Skip to main content

Advertisement

Log in

Personalized systemic treatment for breast cancer patients: is it a reality?

  • Conference Paper
  • Presidential symposium: Individualized diagnosis for tailored treatment of breast cancer
  • Published:
Breast Cancer Aims and scope Submit manuscript

Abstract

There is a clinical demand for tools that could distinguish patients who may benefit or suffer from particular systemic treatments. High throughput technologies such as DNA microarray are anticipated as comprehensive tools for development of accurate predictive markers of treatment outcome. Although technical and statistical problems still exist in pharmacogenomic research, rigorous efforts have been made to realize treatment individualization. Clinicians should be prepared for the future use of these new technologies in the clinic through discussion involving patients and various health-care providers.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  1. Early Breast Cancer Trialists’ Collaborative Group (EBCTCG). Effects of chemotherapy and hormonal therapy for early breast cancer on recurrence and 15-year survival. Lancet. 2005;365:1665–6.

    Article  Google Scholar 

  2. Clarke M, Collins R, Darby S, Davies C, Elphinstone P, Evince E, et al. Effects of radiotherapy and of differences in the extent of surgery for early breast cancer on local-recurrence and 15-year survival: an overview of the randomized trials. Lancet. 2005;366:2087–106.

    PubMed  CAS  Google Scholar 

  3. Goldhirsch A, Wood WC, Gelber RD, Coates AS, Thurlimann B, Senn HJ, et al. Progress and promise: highlights of the international expert consensus on the primary therapy of early breast cancer 2007. Ann Oncol. 2007;18:1133–44.

    Article  PubMed  CAS  Google Scholar 

  4. Ravdin PM, Tandon AK, Allred DC, Clark GM, Fuqua SA, Hilsenbech SH, et al. Computer program to assist in making decisions about adjuvant therapy for women with early breast cancer. J Clin Oncol. 2001;19:980–91.

    PubMed  CAS  Google Scholar 

  5. Sorlie T, Perou CM, Tibishirani R, Aas T, Geisler S, Johnsen H, et al. Gene expression patterns of breast carcinomas distinguish tumor sub- classes with clinical implications. Proc Natl Acad Sci USA. 2001;98:10869–74.

    Google Scholar 

  6. 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;100:8418–23.

    Google Scholar 

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

    Article  PubMed  CAS  Google Scholar 

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

    Article  PubMed  Google Scholar 

  9. Liu R, Wang X, Chen GY, Dalerba P, Gurney A, Hoey T, et al. The prognostic role of a gene-signature from tumorgenic breast cancer cells. N Engl J Med. 2007;356:217–26.

    Article  PubMed  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

  11. Cronin M, Pho M, Dutta D, Stephans JC, Shak S, Kiefer MC, et al. Measurement of gene expression in archival paraffin-embedded tissues: development and performance of a 92-gene reverse transcriptase-polymerase chain reaction assay. Am J Pathol. 2004;164:35–42.

    PubMed  CAS  Google Scholar 

  12. http://www.eortc.be/services/unit/mindact/MINDACT_websiteii.asp

  13. http://www.cancer.gov/clinicaltrials/EORTC-10041

  14. http://www.cancer.gov/newscenter/pressreleases/TAILORxRelease

  15. http://www.cancer.gov/clinicaltrials/ECOG-PACCT-1

  16. Ach RA, Floore A, Curry B, Lazar V, Glas AM, Pover R, et al. Robust interlaboratory reproducibility of a gene expression signature measurement consistent with the needs of a new generation of diagnositic tools. BMJ Genomics. 2007;8:148–57.

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

  18. Herman JG, Baylin SB. Gene silencing in cancer in association with promoter hypermethylation. N Engl J Med. 2003;349:2042–54.

    Article  PubMed  CAS  Google Scholar 

  19. 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;10:1284–91.

    PubMed  CAS  Google Scholar 

  20. Vogel Cl, Cobleigh MA, Tripathy D, Gutheil JC, Harris LN, Fehrenbacher L, et al. Efficacy and safety of trastuzumab as a single agent in first-line treatment of HER2-overexpressing metastatic breast cancer. J Clin Oncol. 2002;20:719–26.

