Targeted Transcriptional Profiling of Kidney Transplant Biopsies

Application of the Banff Human Organ Transplant Panel to kidney transplant biopsies with features suspicious for antibody-mediated rejection

The Banff Classification for Allograft Pathology includes the use of gene expression in the diagnosis of antibody-mediated rejection (AMR) of kidney transplants, but a predictive set of genes for classifying biopsies with 'incomplete' phenotypes has not yet been studied. Here, we developed and assessed a gene score that, when applied to biopsies with features of AMR, would identify cases with a higher risk of allograft loss. To do this, RNA was extracted from a continuous retrospective cohort of 349 biopsies randomized 2:1 to include 220 biopsies in a discovery cohort and 129 biopsies in a validation cohort. The biopsies were divided into three groups: 31 that fulfilled the 2019 Banff Criteria for active AMR, 50 with histological features of AMR but not meeting the full criteria (Suspicious-AMR), and 269 with no features of active AMR (No-AMR). Gene expression analysis using the 770 gene Banff Human Organ Transplant NanoString panel was carried out with LASSO Regression performed to identify a parsimonious set of genes predictive of AMR. We identified a nine gene score that was highly predictive of active AMR (accuracy 0.92 in the validation cohort) and was strongly correlated with histological features of AMR. In biopsies suspicious for AMR, our gene score was strongly associated with risk of allograft loss and independently associated with allograft loss in multivariable analysis. Thus, we show that a gene expression signature in kidney allograft biopsy samples can help classify biopsies with incomplete AMR phenotypes into groups that correlate strongly with histological features and outcomes.

Development and Validation of a Parsimonious Tuberculosis Gene Signature Using the digital NanoString nCounter Platform

BACKGROUND

Blood-based biomarkers for diagnosing active tuberculosis (TB), monitoring treatment response, and predicting risk of progression to TB disease have been reported. However, validation of the biomarkers across multiple independent cohorts is scarce. A robust platform to validate TB biomarkers in different populations with clinical end points is essential to the development of a point-of-care clinical test. NanoString nCounter technology is an amplification-free digital detection platform that directly measures mRNA transcripts with high specificity. Here, we determined whether NanoString could serve as a platform for extensive validation of candidate TB biomarkers.

METHODS

The NanoString platform was used for performance evaluation of existing TB gene signatures in a cohort in which signatures were previously evaluated on an RNA-seq dataset. A NanoString codeset that probes 107 genes comprising 12 TB signatures and 6 housekeeping genes (NS-TB107) was developed and applied to total RNA derived from whole blood samples of TB patients and individuals with latent TB infection (LTBI) from South India. The TBSignatureProfiler tool was used to score samples for each signature. An ensemble of machine learning algorithms was used to derive a parsimonious biomarker.

RESULTS

Gene signatures present in NS-TB107 had statistically significant discriminative power for segregating TB from LTBI. Further analysis of the data yielded a NanoString 6-gene set (NANO6) that when tested on 10 published datasets was highly diagnostic for active TB.

CONCLUSIONS

The NanoString nCounter system provides a robust platform for validating existing TB biomarkers and deriving a parsimonious gene signature with enhanced diagnostic performance.

Advanced Genomics-Based Approaches for Defining Allograft Rejection With Single Cell Resolution

