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Renal carcinoma ranks among the most lethal cancers, primarily attributed to its atypical symptoms and high metastatic potential. The metabolism of nicotinamide (NAM) plays a significant role in the progression of various tumors. However, investigations into the impact of the NAM metabolism-related signature (NMRS) in kidney renal clear cell carcinoma (KIRC) remain insufficient. Clinical and RNA sequencing data (RNA-seq) from 541 KIRC tissues and 72 adjacent normal tissues were extracted from TCGA. NAM metabolism-related genes (NMRGs) were identified through the Molecular Signatures Database. Cox regression analyses (univariate/multivariate) were conducted to develop NMRS. Time-dependent ROC curve analysis showed that this method had good accuracy in predicting 1-year (AUC = 0.691), 3-year (AUC = 0.749), and 5-year (AUC = 0.764) survival. The Receiver Operating Characteristic (ROC) curve from the external RECA-EU dataset (AUC = 0.682) highlights the accurate prognostic assessment of the NMRS. Overall survival (OS) rates across distinct risk groups were compared using KM analysis. The Cox proportional hazards model assessed the influence of clinicopathological factors and risk scores on survival outcomes (HR = 1.437, 95% CI 1.232–1.676; P < 0.001). Evaluation of the immune microenvironment employed the ESTIMATE and CIBERSORT methods, while enrichment analysis examined biological significance. Correlation analysis determined the link between the expression of checkpoint genes and risk scores. StarBase and miRTarBase facilitated the prediction of target miRNAs and lncRNAs bindingto NMRGs. This study presents a novel framework for identifying prognostic biomarkers and therapeutic targets in KIRC.
Dong et al. (Tue,) studied this question.