CDA: Combinatorial Drug Discovery Using Transcriptional Response Modules
| Autor: | Jong Jun Lee, Dae Gyu Kim, Kyoohyoung Rho, Ji-Hyun Lee, Sunghoon Kim, Ji Tae Kim, Byung Cheol Kim, Kyoung Mii Park, Taejeong Bae, Yeongjun Jang |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2012 |
| Předmět: |
Lung Neoplasms
Non-Clinical Medicine Transcription Genetic Microarrays Drug Resistance lcsh:Medicine Drug resistance Bioinformatics Drug Discovery Antineoplastic Combined Chemotherapy Protocols Combinatorial Chemistry Techniques lcsh:Science media_common Regulation of gene expression Evidence-Based Medicine Multidisciplinary Drug discovery Systems Biology Drug Information Precursor Cell Lymphoblastic Leukemia-Lymphoma Gene Expression Regulation Neoplastic Medicine Female Signal transduction Research Article Biotechnology Signal Transduction Drug Drugs and Devices Drug Research and Development Combination therapy media_common.quotation_subject DNA transcription Biological Data Management Breast Neoplasms Computational biology Biology Vinblastine Genetics Humans Models Statistical Gene Expression Profiling lcsh:R Computational Biology Phenanthrenes Signaling Networks Gene expression profiling Gene Expression Regulation Cancer cell lcsh:Q Gene expression Pharmacogenomics |
| Zdroj: | PLOS ONE(7): 8 PLoS ONE, Vol 7, Iss 8, p e42573 (2012) PLoS ONE |
| Popis: | Background Anticancer therapies that target single signal transduction pathways often fail to prevent proliferation of cancer cells because of overlapping functions and cross-talk between different signaling pathways. Recent research has identified that balanced multi-component therapies might be more efficacious than highly specific single component therapies in certain cases. Ideally, synergistic combinations can provide 1) increased efficacy of the therapeutic effect 2) reduced toxicity as a result of decreased dosage providing equivalent or increased efficacy 3) the avoidance or delayed onset of drug resistance. Therefore, the interest in combinatorial drug discovery based on systems-oriented approaches has been increasing steadily in recent years. Methodology Here we describe the development of Combinatorial Drug Assembler (CDA), a genomics and bioinformatics system, whereby using gene expression profiling, multiple signaling pathways are targeted for combinatorial drug discovery. CDA performs expression pattern matching of signaling pathway components to compare genes expressed in an input cell line (or patient sample data), with expression patterns in cell lines treated with different small molecules. Then it detects best pattern matching combinatorial drug pairs across the input gene set-related signaling pathways to detect where gene expression patterns overlap and those predicted drug pairs could likely be applied as combination therapy. We carried out in vitro validations on non-small cell lung cancer cells and triple-negative breast cancer (TNBC) cells. We found two combinatorial drug pairs that showed synergistic effect on lung cancer cells. Furthermore, we also observed that halofantrine and vinblastine were synergistic on TNBC cells. Conclusions CDA provides a new way for rational drug combination. Together with phExplorer, CDA also provides functional insights into combinatorial drugs. CDA is freely available at http://cda.i-pharm.org. |
| Databáze: | OpenAIRE |
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