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PRECISE: a domain adaptation approach to transfer predictors of drug response from pre-clinical models to tumors

机译:精确:一种域适应方法可将药物反应的预测因子从临床前模型转移至肿瘤

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摘要

MotivationCell lines and patient-derived xenografts (PDXs) have been used extensively to understand the molecular underpinnings of cancer. While core biological processes are typically conserved, these models also show important differences compared to human tumors, hampering the translation of findings from pre-clinical models to the human setting. In particular, employing drug response predictors generated on data derived from pre-clinical models to predict patient response remains a challenging task. As very large drug response datasets have been collected for pre-clinical models, and patient drug response data are often lacking, there is an urgent need for methods that efficiently transfer drug response predictors from pre-clinical models to the human setting.
机译:动机细胞系和患者来源的异种移植物(PDXs)已广泛用于了解癌症的分子基础。尽管通常会保留核心生物学过程,但与人类肿瘤相比,这些模型还显示出重要差异,从而阻碍了从临床前模型到人类环境的发现转化。特别地,采用基于从临床前模型得出的数据生成的药物反应预测因子来预测患者反应仍然是一项艰巨的任务。由于已经为临床前模型收集了非常大的药物反应数据集,并且经常缺乏患者药物反应数据,因此迫切需要一种将药物反应预测因子从临床前模型有效转移到人类环境的方法。

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