Cuzick J, Dowsett M, Wale C, Salter J, Quinn E, Zabaglo L, et al. Prognostic value of a combined ER, PgR, Ki67, HER2 immunohistochemical (IHC4) score and comparison with the GHI recurrence score—results from TransATAC. Cancer Res. 2009;Suppl 24: Abstract 74.

    Google Scholar 

  39. Carey LA, Perou CM, Livasy CA, Dressler LG, Cowan D, Conway K, et al. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. J Am Med Assoc (JAMA). 2006;295(21):2492–502. PubMed PMID: ISI:000238057300024.

    Google Scholar 

  40. Kreike B, van Kouwenhove M, Horlings H, Weigelt B, Bartelink H, Van de Vijver MJ. Gene expression profiling and histopathological characterization of triple negative/basal-like breast carcinomas. Breast Cancer Res. 2007;9(5):R65.

    Article  PubMed Central  PubMed  Google Scholar 

  41. Kurebayashi J, Moriya T, Ishida T, Hirakawa H, Kurosumi M, Akiyama F, et al. The prevalence of intrinsic subtypes and prognosis in breast cancer patients of different races. The Breast. 2007;16(2, Suppl 1):72–7.

    Google Scholar 

  42. Aleskandarany MA, Rakha EA, Macmillan RD, Powe DG, Ellis IO, Green AR. MIB1/Ki-67 labelling index can classify grade 2 breast cancer into two clinically distinct subgroups. Breast Cancer Res Treat. 2010;127(3):591–9.

    Article  PubMed  Google Scholar 

  43. Colozza M, Azambuja E, Cardoso F, Sotiriou C, Larsimont D, Piccart MJ. Proliferative markers as prognostic and predictive tools in early breast cancer: where are we now? 2005. p. 1723–39.

    Google Scholar 

  44. Viale G, Regan MM, Mastropasqua MG, Maffini F, Maiorano E, Colleoni M, et al. Predictive value of tumor Ki-67 expression in two randomized trials of adjuvant chemoendocrine therapy for node-negative breast cancer. J Natl Cancer Inst. 2008;100(3):207–12.

    Article  CAS  PubMed  Google Scholar 

  45. Baak JP, Gudlaugsson E, Skaland I, Guo LH, Klos J, Lende TH, et al. Proliferation is the strongest prognosticator in node-negative breast cancer: significance, error sources, alternatives and comparison with molecular prognostic markers. Breast Cancer Res Treat. 2009;115(2):241–54.

    Article  CAS  PubMed  Google Scholar 

  46. Yerushalmi R, Woods R, Ravdin PM, Hayes MM, Gelmon KA. Ki67 in breast cancer: prognostic and predictive potential. Lancet Oncol. 2010;11(2):174–83.

    Article  CAS  PubMed  Google Scholar 

  47. 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.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  48. Aleskandarany MA, Rakha EA, Macmillan RD, Powe DG, Ellis IO, Green AR. MIB1/Ki-67 labelling index can classify grade 2 breast cancer into two clinically distinct subgroups. Breast Cancer Res Treat. 2010. PubMed PMID: 20623333. Epub 2010/07/14. Eng.

    Google Scholar 

  49. Aleskandarany MA, Green AR, Rakha EA, Mohammed RA, Elsheikh SE, Powe DG, et al. Growth fraction as a predictor of response to chemotherapy in node-negative breast cancer. Int J Cancer. 2010. PubMed PMID: 19711345.

    Google Scholar 

  50. Colleoni M, Orvieto E, Nole F, Orlando L, Minchella I, Viale G, et al. Prediction of response to primary chemotherapy for operable breast cancer. Eur J Cancer. 1999;35(4):574–9.

    Article  CAS  PubMed  Google Scholar 

  51. Augenlicht LH, Wahrman MZ, Halsey H, Anderson L, Taylor J, Lipkin M. Expression of cloned sequences in biopsies of human colonic tissue and in colonic carcinoma cells induced to differentiate in vitro. Cancer Res. 1987;47(22):6017–21. PubMed PMID: 3664505. Epub 1987/11/15. eng.

