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Clinical drug response can be predicted using baseline gene expression levels and in vitro drug sensitivity in cell lines

机译:可以使用基线基因表达水平和细胞系中的体外药物敏感性来预测临床药物反应

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We demonstrate a method for the prediction of chemotherapeutic response in patients using only before-treatment baseline tumor gene expression data. First, we fitted models for whole-genome gene expression against drug sensitivity in a large panel of cell lines, using a method that allows every gene to influence the prediction. Following data homogenization and filtering, these models were applied to baseline expression levels from primary tumor biopsies, yielding an in vivo drug sensitivity prediction. We validated this approach in three independent clinical trial datasets, and obtained predictions equally good, or better than, gene signatures derived directly from clinical data.
机译:我们演示了仅使用治疗前基线肿瘤基因表达数据预测患者化疗反应的方法。首先,我们使用允许每个基因影响预测的方法,针对一大批细胞系拟合了针对药物敏感性的全基因组基因表达模型。数据均质化和过滤后,将这些模型应用于原发性肿瘤活检的基线表达水平,从而得出体内药物敏感性预测。我们在三个独立的临床试验数据集中验证了这种方法,并获得了与直接从临床数据中直接获得的基因特征相同或更好的预测。

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