Identification and development of a novel risk model based on cuproptosis-associated RNA methylation regulators for predicting prognosis and characterizing immune status in hepatocellular carcinoma.

Background: Cuproptosis, a novel cell death caused by excess copper, is quite obscure in hepatocellular carcinoma (HCC) and needs more investigation.

Methods: RNA-seq and clinical data of HCC patients TCGA database were analyzed to establish a predictive model through LASSO Cox regression analysis. External dataset ICGC was used for the verification. GSEA and CIBERSORT were applied to investigate the molecular mechanisms and immune microenvironment of HCC. Cuproptosis induced by elesclomol was confirmed via various in vitro experiments. The expression of prognostic genes was verified in HCC tissues using qRT-PCR analysis.

Results: Initially, 18 cuproptosis-associated RNA methylation regulators (CARMRs) were selected for prognostic analysis. A nine-gene signature was created by applying the LASSO Cox regression method. Survival and ROC assays were carried out to validate the model using TCGA and ICGC database. Moreover, there exhibited obvious differences in drug sensitivity in terms of common drugs. A higher tumor mutation burden was shown in the high-risk group. Additionally, significant discrepancies were found between the two groups in metabolic pathways and RNA processing via GSEA analysis. Meanwhile, CIBERSORT analysis indicated different infiltrating levels of various immune cells between the two groups. Elesclomol treatment caused a unique form of programmed cell death accompanied by loss of lipoylated mitochondrial proteins and Fe-S cluster protein. The results of qRT-PCR indicated that most prognostic genes were differentially expressed in the HCC tissues.

Conclusion: Overall, our predictive signature displayed potential value in the prediction of overall survival of HCC patients and might provide valuable clues for personalized therapies.