    Google Scholar 

  52. Bertucci F, Finetti P, Cervera N, Maraninchi D, Viens P, Birnbaum D. Gene expression profiling and clinical outcome in breast cancer. OMICS. 2006;10(4):429–43. PubMed PMID: 17233555. Epub 2007/01/20. eng.

    Google Scholar 

  53. Cowin PA, Anglesio M, Etemadmoghadam D, Bowtell DD. Profiling the cancer genome. Annu Rev Genomics Hum Genet. 2010;11:133–59. PubMed PMID: 20590430. Epub 2010/07/02. eng.

    Google Scholar 

  54. 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. PubMed PMID: ISI:000088767700049.

    Google Scholar 

  55. 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.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  56. Abd El-Rehim DM, Ball G, Pinder SE, Rakha E, Paish C, Robertson JF, et al. High-throughput protein expression analysis using tissue microarray technology of a large well-characterised series identifies biologically distinct classes of breast cancer confirming recent cDNA expression analyses. Int J Cancer. 2005;116(3):340–50.

    Article  CAS  PubMed  Google Scholar 

  57. Foekens JA, Atkins D, Zhang Y, Sweep FC, Harbeck N, Paradiso A, et al. Multicenter validation of a gene expression-based prognostic signature in lymph node-negative primary breast cancer. J Clin Oncol. 2006;24(11):1665–71.

    Article  CAS  PubMed  Google Scholar 

  58. van ’t Veer LJ, Dai H, van de Vijver MJ, He YD, Hart AA, Mao M, et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature. 2002;415(6871):530–6.

    Article  Google Scholar 

  59. Wang Y, Klijn JG, Zhang Y, Sieuwerts AM, Look MP, Yang F, et al. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet. 2005;365(9460):671–9. PubMed PMID: 15721472.

    Google Scholar 

  60. Ma XJ, Wang Z, Ryan PD, Isakoff SJ, Barmettler A, Fuller A, et al. A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen. Cancer Cell. 2004;5(6):607–16.

    Article  CAS  PubMed  Google Scholar 

  61. Zhang Y, Sieuwerts AM, McGreevy M, Casey G, Cufer T, Paradiso A, et al. The 76-gene signature defines high-risk patients that benefit from adjuvant tamoxifen therapy. Breast Cancer Res Treat. 2009;116(2):303–9.

    Article  CAS  PubMed  Google Scholar 

  62. 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.

    Article  CAS  PubMed  Google Scholar 

  63. Potti A, Dressman HK, Bild A, Riedel RF, Chan G, Sayer R, et al. Genomic signatures to guide the use of chemotherapeutics. Nat Med. 2006;12(11):1294–300.

    Article  CAS  PubMed  Google Scholar 

  64. Ma XJ, Salunga R, Tuggle JT, Gaudet J, Enright E, McQuary P, et al. Gene expression profiles of human breast cancer progression. Proc Natl Acad Sci USA. 2003;100(10):5974–9.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  65. Schuetz CS, Bonin M, Clare SE, Nieselt K, Sotlar K, Walter M, et al. Progression-specific genes identified by expression profiling of matched ductal carcinomas in situ and invasive breast tumors, combining laser capture microdissection and oligonucleotide microarray analysis. Cancer Res. 2006;66(10):5278–86.

    Article  CAS  PubMed  Google Scholar 

  66. Korkola JE, DeVries S, Fridlyand J, Hwang ES, Estep AL, Chen YY, et al. Differentiation of lobular versus ductal breast carcinomas by expression microarray analysis. Cancer Res. 2003;63(21):7167–75.

