We have an ongoing collaboration with IBM Research to study why cancers become drug resistant, a study that is fostering many new clinical collaborations with investigators across the US (currently over 20), each bringing their own scientific questions and cohort of patients with a specific cancer type and treatments.
This collaboration is focused on better understanding how cancers become resistant to specific therapies. We, along with our collaborators at the Broad (Genomics Platform, Dependency Map), are generating tumor genome and transcriptome sequencing data from patients that initially respond to treatment but then become drug-resistant. Together with our IBM colleagues, we use our arsenal of tools as well as Artificial Intelligence to analyze these data and identify genomic patterns that may help researchers and clinicians to discover mechanisms of resistance as well as predict drug sensitivity and patient outcome. Concurrently, we employ new genome-editing methods to conduct large-scale cancer drug resistance studies in the laboratory based on our analyses of tumor genome data to help identify tumor-specific vulnerabilities.
This partnership is helping to expand our understanding of the basis of drug resistance in cancer –– both genetic and epigenetic mechanisms observed in patients –– and accelerate research across the cancer community to turn knowledge of resistance mechanisms into therapies.
An example highlighting this work is a study we published early in this partnership with Dr. Ryan Corcoran’s team at MGH (Parikh, Leshchiner, Elagina, et al. Nature Medicine 2019). This study used our PhylogicNDT suite of tools to compare liquid biopsies to standard tumor biopsies in gastrointestinal cancer patients that developed drug resistance. We found that liquid biopsies harbored genetic alterations associated with drug resistance that were not identified through standard tissue biopsies in 80% of cases. Moreover, our analysis revealed that individual patients developed not just one, but many resistance mechanisms, which were both shared and distinct across neoplasms. Beyond this published study, the broader IBM–Broad collaboration currently has many active sub-projects at various stages and across several cancer types, such as lymphoma, melanoma, lung, breast, gastrointestinal, brain, bladder, and head-and-neck cancers. These collaborative studies are revealing valuable and potentially clinically actionable insights into resistance mechanisms.