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神经内分泌肿瘤中机制依赖性的药理学靶向的精准肿瘤学方法。

A precision oncology approach to the pharmacological targeting of mechanistic dependencies in neuroendocrine tumors.

机构信息

Department of Systems Biology, Columbia University, New York, NY, USA.

DarwinHealth Inc, New York, NY, USA.

出版信息

Nat Genet. 2018 Jul;50(7):979-989. doi: 10.1038/s41588-018-0138-4. Epub 2018 Jun 18.

Abstract

We introduce and validate a new precision oncology framework for the systematic prioritization of drugs targeting mechanistic tumor dependencies in individual patients. Compounds are prioritized on the basis of their ability to invert the concerted activity of master regulator proteins that mechanistically regulate tumor cell state, as assessed from systematic drug perturbation assays. We validated the approach on a cohort of 212 gastroenteropancreatic neuroendocrine tumors (GEP-NETs), a rare malignancy originating in the pancreas and gastrointestinal tract. The analysis identified several master regulator proteins, including key regulators of neuroendocrine lineage progenitor state and immunoevasion, whose role as critical tumor dependencies was experimentally confirmed. Transcriptome analysis of GEP-NET-derived cells, perturbed with a library of 107 compounds, identified the HDAC class I inhibitor entinostat as a potent inhibitor of master regulator activity for 42% of metastatic GEP-NET patients, abrogating tumor growth in vivo. This approach may thus complement current efforts in precision oncology.

摘要

我们引入并验证了一种新的精准肿瘤学框架,用于系统地优先考虑针对个体患者的机制肿瘤依赖性的药物。化合物根据其从系统药物扰动测定中评估的,反转机制上调节肿瘤细胞状态的主调节蛋白协同活性的能力进行优先排序。我们在一组 212 个胃肠胰神经内分泌肿瘤 (GEP-NET) 中验证了该方法,GEP-NET 是一种起源于胰腺和胃肠道的罕见恶性肿瘤。该分析确定了几种主调节蛋白,包括神经内分泌谱系祖细胞状态和免疫逃逸的关键调节剂,其作为关键肿瘤依赖性的作用已通过实验证实。用 107 种化合物库对 GEP-NET 衍生细胞进行转录组分析,确定组蛋白去乙酰化酶 (HDAC) 类 I 抑制剂恩替诺司他是 42%转移性 GEP-NET 患者的主调节蛋白活性的有效抑制剂,在体内阻断肿瘤生长。因此,这种方法可以补充当前的精准肿瘤学努力。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e4f3/6421579/30c8de9480bb/nihms-1012261-f0001.jpg

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