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A common rejection module for acute rejection in multiple organs identifies novel therapeutics.

ABSTRACT: Using meta-analysis of eight independent transplant datasets (236 graft biopsy samples) from four organs, we identified a common rejection module (CRM) consisting of 11 genes that were significantly overexpressed in acute rejection (AR) across all transplanted organs. The CRM genes could diagnose AR with high specificity and sensitivity in three additional independent cohorts (794 samples). In another two independent cohorts (151 renal transplant biopsies), the CRM genes correlated with the extent of graft injury and predicted future injury to a graft using protocol biopsies. Inferred drug mechanisms from the literature suggested that two FDA-approved drugs (atorvastatin and dasatinib), approved for non-transplant indications, could regulate specific CRM genes and reduce the number of graft infiltrating cells during acute rejection. We treated mice with HLA-mismatched murine cardiac transplant with atorvastatin and dasatinib and showed reduction of the CRM genes, significant reduction of graft infiltrating cells, and extended graft survival. We further validated the beneficial effect of atorvastatina on graft survival by retrospective analysis of electronic medical records of a single-center cohort of 2,515 renal transplant patients. In conclusion, we identified a CRM in transplantation that provides new opportunities for diagnosis, drug repositioning and rational drug design. The eight transplant data sets used for discovery include GSE4315, GSE2596, GSE4470, GSE9377, GSE1563, GSE9493, GSE13440, GSE6095. The two additional independent cohorts of 151 transplant biopsies are GSE25902 and GSE1563. Not all samples from all studies were used. Only the samples marked as either AR or STA in each data set were used for analysis. The 101 samples in this study were used as case-control experiment between acute rejection (AR) and stable (STA) in renal transplant. The samples in this series are one of the three independent validation cohorts. The other two cohorts are described in GSE21374 and GSE36059

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PROVIDER: S-DIXA-D-1163 | biostudies-other |

REPOSITORIES: biostudies-other

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Project description:Using meta-analysis of eight independent transplant datasets (236 graft biopsy samples) from four organs, we identified a common rejection module (CRM) consisting of 11 genes that were significantly overexpressed in acute rejection (AR) across all transplanted organs. The CRM genes could diagnose AR with high specificity and sensitivity in three additional independent cohorts (794 samples). In another two independent cohorts (151 renal transplant biopsies), the CRM genes correlated with the extent of graft injury and predicted future injury to a graft using protocol biopsies. Inferred drug mechanisms from the literature suggested that two FDA-approved drugs (atorvastatin and dasatinib), approved for non-transplant indications, could regulate specific CRM genes and reduce the number of graft infiltrating cells during acute rejection. We treated mice with HLA-mismatched murine cardiac transplant with atorvastatin and dasatinib and showed reduction of the CRM genes, significant reduction of graft infiltrating cells, and extended graft survival. We further validated the beneficial effect of atorvastatina on graft survival by retrospective analysis of electronic medical records of a single-center cohort of 2,515 renal transplant patients. In conclusion, we identified a CRM in transplantation that provides new opportunities for diagnosis, drug repositioning and rational drug design. The eight transplant data sets used for discovery include GSE4315, GSE2596, GSE4470, GSE9377, GSE1563, GSE9493, GSE13440, GSE6095. The two additional independent cohorts of 151 transplant biopsies are GSE25902 and GSE1563. Not all samples from all studies were used. Only the samples marked as either AR or STA in each data set were used for analysis. The 101 samples in this study were used as case-control experiment between acute rejection (AR) and stable (STA) in renal transplant. The samples in this series are one of the three independent validation cohorts. The other two cohorts are described in GSE21374 and GSE36059

Project description:Long-term kidney transplant (KT) allograft outcomes have not improved as expected despite a better understanding of rejection and improved immunosuppression. Previous work had validated a computed rejection score, the tissue common rejection module (tCRM), measured by amplification-based assessment of 11 genes from formalin-fixed paraffin-embedded (FFPE) biopsy specimens, which allows for quantitative, unbiased assessment of immune injury. We applied tCRM in a prospective trial of 124 KT recipients, and contrasted assessment by tCRM and histology reads from 2 independent pathologists on protocol and cause biopsies post-transplant. Four 10-μm shaves from FFPE biopsy specimens were used for RNA extraction and amplification by qPCR of the 11 tCRM genes, from which the tCRM score was calculated. Biopsy diagnoses of either acute rejection (AR) or borderline rejection (BL) were considered to have inflammation present, while stable biopsies had no inflammation. Of the 77 biopsies that were read by both pathologists, a total of 40 mismatches in the diagnosis were present. The median tCRM scores for AR, BL, and stable diagnoses were 4.87, 1.85, and 1.27, respectively, with an overall significant difference among all histologic groups (Kruskal-Wallis, p < 0.0001). There were significant differences in tCRM scores between pathologists both finding inflammation vs. disagreement (p = 0.003), and both finding inflammation vs. both finding no inflammation (p < 0.001), along with overall significance between all scores (Kruskal-Wallis, p < 0.001). A logistic regression model predicting graft inflammation using various clinical predictor variables and tCRM revealed the tCRM score as the only significant predictor of graft inflammation (OR: 1.90, 95% CI: 1.40-2.68, p < 0.0001). Accurate, quantitative, and unbiased assessment of rejection of the clinical sample is critical. Given the discrepant diagnoses between pathologists on the same samples, individuals could utilize the tCRM score as a tiebreaker in unclear situations. We propose that the tCRM quantitative score can provide unbiased quantification of graft inflammation, and its rapid evaluation by PCR on the FFPE shave can become a critical adjunct to help drive clinical decision making and immunosuppression delivery.

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A common rejection module for acute rejection in multiple organs identifies novel therapeutics.

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