Introduction: Histopathological examination of kidney allograft biopsies is the gold standard for diagnosing transplant pathology. However, limited reproducibility and differential diagnostic dilemma’s remain a problem. Identification of biomarkers of acute kidney allograft rejection (AR) can potentially lead to improved diagnostics. Here, we analyzed the expression of 209 genes in biopsies of kidney transplant patients with AR with the NanoString® nCounter® analysis system. With this novel technique, only low quantities of RNA from formalin fixed paraffin embedded (FFPE) biopsies are required and no amplification is needed. Therefore, residual material used for histopathological diagnosis can be analyzed. The objectives of this study were: i) to examine the gene expression profile in biopsies of patients with acute T cell-mediated rejection (aTCMR) versus patients without aTCMR and ii) to compare the gene expression profiles in patients with aTCMR treated with tacrolimus versus patients treated with belatacept (an inhibitor of the CD28-CD80/86 co-stimulatory pathway).

Materials and Methods: Biopsies from 21 kidney transplant were studied. Seven biopsies from patients with aTCMR (Banff 1b-3, without C4d) treated with tacrolimus as maintenance immunosuppressive therapy, 9 biopsies from patients with aTCMR treated with belatacept, and 5 negative controls (for-cause biopsies without histomorphological changes) were included. Patients were matched for age, days after transplantation and Banff 2015 category. RNA was extracted from FFPE biopsies and gene expression was analyzed using the NanoString® nCounter® analysis system. Gene expression was identified by scaled estimates (JMP, Fit Model). P values were corrected for false discovery (JMP, addin)

Results and Discussion: A distinct pattern was seen in biopsies with aTCMR compared to biopsies without rejection. Comparison of aTCMR and controls (Banff, no rejection) identified 60 genes with higher expression (FDRPV <0.05 to 2E-6). The most significant were T cell associated genes, CD3, CD8, and CD4 (p < 10E-5), and interferon (p = 2x10E-3) inducible genes (CXCL9, CCL5, TBX21 p< 10E-3), plus effector genes (GNLY, ITGAX p<10E-3). This overall pattern is that of aTCMR. Interestingly, pairwise estimates showed no significant differences between belatacept or tacrolimus treated subjects with aTCMR.

Conclusion: Gene expression analysis on FFPE biopsies with the novel technique NanoString® nCounter® analysis system can distinguish kidney transplant biopsies showing aTCMR from those of without aTCMR. Interestingly, we found no differences in gene expression profiles in renal allograft biopsies showing aTCMR in subjects receiving tacrolimus or belatacept-based immunosuppressive regimens. The limitations of this study may relate to the small sample size.