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

作者：Chengli Liu, Meng Pu, Yingbo Ma, Shuhan Zhang, Qike Huang, Haoming Li, Tian Xia, Jingchen Zhang · 发表于：PeerJ · 年份：2025 · DOI：10.7717/peerj.19985 · 被引用次数：1 · 研究领域：Polyamine Metabolism and Applications、Microbial metabolism and enzyme function、Glycosylation and Glycoproteins Research

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 in vitro experiments (CCK8, wound healing, and Transwell assay). The Tumor Immune Estimation Resource (TIMER), MCP-counter, and Cell Identification by Estimating Relative Subsets of RNA Transcripts (CIBERSORT) methods were employed for immune cell infiltration analysis. Finally, drug sensitivity of the HCC samples was analyzed with the oncoPredict package. Results This study identified two molecular subtypes (C1 and C2), with C2 demonstrating a more favorable prognosis. Glucose-6-phosphate dehydrogenase ( G6PD ), alcohol dehydrogen...