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CDRgator: An Integrative Navigator of Cancer Drug Resistance Gene Signatures

Title
CDRgator: An Integrative Navigator of Cancer Drug Resistance Gene Signatures
Authors
Jang S.-K.Yoon B.-H.Kang S.M.Yoon Y.-G.Kim S.-Y.Kim W.
Ewha Authors
김완규
SCOPUS Author ID
김완규scopus
Issue Date
2019
Journal Title
Molecules and cells
ISSN
0219-1032JCR Link
Citation
Molecules and cells vol. 42, no. 3, pp. 237 - 244
Keywords
cancer drug resistancegene expression signaturesmeta-analysismicroarrayRNA-seq analysistranscriptome
Publisher
NLM (Medline)
Indexed
SCIE; SCOPUS; KCI WOS scopus
Document Type
Article
Abstract
Understanding the mechanisms of cancer drug resistance is a critical challenge in cancer therapy. For many cancer drugs, various resistance mechanisms have been identified such as target alteration, alternative signaling pathways, epithelial-mesenchymal transition, and epigenetic modulation. Resistance may arise via multiple mechanisms even for a single drug, making it necessary to investigate multiple independent models for comprehensive understanding and therapeutic application. In particular, we hypothesize that different resistance processes result in distinct gene expression changes. Here, we present a web-based database, CDRgator (Cancer Drug Resistance navigator) for comparative analysis of gene expression signatures of cancer drug resistance. Resistance signatures were extracted from two different types of datasets. First, resistance signatures were extracted from transcriptomic profiles of cancer cells or patient samples and their resistance-induced counterparts for >30 cancer drugs. Second, drug resistance group signatures were also extracted from two large-scale drug sensitivity datasets representing ~1,000 cancer cell lines. All the datasets are available for download, and are conveniently accessible based on drug class and cancer type, along with analytic features such as clustering analysis, multidimensional scaling, and pathway analysis. CDRgator allows meta-analysis of independent resistance models for more comprehensive understanding of drug-resistance mechanisms that is difficult to accomplish with individual datasets alone (database URL: http://cdrgator.ewha.ac.kr).
DOI
10.14348/molcells.2018.0413
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자연과학대학 > 생명과학전공 > Journal papers
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