Advertisement

Molecular Classification of Breast Tumors

Toward Improved Diagnostics and Treatments
  • Therese Sørlie
Part of the Methods in Molecular Biology™ book series (MIMB, volume 360)

Summary

Recent advances in gene expression profiling and other “omics” technologies have revolutionized cancer research and hold the potential of also revolutionizing clinical practice. These high-throughout approaches have radically changed our ability to study cells and tissues in a more comprehensive way. Combined with advanced bioinformatics and the possibility to simulate biological processes in computers, this field of “systems biology” allows us to study the organism as a whole entity. This chapter describes the molecular classification and characterization of breast tumors into distinct subtypes by using DNA microarrays and discusses the statistical relationships of the subgroups with clinical features of the disease.

Key Words

Breast cancer DNA microarrays gene expression patterns prediction prognosis 

Notes

Acknowledgments

All colleagues who have contributed to these projects over the years are acknowledged.

References

  1. 1.
    Lønning, P. E., Sørlie, T., and Børresen-Dale, A.-L. (2005) Genomics in breast Cancer—therapeutic implications. Nat. Clin. Prac. Oncol. 2, 26–33.CrossRefGoogle Scholar
  2. 2.
    Schena, M., Shalon, D., Davis, R. W., and Brown, P. O. (1995) Quantitative monitoring of gene expression patterns with a complementary DNA microarray [see comments]. Science 270, 467–470.CrossRefPubMedGoogle Scholar
  3. 3.
    Novoradovskaya, N., Whitfield, M. L., Basehore, L. S., et al. (2004) Universal Reference RNA as a standard for microarray experiments. BMC Genomics 5, 20.CrossRefPubMedGoogle Scholar
  4. 4.
    Dudoit, S., Gentleman, R. C., and Quackenbush, J. (2003) Open source software for the analysis of microarray data. Biotechniques Suppl, 45–51.Google Scholar
  5. 5.
    Quackenbush, J. (2001) Computational analysis of microarray data. Nat. Rev. Genet. 2, 418–427.CrossRefPubMedGoogle Scholar
  6. 6.
    Rhodes, D. R., and Chinnaiyan, A. M. (2005) Integrative analysis of the cancer transcriptome. Nat. Genet. 37Suppl, S31-S37.Google Scholar
  7. 7.
    Eisen, M. B., Spellman, P. T., Brown, P. O., and Botstein, D. (1998) Cluster analysis, and display of genome-wide expression patterns. Proc. Natl. Acad. Sci. USA 95, 14,863–14,868.CrossRefPubMedGoogle Scholar
  8. 8.
    Brown, M. P., Grundy, W. N., Lin, D., et al. (2000) Knowledge-based analysis of microarray gene expression data by using support vector machines. Proc. Natl. Acad. Sci. USA 97, 262–267.CrossRefPubMedGoogle Scholar
  9. 9.
    Khan, J., Wei, J. S., Ringner, M., et al. (2001) Classification and diagnostic prediction of cancers using gene expression profiling and artificial neural networks. Nat. Med. 7, 673–679.CrossRefPubMedGoogle Scholar
  10. 10.
    Tibshirani, R., Hastie, T., Narasimhan, B., and Chu, G. (2002) Diagnosis of multiple cancer types by shrunken centroids of gene expression. Proc. Natl. Acad. Sci. USA 99, 6567–6572.CrossRefPubMedGoogle Scholar
  11. 11.
    Tusher,V. G., Tibshirani, R., and Chu, G. (2001) Significance analysis of microarrays applied to the ionizing radiation response. Proc. Natl. Acad. Sci. USA 98, 5116–5121.CrossRefPubMedGoogle Scholar
  12. 12.
    Ball, C. A., Sherlock, G., Parkinson, H., et al. (2002) Standards for microarray data. Science 298, 539.CrossRefPubMedGoogle Scholar
  13. 13.
    Yauk, C. L., Berndt, M. L., Williams, A., and Douglas, G. R. (2004) Comprehensive comparison of six microarray technologies. Nucleic Acids Res. 32, e124.CrossRefPubMedGoogle Scholar
