Deciphering the genomic landscape of renal cell carcinoma brain metastases.

4524 Background: Brain metastases from renal cell carcinoma (RCC) remain a major cause of morbidity and mortality, yet the drivers of metastatic dissemination remain poorly understood. Methods: Whole-exome sequencing was performed on 72 RCC brain metastasis samples with matched normal. To identify candidate metastatic drivers, the genetic alterations detected in the brain metastases were compared against alterations in extracranial metastases from the MSK-ECM cohort (n=137) and primary RCC tumors from TCGA (n=432) by case-control analyses. Candidate drivers were also identified by matched-pair analyses on the brain metastases vs. matched primary tumors or extracranial metastases from the same patient (n=25). A random survival forest model incorporating the candidate CNA events was developed to predict overall survival. The candidate metastatic drivers were further evaluated using functional experimental data from MetMap and DepMap. Survival analyses were conducted to assess the prognostic significance of the candidate drivers. Results: We identified metastatic drivers that were significantly enriched in RCC brain metastases, including 4q loss, 7p gain, 7q gain, 8p loss, 8q gain, 9p21.3 deletion, 12q15 amplification, and 14q loss. These driver events were associated with significantly poorer patient survival among RCC patients. A random survival forest model based on these CNA events stratified TCGA-KIRC patients into prognostically distinct risk groups (C-index = 0.64). Among the drivers, 8p loss, 8q gain, 9p21.3 deletion were associated with increased incidence of brain metastases across multiple primary cancer types in xenograft mouse models. These drivers were also strongly associated with metastatic progression and poor prognosis across RCC, lung adenocarcinoma, breast cancer, and melanoma. Conclusions: Somatic copy-number alterations represent key drivers of brain metastasis in RCC and other tumors that frequently metastasize to the brain. These findings indicate a shared genomic basis for brain tropism across cancers and highlight the potential utility of copy-number biomarkers for risk stratification and clinical decision-making.