Background Renal cell carcinoma (RCC; KIRC) is one of the most common malignant tumors in the urinary system, with highly variable prognosis and the urgent need for reliable biomarkers. Necrosis by sodium overload (NECSO) is a novel form of cell death mediated by the TRPM4 channel, and its role in KIRC is unknown. This study aims to construct a prognostic model based on NECSO-related genes and explore its mechanism. Methods We integrated KIRC data from public databases to analyze the functions of TRPM4 co-expressed genes. Using univariate and LASSO-Cox regression, we selected 12 key genes to construct a prognostic risk score model. The key gene RNF123 of the model was evaluated for its effects on the biological behaviors of KIRC cells through CCK8, EdU, apoptosis, cell scratch, Transwell experiments and subcutaneous tumorigenesis model. Results We constructed a NECSO-related prognostic risk model consisting of 12 characteristic genes. This model was able to effectively distinguish high-risk and low-risk patients in both the training set and validation set, and the risk score was an independent prognostic factor with stable predictive efficacy. The high-risk group was enriched in immune activation pathways but accompanied by inhibitory T cell infiltration, and was associated with high tumor mutation burden. Drug sensitivity analysis suggested that high-risk patients were more sensitive to TGFβR inhibitors. Additionally, the key gene RNF123 of prognostic model was lowly expressed in KIRC. Functional experiments indicated that RNF123 can inhibit cell proliferation and migration and promote apoptosis, and its mechanism may be related to upregulation of TRPM4 expression, a key mediator of NECSO, suggesting a potential link to enhanced sensitivity to NECSO. Conclusion This study successfully constructed and validated a KIRC prognostic model based on NECSO, demonstrating good predictive value. It also revealed that RNF123 may inhibit KIRC progression in association with TRPM4‑mediated NECSO, providing new targets and ideas for prognostic assessment and targeted therapy.
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钱亦官 et al. (2026) studied this question.
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