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Simple Summary: Cancer is a disease caused by mutations in DNA differentiating cancer cells from normal cells. Precision medicine could exploit these genetic differences to identify and create therapeutic opportunities that selectively kill cancer cells while sparing normal cells. In some cancers, the same mutations recur, making them desirable biomarkers for genetics-based therapeutic strategies. This is the case for the gene ARID1A which is lost in about 50% of ovarian clear cell carcinomas. We used genetic screening to identify targets for killing an ovarian clear cell carcinoma cell line lacking the ARID1A gene. We identified a cancer stress response regulator called KEAP1 as a potential target for ARID1A-deficient ovarian clear cell carcinomas. Using different approaches and cell lines, we observed a relationship where ARID1A-deficient cells required KEAP1 for fitness. Together these data suggest that KEAP1 could be pursued as a means to selectively kill certain types of ARID1A-deficient cancer. ARID1A is the core DNA-binding subunit of the BAF chromatin remodeling complex and is mutated in about 8% of all cancers. The frequency of ARID1A loss varies between cancer subtypes, with clear cell ovarian carcinoma (CCOC) presenting the highest incidence at > 50% of cases. Despite a growing understanding of the consequences of ARID1A loss in cancer, there remains limited targeted therapeutic options for ARID1A-deficient cancers. Using a genome-wide CRISPR screening approach, we identify KEAP1 as a genetic dependency of ARID1A in CCOC. Depletion or chemical perturbation of KEAP1 results in selective growth inhibition of ARID1A-KO cell lines and edited primary endometrial epithelial cells. While we confirm that KEAP1-NRF2 signalling is dysregulated in ARID1A-KO cells, we suggest that this synthetic lethality is not due to aberrant NRF2 signalling. Rather, we find that KEAP1 perturbation exacerbates genome instability phenotypes associated with ARID1A deficiency. Together, our findings identify a potentially novel synthetic lethal interaction of ARID1A-deficient cells. [ABSTRACT FROM AUTHOR]

In the past decade, there has been a growing appreciation for R-loop structures as important regulators of the epigenome, telomere maintenance, DNA repair, and replication. Given these numerous functions, dozens, or potentially hundreds, of proteins could serve as direct or indirect regulators of R-loop writing, reading, and erasing. In order to understand common properties shared amongst potential R-loop binding proteins, we mined published proteomic studies and distilled 10 features that were enriched in R-loop binding proteins compared with the rest of the proteome. Applying an easy-ensemble machine learning approach, we used these R-loop binding protein-specific features along with their amino acid composition to create random forest classifiers that predict the likelihood of a protein to bind to R-loops. Known R-loop regulating pathways such as splicing, DNA damage repair and chromatin remodeling are highly enriched in our datasets, and we validate 2 new R-loop binding proteins LIG1 and FXR1 in human cells. Together these datasets provide a reference to pursue analyses of novel R-loop regulatory proteins., (© The Author(s) 2022. Published by Oxford University Press on behalf of Genetics Society of America.)