铁死亡相关基因影响肝细胞癌肿瘤微环境及预后风险研究OACSTPCD

Objective:To explore the heterogeneity of hepatocellular carcinoma(HCC),and investigate the association between ferroptosis-related genes and tumor microenvironment(TME),then construct a prognosis prediction model based on these genes through bioinformatics methods.The model aims to offer new strategies for preventing recurrence in HCC pa-tients.Methods:Based on TCGA and NODE databases,non-negative matrix factorization clustering was applied to identify molecular subtypes of ferroptosis-related genes.The ESTIMATE and CIBERSORT algorithms were employed to calculate im-mune scores,while Cox regression analysis was used to develop a risk assessment model and calculate risk scores.A nomo-gram incorporating risk scores and clinical features was established,and in vitro experiments were conducted to validate mR-NA expression levels.Results:HCC was classified into two distinct ferroptosis-related immune molecular subtypes,showing significant difference in immune scores(P＜0.001).G6PD,KIF20A,RRM2 and TXN were identified as the optimal can-didate genes for the risk assessment model.The nomogram accurately predicts the likelihood of HCC recurrence.In vitro ex-periments revealed increased expression levels of these four genes in liver cancer cells(P＜0.05).Conclusion:HCC can be classified into two molecular subtypes which are associated with HCC recurrence,suggesting a critical role of ferroptosis in the TME.The four identified genes may be potential factors for preventing HCC recurrence,and the prognosis prediction model shows significant potential for predicting recurrence of HCC.