    CAS  PubMed  Google Scholar 

  67. Zhao H, Langerod A, Ji Y, Nowels KW, Nesland JM, Tibshirani R, et al. Different gene expression patterns in invasive lobular and ductal carcinomas of the breast. Mol Biol Cell. 2004;15(6):2523–36.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  68. West M, Blanchette C, Dressman H, Huang E, Ishida S, Spang R, et al. Predicting the clinical status of human breast cancer by using gene expression profiles. Proc Natl Acad Sci USA. 2001;98(20):11462–7.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  69. Huang E, Cheng SH, Dressman H, Pittman J, Tsou MH, Horng CF, et al. Gene expression predictors of breast cancer outcomes. Lancet. 2003;361(9369):1590–6.

    Article  CAS  PubMed  Google Scholar 

  70. 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.

    Article  CAS  PubMed  Google Scholar 

  71. Habashy HO, Powe DG, Abdel-Fatah TM, Gee JM, Nicholson RI, Green AR, et al. A review of the biological and clinical characteristics of luminal-like oestrogen receptor-positive breast cancer. Histopathology. 2012;60(6):854–63. PubMed PMID: 21906125. Epub 2011/09/13. eng.

    Google Scholar 

  72. Sotiriou C, Neo SY, McShane LM, Korn EL, Long PM, Jazaeri A, et al. Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci USA. 2003;100(18):10393–8.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  73. Rakha EA, Soria D, Green AR, Lemetre C, Powe DG, Nolan CC, et al. Nottingham Prognostic Index Plus (NPI+): a modern clinical decision making tool in breast cancer. Br J Cancer. 2014;110(7):1688–97. PubMed PMID: 24619074. Pubmed Central PMCID: 3974073.

    Google Scholar 

  74. 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. PubMed PMID: 17493263. Pubmed Central PMCID: 1929138.

    Google Scholar 

  75. Farmer P, Bonnefoi H, Becette V, Tubiana-Hulin M, Fumoleau P, Larsimont D, et al. Identification of molecular apocrine breast tumours by microarray analysis. Oncogene. 2005;24(29):4660–71.

    Article  CAS  PubMed  Google Scholar 

  76. Sorlie T, Tibshirani R, Parker J, Hastie T, Marron JS, Nobel A, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci USA. 2003;100(14):8418–23. PubMed PMID: ISI:000184222500069.

    Google Scholar 

  77. Sotiriou C, Neo SY, McShane LM, Korn EL, Long PM, Jazaeri A, et al. Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci USA. 2003;100(18):10393–8. PubMed PMID: ISI:000185119300048.

    Google Scholar 

  78. Anna Bergamaschi YHKPWTSTH-BPELRTA-LB-DJRP. Distinct patterns of DNA copy number alteration are associated with different clinicopathological features and gene-expression subtypes of breast cancer. Genes Chromosom Cancer. 2006;45(11):1033–40.

    Article  Google Scholar 

  79. Dairkee SH, Ljung BM, Smith H, Hackett A. Immunolocalization of a human basal epithelium specific keratin in benign and malignant breast disease. Breast Cancer Res Treat. 1987;10(1):11–20.

    Article  CAS  PubMed  Google Scholar 

  80. Santini D, Ceccarelli C, Taffurelli M, Pileri S, Marrano D. Differentiation pathways in primary invasive breast carcinoma as suggested by intermediate filament and biopathological marker expression. J Pathol. 1996;179(4):386–91.

    Article  CAS  PubMed  Google Scholar 

  81. van de Vijver MJ, He YD, van’t Veer LJ, Dai H, Hart AA, Voskuil DW, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med. 2002;347(25):1999–2009.

    Article  PubMed  Google Scholar 

  82. Savage K, Lambros MB, Robertson D, Jones RL, Jones C, Mackay A, et al. Caveolin 1 is overexpressed and amplified in a subset of basal-like and metaplastic breast carcinomas: a morphologic, ultrastructural, immunohistochemical, and in situ hybridization analysis. Clin Cancer Res. 2007;13(1):90–101.

    Article  CAS  PubMed  Google Scholar 

  83. Yehiely F, Moyano JV, Evans JR, Nielsen TO, Cryns VL. Deconstructing the molecular portrait of basal-like breast cancer. Trends Mol Med. 2006;12(11):537–44.

