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September 14, 2026Discover OncologyOpen Access

Polyamine metabolism related prognostic genes and risk model in prostate cancer insights into tumor microenvironment and drug sensitivity

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Authors

FLFei LuoYWYa-Shen WangZZZhi-Hua Zhang

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Overview

Bioinformatic analysis identifies a six-gene polyamine metabolism signature in prostate cancer, highlighting potential biomarkers for risk stratification and targeted therapy.

Key Points

  • To identify polyamine metabolism-related prognostic genes in prostate cancer and build a validated risk model reflecting tumor microenvironment dynamics and drug sensitivity.
  • Intersected 6,668 differentially expressed genes from the TCGA-PRAD dataset with 59 polyamine metabolism genes to identify candidate biomarkers.
  • Constructed a prognostic risk model using univariate Cox and LASSO regression analyses, validating it with the GSE70769 external dataset.
  • Conducted gene set enrichment analysis, tumor microenvironment profiling, drug sensitivity predictions, and single-cell RNA sequencing trajectory analyses.
  • Identified six prognostic genes (SRM, SAT1, ODC1, SMOX, PAOX, and OAZ3) that were significantly up-regulated in prostate cancer and formed a model with moderate predictive accuracy.
  • Observed negative correlations between five prognostic genes and differential immune cell infiltration, alongside altered cell-cell communication between helper T cells and epithelial cells.
  • Demonstrated significant differences in predicted drug sensitivity between high- and low-risk cohorts for agents including lapatinib, bleomycin, and pyrimethamine.

Cite This Study

Luo et al. (2026) studied this question.

synapsesocial.com/papers/6aa7b41e0926e14a848b3980https://doi.org/10.1007/s12672-026-05904-2
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  1. 1Polyamine metabolism related gene index prediction of prognosis and immunotherapy response in breast cancer2025 · 1 citations
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  5. 5To explore the potential diagnostic and prognostic value of Golgi related genes in prostate cancer2024