Project description: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.

Project description: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 âmolecular Banffâ 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 HÃ´pital Tenon, Paris (February 2003 until September 2004) and few respective patients from HÃ´pital BicÃªtre, Paris, HÃ´pital Pellegrin, Bordeaux, and HÃ´pital Dupuytren, Limoges, plus control normal kidney samples from HÃ´pital 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. Experiment 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.

Project description: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 M-bM-^@M-^\molecular BanffM-bM-^@M-^] 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 HM-CM-4pital Tenon, Paris (February 2003 until September 2004) and few respective patients from HM-CM-4pital BicM-CM-*tre, Paris, HM-CM-4pital Pellegrin, Bordeaux, and HM-CM-4pital Dupuytren, Limoges, plus control normal kidney samples from HM-CM-4pital 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)

Project description:Long-term allograft survival generally requires lifelong immunosuppression. Rarely, recipients display spontaneous operational tolerance with stable graft function in the absence of immunosuppression. The lack of biological markers of this phenomenon precludes identification of potentially tolerant patients in which immunosuppression could be tapered and hinders the development of new tolerance inducing strategies. The objective of this study was to identify minimally invasive blood biomarkers for operational tolerance and utilize these biomarkers to determine the frequency of this state in immunosupressed patients with stable graft function. Blood gene expression profiles from 75 renal transplant patient cohorts (operational tolerance/acute and chronic rejection/stable graft function on immunosuppression) and 16 healthy individuals were analyzed. A subset of samples was used for microarray analysis where three-class comparison of the different groups of patients identified a tolerant footprint of 49 genes. These biomarkers were applied for prediction of operational tolerance by microarray and real-time PCR in independent test-groups. 33/49 genes correctly segregated tolerance and chronic rejection phenotypes with 99% and 86% specificity. The signature is shared with 1/12 and 5/10 stable patients on triple immunosuppression and low dose steroid monotherapy respectively. The gene signature suggests a pattern of reduced co-stimulatory signaling, immune quiescence, apoptosis and memory T cell responses. This study identifies in the blood of kidney recipients a set of genes associated with operational tolerance that may have utility as a minimally-invasive monitoring tool for guiding immunosuppression titration. Further validation of this tool for safe immunosuppression minimization in prospective clinical trials is warranted. 67 samples were analyzed, no replicates included: 1. TOL (n = 12). patients with long-term stable graft function, without immunosuppression for at least 2 years 2. MIS (n = 10). Patients with stable graft function on steroid monotherapy (<10 mg/day) for 4.6. Calcineurin inhibitors and CellCept were removed in these patients because of previous posttransplant lymphoproliferative disease (n = 6), cancer (n = 2), or uncontrolled infectious disease (n = 2). 3. STA (n = 12). Patients with stable kidney graft function at >5 years posttransplantation while under mycophenolate mofetil or azathioprine and maintenance steroids with (n = 5) or without (n = 7) an associated calcineurin inhibitor. 4. AR (n = 14). Patients experiencing rapid decline (>20% from baseline) in graft function and biopsy-proven AR. 5. CR (n = 11). Patients having a progressive degradation of their renal function (creatinine clearance of <60 ml per min per 1.73 m2 and/or proteinuria of >1.5 g/day) and histological signs CR. 6. N (n = 8). These subjects all had normal blood formulae and no infectious or other concomitant pathology for at least 6 months before the study.

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