Immunofluorescence-Verified Sphingolipid Signatures Indicate Improved Prognosis in Liver Cancer Patients

Background: Hepatocellular carcinoma (HCC) is a highly heterogeneous malignancy, with its pathogenesis involving a complex interplay of molecular mechanisms, including cell cycle dysregulation, evasion of apoptosis, enhanced angiogenesis, and aberrant immune responses. Precision medicine approaches that target specific molecular subtypes through multi-omics integration hold promise for improving patient survival. Among the various molecular players, sphingolipids have emerged as pivotal regulators of tumor growth and apoptosis, positioning them as key targets in the search for novel anticancer therapies. Methods: To identify critical genes involved in sphingolipid metabolism (SM), we employed the AUCell algorithm and correlation analysis in conjunction with scRNA-seq data. A robust prognostic risk model was developed using Cox proportional hazards and Lasso regression, and its predictive performance was validated using an independent cohort from the International Cancer Genome Consortium (ICGC). The model's evaluation also incorporated analyses of the tumor microenvironment (TME), immunotherapy responses, mutational landscape, and pathway enrichment across different risk strata. Finally, we conducted multiplex immunofluorescence assays to investigate the functional role of ZC3HAV1 in HCC. Results: Our analysis yielded a 9-gene signature risk model with strong prognostic capabilities, effectively stratifying HCC patients into high- and low-risk groups, with significant differences in survival outcomes. Notably, the model revealed distinct variations in the immune microenvironment and responsiveness to immunotherapy between the risk groups. Further experimental validation identified ZC3HAV1 as a key gene, with multiplex immunofluorescence suggesting its involvement in promoting malignant progression in HCC through modulation of the epithelial-mesenchymal transition (EMT). Conclusion: This sphingolipid metabolism-based prognostic model is not only predictive of survival in HCC but also indicative of immunotherapy efficacy in certain patient subsets. Our findings underscore the crucial role of sphingolipid metabolism in shaping the immune microenvironment, offering new avenues for targeted therapeutic interventions.