A Metabolism-related Gene Prognostic Index In HBV-infected Hepatocellular Carcinoma

Objective:One of the important hallmarks of cancer is metabolic reprogramming.A variety of alterations in the metabolic profile can be presented in hepatocellular carcinoma due to hepatitis B.However,the impact of such alterations on the tumour immune microenvironment and the efficacy of immunotherapy remains unclear.Here,we constructed a prognostic signature of metabolism-related gene composition and described the immune profile in different subgroups as well as the potential response to immunotherapy.Methods:Obtain HBV-infected hepatocellular carcinoma dataset in TCGA.Metabolismassociated genes were obtained in databases such as KEGG.WGCNA analysis of metabolism-related genes and identification of co-expressed modules.Perform GO and KEGG enrichment analysis on genes within co-expressed modules.Identification of differentially expressed genes in HBV-infected hepatocellular carcinoma.Define the intersection of differentially expressed metabolic genes and co-expressed module genes as differentially expressed module genes.GO and KEGG enrichment analysis was performed on differentially expressed module genes.The differentially expressed module genes were subjected to survival analysis to identify metabolism-related genes associated with survival.The survival-related metabolism-related genes were subjected to multi-factor cox regression analysis to identify independent prognostic genes.This was further combined with clinical information to construct a MRGPI consisting of two genes,and the model was validated by the GEO dataset.Samples were divided into high and low scoring groups based on the prognostic index scores,and differentially expressed genes were identified by comparing the two groups.The high and low differentially expressed genes were subjected to GSEA enrichment analysis separately as a way to identify the molecular characteristics of the different scoring groups.CIBERSORT was used to analyse the immune cell composition of HBV-infected liver cancer patients.TIDE was used to assess the potential clinical efficacy of immunotherapy in the different scoring groups.Potential therapeutic response of samples to conventional drugs was predicted based on pharmacogenomic databases.Results:1.3937 genes were grouped into five modules by WGCNA,with the blue module being the most associated with HBV infection.The three metabolism-related key genes,ATIC,KIF2 C and POLR3 C,which were significantly associated with survival,were indicated by univariate Cox regression analysis.Multi-factor Cox regression analysis identified two independent prognostic markers,ATIC and KIF2 C,which were used to construct a prognostic index for metabolism-related genes.The predictive power of the model was validated in the GEO database.2.In patients infected with HBV,the results of univariate Cox regression analysis showed that risk groups were significantly associated with overall survival.In the multifactor Cox regression analysis,MRGPI risk group was still shown to be an independent predictor significantly associated with overall survival.Comparison of clinical information and molecular characteristics between groups revealed no significant differences between MRGPI risk groups for the Stage distribution and significant differences for the Grade distribution.3.The level of immune cell infiltration differed between MRGPI risk groups.B cells memory and Macrophages M0 were more abundant in the high MRGPI risk group(2),while Monocytes and Mast cells resting were more abundant in the low MRGPI risk group(2).4.The low MRGPI risk group had lower TIDE scores than the high MRGPI risk group.Therefore the low MRGPI risk group had a better immunotherapy outcome than the high MRGPI risk group.The low MRGPI risk group had higher MSI and T-cell dysfunction scores,and lower T-cell exclusion scores.This means that patients in the low MRGPI risk group are more likely to benefit from immunotherapy than those in the high MRGPI risk group.5.The drug Sorafenib showed a higher sensitivity in the high MRGPI risk group.The drugs A.443654 and ABT.263 were also similar to Sorafenib in that both were more sensitive in the high MRGPI risk group.In contrast,the drug AZD6244 showed higher sensitivity in the low MRGPI risk group.Conclusion:MRGPI is a promising biomarker for predicting the prognosis and immune profile of HCC due to HBV infection and for differentiating the prognosis of immunotherapy from conventional drug therapy.