BioGPS
  • Home
  • Help
  • Plugins
  • Datasets
  • Sign Up
  • Login
Examples: Gene Symbol(s), Gene Ontology, Splicing plugins, Melanoma datasets
advanced
Home › Dataset Library › Analyses of heterogeneous renal allograft biopsies reveal conserved rejection signatures and molecular pathways II

Dataset: Analyses of heterogeneous renal allograft biopsies reveal conserved rejection signatures and molecular pathways II

Specific early diagnosis of renal allograft rejection is gaining importance in the current trend to minimize and individualize...

Registered by ArrayExpress Uploader
View Dataset

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 here comprises a small validation batch of renal allograft biopsies for clinical indications plus control normal kidney samples from patients at Hôpital Tenon, Paris (second batch) that complements the first batch of 60 samples. 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 4 renal allograft core biopsies for clinical indications with different histopathological diagnoses according to Banff'97 criteria and 2 normal kidney samples.

Species:
human

Samples:
6

Source:
E-GEOD-9492

Updated:
Dec.12, 2014

Registered:
Sep.22, 2014


Factors: (via ArrayExpress)
Sample AGE OF PATIENT PATIENT IDENTIFIER BANFF'97 SERUM CREATININE RENAL GRAFT BX BIOSOURCEPROVIDER
GSM240943 42 1-ME CAN I 177 microMol/L 1-ME H??pital Tenon, Paris, France
GSM240944 57 3-AO CAN I 131 microMol/L 3-AO H??pital Tenon, Paris, France
GSM240945 35 4-MS CAN I 231 microMol/L 4-MS H??pital Tenon, Paris, France
GSM240946 not specified 70-PJ non-rejecting 128 microMol/L 70-PJ H??pital Tenon, Paris, France
GSM240947 not specified 281004-L7, Control kidney sample from nephrectomy not specified not specified not specified H??pital Tenon, Paris, France
GSM240948 not specified not specified not specified not specified not specified AMS Biotechnology, Abingdon, UK

Tags

  • disease
  • kidney

Other Formats

JSON    XML
  • About
  • Blog
  • Help
  • FAQ
  • Downloads
  • API
  • iPhone App
  • Email updates
© 2025 The Scripps Research Institute. All rights reserved. (ver 94eefe6 )
  • Terms of Use