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

Acute vs stable kidney transplant

Microarrays were normalized using RMA package in bioconductor.The 101 samples in this series were normalized using Bioconductor version 2.8 (or 2.9).

https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE50058