    Article  CAS  PubMed  Google Scholar 

  84. Hu Z, Fan C, Oh DS, Marron JS, He X, Qaqish BF, et al. The molecular portraits of breast tumors are conserved across microarray platforms. BMC Genom. 2006;7:96.

    Article  Google Scholar 

  85. Wilhelmsen K, Litjens SH, Sonnenberg A. Multiple functions of the integrin alpha6beta4 in epidermal homeostasis and tumorigenesis. Mol Cell Biol. 2006;26(8):2877–86.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  86. Vogelstein B, Kinzler KW. Cancer genes and the pathways they control. Nat Med. 2004;10(8):789–99.

    Article  CAS  PubMed  Google Scholar 

  87. Koshikawa N, Giannelli G, Cirulli V, Miyazaki K, Quaranta V. Role of cell surface metalloprotease MT1-MMP in epithelial cell migration over laminin-5. J Cell Biol. 2000;148(3):615–24.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  88. Hanahan D, Weinberg RA. The hallmarks of cancer. Cell. 2000;100(1):57–70.

    Article  CAS  PubMed  Google Scholar 

  89. Dumont N, Arteaga CL. Targeting the TGF beta signaling network in human neoplasia. Cancer Cell. 2003;3(6):531–6.

    Article  CAS  PubMed  Google Scholar 

  90. Fan C, Oh DS, Wessels L, Weigelt B, Nuyten DS, Nobel AB, et al. Concordance among gene-expression-based predictors for breast cancer. N Engl J Med. 2006;355(6):560–9.

    Article  CAS  PubMed  Google Scholar 

  91. Bergamaschi A, Kim YH, Wang P, Sorlie T, Hernandez-Boussard T, Lonning PE, et al. Distinct patterns of DNA copy number alteration are associated with different clinicopathological features and gene-expression subtypes of breast cancer. Genes Chromosomes Cancer. 2006;45(11):1033–40.

    Article  CAS  PubMed  Google Scholar 

  92. Chin K, DeVries S, Fridlyand J, Spellman PT, Roydasgupta R, Kuo WL, et al. Genomic and transcriptional aberrations linked to breast cancer pathophysiologies. Cancer Cell. 2006;10(6):529–41.

    Article  CAS  PubMed  Google Scholar 

  93. Vincent-Salomon A, Gruel N, Lucchesi C, Mac Grogan G, Dendale R, Sigal-Zafrani B, et al. Identification of typical medullary breast carcinoma as a genomic sub-group of basal-like carcinomas, a heterogeneous new molecular entity. Breast Cancer Res. 2007;9(2):R24.

    Article  PubMed Central  PubMed  Google Scholar 

  94. Rakha E, Reis-Filho JS. Basal-like breast carcinoma: from expression profiling to routine practice. Arch Pathol Lab Med. 2009;133(6):860–8. PubMed PMID: 19492878. Epub 2009/06/06. eng.

    Google Scholar 

  95. Turner NC, Reis-Filho JS. Basal-like breast cancer and the BRCA1 phenotype. Oncogene. 2006;25(43):5846–53.

    Article  CAS  PubMed  Google Scholar 

  96. Leidy J, Khan A, Kandil D. Basal-like breast cancer: update on clinicopathologic, immunohistochemical, and molecular features. Arch Pathol Lab Med. 2014;138(1):37–43. PubMed PMID: 24377810. Epub 2014/01/01. eng.

    Google Scholar 

  97. Weigelt B, Baehner FL, Reis-Filho JS. The contribution of gene expression profiling to breast cancer classification, prognostication and prediction: a retrospective of the last decade. J Pathol. 2010;220(2):263–80.

    CAS  PubMed  Google Scholar 

  98. Weigelt B, Mackay A, A’Hern R, Natrajan R, Tan DS, Dowsett M, et al. Breast cancer molecular profiling with single sample predictors: a retrospective analysis. Lancet Oncol. 2010;11(4):339–49.