  14. 13a.
    Sørlie, T., Wang, Y., Xiao, C., et al. (2006) Distinct molecular mechanisms underlying clinically relevant subtypes of breast cancer: gene expression analyses across three different platforms. BMC Genomics 7, 127.CrossRefPubMedGoogle Scholar
  15. 14.
    Perou, C. M., Sorlie, T., Eisen, M. B., et al. (2000) Molecular portraits of human breast tumours. Nature 406, 747–752.CrossRefPubMedGoogle Scholar
  16. 15.
    Perou, C. M., Jeffrey, S. S., van de Rijn, M., et al. (1999) Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proc. Natl. Acad. Sci. USA 96, 9212–9217.CrossRefPubMedGoogle Scholar
  17. 16.
    Ross, D. T., Scherf, U., Eisen, M. B., et al. (2000) Systematic variation in gene expression patterns in human cancer cell lines. Nat. Genet. 24, 227–235.CrossRefPubMedGoogle Scholar
  18. 17.
    Whitfield, M. L., Sherlock, G., Saldanha, A. J., et al. (2002) Identification of genes periodically expressed in the human cell cycle and their expression in tumors. Mol. Biol. Cell 13, 1977–2000.CrossRefPubMedGoogle Scholar
  19. 18.
    Aas, T., Borresen, A. L., Geisler, S., et al. (1996) Specific P53 mutations are associated with de novo resistance to doxorubicin in breast cancer patients. Nat. Med. 2, 811–814.CrossRefPubMedGoogle Scholar
  20. 19.
    Geisler, SI., Lonning, P. E., Aas, T., et al. (2001) Influence of TP53 gene alterations and c-erbB-2 expression on the response to treatment with doxorubicin in locally advanced breast cancer. Cancer Res. 61, 2505–2512.PubMedGoogle Scholar
  21. 20.
    Geisler, S., Borresen-Dale, A. L., Johnsen, H., et al. (2003) TP53 Gene Mutations Predict the Response to Neoadjuvant Treatment with 5-Fluorouracil and Mitomycin in Locally Advanced Breast Cancer. Clin. Cancer Res. 9, 5582–5588.PubMedGoogle Scholar
  22. 21.
    Weigelt, B., Glas, A. M., Wessels, L. F., Witteveen, A. T., Peterse, J. L., and van’t Veer, L. J. (2003) Gene expression profiles of primary breast tumors maintained in distant metastases. Proc. Natl. Acad. Sci. USA 100, 15,901–15,905.CrossRefPubMedGoogle Scholar
  23. 22.
    Sorlie, T., Tibshirani, R., Parker, J., et al. (2003) Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc. Natl. Acad. Sci. USA 100, 8418–8423.CrossRefPubMedGoogle Scholar
  24. 23.
    Sorlie, T., Perou, C. M., Tibshirani, R., et al. (2001) Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl. Acad. Sci. USA 98, 10,869–10,874.CrossRefPubMedGoogle Scholar
  25. 24.
    Bertucci, F., Finetti, P., Rougemont, J., et al. (2005) Gene expression profiling identifies molecular subtypes of inflammatory breast cancer. Cancer Res. 65, 2170–2178.CrossRefPubMedGoogle Scholar
  26. 25.
    Chang, H. Y., Nuyten, D. S., Sneddon, J. B., et al. (2005) Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival. Proc. Natl. Acad. Sci. USA 102, 3738–3743.CrossRefPubMedGoogle Scholar
  27. 26.
    Sotiriou, C., Neo, S. Y., McShane, L. M., et al. (2003) Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc. Natl. Acad. Sci. USA 100, 10,393–10,398.CrossRefPubMedGoogle Scholar
  28. 27.
    Wang, Z. C., Lin, M., Wei, L. J., et al. (2004) Loss of heterozygosity and its correlation with expression profiles in subclasses of invasive breast cancers. Cancer Res. 64, 64–71.CrossRefPubMedGoogle Scholar
  29. 28.
    Yu, K., Lee, C. H., Tan, P. H., and Tan, P. (2004) Conservation of breast cancer molecular subtypes and transcriptional patterns of tumor progression across distinct ethnic populations. Clin. Cancer Res. 10, 5508–5517.CrossRefPubMedGoogle Scholar