Solid organ transplant recipients require long-term immunosuppression for prevention of rejection. Calcineurin inhibitor (CNI)-based immunosuppressive regimens have remained the primary means for immunosuppression for four decades now, yet little is known about their effects on graft resident and infiltrating immune cell populations. Similarly, the understanding of rejection biology under specific types of immunosuppression remains to be defined. Furthermore, development of innovative, rationally designed targeted therapeutics for mitigating or preventing rejection requires a fundamental understanding of the immunobiology that underlies the rejection process. The established use of microarray technologies in transplantation has provided great insight into gene transcripts associated with allograft rejection but does not characterize rejection on a single cell level. Therefore, the development of novel genomics tools, such as single cell sequencing techniques, combined with powerful bioinformatics approaches, has enabled characterization of immune processes at the single cell level. This can provide profound insights into the rejection process, including identification of resident and infiltrating cell transcriptomes, cell-cell interactions, and T cell receptor α/β repertoires. In this review, we discuss genomic analysis techniques, including microarray, bulk RNAseq (bulkSeq), single-cell RNAseq (scRNAseq), and spatial transcriptomic (ST) techniques, including considerations of their benefits and limitations. Further, other techniques, such as chromatin analysis via assay for transposase-accessible chromatin sequencing (ATACseq), bioinformatic regulatory network analyses, and protein-based approaches are also examined. Application of these tools will play a crucial role in redefining transplant rejection with single cell resolution and likely aid in the development of future immunomodulatory therapies in solid organ transplantation.

Acidosis and alkali therapy in patients with kidney transplant is associated with transcriptional changes and altered abundance of genes involved in cell metabolism and acid-base balance

BACKGROUND

Metabolic acidosis occurs frequently in patients with kidney transplant and is associated with higher risk for and accelerated loss of graft function. To date, it is not known whether alkali therapy in these patients improves kidney function and whether acidosis and its therapy is associated with altered expression of proteins involved in renal acid-base metabolism.

METHODS

We collected retrospectively kidney biopsies from 22 patients. Of these patients, 9 had no acidosis, 9 had metabolic acidosis (plasma HCO3- < 22 mmol/l), and 4 had acidosis and received alkali therapy. We performed transcriptome analysis and immunohistochemistry for proteins involved in renal acid-base handling.

RESULTS

We found the expression of 40 transcripts significantly changed between kidneys from non-acidotic and acidotic patients. These genes are mostly involved in proximal tubule amino acid and lipid metabolism and energy homeostasis. Three transcripts were fully recovered by alkali therapy: the Kir4.2 K+-channel, an important regulator of proximal tubule HCO3--metabolism and transport, ACADSB and SHMT1, genes involved in beta-oxidation and methionine metabolism. Immunohistochemistry showed reduced staining for the proximal tubule NBCe1 HCO3- transporter in kidneys from acidotic patients that recovered with alkali therapy. In addition, the HCO3-exchanger pendrin was affected by acidosis and alkali therapy.

CONCLUSIONS

Metabolic acidosis in kidney transplant recipients is associated with alterations in the renal transcriptome that are partly restored by alkali therapy. Acid-base transport proteins mostly from proximal tubule were also affected by acidosis and alkali therapy suggesting that the downregulation of critical players contributes to metabolic acidosis in these patients.

Molecular Analysis of Renal Allograft Biopsies: Where Do We Stand and Where Are We Going?

A renal core biopsy for histological evaluation is the gold standard for diagnosing renal transplant pathology. However, renal biopsy interpretation is subjective and can render insufficient precision, making it difficult to apply a targeted therapeutic regimen for the individual patient. This warrants a need for additional methods assessing disease state in the renal transplant. Significant research activity has been focused on the role of molecular analysis in the diagnosis of renal allograft rejection. The identification of specific molecular expression patterns in allograft biopsies related to different types of allograft injury could provide valuable information about the processes underlying renal transplant dysfunction and can be used for the development of molecular classifier scores, which could improve our diagnostic and prognostic ability and could guide treatment. Molecular profiling has the potential to be more precise and objective than histological evaluation and may identify injury even before it becomes visible on histology, making it possible to start treatment at the earliest time possible. Combining conventional diagnostics (histology, serology, and clinical data) and molecular evaluation will most likely offer the best diagnostic approach. We believe that the use of state-of-the-art molecular analysis will have a significant impact in diagnostics after renal transplantation. In this review, we elaborate on the molecular phenotype of both acute and chronic T cell-mediated rejection and antibody-mediated rejection and discuss the additive value of molecular profiling in the setting of diagnosing renal allograft rejection and how this will improve transplant patient care.

