Abstract
Background/Objectives: Traditional histopathologic grading of renal cell carcinoma (RCC) is subjective, is poorly reproducible, and fails to predict responses to modern targeted agents or immunotherapies. In the era of precision oncology, molecular pathology offers objective tools for individualized management. We aimed to characterize genomic alterations in clear-cell RCC (ccRCC) with venous tumor thrombus and to develop pathology-driven panels for personalized prognostic stratification, with exploratory assessment of their potential to predict therapeutic response. Methods: Formalin-fixed paraffin-embedded pT1 ccRCC samples with and without thrombus underwent whole-exome sequencing. Distinct somatic mutations and copy number variations were incorporated into multigene panels. External assessment was performed in TCGA and PAWG cohorts, assessing survival outcomes and therapeutic biomarkers including homologous recombination deficiency (HRD), tumor mutational burden (TMB), and microsatellite instability (MSI). Results: Thrombus cases showed unique genomic heterogeneity compared with matched controls. Three multigene panels were constructed. Across external datasets, including a 354-patient TCGA-KIRC ccRCC cohort, the panels provided consistent molecular stratification signals for overall, disease-specific, and progression-free survival, complementing established pathological risk factors. They were significantly associated with established therapy-related genomic biomarkers, including HRD, TMB, and MSI, showing high sensitivity and negative predictive value in identifying patients unlikely to harbor these biomarker-positive profiles. These findings support the panels' prognostic utility, with exploratory evidence for their potential in therapy response prediction. Conclusions: Small ccRCC with thrombus harbors distinct molecular pathological features. The proposed pathology-driven panels, compatible with FFPE tissue, represent pathology-compatible genomic tools that may support modern precision pathology by improving molecular risk stratification and informing exploratory therapeutic biomarker assessment.