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共突变的综合分析确定肿瘤发生的协同机制。

Comprehensive Analysis of Co-Mutations Identifies Cooperating Mechanisms of Tumorigenesis.

作者信息

Jiang Limin, Yu Hui, Ness Scott, Mao Peng, Guo Fei, Tang Jijun, Guo Yan

机构信息

Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.

School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin 300350, China.

出版信息

Cancers (Basel). 2022 Jan 14;14(2):415. doi: 10.3390/cancers14020415.

Abstract

Somatic mutations are one of the most important factors in tumorigenesis and are the focus of most cancer-sequencing efforts. The co-occurrence of multiple mutations in one tumor has gained increasing attention as a means of identifying cooperating mutations or pathways that contribute to cancer. Using multi-omics, phenotypical, and clinical data from 29,559 cancer subjects and 1747 cancer cell lines covering 78 distinct cancer types, we show that co-mutations are associated with prognosis, drug sensitivity, and disparities in sex, age, and race. Some co-mutation combinations displayed stronger effects than their corresponding single mutations. For example, co-mutation : in pancreatic adenocarcinoma is significantly associated with disease specific survival (hazard ratio = 2.87, adjusted -value = 0.0003) and its prognostic predictive power is greater than either or as individually mutated genes. Functional analyses revealed that co-mutations with higher prognostic values have higher potential impact and cause greater dysregulation of gene expression. Furthermore, many of the prognostically significant co-mutations caused gains or losses of binding sequences of RNA binding proteins or micro RNAs with known cancer associations. Thus, detailed analyses of co-mutations can identify mechanisms that cooperate in tumorigenesis.

摘要

体细胞突变是肿瘤发生的最重要因素之一,也是大多数癌症测序研究的重点。肿瘤中多个突变的共现作为一种识别有助于癌症发生的协同突变或途径的方法,越来越受到关注。利用来自29559名癌症患者和1747个癌细胞系的多组学、表型和临床数据,涵盖78种不同癌症类型,我们发现共突变与预后、药物敏感性以及性别、年龄和种族差异有关。一些共突变组合显示出比其相应单突变更强的效应。例如,胰腺腺癌中的共突变与疾病特异性生存显著相关(风险比 = 2.87,校正P值 = 0.0003),其预后预测能力大于单独突变基因KRAS或TP53。功能分析表明,具有较高预后价值的共突变具有更高的潜在影响,并导致基因表达的更大失调。此外,许多具有预后意义的共突变导致了与已知癌症关联的RNA结合蛋白或微小RNA结合序列的获得或丢失。因此,对共突变的详细分析可以识别在肿瘤发生中协同作用的机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/af2a/8774165/72ffce26e7bc/cancers-14-00415-g001.jpg

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