Pharmaceutical Research

, Volume 23, Issue 9, pp 1951–1958 | Cite as

Heterogeneity of Breast Cancer among Patients and Implications for Patient Selection for Adjuvant Chemotherapy

  • Fabrice Andre
  • Lajos Pusztai
Expert Review



Although the benefits of adjuvant chemotherapy are not controversial, the absolute effect of such therapy is small. Therefore, there is a need to identify biomarkers that can help select patients with localized breast cancer for treatment. Despite intense research in this field, no biomarker has been shown to be useful to predict benefit of adjuvant chemotherapy in daily practice. This can partially be explained by the fact that breast cancer is composed of several distinct subclasses, as shown by large-scale genomic analyses. In this review, we discuss why the current research approach based on a single biomarker is limited by the heterogeneity of cancer among patients. We then propose three solutions to improve the research strategies in this field: investigate one biomarker in a single homogeneous subclass to improve its predictive value; study the predictive value of multibiomarker assays in larger populations; and use functional pathways to predict the efficacy of a given drug.

Key words

biomarker breast cancer chemotherapy DNA microarrays prognosis 



cyclophosphamide, methotrexate, and 5-fluorouracil


estrogen receptor



Fabrice Andre was supported by a fellowship from Fondation de France and Lilly Foundation.


