Abstract IA33: Precision medicine at Weill Cornell Medicine/New York Presbyterian: Breaking silos, integrating resources, being inclusive
Authors: Sboner Andrea , Sternberg Cora , Mosquera Juan Miguel , Song Wei , Kluk Michael , Tam Wayne , Rennert Hanna , Pisapia David , Catalano Jeffrey , Cheang Gloria , Wilkes David , Bulaon Danielle , Martin M. Laura , Sigaras Alexandros , Eng Kenneth , Bareja Rohan , Kim Rob , Loda Massimo , Elemento Olivier 
Published: September 2020

Abstract
Genomic testing with next-generation sequencing (NGS) has become a pillar of precision medicine, whose aim is to identify the genomic alterations of a patient’s tumor and provide guidelines to clinicians for optimal treatment. Clinical testing is typically performed with targeted panels interrogating a limited set of genes, selected based on our best scientific knowledge on their diagnostic or prognostic role. Despite more recent efforts to be more inclusive, most genomic databases have a limited representation of non-European populations, resulting in a biased selection of those genes, and the potential exclusion of under-represented groups from the benefit of precision medicine. At the Englander Institute for Precision Medicine (EIPM), we developed a whole-exome sequencing (WES) clinical test, EXaCT-1, which interrogates about 21,000 protein coding genes for single-nucleotide variants, indels, and copy number. EXaCT-1 enables an unbiased view of the genomic landscape of a patient’s tumor and allows for the collection of data to investigate genomic diversity. We also tackled one of the major barriers of precision medicine: the infrastructure to execute clinical sequencing. From ordering a test, collecting and processing samples, to the analysis and review of the data and generation of reports, several systems, procedures, and expertise are involved, and their effective coordination is a key component for the timely delivery of results. We have built a framework supporting the entire process of clinical genomic testing: a Laboratory Information Management System (LIMS) helps the clinical lab to receive orders, acquire and process specimens, and seamlessly communicate with the sequencers and the computational pipelines. Molecular pathologists use NGSReporter, a secure web application, to review the data and sign-out reports. NGSReporter integrates the results of a test with our Precision Medicine Knowledge Base (PMKB – https://pmkb.weill.cornell.edu), which classifies variants based on their relevance to clinical management and provides standardized interpretations. Reports are sent to the electronic health record (EHR) as PDFs as well as discrete entities, enabling queries such as: “Which Hispanic patients with KRAS mutations are diabetic?” Sharing de-identified data is also a key aspect of precision medicine. To this end, we provide our investigators and collaborators with a protected cBioPortal instance that, in addition to publicly available datasets, includes internal data, thus enabling the exploration of hypotheses about the role of alterations across different cohorts and clinical features. Being in the center of New York City has the added benefit of an ethnically diverse patient population. Finding the “right treatment for the right person and at the right time” requires a concerted effort of multiple partners. The EIPM infrastructure facilitates these efforts, with the goal of making precision medicine accessible to everyone.
Citation Format: Andrea Sboner, Cora Sternberg, Juan Miguel Mosquera, Wei Song, Michael Kluk, Wayne Tam, Hanna Rennert, David Pisapia, Jeffrey Catalano, Gloria Cheang, David Wilkes, Danielle Bulaon, M. Laura Martin, Alexandros Sigaras, Kenneth Eng, Rohan Bareja, Rob Kim, Massimo Loda, Olivier Elemento. Precision medicine at Weill Cornell Medicine/New York Presbyterian: Breaking silos, integrating resources, being inclusive [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr IA33.