Use of the Tissue Common Rejection Module Score in Kidney Transplant as an Objective Measure of Allograft Inflammation

Long-term kidney transplant (KT) allograft outcomes have not improved as expected despite a better understanding of rejection and improved immunosuppression. Previous work had validated a computed rejection score, the tissue common rejection module (tCRM), measured by amplification-based assessment of 11 genes from formalin-fixed paraffin-embedded (FFPE) biopsy specimens, which allows for quantitative, unbiased assessment of immune injury. We applied tCRM in a prospective trial of 124 KT recipients, and contrasted assessment by tCRM and histology reads from 2 independent pathologists on protocol and cause biopsies post-transplant. Four 10-μm shaves from FFPE biopsy specimens were used for RNA extraction and amplification by qPCR of the 11 tCRM genes, from which the tCRM score was calculated. Biopsy diagnoses of either acute rejection (AR) or borderline rejection (BL) were considered to have inflammation present, while stable biopsies had no inflammation. Of the 77 biopsies that were read by both pathologists, a total of 40 mismatches in the diagnosis were present. The median tCRM scores for AR, BL, and stable diagnoses were 4.87, 1.85, and 1.27, respectively, with an overall significant difference among all histologic groups (Kruskal-Wallis, p < 0.0001). There were significant differences in tCRM scores between pathologists both finding inflammation vs. disagreement (p = 0.003), and both finding inflammation vs. both finding no inflammation (p < 0.001), along with overall significance between all scores (Kruskal-Wallis, p < 0.001). A logistic regression model predicting graft inflammation using various clinical predictor variables and tCRM revealed the tCRM score as the only significant predictor of graft inflammation (OR: 1.90, 95% CI: 1.40–2.68, p < 0.0001). Accurate, quantitative, and unbiased assessment of rejection of the clinical sample is critical. Given the discrepant diagnoses between pathologists on the same samples, individuals could utilize the tCRM score as a tiebreaker in unclear situations. We propose that the tCRM quantitative score can provide unbiased quantification of graft inflammation, and its rapid evaluation by PCR on the FFPE shave can become a critical adjunct to help drive clinical decision making and immunosuppression delivery.

Technical considerations when designing a gene expression panel for renal transplant diagnosis

Gene expression analysis is emerging as a new diagnostic tool in transplant pathology, in particular for the diagnosis of antibody-mediated rejection. Diagnostic gene expression panels are defined on the basis of their pathophysiological relevance, but also need to be tested for their robustness across different preservatives and analysis platforms. The aim of this study is the investigate the effect of tissue sampling and preservation on candidate genes included in a renal transplant diagnostic panel. Using the NanoString platform, we compared the expression of 219 genes in 51 samples, split for formalin-fixation and paraffin-embedding (FFPE) and RNAlater preservation (RNAlater). We found that overall, gene expression significantly correlated between FFPE and RNAlater samples. However, at the individual gene level, 46 of the 219 genes did not correlate across the 51 matched FFPE and RNAlater samples. Comparing gene expression results using NanoString and qRT-PCR for 18 genes in the same pool of RNA (RNAlater), we found a significant correlation in 17/18 genes. Our study indicates that, in samples from the same routine diagnostic renal transplant biopsy procedure split for FFPE and RNAlater, 21% of 219 genes of potential biological significance do not correlate in expression. Whether this is due to fixatives or tissue sampling, selection of gene panels for routine diagnosis should take this information into consideration.

The impact of belatacept on the phenotypic heterogeneity of renal T cell-mediated alloimmune response: The critical role of maintenance treatment and inflammatory load

