Abstract
Background: There is an urgent need to develop and implement low cost, high-throughput standardized methods for routine molecular assessment of transplant biopsies. Given the vast archive of formalin-fixed and paraffin-embedded (FFPE) tissue blocks in transplant centers, a reliable protocol for utilizing this tissue bank for clinical validation of target molecules as predictors of graft outcome over time, would be of great value.Methods: We designed and optimized assays to quantify 19 target genes, including previously reported set of tissue common rejection module (tCRM) genes. We interrogated their performance for their clinical utility for detection of graft rejection and inflammation by analyzing gene expression microarrays analysis of 163 renal allograft biopsies, and subsequently validated in 40 independent FFPE archived kidney transplant biopsies at a single center.Results: A QPCR (Fluidigm) and a barcoded oligo-based (NanoString) gene expression platform were compared for evaluation of amplification of gene expression signal for 19 genes from degraded RNA extracted from FFPE biopsy sections by a set protocol. Increased expression of the selected 19 genes, that reflect a combination of specific cellular infiltrates (8/19 genes) and a graft inflammation score (11/19 genes which computes the tCRM score allowed for segregation of kidney transplant biopsies with stable allograft function and normal histology from those with histologically confirmed acute rejection (AR; p = 0.0022, QPCR; p = 0.0036, barcoded assay) and many cases of histological borderline inflammation (BL). Serial biopsy shaves used for gene expression were also processed for in-situ hybridization (ISH) for a subset of genes. ISH confirmed a high degree of correlation of signal amplification and tissue localization.Conclusions: Target gene expression amplification across a custom set of genes can identify AR independent of histology, and quantify inflammation from archival kidney transplant biopsy tissue, providing a new tool for clinical correlation and outcome analysis of kidney allografts, without the need for prospective kidney biopsy biobanking efforts.
Highlights
Renal transplantation is the preferred treatment of end stage renal disease (ESRD) [1, 2]; acute rejection, both T cell mediated rejection (TCMR) or antibody-mediated rejection (AMR), remain barriers to long-term graft survival
Forty independent renal transplant recipients were identified with Banff supported diagnosis of acute T cellmediated rejection (TCMR, n = 8), antibody-mediated rejection (ABMR, n = 8), borderline changes (BL, n = 8), polyoma virus nephropathy (PVAN, n = 8), and normal functioning (NL, n = 8) were used for clinical validation (Table 1) [20,21,22,23]
We evaluated gene expression changes in different kidney transplant phenotypes on 40 independent samples (8 NL, 8 TCMR, 8 ABMR, 8 BL and 8 PVAN) using two platforms commonly used for quantification of gene expression
Summary
Renal transplantation is the preferred treatment of end stage renal disease (ESRD) [1, 2]; acute rejection, both T cell mediated rejection (TCMR) or antibody-mediated rejection (AMR), remain barriers to long-term graft survival. Current classification methods of histological rejection by modified Banff classification, suffer from heterogeneities in biopsy sampling, poor correlations between blinded pathology reads, and an inability to accurately quantify the inflammatory burden in the allograft, which is an important predictor of long-term graft function and survival [3,4,5,6,7,8,9,10,11,12]. In order to allow this score to be assessed on archival FFPE tissue blocks, we developed and optimized a protocol that would allow for target gene analysis on degraded RNA [11]. Given the vast archive of formalin-fixed and paraffin-embedded (FFPE) tissue blocks in transplant centers, a reliable protocol for utilizing this tissue bank for clinical validation of target molecules as predictors of graft outcome over time, would be of great value
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