Comprehensive Analysis of Co-Mutations Identifies Cooperating Mechanisms of Tumorigenesis
1
Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
2
School of Computer Science and Technology, College of Intelligence and Computing, Tianjin University, Tianjin 300350, China
3
Department of Internal Medicine, Comprehensive Cancer Center, University of New Mexico, Albuquerque, NM 87131, USA
4
School of Computer Science and Engineering, Central South University, Changsha 410083, China
*
Authors to whom correspondence should be addressed.
Cancers 2022, 14(2), 415; https://doi.org/10.3390/cancers14020415
Submission received: 13 December 2021
/
Revised: 7 January 2022
/
Accepted: 11 January 2022
/
Published: 14 January 2022
(This article belongs to the Special Issue Bioinformatics, Big Data and Cancer)
Simple Summary
Somatic mutations are one of the most important causal factors of cancers. In this study, we show that certain mutations, when occurring simultaneously, have a stronger biological effect than their single counterpart. These effects include prognosis and drug sensitivity.
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 TP53:KRAS in pancreatic adenocarcinoma is significantly associated with disease specific survival (hazard ratio = 2.87, adjusted p-value = 0.0003) and its prognostic predictive power is greater than either TP53 or KRAS 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.
Keywords:
cancer; mutation; co-mutation; prognosis; drug sensitivity
