Saturation Genome Editing Resolves the Functional Spectrum of PathogenicVHLAlleles

Abstract

ABSTRACTTo maximize the impact of precision medicine approaches, it is critical to accurately identify genetic variants in cancer-associated genes with functional consequences. Yet, our knowledge of rare variants conferring clinically relevant phenotypes and the mechanisms through which they act remains highly limited. A tumor suppressor gene exemplifying the challenge of variant interpretation isVHL.VHLencodes an E3 ubiquitin ligase that regulates the cellular response to hypoxia. Germline pathogenic variants inVHLpredispose patients to tumors including clear cell renal cell carcinoma (ccRCC) and pheochromocytoma, and somaticVHLmutations are frequently observed in sporadic renal cancer. Here, we optimize and apply Saturation Genome Editing (SGE) to assay nearly all possible single nucleotide variants (SNVs) acrossVHL’s coding sequence. To delineate mechanisms, we quantify mRNA dosage effects over time and compare effects in isogenic cell lines. Function scores for 2,268VHLSNVs identify a core set of pathogenic alleles driving ccRCC with perfect accuracy, inform differential risk across tumor types, and reveal novel mechanisms by which variants impact function. These results have immediate utility for classifyingVHLvariants encountered in both germline testing and tumor profiling and illustrate how precise functional measurements can resolve pleiotropic and dosage-dependent genotype-phenotype relationships across complete genes.