A Breast Cancer Prognostic Model Based on Folic Acid Metabolism-Related Genes to Reveal the Immune Landscape

Abstract

Breast cancer (BC) threatens women’s health, and the prognosis is dismal. Folic acid metabolism affects cancer prognosis, but research on folic acid metabolism-related genes (FMRs) in BC is scarce. We used TCGA-BRCA as the training set and GSE21653 as the validation set. Five FMRs (PLAT, SERPINA3, IFNG, SLC19A1, NFKB2) were screened via univariate and LASSO Cox regression analyses, and a prognostic model was built based on multivariate Cox regression analysis. The model showed excellent predictive performance. Differentially expressed genes in high- and low-risk groups were enriched in steroid hormone biosynthesis and neuroactive ligand-receptor interaction pathways. The low-risk group exhibited higher immune cell infiltration and better immunotherapy response. AM-5992 and 5-fluorodeoxyuridine 10mer may be potential BC drugs. This FMR-based model can accurately predict BC prognosis, offering a clinical reference.

Keywords

folic acid metabolism - breast cancer - feature genes - prognostic analysis

Publikationsverlauf

Eingereicht: 08. Januar 2025

Angenommen nach Revision: 05. März 2025

Artikel online veröffentlicht:
10. April 2025

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