Untangling a complex web: Computational analyses of tumor molecular profiles to decode driver mechanisms

作     者：Sirvan Khalighi Salendra Singh Vinay Varadan Sirvan Khalighi;Salendra Singh;Vinay Varadan

作者机构：Division of General Medical Sciences-OncologyCase Comprehensive Cancer CenterCase Western Reserve University School of MedicineClevelandOH 44106USA 

出 版 物：《Journal of Genetics and Genomics》 (遗传学报（英文版）)

年 卷 期：2020年第47卷第10期

页      面：595-609页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 0711[理学-系统科学] 1002[医学-临床医学] 07[理学] 08[工学] 100214[医学-肿瘤学] 10[医学] 

基　　金：supported by PHS awards:T32 CA094186 to S.K. K25 DK115904 to V.V. P30 CA043703 to V.V. and P20 CA233216 to V.V 

主　　题：Mutations Systems biology Mutational significance Functional impact Pan-cancer analysis Multiomics integration 

摘      要：Genome-scale studies focusing on molecular profiling of cancers across tissue types have revealed a plethora of aberrations across the genomic,transcriptomic,and epigenomic *** significant molecular heterogeneity across individual tumors even within the same tissue context complicates decoding the key etiologic mechanisms of this ***,it is increasingly likely that biologic mechanisms underlying the pathobiology of cancer involve multiple molecular entities interacting across functional *** has motivated the development of computational approaches that integrate molecular measurements with prior biological knowledge in increasingly intricate ways to enable the discovery of driver genomic aberrations across ***,we review diverse methodological approaches that have powered significant advances in our understanding of the genomic underpinnings of cancer at the cohort and at the individual tumor *** outline the key advances and challenges in the computational discovery of cancer mechanisms while motivating the development of systems biology approaches to comprehensively decode the biologic drivers of this complex disease.