The KISMET Project in Precision Oncology: Knowing Individual Significant Mutations Enabling Treatment. No Patient Left Behind

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Abstract

There has been a true revolution in cancer treatment. Numerous genetic alterations are being targeted using new therapies with the potential for improved, less toxic – often durable - outcomes in advanced cancer. Response rates are 3-5% for unmatched treatment with new tyrosine kinases and other similar agents whereas a “high value” alteration can result in response rates of 30-50% for actionable unsuspected mutations such as BRAF V600E, KRAS G12C, or HER2 amplification – regardless of primary disease site or histology. In 2019, the FDA approved genomic analysis and treatment with immune checkpoint inhibitors for patients with an overall high tumor mutation burden (TMB) independent of the specific histology.

We identified 14 specific alterations that we consider high value unexpected treatable targets (HVUTTs). Genomic analysis of 499 advanced cancer patients at MD Anderson revealed 11 patients (2.2%) with HVUTTs without evidence of targeted therapy. This strategy could favorably improve the lives of cancer patients.

We hypothesize that by notifying treating physicians of new opportunities in advanced cancer for patients with unexpected alterations (e.g. BRAF alteration in brain tumors or HER2 in liver cancer) we can improve response rates, outcomes, prolong survival, and mitigate toxicity in hundreds or thousands of patients with a robust statewide infrastructure using our Texas Regional CTSA Consortium (TRCC). We are collaborating with informatics, the MD Anderson Precision Oncology Decision Support (PODS) team, and the clinical research unit to create a central database for our identify-monitor-alert system. We are currently deploying the system locally with plans to expand to the TRCC. The goal of KISMET is to leave no cancer patient behind in Texas and create a model that could be expanded beyond cancer.

This poster was supported by the National Center for Advancing Translational Sciences (NCATS) grant UL1TR003167. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH.

Authors
Elmer
Bernstam
CTSA Informatics Director, Professor and Associate Dean for Research
Richard
Zwelling
Clinical Studies Coordinator
Jackie
Bronicki
Grant Program Manager
Daniel
Karp
Co-Prinicipal Investigator