Belatacept offers superior long-term outcome relative to calcineurin inhibitor (CNI)-based immunosuppression. However, the higher frequency of early T cell-mediated rejection (TCMR) in belatacept-treated patients hampered the widespread adoption of costimulation blockade. Here, we applied gene expression analysis and whole-slide inflammatory cell quantification to assess the impact of belatacept on intragraft immune signature. We studied formalin-fixed, paraffin-embedded renal biopsies from 92 patients stratified by histopathologic diagnosis (TCMR, borderline changes, or normal) and immunosuppression regimen (belatacept, CNI). An interaction model was built to explore maintenance treatment-dependent expression level changes of immune response-related genes across diagnostic categories of normal, borderline changes, and TCMR. Ninety-one percent of genes overexpressed in TCMR showed significant correlation with whole section inflammatory load. There were 27 genes that had a positive association with belatacept treatment. These were mostly related to myeloid cells and innate immunity. Genes negatively associated with costimulation blockade (n = 14) could be linked to B-cell differentiation and proliferation. We concluded that expression levels of genes characteristic of TCMR are strongly interconnected with quantitative changes of the biopsy inflammatory load. Our results might suggest differential involvement of the innate immune system, and an altered B-cell engagement during TCMR in belatacept-treated patients relative to CNI-treated referents.

Novel In Situ Hybridization and Multiplex Immunofluorescence Technology Combined With Whole-slide Digital Image Analysis in Kidney Transplantation

The elusive nature of assessing immunological processes in situ in organ transplantation is one of the major impediments to improve diagnostics and treatment. Here, we present a proof-of-concept study using multiplexed in situ hybridization (ISH) (RNAscope) to detect low-abundance cytokines in formalin-fixed paraffin-embedded (FFPE) human transplant kidney biopsies in combination with immunofluorescence (IF) for cell phenotyping. We show that a multiplex IF and ISH (mIFISH) assay is feasible to identify the cellular source of cytokines and chemokines (tumor necrosis factor-α, interferon-γ, and CXCL9) in FFPE transplant kidney biopsies and that quantification of the mRNA and protein signal is also possible at single-cell resolution in the context of tissue complexity. Furthermore, the mIFISH assay allows precise quantitative assessment of tubulitis, one of the key morphological correlates of alloimmune injury. Simultaneous in situ identification and quantification of multiple cellular phenotypes and mRNA expression of proinflammatory cytokines in FFPE tissues offer a novel insight into the biology of alloimmune injury in kidney transplantation and may contribute to improved diagnostic accuracy and patient care.

Multi-gene technical assessment of qPCR and NanoString n-Counter analysis platforms in cynomolgus monkey cardiac allograft recipients

Quantitative gene expression profiling of cardiac allografts characterizes the phenotype of the alloimmune response, yields information regarding differential effects that may be associated with various anti-rejection drug regimens, and generates testable hypotheses regarding the pathogenesis of the chronic rejection lesions typically observed in non-human primate heart transplant models. The goal of this study was to assess interplatform performance and variability between the relatively novel NanoString nCounter Analysis System, ΔΔCT (relative) RT-qPCR, and standard curve (absolute) RT-qPCR utilizing cynomolgus monkey cardiac allografts. Methods for RNA isolation and preamplification were also systematically evaluated and effective methods are proposed. In this study, we demonstrate strong correlation between the two RT-qPCR methods, but variable and, at times, weak correlation between RT-qPCR and NanoString. NanoString fold change results demonstrate less sensitivity to small changes in gene expression than RT-qPCR. These findings appear to be driven by technical aspects of each platform that influence the conditions under which each technique is ideal. Collectively, our data contribute to the general effort to optimally utilize gene expression profiling techniques, not only for transplanted tissues, but for many other applications where accurate rank-order of gene expression versus precise quantification of absolute gene transcript number may be relatively valuable.

High Dimensional Renal Profiling: Towards a Better Understanding or Renal Transplant Immune Suppression

PURPOSE OF REVIEW

The goal of this review is to discuss new approaches to avoid CNI/CCS toxicities with a focus on new biologics and new methods to understand transplant rejection at the single-cell level.

RECENT FINDINGS

Recently developed biologics hold significant promise as the next wave of therapeutics designed to promote CNI/CCS-free long-term allograft acceptance. Indeed, belatacept, soluble CTLA4-Ig, is largely devoid of CNI-like toxicities, although it is accompanied by an increased frequency of acute rejection. Besides belatacept, other biologics hold promise as CNI-free immune suppressive approaches. Finally, powerful new single cell approaches can enable characterization of cellular populations that drive rejection within the rejecting allograft.

