Hepatocellular carcinoma (HCC) is highly heterogeneous. Molecular subtyping for guiding immunotherapy is warranted. Previous studies have indicated that enhancer RNAs (eRNAs) are involved in tumor heterogeneity and immune infiltration. However, the eRNA landscape and its correlation with immune infiltration in HCC remain unknown. Here we first revealed the genome-wide eRNA landscape in two HCC cohorts. Then we divided individuals with HCC into three immune-related clusters (C1, C2, and C3) based on eRNA expression profiles. The prognosis, biological properties, immune infiltration, clinical features, genomic features, and drug response were analyzed. C1 was enriched in immune infiltration and potentially sensitive to immune checkpoint inhibitors (ICIs). C2 displayed features of immune depletion, high proliferation activity, malignant clinical features, and the worst prognosis. C2 may benefit from targeted therapy. C3 presented moderate immune infiltration, metabolism-related signatures, and the best prognosis. Transarterial chemoembolization (TACE) may be effective for C3. Finally, we constructed a 51-eRNA classifier for subtype prediction and validated its efficacy in The Cancer Genome Atlas (TCGA) cohort and Sun Yat-sen University Cancer Center (SYSUCC) cohort. Our results provide a novel method for immune classification of HCC, shed new light on tumor heterogeneity, and may aid in HCC immunotherapy.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9310078PMC
http://dx.doi.org/10.1016/j.omto.2022.07.001DOI Listing

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