Revealing the contribution of somatic gene mutations to shaping tumor immune microenvironment

免疫系统 免疫疗法 生物 肿瘤微环境 CD8型 癌症免疫疗法 免疫分型 体细胞 基因 癌症研究 免疫学 遗传学 抗原
作者
Liwen Xu,Shiwei Zhu,Yujia Lan,Min Yan,Ze D. Jiang,Jiali Zhu,Gaoming Liao,Yanyan Ping,Jiu Hua Xu,Bo Pang,Yunpeng Zhang,Yun Xiao,Xia Li
出处
期刊:Briefings in Bioinformatics [Oxford University Press]
卷期号:23 (3) 被引量:5
标识
DOI:10.1093/bib/bbac064
摘要

Interaction between tumor cells and immune cells determined highly heterogeneous microenvironments across patients, leading to substantial variation in clinical benefits from immunotherapy. Somatic gene mutations were found not only to elicit adaptive immunity but also to influence the composition of tumor immune microenvironment and various processes of antitumor immunity. However, due to an incomplete view of associations between gene mutations and immunophenotypes, how tumor cells shape the immune microenvironment and further determine the clinical benefit of immunotherapy is still unclear. To address this, we proposed a computational approach, inference of mutation effect on immunophenotype by integrated gene set enrichment analysis (MEIGSEA), for tracing back the genomic factor responsible for differences in immunophenotypes. MEIGSEA was demonstrated to accurately identify the previous confirmed immune-associated gene mutations, and systematic evaluation in simulation data further supported its performance. We used MEIGSEA to investigate the influence of driver gene mutations on the infiltration of 22 immune cell types across 19 cancers from The Cancer Genome Atlas. The top associated gene mutations with infiltration of CD8 T cells, such as CASP8, KRAS and EGFR, also showed extensive impact on other immune components; meanwhile, immune effector cells shared critical gene mutations that collaboratively contribute to shaping distinct tumor immune microenvironment. Furthermore, we highlighted the predictive capacity of gene mutations that are positively associated with CD8 T cells for the clinical benefit of immunotherapy. Taken together, we present a computational framework to help illustrate the potential of somatic gene mutations in shaping the tumor immune microenvironment.
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