American Journal of Transplantation · 2016 · 97 citations · 43 references
Life SciencesImmunologyNephrologyImmunogeneticsKidney TransplantationTransplant ImmunologyHistocompatibilityImmunosuppression In Kidney TransplantationTransplant BiomarkersTransplant ToleranceDifferential Transcript ExpressionMolecular Pathways Of ToleranceProspective Cohort DataRna Expression Signature AnalysisTransplant Biomarker ValidationTransplant Tolerance Mechanisms
We and others have previously described signatures of tolerance in kidney transplantation showing the differential expression of B cell-related genes and the relative expansions of B cell subsets. However, in all of these studies, the index group-namely, the tolerant recipients-were not receiving immunosuppression (IS) treatment, unlike the rest of the comparator groups. We aimed to assess the confounding effect of these regimens and develop a novel IS-independent signature of tolerance. Analyzing gene expression in three independent kidney transplant patient cohorts (232 recipients and 14 tolerant patients), we have established that the expression of the previously reported signature was biased by IS regimens, which also influenced transitional B cells. We have defined and validated a new gene expression signature that is independent of drug effects and also differentiates tolerant patients from healthy controls (cross-validated area under the receiver operating characteristic curve [AUC] = 0.81). In a prospective cohort, we have demonstrated that the new signature remained stable before and after steroid withdrawal. In addition, we report on a validated and highly accurate gene expression signature that can be reliably used to identify patients suitable for IS reduction (approximately 12% of stable patients), irrespective of the IS drugs they are receiving. Only a similar approach will make the conduct of pilot clinical trials for IS minimization safe and hence allow critical improvements in kidney posttransplant management.
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pROC: an open-source package for R and S+ to analyze and compare ROC curves
Xavier Robin, Natacha Turck, Alexandre Hainard et al. · BMC Bioinformatics · 2011 · 14K citations · Full text