ArticleTranslational cancer research2025
Polyamine metabolism and immune related genes as prognostic features in breast cancer: a novel risk model approach.
Article in Translational cancer research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- PSMD14 as a translational target in cancer and beyond: from deubiquitination mechanisms to drug resistance and precision therapy.Cancer drug resistance (Alhambra, Calif.) · 2026Review
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5 authors.
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Abstract
Background: The biological role of polyamine metabolism-related genes (PMRGs) in breast cancer (BRCA) through immune mediation is not well understood. Consequently, this study aimed to explore the prognostic features connected to PMRGs and immune-related genes (IRGs) in BRCA via bioinformatics analysis. Methods: We analyzed The Cancer Genome Atlas (TCGA)-BRCA and GSE20685 datasets. Differential expression analysis revealed differentially expressed genes (DEGs) in TCGA-BRCA, which intersected with 1,793 IRGs and 59 PMRGs to identify candidate genes. A least absolute shrinkage and selection operator (LASSO) Cox regression model was used to screen prognostic genes, which were then used to develop a risk model. This model was validated in both datasets. A nomogram was constructed using independent prognostic factors from univariate and multivariate Cox regression analyses to predict BRCA patient survival. The immune microenvironment landscape and gene set enrichment analysis (GSEA) results were also characterized. Results: Among 9,558 DEGs, 1,793 IRGs, and 59 PMRGs, 10 candidate genes were identified, with Conclusions: PMRGs and IRGs, specifically
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