Saturation Genome Editing (SGE) to delineate pathogenic and benign variants
As we sequence DNA from more and more individuals, we encounter large numbers of rare genetic variants whose effects are difficult to understand. This problem is seen clearly in the clinic by the large numbers of variants of uncertain significance, or VUS, found in many genes linked to disease. These VUS may indicate a serious genetic condition or be entirely benign. For many genes, if a variant is deemed pathogenic, it can have a profound impact on patient care.
For instance, in tumor suppressor genes such as BRCA1 and BRCA2, identifying a pathogenic variant in a patient often leads to interventions that dramatically reduce cancer risk and increase life expectancy by years. If instead, however, a VUS is found, it creates anxiety and confusion over how to proceed. This makes it critically important to know which variants should be considered pathogenic and which should not be. Unfortunately, tens of thousands of VUS have been reported in cancer predisposition genes to date and the number is rapidly increasing. This illustrates how challenging it can be to definitively classify these variants despite the importance of doing so.
Associating variants with phenotypes in humans is the gold standard for determining pathogenicity. However, this classical genetics approach cannot work for most rare variants, many of which are only seen in a single person or family. Instead, we have developed highly scalable functional assays to accurately assess many variants experimentally.
We employ CRISPR/Cas9 genome editing in human cells in culture to create thousands of variants in key genes, all in their native genomic context. This allows us to study the functional impact of each variant on many levels of gene function, including transcriptional activity, splicing, and protein function. Our method, called saturation genome editing (SGE), has been proven to identify pathogenic variants in BRCA1 with extremely high accuracy. This has led to widespread use of SGE data for clinical variant interpretation of BRCA1 variants.
Now, we are expanding far beyond our initial work in this area to study additional regions of tumor suppressor genes like BRCA1 to search for more pathogenic variants. In many cases this requires developing new cell-based assays to assess functional effects in high-throughout. Ultimately, we will integrate our functional data with large-scale sequencing studies and pathological characteristics of relevant tumors to provide a rich genetic accounting of how certain mutations lead to cancer. Our goal is to produce high-quality data that can be directly used for interpreting mutations in patients, thus providing a real benefit to thousands of people.
Check back soon for details on other lab projects:
- Identification of rare non-coding variants that cause cancer predisposition
- Dissecting the logic of tumor suppressor gene regulation
- Advanced methods development for rapid functional genomics