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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:从临床前模型转移药物反应预测因子到肿瘤的域适应方法

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摘要

Motivation Cell 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:刺激细胞系和患者衍生的异种移植物(PDXs)已被广泛用于理解癌症的分子底划症。 虽然核心生物过程通常是节省的,但这些模型也与人类肿瘤相比表现出重要的差异,阻碍了从临床前模型转化为人类环境的结果。 特别地,采用在源自临床前模型的数据上产生的药物反应预测因子来预测患者反应仍然是一个具有挑战性的任务。 由于已经收集了非常大的药物反应数据集进行临床前模型,并且通常缺乏患者药物响应数据,迫切需要从临床前模型到人类环境中有效地转移药物反应预测器的方法。

著录项

  • 来源
    《Bioinformatics 》 |2019年第14期| 共10页
  • 作者单位

    Netherlands Canc Inst Oncode Inst Div Mol Carcinogenesis Computat Canc Biol NL-1066 CX Amsterdam Netherlands;

    Delft Univ Technol Fac EEMCS Dept Intelligent Syst NL-2628 CD Delft Netherlands;

    Univ Amsterdam Med Ctr Amsterdam Publ Hlth Res Inst Dept Epidemiol &

    Biostat NL-1081 HV Amsterdam Netherlands;

    Delft Univ Technol Fac EEMCS Dept Intelligent Syst NL-2628 CD Delft Netherlands;

    Netherlands Canc Inst Oncode Inst Div Mol Carcinogenesis Computat Canc Biol NL-1066 CX Amsterdam Netherlands;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 生物工程学(生物技术) ;
  • 关键词

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