ArticleTranslational cancer research2026
Cation homeostasis-related prognostic genes uncovered by transcriptomic analysis in breast cancer.
Article in Translational cancer research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Disruption of cation homeostasis is increasingly recognized as a driver of breast cancer (BC) progression, yet a clinically actionable gene signature that quantifies this disturbance has been lacking. This study aims to systematically explore the value of cation homeostasis-related genes in the prognosis assessment of BC through bioinformatics analysis, construct and validate a prognostic model based on these genes, and integrate immune mechanism and drug sensitivity analyses to provide novel biomarkers and potential therapeutic targets for precise prognosis evaluation and individualized treatment of BC. Methods: There are 4,006 cation-homeostasis-related genes (CHRGs) integrated with transcriptomic profiles of 1,081 The Cancer Genome Atlas-breast invasive carcinoma (TCGA-BRCA) tumors and 99 normal breast tissues. After differential-expression filtering [|log2fold change (FC)| >2, false discovery rate (FDR) <0.05], 477 CHRGs were retained. Univariate-Cox, least absolute shrinkage and selection operator (LASSO) and multivariable modelling identified an 8-gene signature ( Results: The 8-gene signature stratified patients into high- and low-risk groups with significantly divergent 5-year overall survival probabilities [hazard ratio (HR) =2.34, 95 % confidence interval (CI): 1.79-3.06, P<0.0001; area under the curve (AUC)5-year =0.74]. Multivariable analysis confirmed the risk score as an independent prognostic factor together with age and N-stage (P<0.001). Mechanistically, high-risk tumors exhibited N-/O-glycan reprogramming, TNF-α/NF-κB hyper-activation, CD8 Conclusions: Our study provided the first CHRG-based prognostic model that simultaneously captures tumor-intrinsic aggressiveness and immune-evasive capacity in BC, offering quantitative biomarkers and actionable therapeutic targets for precision oncology.
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