A Validated RT-PCR Based Gene Signature for Tolerance in Kidney Transplant Recipients

Abstract

Long-life immunosuppression is an important factor that contributes to shorten the long-term survival of kidney transplant recipients. Identifying patients in whom donor-specific tolerance has developed would constitute a major advance in their care. Since this ability would allow the minimization or even withdrawal of immunosuppressive therapy in selected patients. We have previously identified a unique set of 14 biomarkers of transplantation tolerance (Sagoo et al JCI 2010). Aims: The GAMBIT study aims to translate these defined biomarkers of tolerance into clinically useful identities. Methods: To simplify the test for clinical use we performed best subset selection using samples from two independent kidney transplant recipient cohorts (Sagoo et al, and Newel et al JCI 2010). This was approached by fitting all possible models from size 1 to 14, and the optimal model was selected via cross-validation using the area under the curve as indicator of performance. One cohort was used for discovery, and the second for replication with microarray data. Platform transition from expression observed in microarray to quantitative RT-PCR has been performed in the GAMBIT study. Housekeeping gene of reference used was HPRT. Results: Best-subset selection suggested that the expression of 3 genes (PNOC, SH2DB1 and TLR5) provided the best and most stable performance. The 3 genes signature could be used to classify tolerant recipients with a specificity and sensitivity of 0.82 and 0.84 respectively in the replication cohort. Using qRT-PCR, the 3 genes signature we found a sensitivity of 0.83 and specificity of 0.98 (AUC=0.95) to predict tolerance, on a third independent cohort of 6 tolerant, 44 patients with stable function, and 13 chronic rejectors.Figure: [3 Genes ROC Curve]Conclusions: Tolerant recipients can be identified using peripheral blood gene expression of just 3 genes measured by RT-PCR with high specificity and sensitivity. Validation for routine clinical use of these biomarkers would bring to the fore the possibility of personalized medicine.