Journal Article

Identification of pathogenic variants in cancer genes using base editing screens with editing efficiency correction

Wu, Jiayu, Liang, Junbo, Huang, Changcai, Li, Guangyu, Wang, Xiaoyue

2021

Overview

Background Millions of nucleotide variants are identified through cancer genome sequencing and it is clinically important to identify the pathogenic variants among them. By introducing base substitutions at guide RNA target regions in the genome, CRISPR-Cas9-based base editors provide the possibility for evaluating a large number of variants in their genomic context. However, the variability in editing efficiency and the complexity of outcome mapping are two existing problems for assigning guide RNA effects to variants in base editing screens. Results To improve the identification of pathogenic variants, we develop a framework to combine base editing screens with sgRNA efficiency and outcome mapping. We apply the method to evaluate more than 9000 variants across all the exons of BRCA1 and BRCA2 genes. Our efficiency-corrected scoring model identifies 910 loss-of-function variants for BRCA1/2 , including 151 variants in the noncoding part of the genes such as the 5′ untranslated regions. Many of them are identified in cancer patients and are reported as “benign/likely benign” or “variants of uncertain significance” by clinicians. Our data suggest a need to re-evaluate their clinical significance, which may be helpful for risk assessment and treatment of breast and ovarian cancer. Conclusions Our results suggest that base editing screens with efficiency correction is a powerful strategy to identify pathogenic variants in a high-throughput manner. Applying this strategy to assess variants in both coding and noncoding regions of the genome could have a direct impact on the interpretation of cancer variants.

• Publisher: BioMed Central,Springer Nature B.V,BMC
• Subject: 5' Untranslated regions / Algorithms / Animal Genetics and Genomics / Base Sequence / Bioinformatics / Biomarkers, Tumor / Biomedical and Life Sciences / BRCA1 protein / BRCA2 protein / Breast cancer / breasts / Cancer / Cancer Evolution and Metastasis / Cell growth / Chromosome Mapping / Computational Biology - methods / CRISPR / CRISPR-Cas Systems / Databases, Genetic / Deoxyribonucleic acid / DNA / Efficiency / Evolutionary Biology / Exons / Gene Editing / Gene mapping / Genes / Genes, BRCA1 / Genes, BRCA2 / Genetic Variation / Genomes / genomics / Human Genetics / Humans / Life Sciences / Loss of Function Mutation / Microbial Genetics and Genomics / Models, Molecular / Mutation / Neoplasms - genetics / Oncogenes / Ovarian cancer / ovarian neoplasms / Plant Genetics and Genomics / Plasmids / Risk assessment / RNA / RNA, Guide, CRISPR-Cas Systems / Structure-Activity Relationship / tumor suppressor proteins / Whole genome sequencing