A Computational Gene Expression Score for Predicting Immune Injury in Renal Allografts. PLoS One. 2015;10:e0138133. [PMID: 26367000 PMCID: PMC4569485 DOI: 10.1371/journal.pone.0138133]

RUNX3-activated apelin signaling inhibits cell proliferation and fibrosis in diabetic nephropathy by regulation of the SIRT1/FOXO pathway

BACKGROUND

Diabetic nephropathy is a major secondary cause of end-stage renal disease. Apelin plays an important role in the development of DN. Understanding the exact mechanism of Apelin can help expand the means of treating DN.

METHODS

Male C57BL/6 mice was used and STZ treatment was implemented for DN model establishment. Lentivirus systems including Lv-sh-RUNX3 and Lv-Apelin were obtained to knockdown RUNX3 and overexpress Apelin, respectively. A total of 36 mice were divided into 6 groups (n = 6 in each group): control, DN, DN + LV-Vector, DN + Lv-Apelin, DN + LV-Apelin + LV-sh-NC and DN + Lv-Apelin + Lv-sh-RUNX3 group. In vitro studies were performed using mesangial cells. Cell viability and proliferation was assessed through CCK8 and EDU analysis. Hematoxylin and eosin staining as well as Masson staining was implemented for histological evaluation. RT-qPCR was conducted for measuring relative mRNA levels, and protein expression was detected by western blotting. The interaction between SIRT1 and FOXO were verified by co-immunoprecipitations, and relations between RUNX3 and Apelin were demonstrated by dual luciferase report and chromatin immunoprecipitation.

RESULTS

The DN group exhibited significantly lower Apelin expression compared to control (p < 0.05). Apelin overexpression markedly improved blood glucose, renal function indicators, ameliorated renal fibrosis and reduced fibrotic factor expression (p < 0.05) in the DN group, accompanied by elevated sirt1 levels and diminished acetylated FOXO1/FOXO3a (p < 0.05). However, RUNX3 knockdown combined with Apelin overexpression abrogated these beneficial effects, leading to impaired renal function, exacerbated fibrosis, increased fibrotic factor expression and acetylated FOXO1/FOXO3a versus Apelin overexpression alone (p < 0.05). In mesangial cells under high glucose, Apelin overexpression significantly inhibited cell proliferation and fibrotic factor production (p < 0.05). Conversely, RUNX3 interference enhanced cell proliferation and the secretion of fibrotic factors. (p < 0.05). Remarkably, combining Apelin overexpression with RUNX3 interference reversed the proliferation and fibrosis induced by RUNX3 interference (p < 0.05). Mechanistic studies revealed RUNX3 binds to the Apelin promoter, with the 467-489 bp site1 as the primary binding region, and SIRT1 physically interacts with FOXO1 and FOXO3a in mesangial cells.

CONCLUSION

RUNX3 activated Apelin and regulated the SIRT1/FOXO signaling pathway, resulting in the suppressed cell proliferation and fibrosis in diabetic nephropathy. Apelin is a promising endogenous therapeutic target for anti-renal injury and anti-fibrosis in diabetic nephropathy. RUNX3 may serve as an endogenous intervention target for diseases related to Apelin deficiency.

Identification of Genes Associated with Decreasing Abundance of Monocytes in Long-Term Peritoneal Dialysis Patients

Purpose

Chronic kidney disease (CKD) will become an end-stage renal disease (ESRD) at stage 5. Peritoneal dialysis (PD) is required for renal replacement therapy. This study aims to identify monocytes-related genes in peritoneal cells from long-term PD (LPD) patients and short-term PD (SPD) patients.

Methods

Bulk RNA-seq data (GSE125498 dataset) and ScRNA-seq data (GSE130888) were downloaded to identify differentially expressed genes, monocytes-related genes, and monocytes marker genes in LPD patients. Immune infiltration was analyzed in the GSE125498 dataset. Core genes associated with monocytes changes were screened out, followed by functional analysis and expression validation using RT-PCR.

Results

Monocytes are the most abundant immune cell in PD. The number of monocytes was remarkably decreased in LPD compared with SPD. A total of 16 up-regulated core genes negatively correlated with the abundance of monocytes were obtained in LPD. The expression of 16 core genes was lower in monocyte clusters than that in other cell clusters. In addition, LCK, CD3G, CD3E, CD3D, and LAT were involved in the signaling pathways of Th1 and Th2 cell differentiation, T cell receptor signaling pathway, and Th17 cell differentiation. CD2 was involved in hematopoietic cell lineage signaling pathway.

Conclusion

Identification of monocytes related-genes and related signaling pathways could be helpful in understanding the molecular mechanism of monocytes changes during PD.

