Meta-analysis of gene expression profiles to predict response to biologic agents in rheumatoid arthritis
- Title
- Meta-analysis of gene expression profiles to predict response to biologic agents in rheumatoid arthritis
- Author
- 배상철
- Keywords
- Biologic agent; Gene expression; Meta-analysis; Response; Rheumatoid arthritis; IN-VIVO; CLASSIFICATION; ASSOCIATION; DENSITY; CANCER
- Issue Date
- 2014-06
- Publisher
- SPRINGER LONDON LTD, 236 GRAYS INN RD, 6TH FLOOR, LONDON WC1X 8HL, ENGLAND
- Citation
- CLINICAL RHEUMATOLOGY, 권: 33 호: 6, p 775-782
- 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.
- URI
- http://link.springer.com./article/10.1007/s10067-014-2547-9http://hdl.handle.net/20.500.11754/47635
- ISSN
- 0770-3198; 1434-9949
- DOI
- 10.1007/s10067-014-2547-9
- Appears in Collections:
- COLLEGE OF MEDICINE[S](의과대학) > MEDICINE(의학과) > Articles
- Files in This Item:
There are no files associated with this item.
- Export
- RIS (EndNote)
- XLS (Excel)
- XML