CDA: Combinatorial Drug Discovery Using Transcriptional Response Modules

Collection with item attached
2012
Item details URL
http://open-repository.kisti.re.kr/cube/handle/open_repository/475754.do
DOI
10.1371/journal.pone.0042573
Title
CDA: Combinatorial Drug Discovery Using Transcriptional Response Modules
Description
This study was supported by the grants of the Global Frontier(NRF-M1AXA002-2010-0029785) and the Research Information CenterSupporting Program (370C-20090004) and the WCU project(R31-2008-000-10103-0) of the Ministry of Education, Science, andTechnology and Korea Healthcare Technology (A092255-0911-1110100), theMinistry of Health and Welfare Affairs, and Gyonggi-do to Dr. SunghoonKim, an EU project of the 7th framework programme (METOXIA), and by theKorean Ministry of Education, Science and Technology (MEST) under grantnumber 20110002321. The funders had no role in study design, datacollection and analysis, decision to publish, or preparation of themanuscript.
abstract
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.
provenance
Made available in Cube on 2018-09-28T11:21:20Z (GMT). No. of bitstreams: 0
language
English
author
Lee, Ji-Hyun
Kim, Dae Gyu
Bae, Tae Jeong
Rho, Kyoohyoung
Kim, Ji-Tae
Lee, Jong-Jun
Jang, Yeongjun
Kim, Byung Cheol
Park, Kyoung Mii
Kim, Sunghoon
orcid
Bae, Taejeong/0000-0002-4626-3725
accessioned
2018-09-28T11:21:20Z
available
2018-09-28T11:21:20Z
issued
2012
citation
PLOS ONE(7): 8
issn
1932-6203
uri
http://open-repository.kisti.re.kr/cube/handle/open_repository/475754.do
Funder
교육과학기술부
Funding Program
기초연구기반구축
Project ID
1345169055
Jurisdiction
Rep.of Korea
Project Name
Information Center for Bio-pharmcological Network
rights
openAccess
type
article


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