  1. 1.
    Early Breast Cancer Trialists' Collaborative Group (EBCTCG). Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival: an overview of the randomised trials. Lancet 365(9472):1687–1717 (2005), May 14–20.CrossRefPubMedGoogle Scholar
  2. 2.
    M. Trudeau, F. Charbonneau, K. Gelmon, K. Laing, J. Latreille, J. Mackey, D. McLeod, K. Pritchard, L. Provencher, and S. Verma. Selection of adjuvant chemotherapy for treatment of node-positive breast cancer. Lancet Oncol. 11:886–898 (2005), Nov. 6.CrossRefGoogle Scholar
  3. 3.
    A. K. Nowak, N. R. Wilcken, M. R. Stockler, A. Hamilton, and D. Ghersi. Systematic review of taxane-containing versus non-taxane-containing regimens for adjuvant and neoadjuvant treatment of early breast cancer. Lancet Oncol. 6:372–380 (2004), Jun 5.CrossRefGoogle Scholar
  4. 4.
    M. D. Pegram, T. Pienkowski, D. W. Northfelt, W. Eiermann, R. Patel, P. Fumoleau, E. Quan, J. Crown, D. Toppmeyer, M. Smylie, A. Riva, S. Blitz, M. F. Press, D. Reese, M. A. Lindsay, and D. J. Slamon. Results of two open-label, multicenter phase II studies of docetaxel, platinum salts, and trastuzumab in HER2-positive advanced breast cancer. J. Natl. Cancer Inst. 96(10):759–769 (2004), May 19.PubMedCrossRefGoogle Scholar
  5. 5.
    J. A. O'Shaughnessy. The evolving role of capecitabine in breast cancer. Clin. Breast Cancer 4(Suppl 1):S20–S25 (2003), Apr.PubMedGoogle Scholar
  6. 6.
    E. Rivera, F. A. Holmes, D. Frye, V. Valero, R. L. Theriault, D. Booser, R. Walters, A. U. Buzdar, K. Dhingra, G. Dhingra, and G. N. Hortobagyi. Phase II study of paclitaxel in patients with metastatic breast carcinoma refractory to standard chemotherapy. Cancer 89(11):2195–2201 (2000), Dec 1.PubMedCrossRefGoogle Scholar
  7. 7.
    G. Contesso, H. Mouriesse, S. Friedman, J. Genin, D. Sarrazin, and J. Rouesse. The importance of histologic grade in long-term prognosis of breast cancer: a study of 1,010 patients, uniformly treated at the Institut Gustave-Roussy. J. Clin. Oncol. 5(9):1378–1386 (1987), Sep.PubMedGoogle Scholar
  8. 8.
    T. Sorlie, C. M. Perou, R. Tibshirani, T. Aas, S. Geisler, H. Johnsen, T. Hastie, M. B. Eisen, M. van de Rijn, S. S. Jeffrey, T. Thorsen, H. Quist, J. C. Matese, P. O. Brown, D. Botstein, P. Eystein Lonning, and A. L. Borresen-Dale. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl. Acad. Sci. USA 98(19):10869–10874 (2001), Sep 11.PubMedCrossRefGoogle Scholar
  9. 9.
    C. M. Perou, T. Sorlie, M. B. Eisen, M. van de Rijn, S. S. Jeffrey, C. A. Rees, J. R. Pollack, D. T. Ross, H. Johnsen, L. A. Akslen, O. Fluge, A. Pergamenschikov, C. Williams, S. X. Zhu, P. E. Lonning, A. L. Borresen-Dale, P. O. Brown, and D. Botstein. Molecular portraits of human breast tumours. Nature 406(6797):747–752(2000), Aug 17.PubMedCrossRefGoogle Scholar
  10. 10.
    C. Sotiriou, S. Y. Neo, L. M. McShane, E. L. Korn, P. M. Long, A. Jazaeri, P. Martiat, S. B. Fox, A. L. Harris, and E. T. Liu. Breast cancer classification and prognosis based on gene expression profiles from a population-based study. Proc Natl Acad Sci USA 100(18):10393–10398 (2003), Sep 2.PubMedCrossRefGoogle Scholar
  11. 11.
    T. Sorlie, R. Tibshirani, J. Parker, T. Hastie, J. S. Marron, A. Nobel. S. Deng, H. Johnsen, R. Pesich, S. Geisler, J. Demeter, C. M. Perou, P. E. Lonning, P. O. Brown, A. L. Borresen-Dale, and D. Botstein. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc. Natl. Acad. Sci. USA 100(14):8418–8423(2003), Jul 8.PubMedCrossRefGoogle Scholar
