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基于整合表观基因组学的策略，对临床激酶抑制剂进行无偏功能分析。

An integrative epigenome-based strategy for unbiased functional profiling of clinical kinase inhibitors.

机构信息

Department of Experimental Oncology, IEO, European Institute of Oncology IRCCS, Milano, 20139, Italy.

出版信息

Mol Syst Biol. 2024 Jun;20(6):626-650. doi: 10.1038/s44320-024-00040-x. Epub 2024 May 9.

DOI:10.1038/s44320-024-00040-x
PMID:38724853
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11148061/
Abstract

More than 500 kinases are implicated in the control of most cellular process in mammals, and deregulation of their activity is linked to cancer and inflammatory disorders. 80 clinical kinase inhibitors (CKIs) have been approved for clinical use and hundreds are in various stages of development. However, CKIs inhibit other kinases in addition to the intended target(s), causing both enhanced clinical effects and undesired side effects that are only partially predictable based on in vitro selectivity profiling. Here, we report an integrative approach grounded on the use of chromatin modifications as unbiased, information-rich readouts of the functional effects of CKIs on macrophage activation. This approach exceeded the performance of transcriptome-based approaches and allowed us to identify similarities and differences among CKIs with identical intended targets, to recognize novel CKI specificities and to pinpoint CKIs that may be repurposed to control inflammation, thus supporting the utility of this strategy to improve selection and use of CKIs in clinical settings.

摘要

在哺乳动物中，有超过 500 种激酶参与控制大多数细胞过程，其活性的失调与癌症和炎症性疾病有关。已经有 80 种临床激酶抑制剂 (CKI) 被批准用于临床使用，还有数百种处于不同的开发阶段。然而，CKI 除了抑制预期的靶标外，还会抑制其他激酶，从而导致增强的临床效果和不可预测的副作用，这些副作用仅部分可以根据体外选择性分析进行预测。在这里，我们报告了一种基于染色质修饰的综合方法，该方法将染色质修饰作为 CKIs 对巨噬细胞激活功能影响的无偏、信息丰富的读出。这种方法优于基于转录组的方法，并使我们能够识别具有相同预期靶标的 CKI 之间的相似性和差异性，识别新的 CKI 特异性，并确定可能被重新用于控制炎症的 CKI，从而支持该策略在改善 CKIs 在临床环境中的选择和使用方面的实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a662/11148061/b926f4ac4226/44320_2024_40_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a662/11148061/ec4622bd9922/44320_2024_40_Fig1_HTML.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a662/11148061/256283dd7d8f/44320_2024_40_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a662/11148061/c50a7f9e1cd9/44320_2024_40_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a662/11148061/b926f4ac4226/44320_2024_40_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a662/11148061/ec4622bd9922/44320_2024_40_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a662/11148061/c65e1a78069c/44320_2024_40_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a662/11148061/f89b6e21f205/44320_2024_40_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a662/11148061/256283dd7d8f/44320_2024_40_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a662/11148061/c50a7f9e1cd9/44320_2024_40_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a662/11148061/b926f4ac4226/44320_2024_40_Fig6_HTML.jpg

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