Development and validation of a novel sodium-overload related genes signature for prognostic prediction in breast cancer: integrating bioinformatics and experimental approaches

Qizhen Feng¹Wenlin Yang²Wenyu Xu³Zhengrui Li³Guohao Su⁴Fei Wu^4*Chungen Xing^1*

• ¹Second Affiliated Hospital of Soochow University, Suzhou, China
• ²University of Florida, Gainesville, United States
• ³Shanghai Jiao Tong University School of Medicine, Shanghai, China
• ⁴Jining Medical University, Jining, China

Necrosis induced by sodium overload (NECSO) has been recently identified as a novel form of regulated cell death. However, the specific genes associated with sodium overload in breast cancer (BC) remain uncharacterized. In this study, 753 differentially expressed SORGs (DESORGs) were identified. Pathway enrichment analyses elucidated their functional roles. Univariate Cox regression identified 67 prognostic DESORGs. 101 combinations of ten machine learning algorithms were employed to construct prognostic models, with Ridge regression model demonstrating optimal performance. SHAP analysis identified key features, with IFNG being the most important. Risk score was identified as an independent prognostic factor, outperforming traditional clinical variables (AUC: 0.845), and was used to develop a nomogram with good calibration (C-index: 0.815). Mendelian randomization analysis suggested a protective causal effect of NR1H3 on BC. Tumor tissues showed significantly reduced NR1H3 expression, which predicted improved overall survival (p=0.02). In vitro, NR1H3 overexpression suppressed proliferation, colony formation, migration, and invasion, while its knockdown had opposite effects. GSEA and GSVA indicated that high NR1H3 expression is linked to immune activation pathways. Molecular docking identified Cephaeline and Emetine as potential drugs that upregulate NR1H3 expression. These findings highlight NR1H3 as a novel SORG and a promising therapeutic target in BC.