M6a Regulator-Associated Methylation Modification Patterns Shape Tumor Microenvironment Characteristics in Hepatocellular Carcinoma

Abstract Although substantial achievements in the tumor microenvironment (TME) of hepatocellular carcinoma (HCC) have led to fundamental improvements both in the basic research and clinical management, the potential mechanisms and regulatory relationships between m6A regulators and the TME are still unknown. We first conducted unsupervised clustering on the samples according to the core m6A expression, and then compared the signaling pathways, differential genes (DEGs), and TME between the m6A phenotypes, and re-validated the relationship between m6A regulators and TME by single cell sequencing. Then, the geneCluster was obtained by another unsupervised clustering of the DEGs, and the clinical as well as TME traits were evaluated among the geneClusters. Finally, the m6A scores of individual patients were calculated by principal component analysis (PCA) to verify the correlation from multiple perspectives, including survivals, clinical characters, mutations, TME, immunotherapy, and chemotherapy. Through a comprehensive analysis of 729 samples, we classified HCC patients into three m6A clusters and three geneClusters. Each group exhibited remarkable variations in terms of signaling pathways, clinical traits, and survival expectations. Notably, the m6A phenotypes corresponded to three different types of TME, namely immune-inflamed, immune-excluded, and immune-desert, respectively. In addition, the m6A regulator can accurately reflect the individualized microenvironment in HCC, and present supreme expression levels in the stromal microenvironment. However, the m6A score system is able to make accurate predictions not only in terms of clinical traits, survival prediction, and TME mentioned above, but also in the sensitivity of HCC patients to immunotherapy and chemotherapy. This study revealed the uniqueness and pluripotency of m6A regulators in the TME of HCC by combining single-cell sequencing and bulk sequencing. The quantified m6A modification indices were able to accurately predict patient survival expectations, clinical traits, TME, and sensitivity to immunotherapy and chemotherapy.