    Article  PubMed  Google Scholar 

  21. Tanner M, Isola J, Wiklund T, Erikstein B, Kellokumpu-Lehtinen P, Malmstrom P, et al. Topoisomerase II alpha gene amplification predicts favorable treatment response to tailored and dose-escalated anthracycline-based adjuvant chemotherapy in HER2/neu-amplified breast cancer: Scandinavian Breast Group Trial 9401. J Clin Oncol. 2006;24:2428–36.

    Google Scholar 

  22. Seve P, Mackey J, Issac S, Tredan O, Souquet PJ, Perol M, et al. Class III beta-tubulin expression in tumor cells predicts response and outcome in patients with non-small cell lung cancer receiving paclitaxel. Mol Cancer Ther. 2005;4:2001–7.

    Article  PubMed  CAS  Google Scholar 

  23. Romond EH, Perez EA, Bryant J, Suman VJ, Geyer CE, Davidson NE, et al. Trastuzumab plus adjuvant chemotherapy for operable HER2-positive breast cancer N Engl J Med. 2005;353:1673–84.

    Article  PubMed  CAS  Google Scholar 

  24. Piccart-Gebhart MJ, Procter M, Leyland-Jones B, Goldhirsch A, Unch M, Smith I, et al. Trastuzumab after adjuvant chemotherapy in Her2-positive breast cancer. N Eng J Med. 2005;353:1659–72.

    Article  CAS  Google Scholar 

  25. Chang JC, Wooten EC, Tsimeizon A, Hilsenbeck SG, Gutierrrez MC, Elledge R, et al. Gene expression profiles predicts therapeutic response to docetaxel (Taxotere) in breast cancer patients. Lancet. 2003;362:362–9.

    Article  PubMed  CAS  Google Scholar 

  26. Ayers M, Symmans WF, Stec J, Damokosh AI, Clark E, Hess K, et al Gene expression profiles predict complete pathologic response to neoadjuvant paclitaxel and fluorouracil, doxorubicin, and cyclophosphamide chemotherapy in breast cancer. J Clin Oncol. 2004;22:2284–93.

    Article  PubMed  CAS  Google Scholar 

  27. Simon R. Roadmap for developing and validating therapeutically relevant genomic classifiers. J Clin Oncol. 2005;23:7232–41.

    Article  Google Scholar 

  28. Hudis CA. Trastuzumab-mechanisim of action and use in clinical practice. N Engl J Med. 2007;357:39–51.

    Article  PubMed  CAS  Google Scholar 

  29. Ando Y, Saka H, Ando M, Sawa T, Muro K, Ueoka H, et al. Polymorphisms of UDP-glucuronosyltransferase gene and irinotecan toxicity: a pharmacogenetic analysis. Cancer Res. 2000;60:6921–6.

    PubMed  CAS  Google Scholar 

  30. Maring JG, van Kuilenburg AB, Haasjes J, Piersma H, Groen HJ, Uges DR, et al. Reduced 5-FU clearance in a patient with low DPD activity due to heterozygosity for a mutant allele of the DPYD gene. Br J Cancer. 2002;86:1028–33.

    Article  PubMed  CAS  Google Scholar 

  31. Clinical implication of CYP2D6 genotypes predictive of tamoxifen pharmacokinetics in metastatic breast cancer. J Clin Oncol. 2007;25:3837–45.

    Google Scholar 

  32. Rogowski W. Current impact of gene technology on healthcare: a map of economic assessments. Health Policy. 2007;80:340–57.

    Article  PubMed  Google Scholar 

Download references

Acknowledgment

Supported by Health and Labour Science Grants for Research in Advanced Medical Technology (H17-pharmaco-006).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Chikako Shimizu.

Additional information

This article is based on a presentation delivered at Presidential Symposium 1, ‘‘Breast cancer: individualized diagnosis for tailored treatment,’’ held on 29 June 2007 at the 15th Annual Meeting of the Japanese Breast Cancer Society in Yokohama.

About this article

Cite this article

Shimizu, C., Fujiwara, Y. Personalized systemic treatment for breast cancer patients: is it a reality?. Breast Cancer 15, 141–144 (2008). https://doi.org/10.1007/s12282-008-0029-0

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12282-008-0029-0

Keywords

Navigation