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定量分析揭示肺腺癌中复杂的药物基因组学特征。

Quantitative Analyses Reveal a Complex Pharmacogenomic Landscape in Lung Adenocarcinoma.

机构信息

Department of Biology, Stanford University, Stanford, California.

Department of Genetics, Stanford University School of Medicine, Stanford, California.

出版信息

Cancer Res. 2021 Sep 1;81(17):4570-4580. doi: 10.1158/0008-5472.CAN-21-0716. Epub 2021 Jul 2.

Abstract

The lack of knowledge about the relationship between tumor genotypes and therapeutic responses remains one of the most critical gaps in enabling the effective use of cancer therapies. Here, we couple a multiplexed and quantitative experimental platform with robust statistical methods to enable pharmacogenomic mapping of lung cancer treatment responses . The complex map of genotype-specific treatment responses uncovered that over 20% of possible interactions show significant resistance or sensitivity. Known and novel interactions were identified, and one of these interactions, the resistance of KEAP1-mutant lung tumors to platinum therapy, was validated using a large patient response data set. These results highlight the broad impact of tumor suppressor genotype on treatment responses and define a strategy to identify the determinants of precision therapies. SIGNIFICANCE: An experimental and analytical framework to generate pharmacogenomic maps that relate tumor genotypes to therapeutic responses reveals a surprisingly complex map of genotype-specific resistance and sensitivity.

摘要

肿瘤基因型与治疗反应之间的关系知识的缺乏仍然是有效利用癌症疗法的最关键差距之一。在这里,我们将一个多重和定量的实验平台与强大的统计方法相结合,以实现肺癌治疗反应的药物基因组学映射。对特定基因型治疗反应的复杂图谱揭示,超过 20%的可能相互作用显示出显著的耐药性或敏感性。确定了已知和新的相互作用,其中一个相互作用,即 KEAP1 突变型肺肿瘤对铂类治疗的耐药性,使用大型患者反应数据集进行了验证。这些结果突出了肿瘤抑制基因基因型对治疗反应的广泛影响,并定义了一种识别精准治疗决定因素的策略。意义:生成将肿瘤基因型与治疗反应相关联的药物基因组学图谱的实验和分析框架揭示了一个令人惊讶的复杂的基因型特异性耐药性和敏感性图谱。

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