Noninvasive prediction of operational tolerance in liver transplantation based on a peripheral blood transcriptional...

One of the ultimate goals in liver transplantation (LT) can be to achieve an immunosuppression (IS)-free state. However, there remains a lack of reliable tools for non-invasively and precisely predicting spontaneous operational tolerance (OT) after LT. This study aimed to develop a powerful model based on a peripheral blood transcriptional biomarker panel for noninvasive prediction of OT in LT.

Based on the GSE28842 and GSE11881 datasets, the peripheral blood transcriptional biomarkers related to OT after LT before IS withdrawal were retrospectively identified by utilizing differential expression analysis and overlapping analysis. Multivariate logistic regression with the least absolute shrinkage and selection operator (LASSO) was used for model construction. Receiver operating characteristic curves, calibration plots, concordance index, and decision curve analysis were performed for comprehensive model evaluation.

Three key genes (including IL2RB, SH2D1B, and KLRC1) related to OT in LT were identified. A three-gene score was constructed and displayed a good predictive efficacy for OT before IS withdrawal [area under the curve (AUC) =0.794, P<0.05]. Besides, a nomogram combining the three-gene score with the clinical feature (namely "pre-withdrawal time") was established and showed high clinical applicability and predictive accuracy (AUC =0.850, P<0.05), which was superior to that of "pre-withdrawal time" (AUC =0.745, P<0.05).

This model might make it feasible to non-invasively identify the propensity to achieve spontaneous OT among liver recipients undergoing IS therapy and safely achieve IS withdrawal.