{"title":"基于叶酸代谢相关基因揭示免疫景观的乳腺癌预后模型","authors":"Lin Lv, Xiaotao Zhu, Cong Jin, Shunlan Ni","doi":"10.1055/a-2554-4861","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":12999,"journal":{"name":"Hormone and Metabolic Research","volume":"57 4","pages":"262-272"},"PeriodicalIF":1.8000,"publicationDate":"2025-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Breast Cancer Prognostic Model Based on Folic Acid Metabolism-Related Genes to Reveal the Immune Landscape.\",\"authors\":\"Lin Lv, Xiaotao Zhu, Cong Jin, Shunlan Ni\",\"doi\":\"10.1055/a-2554-4861\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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.</p>\",\"PeriodicalId\":12999,\"journal\":{\"name\":\"Hormone and Metabolic Research\",\"volume\":\"57 4\",\"pages\":\"262-272\"},\"PeriodicalIF\":1.8000,\"publicationDate\":\"2025-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Hormone and Metabolic Research\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1055/a-2554-4861\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/4/10 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q3\",\"JCRName\":\"ENDOCRINOLOGY & METABOLISM\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Hormone and Metabolic Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1055/a-2554-4861","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/4/10 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"ENDOCRINOLOGY & METABOLISM","Score":null,"Total":0}
A Breast Cancer Prognostic Model Based on Folic Acid Metabolism-Related Genes to Reveal the Immune Landscape.
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.
期刊介绍：
Covering the fields of endocrinology and metabolism from both, a clinical and basic science perspective, this well regarded journal publishes original articles, and short communications on cutting edge topics.
Speedy publication time is given high priority, ensuring that endocrinologists worldwide get timely, fast-breaking information as it happens.
Hormone and Metabolic Research presents reviews, original papers, and short communications, and includes a section on Innovative Methods. With a preference for experimental over observational studies, this journal disseminates new and reliable experimental data from across the field of endocrinology and metabolism to researchers, scientists and doctors world-wide.
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