  30. 29.
    Zhao, H., Langerod, A., Ji, Y., et al. (2004) Different gene expression patterns in invasive lobular and ductal carcinomas of the breast. Mol. Biol. Cell 15, 2523–2536.CrossRefPubMedGoogle Scholar
  31. 30.
    van’t Veer, L. J., Dai, H., van de Vijver, M. J., et al. (2002) Gene expression profiling predicts clinical outcome of breast cancer. Nature 415, 530–536.CrossRefGoogle Scholar
  32. 31.
    Slamon, D. J., Clark, G. M., Wong, S. G., Levin, W. J., Ullrich, A., and McGuire, W. L. (1987) Human breast cancer: correlation of relapse and survival with amplification of the HER-2/neu oncogene. Science 235, 177–182.CrossRefPubMedGoogle Scholar
  33. 32.
    Ahr, A., Karn, T., Solbach, C., et al. (2002) Identification of high risk breast-cancer patients by gene expression profiling. Lancet 359, 131–132.CrossRefPubMedGoogle Scholar
  34. 33.
    Huang, E., Cheng, S. H., Dressman, H., et al. (2003) Gene expression predictors of breast cancer outcomes. Lancet 361, 1590–1596.CrossRefPubMedGoogle Scholar
  35. 34.
    Ma, X. J., Wang, Z., Ryan, P. D., et al. (2004) A two-gene expression ratio predicts clinical outcome in breast cancer patients treated with tamoxifen. Cancer Cell 5, 607–616.CrossRefPubMedGoogle Scholar
  36. 35.
    van de Vijver, M. J., He, Y. D., van’t Veer, L. J., et al. (2002) A gene-expression signature as a predictor of survival in breast cancer. N. Engl. J. Med. 347, 1999–2009.CrossRefPubMedGoogle Scholar
  37. 36.
    Onda, M., Emi, M., Nagai, H., et al. (2004) Gene expression patterns as marker for 5-year postoperative prognosis of primary breast cancers. J. Cancer Res. Clin. Oncol. 130, 537–545.CrossRefPubMedGoogle Scholar
  38. 37.
    Nagahata, T., Onda, M., Emi, M., et al. (2004) Expression profiling to predict postoperative prognosis for estrogen receptor-negative breast cancers by analysis of 25, 344 genes on a cDNA microarray. Cancer Sci. 95, 218–225.CrossRefPubMedGoogle Scholar
  39. 38.
    Eden, P., Ritz, C., Rose, C., Ferno, M., and Peterson, C. (2004) “Good Old” clinical markers have similar power in breast cancer prognosis as microarray gene expression profilers. Eur. J. Cancer 40, 1837–1841.CrossRefPubMedGoogle Scholar
  40. 39.
    Sasco, A. J. (2003) Breast cancer and the environment. Horm. Res. 60Suppl 3, 50.CrossRefPubMedGoogle Scholar
  41. 40.
    Early Breast Cancer Trialists’ Collaborative Group (1998) Tamoxifen for early breast cancer: an overview of the randomised trials. Early Breast Cancer Trialists’ Collaborative Group. Lancet 351, 1451–1467.CrossRefGoogle Scholar
  42. 41.
    Citron, M. L., Berry, D. A., Cirrincione, C., et al. (2003) Randomized trial of dose-dense versus conventionally scheduled and sequential versus concurrent combination chemotherapy as postoperative adjuvant treatment of node-positive primary breast cancer: first report of Intergroup Trial C9741/Cancer and Leukemia Group B Trial 9741. J. Clin. Oncol. 21, 1431–1439.CrossRefPubMedGoogle Scholar
  43. 42.
    Ayers, M., Symmans, W. F., Stec, J., et al. (2004) Gene Expression Profiles Predict Complete Pathologic Response to Neoadjuvant Paclitaxel and Fluorouracil, Doxorubicin, and Cyclophosphamide Chemotherapy in Breast Cancer. J. Clin. Oncol. 22, 2284–2293.CrossRefPubMedGoogle Scholar
  44. 43.
    Chang, J. C., Wooten, E. C., Tsimelzon, A., et al. (2003) Gene expression profiling for the prediction of therapeutic response to docetaxel in patients with breast cancer. Lancet 362, 362–369.CrossRefPubMedGoogle Scholar
  45. 44.
