Polyamine metabolism and immune related genes as prognostic features in breast cancer: a novel risk model approach.

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

SUBMITTER: Li W 

PROVIDER: S-EPMC12268881 | biostudies-literature | 2025 Jun

REPOSITORIES: biostudies-literature