Construction and validation of a prognostic signature based on related genes in hepatocellular carcinoma

Introduction: Given the poor prognosis associated with hepatocellular carcinoma (HCC), identifying reliable biomarkers is critical to aid in prognostication and customized treatment planning. Objective: This study aimed to develop a prognostic gene signature based on anoikis- and autophagy-related genes (AARGs) to predict HCC prognosis. Methods: We analyzed differentially expressed AARGs associated with HCC prognosis using messenger RNA expression profiles and clinicopathological data from the Cancer Genome Atlas Liver Hepatocellular Carcinoma Database. Validation was performed using data from the International Cancer Genome Consortium. AARG signatures were constructed using univariate Cox regression and the least absolute shrinkage and selection operator method. Results: We identified 13 AARGs, of which nine showed significant associations with overall survival (OS). Three AARGs—baculoviral IAP repeat containing 5, mitogen-activated protein kinase 3, and BRI1-associated kinase 1—were selected to establish the prognostic AARGs signature. Statistical analyses confirmed the prognostic capacity of the model. Gene set enrichment analysis was performed to explore potential molecular mechanisms. Further investigations included assessments of clinical parameters, immune landscape, immune checkpoint blockade response, tumor stemness, and chemotherapy sensitivity. Immunohistochemistry was conducted to compare protein expression between normal and tumor tissues. Patients in the high-risk group exhibited advanced tumor stage, shorter survival time, and poorer prognosis, along with anoikis resistance, elevated autophagy, and immunosuppression. The nomogram incorporating the AARG signature showed strong predictive performance for OS. Conclusion: We developed and validated a new AARGs-based signature that effectively predicts prognosis for HCC patients.