Improve precision medicine for renal cell carcinoma patients of African ancestry through computational and functional genomics - PROJECT ABSTRACT Renal cell carcinoma (RCC) affects ~80,000 patients annually in the U.S., causing more than 14,000 deaths. RCC comprises multiple histological subtypes with distinct molecular drivers, and striking disparities exist in incidence, subtype distribution, and outcomes across populations. Clear cell RCC (ccRCC), which predominates in patients of European (EUR) ancestry, is well characterized and has benefited from targeted therapies such as VEGFR inhibitors. In contrast, papillary RCC (pRCC), which occurs more frequently in patients of African (AFR) ancestry, remains poorly understood and lacks effective treatment options. Although MET inhibitors show promise in subsets of pRCC, its genomic landscape is incompletely defined, limiting biomarker discovery and therapy development. This imbalance has left AFR-associated RCC underexplored, constraining accurate classification and the identification of ancestry-relevant therapeutic targets. Preliminary data supported by an R21 grant (R21CA280577) show that RCC tumors from patients of AFR ancestry are significantly depleted in known driver alterations. Strikingly, 70% of AFR pRCC cases were “driverless” compared to only 10% of ccRCC, despite comparable tumor purity. Whole-genome sequencing (WGS) of these “driverless” AFR RCC tumors revealed clinically actionable MET structural variants that had been missed by panel-based testing. These findings highlight both the limitations of current approaches and the opportunity to discover novel drivers that may improve diagnosis and treatment for AFR RCC patients. Our central hypothesis is that non-ccRCC, particularly pRCC in patients of AFR ancestry, harbors unrecognized molecular features. By integrating computational and functional models, we aim to identify novel biomarkers and refine RCC classification in this understudied population. In Aim 1, we will perform WGS on 200 “driver-negative” tumors to uncover novel driver alterations. Candidate drivers, such as MET structural variants, will be experimentally validated in vitro to assess oncogenic potential and therapeutic relevance. While ccRCC is characterized by chromosome 3p deletion and VHL loss, pRCC, particularly in patients of AFR ancestry, shows enrichment for NF2 loss and chromosome 22q deletion. In Aim 2, we will generate isogenic kidney cell lines with targeted chr3p or chr22q deletions and assess their phenotypic impact, focusing on hypoxia pathway dysregulation from chr3p loss and NF2/YAP–TAZ signaling disruption from chr22q loss. Finally, AFR patients are often overrepresented among unclassified RCC. In Aim 3, we will refine RCC subtype classification through integrating genomic and transcriptomic data. We will also leverage genomic and digital pathology-derived features of over 2,500 RCC cases for an ancestry-aware, multi-modal classifier to improve outcome prediction. This project will deepen understanding of RCC biology, especially for subtypes common in patients of AFR ancestry (e.g. pRCC and unclassified RCC) and improve diagnostic and therapeutic precision for that population.
