From cell lines to living biosensors: new opportunities to prioritize cancer dependencies using ex vivo tumor cultures

Abstract

Precision cancer medicine is based on the ability to predict the dependencies of a given tumor from its molecular makeup. These dependencies can be exploited with targeted, cytotoxic and/or immunity-inducing therapeutics. Ongoing efforts to perform genomic and cellular analyses on clinically annotated patient tumors are powerful, but bounded to existing therapies and focused cohorts. Here, we describe how living tumor material is increasingly being used in the generation of a systematic laboratory-based functional map of cancer dependencies (a 'Cancer Dependency Map'). In particular, we emphasize the important contributions of long-term cell models, emerging uses for short-term cell models and future potential for 'alpha cultures' that are mere hours or days from the cancer patient. Collecting research-grade cancer dependency data with each of these model formats could pave the way to ensure that the Map increasingly reflects all tumors. The integration of clinical genomics and preclinical functional genomics data should provide a powerful research platform to improve the accuracy of precision medicine predictions.