    Article  CAS  PubMed  Google Scholar 

  99. Sorlie T, Tibshirani R, Parker J, Hastie T, Marron JS, Nobel A, et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci U S A. 2003;100(14):8418–23.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  100. Calza S, Hall P, Auer G, Bjohle J, Klaar S, Kronenwett U, et al. Intrinsic molecular signature of breast cancer in a population-based cohort of 412 patients. Breast Cancer Res. 2006;8(4):R34.

    Article  PubMed Central  PubMed  Google Scholar 

  101. 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. PubMed PMID: 22522925. Pubmed Central PMCID: 3440846.

    Google Scholar 

  102. Bertucci F, Finetti P, Cervera N, Charafe-Jauffret E, Mamessier E, Adelaide J, et al. Gene expression profiling shows medullary breast cancer is a subgroup of basal breast cancers. Cancer Res. 2006;66(9):4636–44.

    Article  CAS  PubMed  Google Scholar 

  103. Vincent-Salomon A, Gruel N, Lucchesi C, MacGrogan G, Dendale R, Sigal-Zafrani B, et al. Identification of typical medullary breast carcinoma as a genomic sub-group of basal-like carcinomas, a heterogeneous new molecular entity. Breast Cancer Res. 2007;9(2):R24. PubMed PMID: 17417968. Pubmed Central PMCID: PMC1868916. Epub 2007/04/10. eng.

    Google Scholar 

  104. Weigelt B, Kreike B, Reis-Filho JS. Metaplastic breast carcinomas are basal-like breast cancers: a genomic profiling analysis. Breast Cancer Res Treat. 2009;117(2):273–80.

    Article  CAS  PubMed  Google Scholar 

  105. Weigelt B, Horlings HM, Kreike B, Hayes MM, Hauptmann M, Wessels LF, et al. Refinement of breast cancer classification by molecular characterization of histological special types. J Pathol. 2008;216(2):141–50.

    Article  CAS  PubMed  Google Scholar 

  106. Weigelt B, Geyer FC, Reis-Filho JS. Histological types of breast cancer: how special are they? Mol Oncol. 2010;4(3):192–208.

    Google Scholar 

  107. 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.

    Article  CAS  PubMed  Google Scholar 

  108. Paik S, Shak S, Tang G, Kim C, Baker J, Cronin M, et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med. 2004;351(27):2817–26.

    Article  CAS  PubMed  Google Scholar 

  109. Wirapati P, Sotiriou C, Kunkel S, Farmer P, Pradervand S, Haibe-Kains B, et al. Meta-analysis of gene expression profiles in breast cancer: toward a unified understanding of breast cancer subtyping and prognosis signatures. Breast Cancer Res. 2008;10(4):R65.

    Article  PubMed Central  PubMed  Google Scholar 

  110. Cheang MCU, van de Rijn M, Nielsen TO. Gene expression profiling of breast cancer. Annu Rev Pathol. 2008;3(1):67–97.

    Article  CAS  PubMed  Google Scholar 

  111. Prat A, Parker JS, Fan C, Cheang MC, 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. PubMed PMID: 22532584. Pubmed Central PMCID: 3477878.

    Google Scholar 

  112. Gyorffy B, Hatzis C, Sanft T, Hofstatter E, Aktas B, Pusztai L. Multigene prognostic tests in breast cancer: past, present, future. Breast Cancer Res. 2015;17(1):11. PubMed PMID: doi:10.1186/s13058-015-0514-2.

  113. Kim C, Paik S. Gene-expression-based prognostic assays for breast cancer. Nat Rev Clin Oncol. 2010;7(6):340–7. PubMed PMID: 20440284. Epub 2010/05/05. eng.

    Google Scholar 

  114. Azim HA, Jr., Michiels S, Zagouri F, Delaloge S, Filipits M, Namer M, et al. Utility of prognostic genomic tests in breast cancer practice: The IMPAKT 2012 Working Group Consensus Statement. Ann Oncol (official journal of the European Society for Medical Oncology/ESMO). 2013;24(3):647–54. PubMed PMID: 23337633. Epub 2013/01/23. eng.

