Complementing DepMap: Expanding the toolkit for oncology target discovery and de-risking

The article discusses expanding tools for identifying genes that cancer cells depend on, which is crucial for developing targeted therapies. DepMap and Open Targets Platform are large collaborative initiatives that used CRISPR-Cas9 and RNA interference to disable genes in 900 cancer cell lines and tracked which knockouts reduced cell viability. Although these databases are useful, they have limitations – they do not cover complex perturbations and lack interpretability of mechanisms of action. Virtual Assays using machine learning model cancer cells to predict genetic dependencies and identify synthetic lethality. In the example with PARP inhibitors, 13 potential biomarker candidates were identified, eight were validated in vitro, and two are now included in clinical panels. Approximately 40% of patients with BRCA mutations do not respond to PARP inhibitors, indicating the need for better predictive methods.