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Predicting response of bladder cancers to gemcitabine and carboplatin neoadjuvant chemotherapy through genome-wide gene expression profiling

机译:通过全基因组基因表达谱预测膀胱癌对吉西他滨和卡铂新辅助化疗的反应

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摘要

Neoadjuvant chemotherapy with gemcitabine and carboplatin (GC) for invasive bladder cancer increases the chance of a radical response for a subset of patients, while other patients suffer from severe adverse drug reactions without any benefit. To establish a method for predicting the response to chemotherapy with GC, the expression profiles of biopsy samples from 37 advanced bladder cancers were analyzed using a microarray consisting of 38,500 genes or ESTs. Upon analysis of 9 ‘responder’ and 9 ‘non-responder’ tumors, 12 ‘predictive’ genes were found to be significantly differentially expressed between the ‘responder’ and ‘non-responder’ groups, and a numerical prediction scoring system that clearly separated the responder group from the non-responder group was established. This system accurately predicted the drug responses of 18 of 19 additional test cases that were reserved from the original 37 cases. Moreover, a quantitative PCR-based prediction system was developed that may be feasible for routine clinical use, and the sensitivity of invasive bladder cancer to neoadjuvant chemotherapy with GC was able to be predicted by the expression patterns in this set of genes. Nearly 50% of patients treated with GC or methotrexate, vinblastine, doxorubicin and cisplatin (M-VAC) therapy have been reported to achieve complete or partial response to either of these therapies. When we applied this prediction system as well as the system for M-VAC, we expected that approximately 80% of the patients would achieve significant tumor shrinking (>60%) by selection of either the GC or M-VAC regimens. Our results suggest that the two prediction scoring systems lead to achievement of ‘personalized therapy’ for the treatment of invasive bladder cancer and should improve the quality of life for patients with this disease.
机译:吉西他滨和卡铂(GC)的新辅助化学疗法治疗浸润性膀胱癌增加了部分患者发生根本反应的机会,而其他患者则患有严重的药物不良反应而没有任何益处。为了建立一种用GC预测对化学疗法的反应的方法,使用由38,500个基因或EST组成的微阵列分析了37种晚期膀胱癌的活检样品的表达谱。通过分析9个“响应者”和9个“非响应者”肿瘤,发现12个“预测”基因在“响应者”和“非响应者”组之间显着差异表达,并且一个数值预测评分系统清楚地将其分开建立了非响应者组中的响应者组。该系统准确地预测了从最初的37个案例中保留的19个其他测试案例中的18个的药物反应。此外,开发了基于定量PCR的预测系统,该系统对于常规临床应用可能是可行的,并且侵袭性膀胱癌对GC新辅助化疗的敏感性可以通过这组基因的表达模式来预测。据报道,近50%的接受GC或甲氨蝶呤,长春碱,阿霉素和顺铂(M-VAC)治疗的患者对这两种疗法均达到了完全或部分缓解。当我们应用此预测系统以及M-VAC系统时,我们预期通过选择GC或M-VAC方案,大约80%的患者将实现显着的肿瘤缩小(> 60%)。我们的结果表明,这两种预测评分系统可实现“浸润性膀胱癌”的“个性化治疗”,并应改善患有这种疾病的患者的生活质量。

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