SUMMARY

We propose that the incorporated single cell profiling into studies investigating new biologics in transplantation, could be tailored to each patient, correlated with potential biomarkers in the blood and urine, and provide a platform where therapeutic targets can be rationally defined, mechanistically-based, and exploited.

Assessment of 19 Genes and Validation of CRM Gene Panel for Quantitative Transcriptional Analysis of Molecular Rejection and Inflammation in Archival Kidney Transplant Biopsies

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.

WNT pathway signaling is associated with microvascular injury and predicts kidney transplant failure

Microvascular injury is associated with accelerated kidney transplant dysfunction and allograft failure. Molecular pathology can identify new mechanisms of microvascular injury while improving on the diagnostic and prognostic capabilities of traditional histology. We conducted a case-control study of archived kidney biopsy specimens stored up to 10 years with microvascular injury (n = 50) compared with biopsy specimens without histologic injury (n = 45) from patients of similar age, race, and sex. We measured WNT gene expression with a multiplex quantification platform by using digital barcoding, given the importance of WNT reactivation to the response to wounding in the kidney microvasculature and other compartments. Of 210 genes from a commercial WNT panel, 71 were associated with microvascular injury and 79 were associated with allograft failure, with considerable overlap of genes between each set. Molecular pathology identified 46 biopsy specimens with molecular evidence of microvascular injury; 18 (39%) were either C4d negative, donor-specific antibody negative, or had no microvascular injury by histology. The majority of cases with molecular evidence of microvascular injury had poor long-term outcomes. We identified novel WNT pathway genes associated with microvascular injury and allograft failure in residual clinical biopsy specimens obtained up to 10 years earlier. Further mechanistic studies may identify the WNT pathway as a new diagnostic and therapeutic target.

Immunomics of Renal Allograft Acute T Cell-Mediated Rejection Biopsies of Tacrolimus- and Belatacept-Treated Patients

Supplemental digital content is available in the text.

Background

Belatacept-based therapy in kidney transplant recipient has been shown to increase long-term renal allograft and patient survival compared with calcineurin inhibitor–based therapy, however, with an increased risk of acute T cell-mediated rejection (aTCMR). An improved understanding of costimulation blockade-resistant rejections could lead to a more personalized approach to belatacept therapy. Here, immunomic profiles of aTCMR biopsies of patients treated with either tacrolimus or belatacept were compared.

Methods

Formalin-fixed paraffin-embedded renal transplant biopsies were used for immunohistochemistry and gene expression analysis using the innovative NanoString technique. To validate NanoString, transcriptomic profiles of patients with and without biopsy-proven aTCMR were compared. Biopsies from 31 patients were studied: 14 tacrolimus-treated patients with aTCMR, 11 belatacept-treated patients with aTCMR, and 6 controls without rejection.

Results

A distinct pattern was seen in biopsies with aTCMR compared to negative controls: 78 genes had a higher expression in the aTCMR group (false discovery rate P value <.05 to 1.42e–05). The most significant were T cell-associated genes (CD3, CD8, and CD4; P < 1.98e-04), γ-interferon-inducible genes (CCL5, CXCL9, CXCL11, CXCL10, TBX21; P < 1.33e-04) plus effector genes (GNLY, GZMB, ITGAX; P < 2.82e-03). Immunophenotypical analysis of the classic immune markers of the innate and adaptive immune system was comparable between patients treated with either tacrolimus or belatacept. In addition, the transcriptome of both groups was not significantly different.

Conclusions

In this small pilot study, no difference was found in immunomics of aTCMR biopsies of tacrolimus- and belatacept-treated patients. This suggests that clinically diagnosed aTCMR reflects a final common pathway of allorecognition which is unaffected by the type of immunosuppressive therapy.

