M6A-related lncRNAs predict clinical outcome and regulate the tumor immune microenvironment in hepatocellular carcinoma

LncRNA N6-methylandenosine (m6A) modification has been shown to be associated with the constitution of the tumor microenvironment (TME) and tumorigenesis. It's essential to understand the mechanisms of lncRNA m6A modification in hepatocellular carcinoma (HCC) and identify relative prognostic predictors to guide therapy and explore potential therapeutic targets. Pearson correlation analysis was performed to identify m6A-related lncRNAs in 374 patients with HCC. Unsupervised cluster analysis of the potential m6A-related lncRNA-based HCC subtypes was conducted, followed by the concurrent analysis of their relationship with TME characteristics, immune checkpoints, immune features, and prognosis through single sample gene set enrichment analysis and ESTIMATE algorithm. Cox regression analyses were performed to screen prognostic m6A-related lncRNA, construct an m6A-related lncRNA signature (m6A-RLRS), and establish an integrated nomogram for the prognosis of patients with HCC. We identified 61 m6A-related lncRNAs and two HCC subtypes defined by consensus cluster of m6A-related lncRNAs with distinct clinical features. Progression-free survival (PFS), three TME-related scores, 15 immune-associated gene sets, and two immune checkpoints expression were found to be significantly different among the two subtypes. Twenty-five prognostic m6A-related lncRNAs were determined, four of which were included to establish an m6A-RLRS with favorable discrimination, and the signature was validated in the validation set and an independent FAHWMU cohort (n = 60). Furthermore, a novel nomogram combining signature and clinical predictors was generated with a C-index of 0.703, and an original ceRNA regulatory network consisting of 9 lncRNAs, 28 miRNAs, and 75 target mRNAs was constructed. Finally, the differential expression of four m6A-related lncRNA was verified by qRT-PCR. In conclusion, m6A-related lncRNA prognostic signature and molecular subtype contributes to accurately predict the prognosis of HCC and provide potential novel therapeutic targets.