Clear cell renal cell carcinoma (ccRCC) continues to pose a significant global health concern, with rising incidence and high mortality rate. Accordingly, identifying molecular alternations associated with ccRCC is crucial to boost our understanding of its onset, persistence, and progression as well as developing prognostic biomarkers and novel therapies. Bulk RNA sequencing data and its associated clinicopathological variables of ccRCC were obtained from The Cancer Genome Atlas Program. Atypical differential gene expression analysis of advanced disease states using the extreme categories of staging and grading components was performed. Upregulated differentially expressed genes shared across the aforementioned components were selected. The risk-score construction pipeline started with univariate Cox logistic regression analysis, least absolute shrinkage and selection operator, and multivariate Cox logistic regression analysis in sequence. The generated risk score classified patients into low- vs high-risk groups. The predictive power of the constructed risk score was assessed using Kaplan-Meier curves analysis, multivariate Cox logistic regression analysis, and receiver operator curve of the overall survival. External validation of the risk score was performed using the E-MTAB-1980 cohort. The analysis work scheme established a novel nine-gene prognostic risk score composed of the following genes: ZIC2, TNNT1, SAA1, OTX1, C20orf141, CDHR4, HOXB13, IGFL2, and IGFN1. The high-risk group was associated with shortened overall survival and possessed an independent predictive power (hazard ratio: 1.942, 95% CI: 1.367-2.758, P < .0001, area under the curve = 0.719). In addition, the high-risk score was associated with advance clinicopathological parameters. The same pattern was observed within the external validation dataset (E-MTAB-1980 cohort), in which the high-risk score held a poor prognostic signature as well as independent predictive potential (hazard ratio: 5.121, 95% CI: 1.412-18.568, P = .013, area under the curve = 0.787). In the present work, a novel nine-gene prognostic risk score was constructed and validated. The risk score correlated with tumor immune microenvironment, somatic mutation patterns, and altered molecular pathways involved in tumorigenesis. Further experimental data are warranted to expand the work.