  12. 12.
    W. D. Foulkes, J. S. Brunet, I. M. Stefansson, O. Straume, P. O. Chappuis, L. R. Begin, N. Hamel, J. R. Goffin, N. Wong, M. Trudel, L. Kapusta, P. Porter, and L. A. Akslen. The prognostic implication of the basal-like (cyclin E high/p27 low/p53+/glomeruloid-microvascular-proliferation+) phenotype of BRCA1-related breast cancer. Cancer Res. 64(3):830–835 (2004), Feb 1.PubMedCrossRefGoogle Scholar
  13. 13.
    T. O. Nielsen, F. D. Hsu, K. Jensen, M. Cheang, G. Karaca, Z. Hu, T. Hernandez-Boussard, C. Livasy, D. Cowan, L. Dressler, L. A. Akslen, J. Ragaz, A. M. Gown, C. B. Gilks, M. van de Rijn, and C. M. Perou. Immunohistochemical and clinical characterization of the basal-like subtype of invasive breast carcinoma. Clin. Cancer Res. 10(16):5367–5374 (2004), Aug 15.PubMedCrossRefGoogle Scholar
  14. 14.
    D. M. Abd El-Rehim, G. Ball, S. E. Pinder, E. Rakha, C. Paish, J. F. Robertson, D. Macmillan, R. W. Blamey, and I. O. Ellis. 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 116(3):340–350 (2005), Sep 1.PubMedCrossRefGoogle Scholar
  15. 15.
    M. A. Troester, K. A. Hoadley, T. Sorlie, B. S. Herbert, A. L. Borresen-Dale, P. E. Lonning, J. W. Shay, W. K. Kaufmann, and C. M. Perou. Cell-type-specific responses to chemotherapeutics in breast cancer. Cancer Res. 64(12):4218–4226 (2004), Jun 15.PubMedCrossRefGoogle Scholar
  16. 16.
    R. Rouzier, C. M. Perou, W. F. Symmans, N. Ibrahim, M. Cristofanilli, K. Anderson, K. R. Hess, J. Stec, M. Ayers, P. Wagner, P. Morandi, C. Fan, I. Rabiul, J. S. Ross, G. N. Hortobagyi, and L. Pusztai. Breast cancer molecular subtypes respond differently to preoperative chemotherapy. Clin. Cancer Res. 11(16):5678–5685 (2005), Aug 15.PubMedCrossRefGoogle Scholar
  17. 17.
    R. Arriagada, M. Spielmann, S. Koscielny, T. Le Chevalier, T. Delozier, M. Reme-Saumon, M. Ducourtieux, T. Tursz, and C. Hill. Results of two randomized trials evaluating adjuvant anthracycline-based chemotherapy in 1146 patients with early breast cancer. Acta Oncol. 44(5):458–466 (2005).PubMedCrossRefGoogle Scholar
  18. 18.
    I. C. Henderson, D. A. Berry, G. D. Demetri, C. T. Cirrincione, L. J. Goldstein, S. Martino, J. N. Ingle, M. R. Cooper, D. F. Hayes, K. H. Tkaczuk, G. Fleming, J. F. Holland, D. B. Duggan, J. T. Carpenter, E. Frei 3rd, R. L. Schilsky, W. C. Wood, H. B. Muss, and L. Norton. Improved outcomes from adding sequential paclitaxel but not from escalating doxorubicin dose in an adjuvant chemotherapy regimen for patients with node-positive primary breast cancer. J. Clin. Oncol. 21(6):976–983 (2003), Mar 15.PubMedCrossRefGoogle Scholar
  19. 19.
    M. Colozza, A. Sidoni, A. M. Mosconi, A. Cavaliere, G. Bisagni, S. Gori, V. De Angelis, A. Frassoldati, R. Cherubini, A. R. Bian, C. Rodino, B. Mazzocchi, Z. Mihailova, E. Bucciarelli, M. Tonato, and Italian Oncology Group for Clinical Research. HER2 overexpression as a predictive marker in a randomized trial comparing adjuvant cyclophosphamide/methotrexate/5-fluorouracil with epirubicin in patients with stage I/II breast cancer: long-term results. Clin. Breast Cancer 6(3):253–259 (2005), Aug.PubMedCrossRefGoogle Scholar
  20. 20.
    P. M. Ravdin. Is Her2 of value in identifying patients who particularly benefit from anthracyclines during adjuvant therapy? A qualified yes. J. Natl. Cancer Inst. Monographs (30):80–84 (2001).Google Scholar
