Concordant gene expression signatures predict clinical outcomes of cancer patients undergoing systemic therapy.
Concordant gene expression signatures predict clinical outcomes of cancer patients undergoing systemic therapy.
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DOI:
10.1158/0008-5472.can-09-0798
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发表时间:
2009-11-01
期刊:
影响因子:
11.2
通讯作者:
Lee JK
中科院分区:
文献类型:
--
作者:
Williams PD;Cheon S;Havaleshko DM;Jeong H;Cheng F;Theodorescu D;Lee JK
Conventional development of multi-gene expression models (GEMs) predicting therapeutic response of cancer patients are based on analysis of patients treated with specific regimens, which limits generalization to different or novel drug combinations. We overcome this limitation by developing GEMs based on in vitro drug sensitivities and microarray analyses of the NCI-60 cancer cell line panel. These GEMs were evaluated in blind fashion as predictors of tumor response and/or patient survival in seven independent cohorts of patients with breast (N=275), bladder (N=59), and ovarian (N=143) cancer treated with multi-agent chemotherapy, of which 233 patients were from prospectively-enrolled clinical trials. In all studies, GEMs effectively stratified tumor response and patient survival independent of established clinical and pathologic tumor variables. In bladder cancer patients treated with neoadjuvant MVAC (Methotrexate, Vinblastine, Doxorubicin, Cisplatin), the 3-year overall survival for those with favorable GEM scores was 81% vs. 33% for those with less favorable scores (p=0.002). GEMs for breast cancer patients treated with FAC (Fluorouracil, Doxorubicin, Cyclophosphamide) and ovarian cancer patients treated with platinum-containing regimens also stratified patient survival (5-year overall survival 100% vs. 74% (p=0.05) and 3-year overall survival 68% vs. 43% (p=0.008), respectively. Importantly, clinical prediction using our in vitro GEM was superior to that of conventionally-derived GEMs. We demonstrate a facile yet effective approach to GEM derivation that identifies patients most likely to benefit from selected multi-agent therapy. Use of such in vitro-based GEMs may provide a robust and generalizable approach to personalized cancer therapy.