Abstract P4-05-13: The SUM breast cancer cell line knowledge base (SLKBase): A knowledge base and functional genomics platform for breast cancer cell lines

Abstract

Abstract The SUM breast cancer cell lines were developed in the 1990s and since that time, one or more of these cell lines have been distributed to over 500 laboratories world-wide. As a result, there are currently nearly 4000 papers in the peer-reviewed literature that contain data obtained with one or more of these cell lines. In addition, over the years, our laboratory and others have developed a number of complex genomic data sets for these cell lines, most of which are unavailable to the research community. The genomic data that have been developed for the SUM lines include: copy number/gene amplification data, gene expression profiling data using multiple platforms, whole exome sequencing data with cancer specific point mutation data, proteomic profiling data, and most recently, genome-scale shRNA screening data for each of the lines. The shRNA screening data functionalizes the other genomic data sets, adding significant power to these analyses. To make these genomic data sets available to the research community, we developed the SUM Breast Cancer Cell Line Knowledge Base (www.sumlineknowledgebase.com). This web-based resource provides information about each cell line, such as information on the patient from which the line was derived, a narrative summary of each cell line with a focus on the genomic drivers that are important for each line, a bibliography of published papers using each cell line and much more. To make the genomic data accessible to all breast cancer researchers, we have developed a number of data mining tools that allow researchers to rapidly and easily identify the key functional genes and pathways operative for each cell line. The tools developed so far include: a series of KEGG Pathway Engines, an Oncogene Signature tool, a Gene Query tool, a Proteomics tool and a Functional Druggable Signature tool. The KEGG Pathway Engines allows users to map shRNA screen data or gene expression data onto any KEGG pathway for any cell line and rank order pathways based on essentialness and druggability. The Oncogene Signature tool identifies all genes in each line that are genomically altered in each line, the status of each of those genes in the shRNA screen, and the druggability of each potential oncogene. The Gene Query tool allows researchers to search for any gene and obtain data on the status of that gene in any of the cell lines. The tool also generates a rank-ordered list of the cell lines based on the essentialness of the gene in each cell line., and provides data on copy number, expression level, hit status in the shRNA screen and the potential druggability of each gene. Thus, this SUM Breast Cancer Cell Line Knowledge Base and the tools contained within this web-based resource, allow researchers using any of the SUM lines to rapidly probe the deep biology of any cell line, identify the driving genomic alterations, most important KEGG pathways, and the most effective drug strategies for each cell line line. Work currently in progress is aimed at expanding this Knowledge Base to include all breast cancer cell lines, which will make this resource useful to all breast cancer researchers who use cell lines in their work. Citation Format: Stephen Paul Ethier, Kathryn Duchinsky, Daniel Couch. The SUM breast cancer cell line knowledge base (SLKBase): A knowledge base and functional genomics platform for breast cancer cell lines [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-05-13.