  21. 21.
    S. Paik, J. Bryant, E. Tan-Chiu, G. Yothers, C. Park, D. L. Wickerham, and N. Wolmark. HER2 and choice of adjuvant chemotherapy for invasive breast cancer: national surgical adjuvant breast and bowel project protocol B-15. J. Natl. Cancer Inst. 92(24):1991–1998 (2000), Dec 20.PubMedCrossRefGoogle Scholar
  22. 22.
    C. G. Ferreira, C. Tolis, and G. Giaccone. p53 and chemosensitivity. Ann. Oncol. 10(9):1011–1021 (1999), Sep.PubMedCrossRefGoogle Scholar
  23. 23.
    E. Rahko, G. Blanco, Y. Soini, R. Bloigu, and A. Jukkola. A mutant TP53 gene status is associated with a poor prognosis and anthracycline-resistance in breast cancer patients. Eur. J. Cancer 39(4):447–453 (2003), Mar.PubMedCrossRefGoogle Scholar
  24. 24.
    A. Anelli, R. R. Brentani, A. P. Gadelha, A. Amorim De Albuquerque, and F. Soares. Correlation of p53 status with outcome of neoadjuvant chemotherapy using paclitaxel and doxorubicin in stage IIIB breast cancer. Ann. Oncol. 14(3):428–432 (2003), Mar.PubMedCrossRefGoogle Scholar
  25. 25.
    S. Geisler, P. E. Lonning, T. Aas, H. Johnsen, O. Fluge, D. F. Haugen, J. R. Lillehaug, L. A. Akslen, and A. L. Borresen-Dale. 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(6):2505–2512 (2001), Mar 15.PubMedGoogle Scholar
  26. 26.
    P. Bertheau, F. Plassa, M. Espie, E. Turpin, A. de Roquancourt, M. Marty, F. Lerebours, Y. Beuzard, A. Janin, and H. de The. Effect of mutated TP53 on response of advanced breast cancers to high-dose chemotherapy. Lancet 360(9336):852–854 (2002), Sep 14.PubMedCrossRefGoogle Scholar
  27. 27.
    A. Fedier, A. Moawad, U. Haller, and D. Fink. p53-deficient cells display increased sensitivity to anthracyclines after loss of the catalytic subunit of the DNA-dependent protein kinase. Int. J. Oncol. 23(5):1431–1437 (2003), Nov.PubMedGoogle Scholar
  28. 28.
    A. M. Minisini, C. Di Loreto, M. Mansutti, D. Artico, S. Pizzolitto, A. Piga, and F. Puglisi. Topoisomerase IIalpha and APE/ref-1 are associated with pathologic response to primary anthracycline-based chemotherapy for breast cancer. Cancer Lett. 224(1):133–139 (2005), Jun 16.PubMedGoogle Scholar
  29. 29.
    F. Cardoso, V. Durbecq, D. Larsimont, M. Paesmans, J. Y. Leroy, G. Rouas, C. Sotiriou, N. Renard, V. Richard, M. J. Piccart, and A. Di Leo. Correlation between complete response to anthracycline-based chemotherapy and topoisomerase II-alpha gene amplification and protein overexpression in locally advanced/metastatic breast cancer. Int. J. Oncol. 24(1):201–209 (2004), Jan.PubMedGoogle Scholar
  30. 30.
    T. Petit, M. Wilt, M. Velten, R. Millon, J. F. Rodier, C. Borel, R. Mors, P. Haegele, M. Eber, and J. P. Ghnassia. Comparative value of tumour grade, hormonal receptors, Ki-67, HER-2 and topoisomerase II alpha status as predictive markers in breast cancer patients treated with neoadjuvant anthracycline-based chemotherapy. Eur. J. Cancer. 40(2):205–211 (2004), Jan.PubMedCrossRefGoogle Scholar
  31. 31.
    D. G. Hicks, B. J. Yoder, J. Pettay, E. Swain, S. Tarr, M. Hartke, M. Skacel, J. P. Crowe, G. T. Budd, and R. R. Tubbs. The incidence of topoisomerase II-alpha genomic alterations in adenocarcinoma of the breast and their relationship to human epidermal growth factor receptor-2 gene amplification: a fluorescence in situ hybridization study. Human Pathol. 36(4):348–356 (2005), Apr.CrossRefGoogle Scholar
