Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 배상철 | - |
dc.date.accessioned | 2018-03-16T01:33:48Z | - |
dc.date.available | 2018-03-16T01:33:48Z | - |
dc.date.issued | 2014-06 | - |
dc.identifier.citation | CLINICAL RHEUMATOLOGY, 권: 33 호: 6, p 775-782 | en_US |
dc.identifier.issn | 0770-3198 | - |
dc.identifier.issn | 1434-9949 | - |
dc.identifier.uri | http://link.springer.com./article/10.1007/s10067-014-2547-9 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11754/47635 | - |
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. | en_US |
dc.description.sponsorship | This study wassupported in part bya grant ofthe Korea Healthcare technology R&D project, Ministry for Health & Welfare, Republic of Korea (HI12C1834) | en_US |
dc.language.iso | en | en_US |
dc.publisher | SPRINGER LONDON LTD, 236 GRAYS INN RD, 6TH FLOOR, LONDON WC1X 8HL, ENGLAND | en_US |
dc.subject | Biologic agent | en_US |
dc.subject | Gene expression | en_US |
dc.subject | Meta-analysis | en_US |
dc.subject | Response | en_US |
dc.subject | Rheumatoid arthritis | en_US |
dc.subject | IN-VIVO | en_US |
dc.subject | CLASSIFICATION | en_US |
dc.subject | ASSOCIATION | en_US |
dc.subject | DENSITY | en_US |
dc.subject | CANCER | en_US |
dc.title | Meta-analysis of gene expression profiles to predict response to biologic agents in rheumatoid arthritis | en_US |
dc.type | Article | en_US |
dc.relation.no | 6 | - |
dc.relation.volume | 33 | - |
dc.identifier.doi | 10.1007/s10067-014-2547-9 | - |
dc.relation.page | 775-782 | - |
dc.relation.journal | CLINICAL RHEUMATOLOGY | - |
dc.contributor.googleauthor | Lee, Young Ho | - |
dc.contributor.googleauthor | Bae, Sang-Cheol | - |
dc.contributor.googleauthor | Song, Gwan Gyu | - |
dc.relation.code | 2014027472 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF MEDICINE[S] | - |
dc.sector.department | DEPARTMENT OF MEDICINE | - |
dc.identifier.pid | scbae | - |
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