Meta-analysis of gene expression profiles to predict response to biologic agents in rheumatoid arthritis
DC Field | Value | Language |
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dc.contributor.author | Lee, Young Ho | - |
dc.contributor.author | Bae, Sang-Cheol | - |
dc.contributor.author | Song, Gwan Gyu | - |
dc.date.accessioned | 2021-09-05T08:29:01Z | - |
dc.date.available | 2021-09-05T08:29:01Z | - |
dc.date.created | 2021-06-15 | - |
dc.date.issued | 2014-06 | - |
dc.identifier.issn | 0770-3198 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/98407 | - |
dc.description.abstract | Our aim was to identify differentially expressed (DE) genes and biological processes that may help predict patient response to biologic agents for rheumatoid arthritis (RA). Using the INMEX (integrative meta-analysis of expression data) software tool, we performed a meta-analysis of publicly available microarray Gene Expression Omnibus (GEO) datasets that examined patient response to biologic therapy for RA. Three GEO datasets, containing 79 responders and 34 non-responders, were included in the metaanalysis. We identified 1,374 genes that were consistently differentially expressed in responders vs. non-responders (651 up-regulated and 723 down-regulated). The upregulated gene with the smallest p value (p=0.000192) was ASCC2 (Activating Signal Cointegrator 1 Complex Subunit 2), and the up-regulated gene with the largest fold change (average log fold change=-0.75869, p=0.000206) was KLRC3 (Killer Cell Lectin-Like Receptor Subfamily C, Member 3). The down-regulated gene with the smallest p value (p=0.000195) was MPL (Myeloproliferative Leukemia Virus Oncogene). Among the 236 GO terms associated with the set of DE genes, the most significantly enriched was "CTP biosynthetic process" (GO:0006241; p=0.000454). Our meta-analysis identified genes that were consistently DE in responders vs. non-responders, as well as biological pathways associated with this set of genes. These results provide insight into the molecular mechanisms underlying responsiveness to biologic therapy for RA. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | SPRINGER LONDON LTD | - |
dc.subject | IN-VIVO | - |
dc.subject | CLASSIFICATION | - |
dc.subject | CANCER | - |
dc.title | Meta-analysis of gene expression profiles to predict response to biologic agents in rheumatoid arthritis | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, Young Ho | - |
dc.contributor.affiliatedAuthor | Song, Gwan Gyu | - |
dc.identifier.doi | 10.1007/s10067-014-2547-9 | - |
dc.identifier.scopusid | 2-s2.0-84903821119 | - |
dc.identifier.wosid | 000338323800008 | - |
dc.identifier.bibliographicCitation | CLINICAL RHEUMATOLOGY, v.33, no.6, pp.775 - 782 | - |
dc.relation.isPartOf | CLINICAL RHEUMATOLOGY | - |
dc.citation.title | CLINICAL RHEUMATOLOGY | - |
dc.citation.volume | 33 | - |
dc.citation.number | 6 | - |
dc.citation.startPage | 775 | - |
dc.citation.endPage | 782 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Rheumatology | - |
dc.relation.journalWebOfScienceCategory | Rheumatology | - |
dc.subject.keywordPlus | IN-VIVO | - |
dc.subject.keywordPlus | CLASSIFICATION | - |
dc.subject.keywordPlus | CANCER | - |
dc.subject.keywordAuthor | Biologic agent | - |
dc.subject.keywordAuthor | Gene expression | - |
dc.subject.keywordAuthor | Meta-analysis | - |
dc.subject.keywordAuthor | Response | - |
dc.subject.keywordAuthor | Rheumatoid arthritis | - |
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