Development of a novel 4-protein signature for prognostic prediction in hepatitis B virus-induced hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) remains a major global health challenge, with the pathogenesis of HBV-induced HCC incompletely understood. Due to HCC's significant heterogeneity, more accurate prognostic models and reliable biomarkers are urgently needed. This study aimed to develop such tools for HBV-related HCC. METHODS: Protein expression profiles and clinicopathological data were obtained from the CPTAC (Clinical Proteomic Tumor Analysis Consortium) database. Differential protein expression analysis between HBV-induced HCC and normal tissues were performed, followed by univariate and multivariate Cox regression to construct a prognostic protein signature. The four-protein signature's prognostic power was assessed using time-dependent receiver operating characteristic (ROC) curves, Kaplan-Meier analysis, multivariate Cox regression, and a nomogram. Protein expression levels of the four proteins were validated in clinical specimens of HBV-related HCC. The signature was further validated in an independent cohort. RESULTS: A novel four-protein signature (SMC2, SMC4, UBE2C, UHRF1) was established for prognostic prediction in HBV-related HCC. ROC curves demonstrated good survival prediction performance in both the CPTAC HCC cohort and the validation cohort. Transcriptomic and immunohistochemical (IHC) analyses revealed significant overexpression of these four proteins at both mRNA and protein levels in HCC tissues. The signature stratified patients into high-risk and low-risk groups with significantly different survival outcomes. Multivariate Cox regression analysis confirmed that the 4-protein signature independently predicted overall survival (OS). Furthermore, the signature showed strong discriminatory power between HBV-related HCC and normal tissue. Time-dependent ROC analysis indicated that the protein signature exhibited superior specificity and sensitivity compared to alpha-fetoprotein (AFP) for diagnosing HBV-associated HCC. CONCLUSIONS: Our study establishes a novel 4-protein signature and nomogram for predicting OS in HBV-related HCC, potentially aiding individualized clinical treatment decisions.