Dataset: Analyses of heterogeneous renal allograft biopsies reveal conserved rejection signatures and molecular pathways I, partB
Specific early diagnosis of renal allograft rejection is gaining importance in the current trend to minimize and individualize...
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 Keywords: Expression profiling by array 16 renal allograft core biopsies for clinical indications with different histopathological diagnoses according to BANFF'97 criteria (additional samples associated with GSE9489)
- Species:
- human
- Samples:
- 16
- Source:
- E-GEOD-17861
- PubMed:
- 19017305
- Updated:
- Dec.12, 2014
- Registered:
- Sep.15, 2014
Sample | AGE OF PATIENT | PATIENT IDENTIFIER | SERUM CREATININE | RENAL GRAFT BX | SEX | 97 |
---|---|---|---|---|---|---|
GSM442670 | 53 | 4285557 | 107 microMol/L | Z01 | female | non-rejecting |
GSM44267 | 52 | 7409460 | n.d. Renal graft bx: Z02 | not specified | female | non-rejecting |
GSM442672 | 47 | 652033 | 94 microMol/L | Z05 | male | borderline changes |
GSM442673 | 53 | 525928 | 167 microMol/L | Z06 | male | non-rejecting |
GSM442674 | 53 | 525928 | 163 microMol/L | Z07 | male | AR IB, IIA |
GSM442675 | 45 | 718181 | 95 microMol/L | Z10 | male | non-rejecting |
GSM442676 | 45 | 718181 | 106 microMol/L | Z11 | male | non-rejecting |
GSM442677 | 30 | 7358285 | 159 microMol/L | Z13 | male | non-rejecting |
GSM442678 | 64 | 7974116 | 115 microMol/L | Z14 | female | non-rejecting |
GSM442679 | 64 | 7974116 | 114 microMol/L | Z15 | female | non-rejecting |
GSM442680 | 53 | 2727137 | 117 microMol/L | Z16 | male | non-rejecting |
GSM44268 | 29 | 4260341 | 152 microMol/L | Z17 | male | non-rejecting |
GSM442682 | 29 | 4260341 | 108 microMol/L | Z18 | male | non-rejecting |
GSM442683 | 59 | 4138406 | 144 microMol/L | Z19 | male | AR IIA |
GSM442684 | 52 | 7409460 | n.d. microMol/L | Z20 | female | non-rejecting |
GSM442685 | 30 | 6836879 | 94 microMol/L | Z21 | female | non-rejecting |