  32. 32.
    R. Bhargava, P. Lal, and B. Chen. HER-2/neu and topoisomerase IIa gene amplification and protein expression in invasive breast carcinomas: chromogenic in situ hybridization and immunohistochemical analyses. Am. J. Clin. Pathol. 123(6):889–895 (2005), Jun.PubMedCrossRefGoogle Scholar
  33. 33.
    A. Di Leo, D. Gancberg, D. Larsimont, M. Tanner, T. Jarvinen, G. Rouas, S. Dolci, J. Y. Leroy, M. Paesmans, J. Isola, and M. J. Piccart. HER-2 amplification and topoisomerase IIalpha gene aberrations as predictive markers in node-positive breast cancer patients randomly treated either with an anthracycline-based therapy or with cyclophosphamide, methotrexate, and 5-fluorouracil. Clin. Cancer Res. 8(5):1107–1116 (2002), May.PubMedGoogle Scholar
  34. 34.
    M. F. Press, L. Bernstein, G. Sauter et al. Topoisomerase II-alpha gene amplification as a predictor of responsiveness to anthracycline-containing chemotherapy in the Cancer International Research Group 006 clinical trial of trastuzumab (herceptin) in the adjuvant setting. San Antonio Breast Cancer Symposium, Abs 1045 (2005).Google Scholar
  35. 35.
    M. Ayers, W. F. Symmans, J. Stec, A. I. Damokosh, E. Clark, K. Hess, M. Lecocke, J. Metivier, D. Booser, N. Ibrahim, V. Valero, M. Royce, B. Arun, G. Whitman, J. Ross, N. Sneige, G. N. Hortobagyi, and L. Pusztai. Gene expression profiles predict complete pathologic response to neoadjuvant paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide chemotherapy in breast cancer. J. Clin. Oncol. 22(12):2284–2293 (2004), Jun 15.PubMedCrossRefGoogle Scholar
  36. 36.
    L. Gianni, M. Zambetti, K. Clark, J. Baker, M. Cronin, J. Wu, G. Mariani, J. Rodriguez, M. Carcangiu, D. Watson, P. Valagussa, R. Rouzier, W. F. Symmans, J. S. Ross, G. N. Hortobagyi, L. Pusztai, and S. Shak. Gene expression profiles in paraffin-embedded core biopsy tissue predict response to chemotherapy in women with locally advanced breast cancer. J. Clin. Oncol. 23(29):7265–7277 (2005), Oct 10.PubMedCrossRefGoogle Scholar
  37. 37.
    J. C. Chang, E. C. Wooten, A. Tsimelzon, S. G. Hilsenbeck, M. C. Gutierrez, R. Elledge, S. Mohsin, C. K. Osborne, G. C. Chamness, D. C. Allred, and P. O'Connell. Gene expression profiling for the prediction of therapeutic response to docetaxel in patients with breast cancer. Lancet 362(9381):362–369 (2003), Aug 2.PubMedCrossRefGoogle Scholar
  38. 38.
    K. R. Hess, K. Anderson, W. Symmans, V. Valero, N. Ibrahim, J. A. Mejia, D. Booser, R. L. Theriault, A. U. Buzdar, P. J. Dempsey, R. Rouzier, N. Sneige, J. S. Ross, T. Vidaurre, H. L. Gomez, G. N. Hortobagyi, and L. Pusztai. Pharmacogenomic predictor of sensitivity to preoperative paclitaxel and 5-fluorouracil, doxorubicin, cyclophosphamide chemotherapy in breast cancer. J. Clin. Oncol. (2006) in press.Google Scholar
  39. 39.
    S. Michiels, S. Koscielny, and C. Hill. Prediction of cancer outcome with microarrays: a multiple random validation strategy. Lancet 365(9458):488–492 (2005), Feb 5–11.PubMedCrossRefGoogle Scholar
  40. 40.
    L. Ein-Dor, I. Kela, G. Getz, D. Givol, and E. Domany. Outcome signature genes in breast cancer: is there a unique set? Bioinformatics 21(2):171–178 (2005), Jan 15.PubMedCrossRefGoogle Scholar
  41. 41.
