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Series GSE9489 Query DataSets for GSE9489
Status Public on Feb 24, 2009
Title Analyses of heterogeneous renal allograft biopsies reveal conserved rejection signatures and molecular pathways I
Organism Homo sapiens
Experiment type Expression profiling by array
Summary Specific early diagnosis of renal allograft rejection is gaining importance in the current trend to minimize and individualize immunosuppression. Gene expression analyses could contribute significantly by defining “molecular Banff” signatures. Several previous studies have applied transcriptomics to distinguish different classes of kidney biopsies. However, the heterogeneity of microarray platforms, clinical samples and data analysis methods complicates the identification of robust signatures for the different types and grades of rejection. To address these issues, a comparative meta-analysis was performed across five different microarray datasets of heterogeneous sample collections from two published clinical datasets and three own datasets including biopsies for clinical indications, protocol biopsies, as well as comparative samples from non-human primates (NHP). This work identified conserved gene expression signatures that can differentiate groups with different histopathological findings in both human and NHP, regardless of the technical platform used. The marker panels comprise genes that clearly support the biological changes known to be involved in allograft rejection. A characteristic dynamic expression change of genes associated with immune and kidney functions was observed across samples with different grades of CAN. In addition, differences between human and NHP rejection were essentially limited to genes reflecting interstitial fibrosis progression. This data set comprises all renal allograft biopsies for clinical indications from patients at Hôpital Tenon, Paris (February 2003 until September 2004) and few respective patients from Hôpital Bicêtre, Paris, Hôpital Pellegrin, Bordeaux, and Hôpital Dupuytren, Limoges, plus control normal kidney samples from Hôpital Tenon, Paris, France (first batch).
We used microarrays to identify different gene expression signatures of renal allograft biopsies that can classify them according to different types of allograft rejection or CAN.
Keywords: disease state analysis
 
Overall design 47 renal allograft core biopsies for clinical indications with different histopathological diagnoses according to BANFF'97 criteria, and 13 normal kidney samples as controls.
 
Contributor(s) Raulf F, Saint-Mezard P, Rondeau E, Marti H
Citation(s) 19017305
Submission date Oct 31, 2007
Last update date Mar 25, 2019
Contact name Friedrich Raulf
E-mail(s) friedrich.raulf@novartis.com
Phone +41 61 324 6880
Fax +41 61 324 3576
Organization name Novartis Pharma AG
Department Novartis Institutes for BioMedical Research / ATDA
Lab Raulf
Street address WSJ-386.6.09
City Basel
ZIP/Postal code 4002
Country Switzerland
 
Platforms (1)
GPL570 [HG-U133_Plus_2] Affymetrix Human Genome U133 Plus 2.0 Array
Samples (60)
GSM240785 Patient TX40, renal graft bx 1.48, diagnosis AR IA
GSM240786 Patient TX22, renal graft bx 1.27, diagnosis AR IA
GSM240787 Patient TX01, renal graft bx 1.15, diagnosis AR IA
This SubSeries is part of SuperSeries:
GSE9493 Transcriptomic analyses of renal allograft biopsies reveal conserved rejection signatures and molecular pathways
Relations
BioProject PRJNA105167

Download family Format
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Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE9489_RAW.tar 518.4 Mb (http)(custom) TAR (of CEL)
Processed data included within Sample table

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