The common rejection module in chronic rejection post lung transplantation

Rationale

Recent studies suggest that similar injury mechanisms are in place across different solid organ transplants, resulting in the identification of a common rejection module (CRM), consisting of 11 genes that are overexpressed during acute and, to a lesser extent, chronic allograft rejection.

Objectives

We wanted to evaluate the usefulness of the CRM module in identifying acute rejection (AR) and different phenotypes of chronic lung transplant rejection (CLAD), i.e., bronchiolitis obliterans syndrome (BOS) and restrictive allograft syndrome (RAS), using transbronchial brushings, broncho-alveolar lavage (BAL) samples, and explant tissue.

Methods

Gene expression measurements for the 11 CRM genes (CD6, TAP1, CXCL10, CXCL9, INPP5D, ISG20, LCK, NKG7, PSMB9, RUNX3, and BASP1) were performed via qRT-PCR in 14 transbronchial brushings (AR, n = 4; no AR, n = 10), 32 BAL samples (stable, n = 13; AR, n = 8; BOS, n = 9; RAS, n = 10), and 44 tissue specimens (unused donor lungs, n = 15; BOS, n = 13; RAS, n = 16). A geometric mean score was calculated to quantitate overall burden of immune injury and a new computational model was built for the most significant genes in lung transplant injury.

Results

Acute rejection showed a significant difference in almost every gene analysed, validating previous observations from microarray analysis. RAS tissue demonstrated a higher geometric mean score (6.35) compared to donor tissue (4.09, p = 0.018). Analysis of individual CRM genes showed an increased expression of ISG20, CXCL10 and CXCL9 in RAS. In BAL samples, no differences were detected in gene expression or geometric mean scores between the various groups (stable, 5.15; AR, 5.81; BOS, 5.62; RAS, 7.31). A newly modelled 2-gene tissue CRM score did not demonstrate any difference between BOS and RAS (p>0.05). However, the model was able to discriminate RAS from BOS tissue (AUC = 0.75, 95% CI = 0.55–0.94, p = 0.025).

Conclusion

Transcriptional tissue analysis for CRM genes in CLAD can identify acute rejection and distinguish RAS from BOS. The immune activation in RAS seems similar to acute rejection after kidney/liver/heart transplantation.

Molecular Assessment of C4d-Positive Renal Transplant Biopsies Without Evidence of Rejection

Introduction

Immunohistochemical staining for C4d in peritubular capillaries has been part of antibody-mediated rejection (AbMR) definition in the Banff Classification for Allograft Pathology since 2003. However, it has limited sensitivity and specificity, therefore the clinical significance of C4d-positive biopsies without evidence of rejection (C4d+ WER) is unknown. We investigated the transcript levels of genes associated with AbMR in C4d+ WER biopsies from both ABO-compatible and incompatible renal transplant patients.

Methods

RNA was extracted from formalin-fixed paraffin-embedded renal transplant biopsies (n = 125) and gene expression analysis of 35 AbMR-associated transcripts carried out using the NanoString nCounter system.

Results

AbMR-associated transcripts were significantly increased in samples with AbMR or suspicious AbMR. A subgroup of 17 of 35 transcripts that best distinguished AbMR from C4d-negative biopsies without evidence of rejection was used to study C4d+ WER samples. There was no differential expression between C4d-negative and C4d+ WER from both ABO-incompatible and -compatible transplants. The geometric mean of 17 differentially expressed genes was used to assign the C4d+ WER biopsies a high- or low-AbMR transcript score. Follow-up biopsies showed AbMR within 1 year of initial biopsy in 5 of 7 high-AbMR transcript patients but only 2 of 46 low-AbMR transcript patients. In multivariate logistic regression analysis, elevated transcript levels in a C4d+ WER biopsy were associated with increased odds for biopsy-proven AbMR on follow-up (P = 0.032, odds ratio 16.318), whereas factors including donor-specific antibody (DSA) status and time since transplantation were not.

Conclusion

Gene expression analysis in C4d+ WER samples has the potential to identify patients at higher risk of developing AbMR.