AUTHOR=Xu Yangtao , He Xiaoqin , Deng Junjian , Xiong Lin , Li Yue , Zhang Xiaoyu , Chen Wenliang , Liu Xin , Xu Ximing 

TITLE=Comprehensive Analysis of the Immune Infiltrates and PD-L1 of m6A RNA Methylation Regulators in Hepatocellular Carcinoma

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=Volume 9 - 2021

YEAR=2021

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2021.681745

DOI=10.3389/fcell.2021.681745

ISSN=2296-634X

ABSTRACT=Hepatocellular carcinoma (HCC) is the most common type of liver cancer, which is significantly harmful to human health. Recently, the role of N6‐methyladenosine (m6A) RNA methylation in eukaryotic mRNA in the pathogenesis and prognosis of cancer has become increasingly obvious. Moreover, tumor microenvironment plays an important role in the regulation of tumorigenesis. In this research, the clinical data of 374 tumor and 50 normal patients was downloaded from the Cancer Genome Atlas (TCGA). Then 19 m6A RNA methylation regulators were selected from previous studies. HCC patients were clustered in cluster1 and cluster2, based on consensus clustering for the m6A RNA regulators. The m6A RNA methylation regulators were up-regulated in cluster1. The cluster1 was associated with higher PD-L1 expression level, higher immuescore, worse prognosis and distinct immune cell infiltration compared to cluster2. Furthermore, HCC patients were randomly divided into training dataset (170 patients) and validation dataset (170 patients). Univariate Cox analysis and LASSO regression to identify five risk signatures, including YTHDF1, YTHDF2, HNRNPC, WTAP and METTL3. HCC patients were divided into high-risk group and low-risk group according to riskscore. Similarly, the high-risk group was extremely associated with higher PD-L1 expression level, higher grade and worse overall survival (OS). Also, the cluster1 was mainly enrich in high-risk group. Receiver operating characteristic (ROC) and a nomogram were used to predictive the ability and the probability of 3‐ and 5‐year OS of HCC patients. In training dataset, the time-dependent ROC curve (AUC) reached 0.77, 0.67 and 0.68 at 1- year, 3- year and 5- year. And the 1- year, 3- year and 5- year AUC values were 0.7, 0.63 and 0.55 in validation dataset. The GSEA showed that MTOR signaling pathway and WNT signaling pathway were correlated with the cluster1 and high-risk group. Collectively, the research indicated that the m6A RNA regulators could play a crucial role in TIME in HCC. The m6A regulator-based risk signatures might predict the prognosis of HCC patients and provide new therapeutic targets in improving immunotherapeutic efficacy.