Immune prognostic implications of PSMD14 and its associated genes signatures in hepatocellular carcinoma

PSMD14 played a vital role in initiation and progression of hepatocellular carcinoma(HCC).However,PSMD14 and its-related genes for the immune prognostic implications of HCC patients have rarely been analyzed.Messenger RNA expression profiles and clinicopathological data were downloaded from The Cancer Genome Atlas(TCGA)and International Cancer Genome Consortium(ICGC)database-Liver Hepatocellular Carcinoma(LIHC).Additionally,we used multi-dimensional bioinformatics analysis to construct and validate a PSMD14-based immune prognostic signature(including RBM45,PSMD1,OLA1,CCT6A,LCAT and IVD)for HCC prognosis prediction.Patients in the high-risk group shown significantly poorer survival than patients in the low-risk group.Calibration curves confirmed the good consistency between the clinical nomogram prediction and the actual observation.Gene set enrichment analyses(GSEA)revealed several significantly enriched pathways,which might help explain the underlying mechanisms.Besides,the rt-PCR further validates the expression of seven immune genes in HCC cells.Our study identified a novel PSMD14-based signature for HCC prognosis prediction,it provided new potential prognostic biomarkers and therapeutic targets for immunotherapy of HCC.

A novel nomogram for predicting the prognosis of hepatocellular carcinoma patients following immune checkpoint inhibitors treatment beyond progression:a single center study based on Chinese population

Background:Hepatocellular carcinoma(HCC)persists as a dominant cause of cancer-related mortality globally,with a notably rapid escalation in mortality rates.The advent of immunotherapy,particularly immune checkpoint inhibitors(ICIs),has ushered in a new era in the management of liver cancer,albeit with unresolved challenges in the context of treatment beyond progression(TBP)and stratified prognosis in diverse populations.This study aimed to develop and validate a novel nomogram model to identify factors that predict the benefit of continued immunotherapy for hepatocellular carcinoma patients following disease progression in clinical practice.Methods:This study retrospectively analyzed the efficacy of ICIs in TBP,focusing on the Chinese population with advanced liver cancer.A nomogram was constructed based on four independent risk factors identified through Cox multivariate analysis,aiming to predict patient prognosis post-ICI treatment.The model was validated through receiver operating characteristic(ROC)curve analysis and categorized patients into high-,intermediate-,and low-risk groups,with further validation using calibration plots and decision curve analysis(DCA).Results:The low-risk group demonstrated significantly enhanced overall survival(OS)compared to the high-risk group,with the nomogram predictions aligning closely with actual outcomes for 6-and 9-month OS.The model exhibited commendable predictive accuracy,achieving a C-index exceeding 0.7 in both training and validation datasets.The DCA underscored the clinical utility of the nomogram-based prognostic model,further substantiated by the area under the ROC curve(AUC).Conclusions:The developed nomogram presents a potentially valuable tool for predicting the prognosis of HCC patients undergoing ICI therapy beyond progression,particularly within the Chinese demographic.However,the study is constrained by its retrospective,single-center nature and necessitates further validation through large-scale,multicenter clinical studies across varied populations.