    Iwao-Koizumi, K., Matoba, R., Ueno, N., et al. (2005) Prediction of docetaxel response in human breast cancer by gene expression profiling. J. Clin. Oncol. 23, 422–431.CrossRefPubMedGoogle Scholar
  46. 45.
    Jansen, M. P., Foekens, J. A., van Staveren, I. L., et al. (2005) Molecular classification of tamoxifen-resistant breast carcinomas by gene expression profiling. J. Clin. Oncol. 23, 732–740.CrossRefPubMedGoogle Scholar
  47. 46.
    Kannan, K., Kaminski, N., Rechavi, G., et al. (2001) DNA microarray analysis of genes involved in p53 mediated apoptosis: activation of Apaf-1. Oncogene 20, 3449–3455.CrossRefPubMedGoogle Scholar
  48. 47.
    Yoon, H., Liyanarachchi, S., Wright, F. A., Davuluri, R., Lockman, J. C., de la, C. A., and Pellegata, N. S. (2002) Gene expression profiling of isogenic cells with different TP53 gene dosage reveals numerous genes that are affected by TP53 dosage and identifies CSPG2 as a direct target of p53. Proc. Natl. Acad. Sci. USA 99, 15,632–15,637.CrossRefPubMedGoogle Scholar
  49. 48.
    Schaner, M. E., Ross, D. T., Ciaravino, G., et al.. (2003) Gene expression patterns in ovarian carcinomas. Mol. Biol. Cell 14, 4376–4386.CrossRefPubMedGoogle Scholar
  50. 49.
    Alizadeh, A. A., Eisen, M. B., Davis, R. E., et al. (2000) Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling [see comments]. Nature 403, 503–511.CrossRefPubMedGoogle Scholar
  51. 50.
    Chen, X., Cheung, S. T., So, S., et al. (2002) Gene expression patterns in human liver cancers. Mol. Biol. Cell 13, 1929–1939.CrossRefPubMedGoogle Scholar
  52. 51.
    Lapointe, J., Li, C., Higgins, J. P., Van de, R. M., et al. (2004) Gene expression profiling identifies clinically relevant subtypes of prostate cancer. Proc. Natl. Acad. Sci. USA 101, 811–816.CrossRefPubMedGoogle Scholar
  53. 52.
    Ford, D., Easton, D. F., Stratton, M., et al. (1998) Genetic heterogeneity and penetrance analysis of the BRCA1 and BRCA2 genes in breast cancer families. The Breast Cancer Linkage Consortium. Am. J. Hum. Genet.,62, 676–689.CrossRefPubMedGoogle Scholar
  54. 53.
    Hedenfalk, I., Duggan, D., Chen, Y., et al. (2001) Gene-expression profiles in hereditary breast cancer. N. Engl. J. Med. 344, 539–548.CrossRefPubMedGoogle Scholar
  55. 54.
    Armes, J. E., Trute, L., White, D., et al. (1999) Distinct molecular pathogeneses of early-onset breast cancers in BRCA1 and BRCA2 mutation carriers: a population-based study. Cancer Res. 59, 2011–2017.PubMedGoogle Scholar
  56. 55.
    Lakhani, S. R., Reis-Filho, J. S., Fulford, L., et al. (2005) Prediction of BRCA1 status in patients with breast cancer using estrogen receptor and basal phenotype. Clin. Cancer Res. 11, 5175–5180.CrossRefPubMedGoogle Scholar
  57. 56.
    Fan, S., Wang, J., Yuan, R., Ma, Y., et al. (1999) BRCA1 inhibition of estrogen receptor signaling in transfected cells. Science, 284, 1354–1356.CrossRefPubMedGoogle Scholar
  58. 57.
    Razandi, M., Pedram, A., Rosen, E. M., and Levin, E. R. (2004) BRCA1 inhibits membrane estrogen and growth factor receptor signaling to cell proliferation in breast cancer. Mol. Cell Biol. 24, 5900–5913.CrossRefPubMedGoogle Scholar
  59. 58.
    Finlin, B. S., Gau, C. L., Murphy, G. A., et al. (2001) RERG is a novel ras-related, estrogen-regulated and growth-inhibitory gene in breast cancer. J. Biol. Chem. 276, 42,259–42,267.CrossRefPubMedGoogle Scholar
  60. 59.
    Balint, E. E. and Vousden, K. H. (2001) Activation and activities of the p53 tumour suppressor protein. Br. J. Cancer 85, 1813–1823.CrossRefGoogle Scholar
  61. 60.
    Guimaraes, D. P. and Hainaut, P. (2002) TP53: a key gene in human cancer. Biochimie,84, 83–93.CrossRefPubMedGoogle Scholar
