基因签名由病人肿瘤外植体生长在裸小鼠来预测肿瘤反应11细胞毒性药物。

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Fiebig HH,舒勒J,博士伦N,霍夫曼M,梅茨T, Korrat

基因签名由病人肿瘤外植体生长在裸小鼠来预测肿瘤反应11细胞毒性药物。

癌症基因组蛋白质组学。2007年May-Jun; 4 (3): 197 - 209。

PubMed ID

17878523 (在PubMed

]

文摘

肿瘤病人在串行通道在裸小鼠皮下外植体建立了特征对11标准细胞毒性抗癌药物的敏感性。后者包括烷化剂环磷酰胺、异环磷酰胺、丝裂霉素C,顺铂和CCNU,抗代谢物研究者用甲氨蝶呤;拓扑异构酶ⅱ抑制剂阿霉素和依托泊苷,以及微管蛋白绑定紫杉醇和长春地辛。肿瘤治疗的平均数量的各种药物是54岁(范围31 - 78)。异种移植肿瘤的基因表达谱测定使用Affymetrix HG-U133 + 2.0代表大约38.500人类基因的mRNA表达数组。假设是药物反应基因表达的相关性识别基因签名可以预测个体肿瘤的药物反应这些代理。预测基因签名,随后被发现使用分析交叉验证(LOOCV)技术验证。肿瘤被认为是反应如果药物影响肿瘤抑制体积小于11 - 41%的车辆控制肿瘤的体积(T / C %)。切断了所有药物中值为25%的T / C。使用这些标准,平均三分之一的测试肿瘤抗敏感(反应),三分之二(无)。 The bio-informatic analysis yielded predictive gene signatures consisting of 42-129 genes (mean for the 11 drugs: 87 genes). On average, the response rate for predicted responders (83%) was 2.45 fold higher than that for all test tumors (random testing, 34%). This increase of response rates, following signature-guided testing, was consistent for all 11 agents. Conversely, 94% of the predicted non-responders (range: 84-100%) proved to be non-responders in nude mouse studies while the proportion of non-responders among all test tumors was approximately 66%. The majority of genes (59%) making up the predictive gene signatures had an unknown function. Known genes were implicated in cell proliferation, apoptosis, DNA repair, cell cycle, metabolism and transcription. The predictive gene signatures presented here for 11 cytotoxic agents have the potential, if employed in the clinic, to substantially increase tumor response rates compared to empirical drug treatment. However they need to be further validated, both preclinically and clinically.

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药物靶点

药物	目标	类	生物	药理作用	行动
长春地辛	微管蛋白beta 1链	蛋白质	人类	是的	抑制剂	细节