Objectives:Tumor recurrence is a major determinant of poor prognosis in hepatocellular carcinoma(HCC),yet its cellular and molecular basis remains incompletely understood.This study aimed to identify recurrenceassocia...Objectives:Tumor recurrence is a major determinant of poor prognosis in hepatocellular carcinoma(HCC),yet its cellular and molecular basis remains incompletely understood.This study aimed to identify recurrenceassociated genes at single-cell resolution and to develop a prognostic model for predicting survival outcomes and immunotherapy responsiveness in HCC.Methods:Single-cell RNA sequencing data from 12 primary and 6 recurrent HCC samples were integrated and analyzed to identify genes characteristic of recurrence.After quality control,principal component analysis,and t-SNE-based clustering were used to identify highly variable genes for cell clustering and annotation.Based on macrophage characteristic genes,a recurrence-related risk score was constructed using a LASSOCox regression model,and a nomogram integrating clinical variables was developed.Prognostic performance was assessed using Kaplan-Meier analysis and time-dependent ROC curves.Immune infiltration profiling was performed to compare immune characteristics between risk groups defined by the prognostic model.Multivariate Cox regression was applied to identify independent prognostic biomarkers,which were subsequently validated by cell function experiments.Results:The risk model effectively stratified patients into high-and low-risk groups with distinct survival outcomes,demonstrating high predictive accuracy for 1-,3-,and 5-year survival.High-risk patients showed altered immune profiles and a reduced predicted response to immunotherapy.GRID2,RNF186,and SLC4A10 were identified as independent prognostic genes,with RNF186 promoting HCC cell proliferation in a SESN2-dependent manner.Conclusion:This prognostic model provides new insights into precision medicine and immunotherapy for HCC,highlighting the potential clinical significance of RNF186 as a therapeutic target.展开更多
文摘Objectives:Tumor recurrence is a major determinant of poor prognosis in hepatocellular carcinoma(HCC),yet its cellular and molecular basis remains incompletely understood.This study aimed to identify recurrenceassociated genes at single-cell resolution and to develop a prognostic model for predicting survival outcomes and immunotherapy responsiveness in HCC.Methods:Single-cell RNA sequencing data from 12 primary and 6 recurrent HCC samples were integrated and analyzed to identify genes characteristic of recurrence.After quality control,principal component analysis,and t-SNE-based clustering were used to identify highly variable genes for cell clustering and annotation.Based on macrophage characteristic genes,a recurrence-related risk score was constructed using a LASSOCox regression model,and a nomogram integrating clinical variables was developed.Prognostic performance was assessed using Kaplan-Meier analysis and time-dependent ROC curves.Immune infiltration profiling was performed to compare immune characteristics between risk groups defined by the prognostic model.Multivariate Cox regression was applied to identify independent prognostic biomarkers,which were subsequently validated by cell function experiments.Results:The risk model effectively stratified patients into high-and low-risk groups with distinct survival outcomes,demonstrating high predictive accuracy for 1-,3-,and 5-year survival.High-risk patients showed altered immune profiles and a reduced predicted response to immunotherapy.GRID2,RNF186,and SLC4A10 were identified as independent prognostic genes,with RNF186 promoting HCC cell proliferation in a SESN2-dependent manner.Conclusion:This prognostic model provides new insights into precision medicine and immunotherapy for HCC,highlighting the potential clinical significance of RNF186 as a therapeutic target.
