Leveraging Observational (Real World) Data to Advance Precision Oncology

OVERALL ABSTRACT Leveraging Observational (Real World) Data to Advance Precision Oncology Principal Investigator: Charles Sawyers, Memorial Sloan Kettering Cancer Center Precision oncology is a firmly established pillar in the practice of cancer medicine, but we now recognize new challenges to its broad implementation. These include: (i) heterogeneity in response to precision oncology

drugs in patients with identical driver mutations, (ii) differences in driver mutation frequencies in patients from different ethnicities, with implications for ensuring optimal treatment, (iii) increased subtyping of cancer into hundreds of “rare” diseases, and the resultant operational challenges in clinical trial design and execution, and

(iv) a limited understanding of how to effectively leverage observational (real world) data to address these challenges. The investigators in this P01 Program have had a longstanding collaboration over the past 8-years, helping to build a large (>148,000 patients), international clinico-genomic cancer registry known as AACR Project GENIE.

We have come together to investigate these issues and propose four highly integrated projects related to these themes. Project 1 seeks to overcome methodologic barriers in the analysis of observational clinico-genomic data. Project 2 will address the role of genetic ancestry in precision oncology outcomes and potential inequities

in how precision oncology diagnostic tests are developed. Project 3 will use real world evidence to inform clinical decisions for the treatment of cancer patients that cannot be addressed using conventional clinical trial datasets and will optimize the reporting of these findings using the OncoKB knowledge base. The projects will be

supported by the Curation and Statistical Analysis Core (data abstraction and biostatistics support); the Molecular Pathology and Bioinformatics Core (molecular profiling and data capture); and the Administrative Core (incorporating existing GENIE infrastructure for data sharing, communications, and administrative support).

Our proposal is highly synergistic as it brings together a multi-institutional team of distinguished investigators in population science, population genetics, cancer genomics and experimental therapeutics, with a substantial track record of collaborative interactions, who will work together to address these important topics in precision

oncology.