  62. 61.
    Vogelstein, B., Lane, D., and Levine, A. J. (2000) Surfing the p53 network. Nature 408, 307–310.CrossRefPubMedGoogle Scholar
  63. 62.
    Bergh, J., Norberg, T., Sjogren, S., Lindgren, A., and Holmberg, L. (1995) Complete sequencing of the p53 gene provides prognostic information in breast cancer patients, particularly in relation to adjuvant systemic therapy and radiotherapy. Nat. Med. 1, 1029–1034.CrossRefPubMedGoogle Scholar
  64. 63.
    Berns, E. M., Foekens, J. A., Vossen, R., et al. (2000) Complete sequencing of TP53 predicts poor response to systemic therapy of advanced breast cancer. Cancer Res. 60, 2155–2162.PubMedGoogle Scholar
  65. 64.
    Borresen, A. L., Andersen, T. I., Eyfjord, J. E., et al. (1995) TP53 mutations and breast cancer prognosis: particularly poor survival rates for cases with mutations in the zinc-binding domains. Genes Chromosomes Cancer 14, 71–75.CrossRefPubMedGoogle Scholar
  66. 65.
    Sorlie, T., Johnsen, H., Vu, P., Lind, G. E., Lothe, R., and Borresen-Dale, A. L. (2004) Mutation Screening of the TP53 Gene by Temporal Temperature Gradient Gel Electrophoresis. Methods Mol. Biol. 291, 207–216.Google Scholar
  67. 66.
    Nakopoulou, L. L., Alexiadou, A., Theodoropoulos, G. E., Lazaris, A. C., Tzonou, A., and Keramopoulos, A. (1996) Prognostic significance of the co-expression of p53 and c-erbB-2 proteins in breast cancer. J. Pathol. 179, 31–38.CrossRefPubMedGoogle Scholar
  68. 67.
    Sorlie, T. (2004) Molecular portraits of breast cancer: tumour subtypes as distinct disease entities. Eur. J. Cancer 40, 2667–2675.CrossRefPubMedGoogle Scholar
  69. 68.
    Pollack, J. R., Perou, C. M., Alizadeh, A. A., et al. (1999) Genome-wide analysis of DNA copy-number changes using cDNA microarrays. Nat. Genet. 23, 41–46.CrossRefPubMedGoogle Scholar
  70. 69.
    Pollack, J. R., Sorlie, T., Perou, C. M., et al. (2002) 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 99, 12,963–12,968.CrossRefPubMedGoogle Scholar
  71. 70.
    Forozan, F., Mahlamaki, E. H., Monni, O., et al. (2000) Comparative genomic hybridization analysis of 38 breast cancer cell lines: a basis for interpreting complementary DNA microarray data. Cancer Res. 60, 4519–4525.PubMedGoogle Scholar
  72. 71.
    Kallioniemi, A., Kallioniemi, O. P., Piper, J., et al. (1994) Detection and mapping of amplified DNA sequences in breast cancer by comparative genomic hybridization. Proc. Natl. Acad. Sci. USA 91, 2156–2160.CrossRefPubMedGoogle Scholar
  73. 72.
    Tirkkonen, M., Tanner, M., Karhu, R., Kallioniemi, A., Isola, J., and Kallioniemi, O. P. (1998) Molecular cytogenetics of primary breast cancer by CGH. Genes Chromosomes Cancer 21, 177–184.CrossRefPubMedGoogle Scholar
  74. 73.
    Hyman, E., Kauraniemi, P., Hautaniemi, et al. (2002) Impact of DNA amplification on gene expression patterns in breast cancer. Cancer Res. 62, 6240–6245.PubMedGoogle Scholar
  75. 74.
    Ramaswamy, S., Ross, K. N., Lander, E. S., and Golub, T., R. (2003) Amolecular signature of metastasis in primary solid tumors. Nat. Genet. 33, 49–54.CrossRefPubMedGoogle Scholar
  76. 75.
    Ein-Dor, L., Kela, I., Getz, G., Givol, D., and Domany, E. (2005) Outcome signature genes in breast cancer: is there a unique set? Bioinformatics 21, 171–178.CrossRefPubMedGoogle Scholar

Copyright information

© Humana Press Inc. 2007

Authors and Affiliations

  • Therese Sørlie
    • 1
  1. 1.Department of Genetics, Institute for Cancer Research, The Norwegian Radium HospitalUniversity of OsloOsloNorway

Personalised recommendations