A major goal of precision oncology is to use tumor genomics to guide therapy. However, many commonly mutated cancer genes are difficult to target with drugs and even for genes that might be targetable, it is not clear which one should be prioritized or which drug would be effective for any given patient. Tumors are genetically heterogeneous and the uniqueness of each patient’s tumor can affect drug responses in unpredictable ways. Another challenge is the shortage of druggable targets and associated therapeutic agents. Even in cases where genome guided targeted therapy works, development of resistance is common, further highlighting the need for additional targeted agents and effective drug combinations. 

To address these challenges we have developed an integrated platform whose main innovation is the use functional profiling in patient derived tumor models. By combining high throughput functional testing with cancer genomics in the autologous patient derived cells, we can prioritize driver genetic events, discover new synthetic lethal gene targets, and identify effective drug combinations. Prioritized targets are confirmed with orthogonal assays, in increasingly complex patient relevant cancer models, and across tumor types. To date, we have functionally profiled dozens of solid tumors and have identified several high value synthetic lethal gene targets which have generated drug discovery efforts. We have shown the predictive value of our platform to identify novel therapies and combinations in a precision medicine context. For example, our results directly led to an investigator-initiated clinical trial where the WEE1 inhibitor AZD1775 is used in the neoadjuvant setting for head and neck squamous cell carcinoma (HNSCC).

This drug target discovery platform can be customized and scaled to address a range of important clinical problems such as drug resistance or metastasis or biological questions such as epigenetic- or oncogene-specific vulnerabilities, lineage dependencies, or mechanisms of cell death.

An important aspect of our approach is to engage and participate in a larger ecosystem of researchers including clinicians, computational biologists, domain experts and patient advocates to optimize and accelerate bench to bedside translation.