    Google Scholar 

  115. Rakha EA, Elsheikh SE, Aleskandarany MA, Habashi HO, Green AR, Powe DG, et al. Triple-negative breast cancer: distinguishing between basal and nonbasal subtypes. Clin Cancer Res. 2009;15(7):2302–10.

    Article  CAS  PubMed  Google Scholar 

  116. 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.

    Article  CAS  PubMed  Google Scholar 

  117. Abd El-Rehim DM, Ball G, Pinder SE, Rakha E, Paish C, Robertson JFR, et al. High-throughput protein expression analysis using tissue microarray technology of a large well-characterised series identifies biologically distinct classes of breast cancer confirming recent cDNA expression analyses. Int J Cancer. 2005;116(3):340–50. PubMed PMID: ISI:000230466100002.

    Google Scholar 

  118. Blows FM, Driver KE, Schmidt MK, Broeks A, van Leeuwen FE, Wesseling J, et al. Subtyping of breast cancer by immunohistochemistry to investigate a relationship between subtype and short and long term survival: a collaborative analysis of data for 10,159 cases from 12 studies. PLoS Med. 2010;7(5):e1000279. PubMed PMID: 20520800. Pubmed Central PMCID: 2876119.

    Google Scholar 

  119. Rakha EA, El-Sayed ME, Reis-Filho JS, Ellis IO. Expression profiling technology: its contribution to our understanding of breast cancer. Histopathology. 2008;52(1):67–81.

    Article  CAS  PubMed  Google Scholar 

  120. Goldhirsch A, Winer EP, Coates AS, Gelber RD, Piccart-Gebhart M, Thurlimann B, et al. Personalizing the treatment of women with early breast cancer: highlights of the St Gallen International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013. Ann Oncol (official journal of the European Society for Medical Oncology/ESMO). 2013;24(9):2206–23. PubMed PMID: 23917950. Pubmed Central PMCID: PMC3755334. Epub 2013/08/07. eng.

    Google Scholar 

  121. Weinstein IB, Joe A. Oncogene addiction. Cancer Res. 2008;68(9):3077–80.

    Google Scholar 

  122. Aleskandarany MA, Green AR, Benhasouna AA, Barros FF, Neal K, Reis-Filho JS, et al. Prognostic value of proliferation assay in the luminal, HER2-positive, and triple-negative biologic classes of breast cancer. Breast Cancer Res. 2012;14(1):R3. PubMed PMID: 22225836. Pubmed Central PMCID: PMC3496118. Epub 2012/01/10. eng.

    Google Scholar 

  123. 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.

    Article  CAS  PubMed  Google Scholar 

  124. Livasy CA, Karaca G, Nanda R, Tretiakova MS, Olopade OI, Moore DT, et al. Phenotypic evaluation of the basal-like subtype of invasive breast carcinoma. Mod Pathol. 2006;19(2):264–71.

    Article  CAS  PubMed  Google Scholar 

  125. Badve S, Dabbs DJ, Schnitt SJ, Baehner FL, Decker T, Eusebi V, et al. Basal-like and triple-negative breast cancers: a critical review with an emphasis on the implications for pathologists and oncologists. Mod Pathol. 2011;24(2):157–67.

    Google Scholar 

  126. Green AR, Powe DG, Rakha EA, Soria D, Lemetre C, Nolan CC, et al. Identification of key clinical phenotypes of breast cancer using a reduced panel of protein biomarkers. Br J Cancer. 2013;109(7):1886–94.

    Google Scholar 

  127. Soria D, Garibaldi Jm, Ambrogi F, Green AR, Powe D, Rakha E, Macmillan RD, et al. A methodology to identify consensus classes from clustering algorithms applied to immunohistochemical data from breast cancer patients. 2010 20100308 DCOM- 20100701(1879-0534 (Electronic)). eng.

    Google Scholar 

  128. Green AR, Powe DG, Rakha EA, Soria D, Lemetre C, Nolan CC, et al. Identification of key clinical phenotypes of breast cancer using a reduced panel of protein biomarkers. Br J Cancer. 2013;109(7):1886–94. PubMed PMID: 24008658. Pubmed Central PMCID: 3790179.

