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Background:  Hepatocellular carcinoma (HCC) is the sixth most common malignancy with a high mortality worldwide. N6-methyladenosine (m6A) may participate extensively in tumor progression.   Methods:  To reveal the landscape of tumor immune microenvironment (TIME), ESTIMATE analysis, ssGSEA algorithm, and the CIBERSORT method were used. Taking advantage of consensus clustering, two different HCC categories were screened. We analyzed the correlation of clustering results with TIME and immunotherapy. Then, we yielded a risk signature by systematical bioinformatics analyses. Immunophenoscore (IPS) was implemented to estimate the immunotherapeutic significance of risk signature.   Results:  The m6A-based clusters were significantly correlated with overall survival (OS), immune score, immunological signature, immune infiltrating, and ICB-associated genes. Risk signature possessed robust prognostic validity and significantly correlated with TIME context. IPS was employed as a surrogate of immunotherapeutic outcome, and patients with low-risk scores showed significantly higher immunophenoscores.   Conclusion:  Collectively, m6A-based clustering subtype and signature was a robust prognostic indicator and correlated with TIME and immunotherapy, providing novel insight into antitumor management and prognostic prediction in HCC.

Landscape of Prognostic m6A RNA Methylation Regulators in Hepatocellular Carcinoma to Aid Immunotherapy