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<p>This study aimed to identify and validate prognostic genes associated with polyamine metabolism-related genes (PMRGs) in hepatocellular carcinoma (HCC), offering potential novel therapeutic targets and strategies. The HCC-related datasets and 19 PMRGs were included in this study. Prognostic genes were screened out through differential expression analysis, univariate and multivariate Cox regression analysis. Subsequently, the construction of the risk model and nomogram, as well as functional enrichment and immune infiltration analysis were carried out. Ultimately, prognostic gene expression was further validated by quantitative real-time polymerase chain reaction (qRT-PCR) and enzyme linked immunosorbent assay (ELISA). SMOX, SRM, and SAT1 were identified as prognostic genes. risk score and stage were investigated as independent prognostic factors to construct nomogram. Moreover, the drug metabolism cytochrome p450 pathway was found had a significantly enriched in different risk groups. After that, 11 immune cells differed significantly across risk groups, with Eosinophi having the highest positive/negative correlation with SAT1/SRM, respectively. Finally, SMOX and SRM were highly expressed in the HCC group, while SAT1 showed the opposite pattern. The three genes linked to PMRGs, were identified as prognostic genes for constructing risk models, which may provide a basis for understanding HCC pathogenesis.</p>

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Prognostic poteintial of polyamine metabolism-related genes in hepatocellular carcinoma

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月2日

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  • Wei Zheng,
  • Chengan Xu,
  • Qiaoqiao Yin,
  • Yicheng Huang,
  • Hongying Zhou,
  • Guoliang Shen,
  • Keyang Xu,
  • Shouhao Wang

摘要

This study aimed to identify and validate prognostic genes associated with polyamine metabolism-related genes (PMRGs) in hepatocellular carcinoma (HCC), offering potential novel therapeutic targets and strategies. The HCC-related datasets and 19 PMRGs were included in this study. Prognostic genes were screened out through differential expression analysis, univariate and multivariate Cox regression analysis. Subsequently, the construction of the risk model and nomogram, as well as functional enrichment and immune infiltration analysis were carried out. Ultimately, prognostic gene expression was further validated by quantitative real-time polymerase chain reaction (qRT-PCR) and enzyme linked immunosorbent assay (ELISA). SMOX, SRM, and SAT1 were identified as prognostic genes. risk score and stage were investigated as independent prognostic factors to construct nomogram. Moreover, the drug metabolism cytochrome p450 pathway was found had a significantly enriched in different risk groups. After that, 11 immune cells differed significantly across risk groups, with Eosinophi having the highest positive/negative correlation with SAT1/SRM, respectively. Finally, SMOX and SRM were highly expressed in the HCC group, while SAT1 showed the opposite pattern. The three genes linked to PMRGs, were identified as prognostic genes for constructing risk models, which may provide a basis for understanding HCC pathogenesis.