DOI: 10.6084/m9.figshare.12497630.v1
title: Data and metadata supporting the published article: Development and implementation of the SUM breast cancer cell line functional genomics knowledge base.

description: The SUM human breast cancer cell lines have been used by many labs around the world to develop extensive data sets derived from comparative genomic hybridization analysis, gene expression profiling, whole exome sequencing, and reverse phase protein array analysis. In a previous study, the authors of this paper performed genome-scale shRNA essentiality screens on the entire SUM line panel, as well as on MCF10A cells, MCF-7 cells, and MCF-7LTED cells. In this study, the authors have developed the SUM Breast Cancer Cell Line Knowledge Base, to make all of these omics data sets available to users of the SUM lines, and to allow users to mine the data and analyse them with respect to biological pathways enriched by the data in each cell line.<br><b>Data access</b>: All the datasets supporting the findings of this study are publicly available in the SLKBase platform here: <b>https://sumlineknowledgebase.com/</b>. RPPA data, drug sensitivity data, apelisib response data, and data on dose response, are also part of this figshare data record (<b>https://doi.org/10.6084/m9.figshare.12497630</b>).<br><b>Study aims and methodology</b>: This web-based knowledge base provides users with data and information on the derivation of each of the cell lines, provides narrative summaries of the genomics and cell biology of each breast cancer cell line, and provides protocols for the proper maintenance of the cells. The database includes a series of data mining tools that allow rapid identification of the functional oncogene signatures for each line, the enrichment of any KEGG pathway with screen hit and gene expression data for each of the lines, and a rapid analysis of protein and phospho-protein expression for the cell lines. A gene search tool that returns all of the functional genome and functional druggable data for any gene for the entire cell line panel, is included. Additionally, the authors have expanded the database to include functional genomic data for an additional 29 commonly used breast cancer cell lines. The three overarching goals in the original development of the SLKBase are: 1) to provide a rich source of information for anyone working with any of the SUM breast cancer cell lines, 2) to give researchers ready access to the large genomic data sets that have been developed with these cells, and 3) to allow researchers to perform orthogonal analyses of the various genomics data sets that we and others have obtained from the SUM lines. For more information on the development and contents of the database, please read the related article.<br><b>Datasets supporting the paper:</b><b>The data mining tools accessed the following datasets to generate the figures and tables, and these datasets are downloadable from the Data Download centre on the SLKBase:</b> <br><i>Exome sequencing data</i>: SLKBase.exome_.seq_.sum_.xlsx<br><i>Gene amplification and expression data for the SUM cell lines</i>: SUM44amplificationdata.xlsSUM52.xlsSUM149.xlsSUM159.xlsSUM185.xlsSUM190.xlsSUM225.xlsSUM229.xlsSUM1315.xls<br><i>Cellecta shRNA screen data for the SUM cell lines:</i>SUM44Celectadata.csv<br>SUM52Cellectadata.csvSUM102Cellectadata.csvSUM149Cellectadata.csvSUM159Cellectadata.csvSUM185Cellectadata.csvSUM190Cellectadata.csvSUM225Cellectadata.csvSUM229Cellectadata.csvSUM1315hits.hit.csvMCF10A.hits_.csv<br><b>Breast cancer cell line data included in this data record (these datasets were used to generate figures 1, 2 and 7 in the article):</b><i>Proteomics data from the Reverse Phase Protein Array (RPPA) assay analysis</i>: Ethier.SUMline.RPPA.xlsx<i>Drug sensitivity data: </i>NAVITOCLAX.drugsensitivity.Zscores.xlsx<i>Apelisib response data:</i> Apelisib all lines (2).xlsx<i>Dose response data:</i> 092614 Dose Response CP 52s.11.15.xlsx<br>All the files are either in .<b>xlsx</b> or <b>.csv</b> file format.<br>