ABSTRACT: Polyoma virus nephropathy (PVAN) is a common cause of kidney allograft dysfunction and loss. Microscopic descriptions of PVAN are very similar to T-cell mediated rejection (TCMR) and have unclear underlying molecular mechanisms. To identify PVAN-specific gene expression, we analyzed 162 kidney biopsies with and without PVAN for global gene expression. Unsupervised hierarchical clustering analysis of all 162 biopsies revealed high similarity between PVAN and TCMR gene expression. Increasing the stringency for the specificity (p <0.001 and >2-fold expression) between PVAN and TCMR, 158 and 252 unique PVAN and TCMR injury-specific probesets were observed, respectively. While TCMR-specific probeset were overwhelmingly involved in immune response costimulation (CTLA4, CD28, CD86) and TCR (NFATC2, LCP2) signaling, PVAN-specific probesets were mainly related to viral replication process (IFITM1, LTF, NOSIP, RARRES3), RNA polymerase assembly (POLR2l, TAF10, RPS15) and pathogen recognition receptors (C1QA, C3, CFD). A principal component analysis using these genes further confirmed the most optimal separation between the 3 different clinical phenotypes. Validation of 4 PVAN-specific probesets (RPS15, CFD, LTF, and NOSIP) by QPCR and further confirmation by IHC of 2 PVAN-specific proteins with anti-viral function (LTF and IFITM1) was done, showing significantly higher expression within interstitial cellular infiltrates and in tubuli in PVAN specimens as compared to TCMR and NL kidney biopsies. In conclusion, even though PVAN and TCMR kidney allografts share great similarities on gene perturbation, particular PVAN-specific transcripts were identified with well-known anti-viral properties that provide tools for discerning PVAN and AR as well as attractive targets for rational drug design. A total of 168 kidney biopsies from kidney transplant patients were used. The kidney biopsies included renal biopsies from PVAN (n=10), T cell mediated cellular rejection (n=26), patients with IFTA (n=59), patients with stable grafts (STA) (n=73). This dataset is part of the TransQST collection.
