Abstract
Development of a clear index to select drugs, i.e., accurate prediction of drug sensitivity, is important not only to obtain the maximum therapeutic effects of drugs, but also realize personalized medicine (tailor-made medicine). With the recent advancement in genome science represented by microarrays, molecular-level elucidation of many diseases including cancers has been progressing. It has been clarified that molecular information, such as gene expression profiles of cancer cells and gene polymorphisms in individual patients, affects not only cancer development and progression, but also therapeutic and adverse effects. The establishment of a therapeutic method by clinical application of this information has been progressing, in which the therapeutic effects of drugs are accurately predicted, and the maximum effects are obtained corresponding to cancer properties and patients’ characteristics.
Similar content being viewed by others
References
Goldhirsch A, Wood WC, Gelber RD, Coates AS, Thürlimann B, Senn HJ. Progress and promise: highlights of the international expert consensus on the primary therapy of early breast cancer 2007. In: 10th St. Gallen conference. Ann Oncol. 2007;18:1133–44.
Chang JC, Wooten EC, Tsimelzon A, Hilsenbeck SG, Gutierrez MC, Elledge R, et al. Gene expression profiling for the prediction of therapeutic response to docetaxel in patients with breast cancer. Lancet. 2003;362:362–9.
Iwao-Koizumi K, Matoba R, Ueno N, Kim SJ, Ando A, Miyoshi Y, et al. Prediction of docetaxel response in human breast cancer by gene expression profiling. J Clin Oncol. 2005;23:422–31.
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.
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;24:4236–44.
Kihara C, Tsunoda T, Tanaka T, Yamana H, Furukawa Y, Ono K, et al. Prediction of sensitivity of esophageal tumors to adjuvant chemotherapy by cDNA microarray analysis of gene-expression profiles. Cancer Res. 2001;61:6474–9.
Kakiuchi S, Daigo Y, Ishikawa N, Furukawa C, Tsunoda T, Yano S, et al. Prediction of sensitivity of advanced non-small cell lung cancers to gefitinib (Iressa, ZD1839). Hum Mol Genet. 2004;13:3029–43.
Kok M, Linn SC, Van Laar RK, Jansen MP, van den Berg TM, Delahaye LJ, et al. Comparison of gene expression profiles predicting progression in breast cancer patients treated with tamoxifen. Breast Cancer Res Treat. 2009;113:275–83.
Zembutsu H, Suzuki Y, Sasaki A, Tsunoda T, Okazaki M, Yoshimoto M, et al. Predicting response to docetaxel neoadjuvant chemotherapy for advanced breast cancers through genome-wide gene expression profiling. Int J Oncol. 2009;34:361–70.
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;27:1160–7.
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;24:1665–71.
Golub TR, Slonim DK, Tamayo P, Huard C, Gaasenbeek M, Mesirov JP, et al. Molecular classification of cancer: class discovery and class prediction by gene expression monitoring. Science. 1999;286:531–7.
Perou CM, Jeffrey SS, van de Rijn M, Rees CA, Eisen MB, Ross DT, et al. Distinctive gene expression patterns in human mammary epithelial cells and breast cancers. Proc Natl Acad Sci USA. 1999;96:9212–7.
Sørlie 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;98:10869–74.
Massagué J. Sorting out breast-cancer gene signatures. N Engl J Med. 2007;356:294–7.
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;351:2817–26.
Paik S, Tang G, Shak S, Kim C, Baker J, Kim W, et al. Gene expression and benefit of chemotherapy in women with node-negative, estrogen receptor-positive breast cancer. J Clin Oncol. 2006;24:3726–34.
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;415:530–6.
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;347:1999–2009.
Wu RZ, Bailey SN, Sabatini DM. Cell-biological applications of transfected-cell microarrays. Trends Cell Biol. 2002;12:485–8.
Vanhecke D, Janitz M. High-throughput gene silencing using cell arrays. Oncogene. 2004;23:8353–8.
Fujita S, Ota E, Sasaki C, Takano K, Miyake M, Miyake J. Highly efficient reverse transfection with siRNA in multiple wells of microtiter plates. J Biosci Bioeng. 2007;104:329–33.
Whitehurst AW, Bodemann BO, Cardenas J, Ferguson D, Girard L, Peyton M, et al. Synthetic lethal screen identification of chemosensitizer loci in cancer cells. Nature. 2007;446:815–9.
Nagasaki K, Miki Y. Molecular prediction of the therapeutic response to neoadjuvant chemotherapy in breast cancer. Breast Cancer. 2008;15:117–20.
Author information
Authors and Affiliations
Corresponding author
About this article
Cite this article
Miki, Y. Gene expression-based diagnosis of efficacy of chemotherapy for breast cancer. Breast Cancer 17, 97–102 (2010). https://doi.org/10.1007/s12282-009-0180-2
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12282-009-0180-2