    Google Scholar 

  129. Allred DC. Commentary: hormone receptor testing in breast cancer: a distress signal from Canada. Oncologist. 2008;13(11):1134–6.

    Article  PubMed  Google Scholar 

  130. Simon R, Radmacher MD, Dobbin K, McShane LM. Pitfalls in the use of DNA microarray data for diagnostic and prognostic classification. J Natl Cancer Inst. 2003;95(1):14–8.

    Article  CAS  PubMed  Google Scholar 

  131. Forster T, Roy D, Ghazal P. Experiments using microarray technology: limitations and standard operating procedures. J Endocrinol. 2003;178(2):195–204.

    Article  CAS  PubMed  Google Scholar 

  132. Jansen MP, Foekens JA, van Staveren IL, Dirkzwager-Kiel MM, Ritstier K, Look MP, et al. Molecular classification of tamoxifen-resistant breast carcinomas by gene expression profiling. J Clin Oncol. 2005;23(4):732–40.

    Article  CAS  PubMed  Google Scholar 

  133. Loi S, Haibe-Kains B, Desmedt C, Wirapati P, Lallemand F, Tutt AM, et al. Predicting prognosis using molecular profiling in estrogen receptor-positive breast cancer treated with tamoxifen. BMC Genom. 2008;9:239.

    Article  Google Scholar 

  134. 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.

    Article  PubMed Central  PubMed  Google Scholar 

  135. Pollack JR, Sorlie T, Perou CM, Rees CA, Jeffrey SS, Lonning PE, et al. Microarray analysis reveals a major direct role of DNA copy number alteration in the transcriptional program of human breast tumors. Proc Natl Acad Sci USA. 2002;99(20):12963–8.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  136. Fritz B, Schubert F, Wrobel G, Schwaenen C, Wessendorf S, Nessling M, et al. Microarray-based copy number and expression profiling in dedifferentiated and pleomorphic liposarcoma. Cancer Res. 2002;62(11):2993–8.

    CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Histopathology, Division of Cancer and Stem Cells, School of Medicine, The University of Nottingham and Nottingham University Hospitals NHS Trust, Nottingham City Hospital, Nottingham, NG5 1PB, UK

    Mohammed A. Aleskandarany, Ian O. Ellis & Emad A. Rakha

Authors
  1. Mohammed A. Aleskandarany
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ian O. Ellis
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Emad A. Rakha
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Emad A. Rakha .

Editor information

Editors and Affiliations

  1. Department of Pathology, University of Massachusetts Medical School, UMassMemorial Medical Center, Worcester, Massachusetts, USA

    Ashraf Khan

  2. Department of Histopathology, University of Nottingham, Nottingham, United Kingdom

    Ian O. Ellis

  3. Leeds Institute of Cancer and Pathology, St. James University Hospital, Leeds, West Yorkshire, United Kingdom

    Andrew M. Hanby

  4. Department of Pathology, University of Massachusetts Medical School, UMassMemorial Medical Center, Worcester, Massachusetts, USA

    Ediz F. Cosar

  5. Department of Histopathology, University of Nottingham, Nottingham, United Kingdom

    Emad A. Rakha

  6. Department of Pathology, University of Massachusetts Medical School, UMassMemorial Medical Center, Worcester, Massachusetts, USA

    Dina Kandil

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Science+Business Media New York

About this chapter

Cite this chapter

Aleskandarany, M.A., Ellis, I.O., Rakha, E.A. (2015). Molecular Classification of Breast Cancer. In: Khan, A., Ellis, I., Hanby, A., Cosar, E., Rakha, E., Kandil, D. (eds) Precision Molecular Pathology of Breast Cancer. Molecular Pathology Library, vol 10. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2886-6_10

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-2886-6_10

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4939-2885-9

  • Online ISBN: 978-1-4939-2886-6

  • eBook Packages: MedicineMedicine (R0)

Publish with us

Policies and ethics

Search

Navigation