There is an unmet demand for functional characterization of variants observed in clinical DNA sequencing. This is evidenced by sequencing tests frequently reporting `variants of uncertain significance', information that cannot be acted on clinically. Of the approaches to characterize mutations in the absence of genetic evidence, all current methods have limitations ? namely, they aren't scalable to the large number of variants being sequenced, or they have inherent limits to their accuracy, a key one of which is that variants are removed from their genomic contexts to be assayed. This project aims to significantly improve experimental variant testing by using a novel genome editing method. This technique, called saturation editing, enables functional testing of large numbers of variants in multiplex, each in their endogenous genomic location. Through application to two genes in which mutations cause either chemotherapy resistance or oncogenesis, the method will yield powerful and accurate data for thousands of variants potentially playing key roles in disease. The first goal will be to generate functional scores for every variant across the coding sequence of the HPRT1 gene for causing resistance to the leukemia drug, 6-thioguanine. This work will provide a richly informative database of variant effects as measured in the genome that can be compared to data from HPRT1- deficient patients to evaluate accuracy. Next, by extending this assay to study over 1,000 mutations in non- coding regions of the same gene, the potential for loss-of-function mutations in non-coding sequences of the genome will be systematically interrogated for the first time. This will provide insights into why clinical sequencing sometimes fails to find coding mutations despite knowledge of which gene is mutated. Finally, saturation editing will be implemented to assay BRCA1 variants for their affects on the homology-directed repair pathway. Experiments will be targeted to the RING domain of BRCA1, where there is a high occurrence of pathogenic missense mutations, most of which have been incompletely characterized. The ability of BRCA1 variants to promote homology-directed repair accurately predicts whether a BRCA1 variant maintains tumor- suppressor function or not. Through this study, more interpretable functional scores for hundreds of BRCA1 variants will be generated, potentially informing clinical decision-making. Collectively, these experiments will generate valuable data for the cancer community, while also establishing a new approach for scalable and accurate functional testing of variants in genes relevant to cancer.
A critical problem for understanding cancer at the level of DNA is our limited ability to tell which mutations in the genome matter and which don't. This project will use new technology to edit the genome of growing human cells to create thousands of mutations to key cancer genes. By testing how each of these mutations behave at once, this approach promises to speed our understanding of mutations in cancer, therefore potentially leading to more accurate clinical information for patients and doctors.
|Findlay, Gregory M; Daza, Riza M; Martin, Beth et al. (2018) Accurate classification of BRCA1 variants with saturation genome editing. Nature 562:217-222|
|Gasperini, Molly; Findlay, Gregory M; McKenna, Aaron et al. (2017) CRISPR/Cas9-Mediated Scanning for Regulatory Elements Required for HPRT1 Expression via Thousands of Large, Programmed Genomic Deletions. Am J Hum Genet 101:192-205|