INCISOR：一种识别对靶向治疗和免疫治疗耐药的合成救援介质的算法。

INCISOR: An Algorithm to Identify Synthetic Rescue Mediators of Resistance to Targeted and Immunotherapy.

作者信息

Wang Xiaoman, Vizeacoumar Frederick Sagayaraj, Sahu Avinash Das

机构信息

Dana Farber Cancer Institute, Boston, MA, USA.

State Key Laboratory of Medical Molecular Biology, Department of Biochemistry and Molecular Biology, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.

出版信息

Methods Mol Biol. 2021;2381:203-215. doi: 10.1007/978-1-0716-1740-3_11.

DOI:10.1007/978-1-0716-1740-3_11

PMID:34590278

Abstract

Despite the success of targeted therapies including immunotherapies in cancer treatments, tumor resistance to targeted therapies remains a fundamental challenge. Tumors can evolve resistance to a therapy that targets one gene by acquiring compensatory alterations in another gene, such compensatory interaction between two genes is referred to as synthetic rescue (SR) interactions. To identify SRs, here we describe an algorithm, INCISOR, that leverages tumor transcriptomics and clinical information from 10,000 patients as well as data from experimental screens. INCISOR can identify SRs that are common across several cancer-types in genome-wide fashion by sifting through half a billion possible gene-gene combinations and provide a framework to design therapies to tackle resistance.

摘要

尽管包括免疫疗法在内的靶向疗法在癌症治疗中取得了成功，但肿瘤对靶向疗法的耐药性仍然是一个根本性挑战。肿瘤可以通过在另一个基因中获得补偿性改变来对靶向一个基因的疗法产生耐药性，两个基因之间的这种补偿性相互作用被称为合成拯救（SR）相互作用。为了识别SR相互作用，我们在此描述了一种算法INCISOR，它利用来自10000名患者的肿瘤转录组学和临床信息以及实验筛选数据。INCISOR可以通过筛选5亿种可能的基因-基因组合，以全基因组方式识别几种癌症类型中常见的SR相互作用，并提供一个设计疗法来应对耐药性的框架。