Predicting the prognosis of hepatocellular carcinoma based on genes related to polyamine metabolism.

Background: Hepatocellular carcinoma (HCC) is a highly prevalent malignant tumor worldwide. Evidence showed that polyamine metabolism plays a crucial part in the regulation of cancer onset and development, however, its clinical significance in HCC remains unclear. Methods: Bulk RNA sequencing (RNA-seq) and single-cell RNA sequencing (scRNA-seq) data of HCC were collected from public databases. Polyamine metabolism-related genes (PMRGs) were obtained from the MSigDB database. The molecular subtypes of HCC were classified by ConsensusClusterPlus package, and differentially expressed genes (DEGs) of the molecular subtypes were identified by the limma package, followed by enrichment analysis with clusterProfiler package. Univariate Cox and Lasso Cox regression analyses were performed to screen core genes, construct risk model, and develop a nomogram integrating clinical characteristics for survival prediction. The obtained biomarkers were validated using Results: This study identified two molecular subtypes (C1 and C2), with C2 demonstrating a more favorable prognosis. Glucose-6-phosphate dehydrogenase ( Conclusion: In conclusion, this study screened four key genes based on PMRGs and constructed a risk model to effectively predict the prognosis of HCC, providing novel potential targets and theoretical basis for the molecular subtyping and individualized treatment of HCC.