Implications of m6A-associated snRNAs in the prognosis and immunotherapeutic responses of hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is the most prevalent pathological type of liver cancer worldwide with high mortality and poor prognosis. N6-methyladenosine (m6A) can modify RNAs such as mRNA, lncRNA, miRNA, and tRNA, thereby playing a critical role in the pathogenesis of HCC. However, the role of m6A-associated small nuclear RNA (snRNA) in the prognostic value and immunotherapeutic response in HCC remains unclear. Materials and methods: In this study, snRNA expression data, gene mutation data, and clinical data of HCC patients were acquired from The Cancer Genome Atlas (TCGA) database. We used the least absolute shrinkage and selection operator (LASSO) Cox regression analysis to identify significant prognostic m6A-associated snRNAs, and then developed a multivariate Cox model based on the selected snRNAs. HCC patients were split into low- and high-risk groups based on the median risk score. We subsequently performed Kaplan-Meier curve analysis to estimate overall survival (OS) by clinicopathological characteristics and tumor mutational burden (TMB) status in low- and high-risk HCC patients. Finally, we compared the immunotherapeutic response as represented by tumor immune dysfunction and exclusion (TIDE) scores between the two risk groups. Results: Eight m6A-associated snRNAs were selected as independent predictors to develop the risk model. Our results revealed that the OS of HCC patients in the high-risk group was significantly worse than that in the low-risk group on clinicopathologic characteristics, including age (≤65 years and >65 years), gender (male), grade (G I-II and G III-IV) and TNM staging (Stage I-II and Stage III-IV). In addition, the OS of low-TMB and low-risk group was longer than that of high-TMB and high-risk group. The TIDE score indicated that HCC patients in the high-risk group were more susceptible to immunotherapy. Conclusion: Our study suggests that m6A-associated snRNAs may be useful biomarkers for the prognosis of HCC and that m6A-associated snRNA models can predict the effect of immunotherapy in HCC patients.