While nearly everyone engaged in breast cancer research uses breast cancer cell lines, most researchers who use cell lines know relatively little about the patients from which they were derived, or the complex biology that is inherent in each cell line. This is because data on the patients from which cell lines were derived are rarely published in the literature. Thus, it is rare for researchers to have knowledge of the clinical characteristics and clinical outcomes of the patients from which the cell line was derived. This is important because each cell line reveals a detailed molecular portrait of that patient’s breast cancer, and by extension, that of other patient’s breast cancers that have similar driving genomic alterations and gene expression profiles. Unfortunately, most researchers who acquire and use a particular cell line do so because of one or two characteristics of the line, and they fail to appreciate the depth and complexity of the disease of that patient. For example, the MCF-7 breast cancer cell line is the most widely used in breast cancer research because it expresses a functional estrogen receptor. Thus, the majority of the published data in the literature derived from this cell line is focused on the estrogen-estrogen receptor axis, with little regard to the rest of the important biology associated with this cell line, and indeed this patient. This tunnel vision approach to breast cancer research has had a negative effect on progress in improving therapies because it fails to appreciate the complex biology inherent in each patient’s cancer.
Up to now, this has been impossible because researchers do not have access to vitally important information on the patient history, the published literature, and especially, the genomic data associated with each cell line. Thus, there is a need for access to a high-quality and comprehensive knowledge base on breast cancer cell lines in routine use around the world. In addition, with the advent of complex genomic technologies, large and complex data sets have been generated with the SUM cell lines, as well as other cell lines, and most researchers do not have access to these data sets, nor are the data available in a manner that allows interpretation by individuals without expertise in bioinformatics and computer science. Thus, a key goal of the SUM line Knowledge Base is to provide in depth bioinformatic and functional genomic analyses of these complex data sets in a manner that is readily interpretable by scientists and clinicians in the field.
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