M6A regulator-mediated immune infiltration and methylation modification in hepatocellular carcinoma microenvironment and immunotherapy - Zhao, Kun; Wei, Bing; Zhang, Yingxuan; Shi, Wenkai; Zhang, Guokun; Wang, Zhengfeng (Frontiers in Pharmacology, 2022)
Introduction: Tremendous evidences indicated that N6-methyladenosine (m6A) epigenetic modification and m6A-releted enzymes constitute a complex network, which jointly regulates prevailing pathological processes and various signaling pathways in humankind. Currently, the role of m6A-mediated molecular regulatory network in hepatocellular carcinoma (HCC) remains elusive. Methods: We recruited expression and pathological files of 368 HCC patients from The Cancer Genome Atlas cohort. Four public datasets serve as external authentication sets for nearest template prediction (NTP) validation. The correlation between 35 regulators and their prognostic value were compared. Gene set variation analysis (GSVA) was used to explore the latent mechanism. Using four independent algorithms (ssGSEA, xCell, MCPcounter, and TIMER) to calculated the ratio of tumor cells and non-tumor cells to evolute the tumor immune microenvironment. The m6Ascore model was established by principal component analysis (PCA). Prediction of immunotherapy and potential drugs were performed by TIDE and submap. Results: The 35 m6A regulators were widely associated, most of which were risk factors for HCC patients. M6A phenotypic-cluster revealed differences in regulator transcriptional level, gene mutation frequency, functional pathways and immune cell infiltration abundance under distinct m6A patterns. As expected, m6A gene-cluster confirmed the above results. The m6Ascore model further found that patients in high m6Ascore group were associated with lower tumor purity, higher enrichment of immune and stromal cells, up-regulation of metabolic pathways, lower expression of m6A regulators, and favorable outcomes. Low m6Ascore patients were associated with adverse outcomes. Notably, low m6Ascore patients might be more sensitive to anti-PD-L1 therapy. Conclusions: This study found that a classification model based on m6A manner could predict HCC prognosis and response to immunotherapy for HCC patients, which might improve prognosis and contribute to clinical individualized decision making.