Abstract 7175: Web-based cross-database exploration of molecular pharmacology data from cancer cell lines and patient genomics

Abstract CellMiner Cross-Database (CellMinerCDB, discover.nci.nih.gov/cellminercdb) allows integration and analysis of molecular and pharmacological data within and across cancer cell line datasets from the National Cancer Institute (NCI), Broad Institute, Sanger/MGH, MD Anderson Cancer Center (MDACC), and the National Center for Advancing Translational Sciences (NCATS, discover.nci.nih.gov/rsconnect/cellminercdb_ncats/). Altogether, our database spans over 1,700 distinct cell lines, over 1,000 clinically relevant drugs, ~25,000 experimental compounds, and molecular profiling data, such as gene/protein expression, molecular signatures including epithelial mesenchymal transition (EMT), replication stress (RepStress), neuroendocrine evaluation (NE), DNA copy, methylation, mutational status, and gene dependencies (Broad DepMap). This rich and growing set of cell lines and tested drugs allows for novel avenues for response determinant discovery and clinical translation that is facilitated by 1) common annotations (e.g., tissues of origin and matched drug names) across pharmacogenomic datasets and 2) various univariate and multivariate analyses tools. A major challenge to clinical translation occurs in relating pre-clinical models to patient samples. As part of this work, we show how the CellMinerCDB infrastructure additionally supports annotated patient multi-omics data to aid researchers to relate findings from cancer cell lines with patient data; we use data from small cell lung cancer (SCLC) and neuroendocrine tumors as illustrative examples. This work provides significant pharmacogenomic integration that allows exploration within a comprehensive dataset of cancer cell lines and to inter-relationships with patient-derived datasets; this is being developed to display and mine patient samples as part of the complementary web-based tool (PatientTumorMiner). Citation Format: William C. Reinhold, Augustin Luna, Fathi Elloumi, Sudhir Varma, Daiki Taniyama, Makito Mizunuma, Jaydira del Rivero, Anish Thomas, Karyyne Reilly, Karel Pacak, Mirit Aladjem, Yves Pommier. Web-based cross-database exploration of molecular pharmacology data from cancer cell lines and patient genomics [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7175.