    K. Anderson, K. R. Hess, M. Kapoor, S. Tirrell, J. Courtemanche, B. Wang, Y. Wu, Y. Gong, G. N. Hortobagyi, W. F. Symmans, and L. Pusztai. Reproducibility of gene expression signature-based predictions in replicate experiments. Clin. Cancer Res. 12(6):1721–1727 (2006), Mar 15.PubMedCrossRefGoogle Scholar
  42. 42.
    The Toxicogenomics Research Consortium. Standardizing global gene expression analysis between laboratories and across platforms. Nat. Methods 2(5):351–356 (2005), May.CrossRefGoogle Scholar
  43. 43.
    R. A. Irizarry, D. Warren, F. Spencer, I. F. Kim, S. Biswal, B. C. Frank, E. Gabrielson, J. G. Garcia, J. Geoghegan, G. Germino, C. Griffin, S. C. Hilmer, E. Hoffman, A. E. Jedlicka, E. Kawasaki, F. Martinez-Murillo, L. Morsberger, H. Lee, D. Petersen, J. Quackenbush, A. Scott, M. Wilson, Y. Yang, S. Q. Ye, and W. Yu. Multiple-laboratory comparison of microarray platforms. Nat. Methods 2(5):345–350 (2005), May.PubMedCrossRefGoogle Scholar
  44. 44.
    E. Huang, S. H. Cheng, H. Dressman, J. Pittman, M. H. Tsou, C. F. Horng, A. Bild, E. S. Iversen, M. Liao, C. M. Chen, M. West, J. R. Nevins, and A. T. Huang. Gene expression predictors of breast cancer outcomes. Lancet 361(9369):1590–1596 (2003), May 10.PubMedCrossRefGoogle Scholar
  45. 45.
    Y. Wang, J. G. Klijn, Y. Zhang, A. M. Sieuwerts, M. P. Look, F. Yang, D. Talantov, M. Timmermans, M. E. Meijer-van Gelder, J. Yu, T. Jatkoe, E. M. Berns, D. Atkins, and J. A. Foekens. Gene-expression profiles to predict distant metastasis of lymph-node-negative primary breast cancer. Lancet 365(9460):671–679 (2005), Feb 19–25.PubMedGoogle Scholar
  46. 46.
    S. Paik, S. Shak, G. Tang, C. Kim, J. Baker, M. Cronin, F. L. Baehner, M. G. Walker, D. Watson, T. Park, W. Hiller, E. R. Fisher, D. L. Wickerham, J. Bryant, and N. Wolmark. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N. Engl. J. Med. 351(27):2817–2826 (2004), Dec 30.PubMedCrossRefGoogle Scholar
  47. 47.
    M. Ashburner, C. A. Ball, J. A. Blake, D. Botstein, H. Butler, J. M. Cherry, A. P. Davis, K. Dwight, S. S. Dolinski, J. T. Eppig, M. A. Harris, D. P. Hill, L. Issel-Tarver, A. Kasarskis, S. Lewis, J. C. Matese, J. E. Richardson, M. Ringwald, G. M. Rubin, and G. Sherlock. Gene ontology: tool for the unification of biology. The gene ontology consortium. Nat. Genet. 25(1):25–29 (2000), May.PubMedCrossRefGoogle Scholar
  48. 48.
    A. Subramanian, P. Tamayo, V. K. Mootha, S. Mukherjee, B. L. Ebert, M. A. Gillette, A. Paulovich, S. L. Pomeroy, T. R. Golub, E. S. Lander, and J. P. Mesirov. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc. Natl. Acad. Sci. USA 102(43):15545–15550 (2005), Oct 25.PubMedCrossRefGoogle Scholar
  49. 49.
    A. Linjawi, M. Kontogiannea, F. Halwani, M. Edwardes, and S. Meterissian. Prognostic significance of p53, bcl-2, and Bax expression in early breast cancer. J. Am. Coll. Surg. 198(1):83–90 (2004), Jan.PubMedCrossRefGoogle Scholar
  50. 50.
    R. Rouzier, R. Rajan, P. Wagner, K. R. Hess, D. L. Gold, J. Stec, M. Ayers, J. S. Ross, P. Zhang, T. A. Buchholz, H. Kuerer, M. Green, B. Arun, G. N. Hortobagyi, W. F. Symmans, and L. Pusztai. Microtubule-associated protein tau: a marker of paclitaxel sensitivity in breast cancer. Proc. Natl. Acad. Sci. USA 102(23):8315–8320 (2005), Jun 7.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science + Business Media, Inc. 2006

Authors and Affiliations

  1. 1.Department of Breast Medical Oncology, Unit 1354The University of Texas M. D. Anderson Cancer CenterHoustonUSA

Personalised recommendations