Gene expression-based diagnosis of efficacy of chemotherapy for breast cancer

被引:0
作者
Yoshio Miki
机构
[1] Tokyo Medical and Dental University,Department of Molecular Genetics, Medical Research Institute
来源
Breast Cancer | 2010年 / 17卷
关键词
Breast cancer; Gene expression; Chemotherapy; Response prediction; Tailor-made medicine;
D O I
暂无
中图分类号
学科分类号
摘要
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.
引用
收藏
页码:97 / 102
页数:5
相关论文
共 50 条
[21]   VEGFA Gene Expression in Breast Cancer Is Associated With Worse Prognosis, but Better Response to Chemotherapy and Immunotherapy [J].
Sharma, Pia ;
Chida, Kohei ;
Wu, Rongrong ;
Tung, Kaity ;
Hakamada, Kenichi ;
Ishikawa, Takashi ;
Takabe, Kazuaki .
WORLD JOURNAL OF ONCOLOGY, 2025, 16 (01) :120-130
[22]   A meta-analysis of gene expression-based biomarkers predicting outcome after tamoxifen treatment in breast cancer [J].
Mihaly, Zsuzsanna ;
Kormos, Mate ;
Lanczky, Andras ;
Dank, Magdolna ;
Budczies, Jan ;
Szasz, Marcell A. ;
Gyorffy, Balazs .
BREAST CANCER RESEARCH AND TREATMENT, 2013, 140 (02) :219-232
[23]   A meta-analysis of gene expression-based biomarkers predicting outcome after tamoxifen treatment in breast cancer [J].
Zsuzsanna Mihály ;
Máté Kormos ;
András Lánczky ;
Magdolna Dank ;
Jan Budczies ;
Marcell A Szász ;
Balázs Győrffy .
Breast Cancer Research and Treatment, 2013, 140 :219-232
[24]   Concordance among gene expression-based predictors for ER-positive breast cancer treated with adjuvant tamoxifen [J].
Prat, A. ;
Parker, J. S. ;
Fan, C. ;
Cheang, M. C. U. ;
Miller, L. D. ;
Bergh, J. ;
Chia, S. K. L. ;
Bernard, P. S. ;
Nielsen, T. O. ;
Ellis, M. J. ;
Carey, L. A. ;
Perou, C. M. .
ANNALS OF ONCOLOGY, 2012, 23 (11) :2866-2873
[25]   Global gene expression changes during neoadjuvant chemotherapy for human breast cancer [J].
Buchholz, TA ;
Stivers, DN ;
Stec, J ;
Ayers, M ;
Clark, E ;
Bolt, A ;
Sahin, AA ;
Symmans, WF ;
Hess, KR ;
Kuerer, HM ;
Valero, V ;
Hortobagyi, GN ;
Pusztai, L .
CANCER JOURNAL, 2002, 8 (06) :461-468
[26]   Gene expression profiling: Decoding breast cancer [J].
de Snoo, Femke ;
Bender, Richard ;
Glas, Annuska ;
Rutgers, Emiel .
SURGICAL ONCOLOGY-OXFORD, 2009, 18 (04) :366-378
[27]   Gene-Network-Based Feature Set (GNFS) for Expression-Based Cancer Classification [J].
Doungpan, Narumol ;
Engchuan, Worrawat ;
Meechai, Asawin ;
Fong, Simon ;
Chan, Jonathan H. .
JOURNAL OF MEDICAL IMAGING AND HEALTH INFORMATICS, 2016, 6 (04) :1093-1101
[28]   Developing a gene expression classifier for breast cancer diagnosis [J].
Hosseinpour, Zahra ;
Rezaei-Tavirani, Mostafa ;
Akbari, Mohammad-Esmaeil ;
Farahani, Masoumeh .
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING, 2025,
[29]   Feature (gene) selection in gene expression-based tumor classification [J].
Xiong, MM ;
Li, WJ ;
Zhao, JY ;
Jin, L ;
Boerwinkle, E .
MOLECULAR GENETICS AND METABOLISM, 2001, 73 (03) :239-247
[30]   Gene expression and pathologic response to neoadjuvant chemotherapy in breast cancer [J].
Kolacinska, Agnieszka ;
Fendler, Wojciech ;
Szemraj, Janusz ;
Szymanska, Bozena ;
Borowska-Garganisz, Ewa ;
Nowik, Magdalena ;
Chalubinska, Justyna ;
Kubiak, Robert ;
Pawlowska, Zofia ;
Blasinska-Morawiec, Maria ;
Potemski, Piotr ;
Jeziorski, Arkadiusz ;
Morawiec, Zbigniew .
MOLECULAR BIOLOGY REPORTS, 2012, 39 (07) :7435-7441