Precision Medicine

Historically cancer treatment has taken a ‘one size fits all’ approach. However, it’s clear that every patient’s cancer is different and being able to understand and accurately differences in drug response and efficacy of therapies may provide better treatment options. Using Chronic Lymphocytic Leukemia (CLL) and breast cancer as a disease models, we are developing imaged based screening techniques that report on multifactorial drug-responses of primary patient cells with the goal of personalizing cancer treatment decisions and drug-response monitoring.  For any particular drug treatment we identify cells that respond by entering quiescence, activating a stress response, initiating programmed cell death, undergoing autophagy, or by changing intercellular interactions.  To analyze drug responses in CLL, circulating tumor cells from the peripheral blood of individual patients are cultured in conditions that recapitulate the highly treatment-resistant tumor microenvironment and then used to screen drugs and drug combinations used clinically. For breast cancer, conditional reprogramming and organoid cultures are being used to create a living biobank from which drug responses can be measured using genetically encoded stress sensors and novel dyes that we have developed. Artificial intelligence software is used to interpret the images with the goal of identifying optimal drug combinations for individual patients.