Genome-scale regression analysis reveals a linear relationship for promoters and enhancers after combinatorial drug treatment

Handle URI:
http://hdl.handle.net/10754/625365
Title:
Genome-scale regression analysis reveals a linear relationship for promoters and enhancers after combinatorial drug treatment
Authors:
Rapakoulia, Trisevgeni; Gao, Xin ( 0000-0002-7108-3574 ) ; Huang, Yi; de Hoon, Michiel; Okada-Hatakeyama, Mariko; Suzuki, Harukazu; Arner, Erik
Abstract:
Motivation: Drug combination therapy for treatment of cancers and other multifactorial diseases has the potential of increasing the therapeutic effect, while reducing the likelihood of drug resistance. In order to reduce time and cost spent in comprehensive screens, methods are needed which can model additive effects of possible drug combinations. Results: We here show that the transcriptional response to combinatorial drug treatment at promoters, as measured by single molecule CAGE technology, is accurately described by a linear combination of the responses of the individual drugs at a genome wide scale. We also find that the same linear relationship holds for transcription at enhancer elements. We conclude that the described approach is promising for eliciting the transcriptional response to multidrug treatment at promoters and enhancers in an unbiased genome wide way, which may minimize the need for exhaustive combinatorial screens.
KAUST Department:
Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Rapakoulia T, Gao X, Huang Y, de Hoon M, Okada-Hatakeyama M, et al. (2017) Genome-scale regression analysis reveals a linear relationship for promoters and enhancers after combinatorial drug treatment. Bioinformatics. Available: http://dx.doi.org/10.1093/bioinformatics/btx503.
Publisher:
Oxford University Press (OUP)
Journal:
Bioinformatics
Issue Date:
9-Aug-2017
DOI:
10.1093/bioinformatics/btx503
Type:
Article
ISSN:
1367-4803; 1460-2059
Sponsors:
The research reported in this work was supported by RIKEN CLST Center Director’s Strategic Program MNC. Additional funding was provided by King Abdullah University of Science and Technology (KAUST), JSPS KAKENHI Grant No.15KT0084 and RIKEN Epigenome and Single Cell Project Grants to MO-H.
Additional Links:
https://academic.oup.com/bioinformatics/article/doi/10.1093/bioinformatics/btx503/4082269/Genomescale-regression-analysis-reveals-a-linear
Appears in Collections:
Articles; Computational Bioscience Research Center (CBRC); Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorRapakoulia, Trisevgenien
dc.contributor.authorGao, Xinen
dc.contributor.authorHuang, Yien
dc.contributor.authorde Hoon, Michielen
dc.contributor.authorOkada-Hatakeyama, Marikoen
dc.contributor.authorSuzuki, Harukazuen
dc.contributor.authorArner, Eriken
dc.date.accessioned2017-08-21T06:28:04Z-
dc.date.available2017-08-21T06:28:04Z-
dc.date.issued2017-08-09en
dc.identifier.citationRapakoulia T, Gao X, Huang Y, de Hoon M, Okada-Hatakeyama M, et al. (2017) Genome-scale regression analysis reveals a linear relationship for promoters and enhancers after combinatorial drug treatment. Bioinformatics. Available: http://dx.doi.org/10.1093/bioinformatics/btx503.en
dc.identifier.issn1367-4803en
dc.identifier.issn1460-2059en
dc.identifier.doi10.1093/bioinformatics/btx503en
dc.identifier.urihttp://hdl.handle.net/10754/625365-
dc.description.abstractMotivation: Drug combination therapy for treatment of cancers and other multifactorial diseases has the potential of increasing the therapeutic effect, while reducing the likelihood of drug resistance. In order to reduce time and cost spent in comprehensive screens, methods are needed which can model additive effects of possible drug combinations. Results: We here show that the transcriptional response to combinatorial drug treatment at promoters, as measured by single molecule CAGE technology, is accurately described by a linear combination of the responses of the individual drugs at a genome wide scale. We also find that the same linear relationship holds for transcription at enhancer elements. We conclude that the described approach is promising for eliciting the transcriptional response to multidrug treatment at promoters and enhancers in an unbiased genome wide way, which may minimize the need for exhaustive combinatorial screens.en
dc.description.sponsorshipThe research reported in this work was supported by RIKEN CLST Center Director’s Strategic Program MNC. Additional funding was provided by King Abdullah University of Science and Technology (KAUST), JSPS KAKENHI Grant No.15KT0084 and RIKEN Epigenome and Single Cell Project Grants to MO-H.en
dc.publisherOxford University Press (OUP)en
dc.relation.urlhttps://academic.oup.com/bioinformatics/article/doi/10.1093/bioinformatics/btx503/4082269/Genomescale-regression-analysis-reveals-a-linearen
dc.rightsThis is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.comen
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/en
dc.titleGenome-scale regression analysis reveals a linear relationship for promoters and enhancers after combinatorial drug treatmenten
dc.typeArticleen
dc.contributor.departmentComputational Bioscience Research Center (CBRC)en
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalBioinformaticsen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionRIKEN Center for Life Science Technologies, Molecular Network Control Genomics Unit, Yokohama, Kanagawa 230-0045, Japanen
dc.contributor.institutionRIKEN Center for Life Science Technologies (Division of Genomic Technologies) (CLST (DGT)), Yokohama, Kanagawa 230-0045, Japanen
dc.contributor.institutionInstitute for Protein Research, Osaka University, Suita, Osaka 565-0871, Japanen
dc.contributor.institutionRIKEN Center for Integrative Medical Sciences, Yokohama, Kanagawa 230-0045, Japanen
kaust.authorRapakoulia, Trisevgenien
kaust.authorRapakoulia, Trisevgenien
kaust.authorGao, Xinen
kaust.authorGao, Xinen
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