Molecular immune monitoring in kidney transplant rejection: a state-of-the-art review

Although current regimens of immunosuppressive drugs are effective in renal transplant recipients, long-term renal allograft outcomes remain suboptimal. For many years, the diagnosis of renal allograft rejection and of several causes of renal allograft dysfunction, such as chronic subclinical inflammation and infection, was mostly based on renal allograft biopsy, which is not only invasive but also possibly performed too late for proper management. In addition, certain allograft dysfunctions are difficult to differentiate from renal histology due to their similar pathogenesis and immune responses. As such, non-invasive assays and biomarkers may be more beneficial than conventional renal biopsy for enhancing graft survival and optimizing immunosuppressive drug regimens during long-term care. This paper discusses recent biomarker candidates, including donor-derived cell-free DNA, transcriptomics, microRNAs, exosomes (or other extracellular vesicles), urine chemokines, and nucleosomes, that show high potential for clinical use in determining the prognosis of long-term outcomes of kidney transplantation, along with their limitations.

Contemporary Biomarkers for Renal Transplantation: A Narrative Overview

Renal transplantation (RT) is the preferred treatment for end-stage renal disease. However, clinical challenges persist, i.e., early detection of graft dysfunction, timely identification of rejection episodes, personalization of immunosuppressive therapy, and prediction of long-term graft survival. Biomarkers have emerged as valuable tools to address these challenges and revolutionize RT patient care. Our review synthesizes the existing scientific literature to highlight promising biomarkers, their biological characteristics, and their potential roles in enhancing clinical decision-making and patient outcomes. Emerging non-invasive biomarkers seemingly provide valuable insights into the immunopathology of nephron injury and allograft rejection. Moreover, we analyzed biomarkers with intra-nephron specificities, i.e., glomerular vs. tubular (proximal vs. distal), which can localize an injury in different nephron areas. Additionally, this paper provides a comprehensive analysis of the potential clinical applications of biomarkers in the prediction, detection, differential diagnosis and assessment of post-RT non-surgical allograft complications. Lastly, we focus on the pursuit of immune tolerance biomarkers, which aims to reclassify transplant recipients based on immune risk thresholds, guide personalized immunosuppression strategies, and ultimately identify patients for whom immunosuppression may safely be reduced. Further research, validation, standardization, and prospective studies are necessary to fully harness the clinical utility of RT biomarkers and guide the development of targeted therapies.

Markers of Bronchiolitis Obliterans Syndrome after Lung Transplant: Between Old Knowledge and Future Perspective

Bronchiolitis obliterans syndrome (BOS) is the most common form of CLAD and is characterized by airflow limitation and an obstructive spirometric pattern without high-resolution computed tomography (HRCT) evidence of parenchymal opacities. Computed tomography and microCT analysis show abundant small airway obstruction, starting from the fifth generation of airway branching and affecting up to 40-70% of airways. The pathogenesis of BOS remains unclear. It is a multifactorial syndrome that leads to pathological tissue changes and clinical manifestations. Because BOS is associated with the worst long-term survival in LTx patients, many studies are focused on the early identification of BOS. Markers may be useful for diagnosis and for understanding the molecular and immunological mechanisms involved in the onset of BOS. Diagnostic and predictive markers of BOS have also been investigated in various biological materials, such as blood, BAL, lung tissue and extracellular vesicles. The aim of this review was to evaluate the scientific literature on markers of BOS after lung transplant. We performed a systematic review to find all available data on potential prognostic and diagnostic markers of BOS.

T Cells With Activated STAT4 Drive the High-Risk Rejection State to Renal Allograft Failure After Kidney Transplantation

In kidney transplantation, deteriorated progression of rejection is considered to be a leading course of postoperative mortality. However, the conventional histologic diagnosis is limited in reading the rejection status at the molecular level, thereby triggering mismatched pathogenesis with clinical phenotypes. Here, by applying uniform manifold approximation and projection and Leiden algorithms to 2,611 publicly available microarray datasets of renal transplantation, we uncovered six rejection states with corresponding signature genes and revealed a high-risk (HR) state that was essential in promoting allograft loss. By identifying cell populations from single-cell RNA sequencing data that were associated with the six rejection states, we identified a T-cell population to be the pathogenesis-triggering cells associated with the HR rejection state. Additionally, by constructing gene regulatory networks, we identified that activated STAT4, as a core transcription factor that was regulated by PTPN6 in T cells, was closely linked to poor allograft function and prognosis. Taken together, our study provides a novel strategy to help with the precise diagnosis of kidney allograft rejection progression, which is powerful in investigating the underlying molecular pathogenesis, and therefore, for further clinical intervention.

Can Gene Expression Analysis in Zero-Time Biopsies Predict Kidney Transplant Rejection?

Zero-time biopsies are taken to determine the quality of the donor organ at the time of transplantation. Histological analyses alone have so far not been able to identify parameters that allow the prediction of subsequent rejection episodes or graft survival. This study investigated whether gene expression analyses of zero-time biopsies might support this prediction. Using a well-characterized cohort of 26 zero-time biopsies from renal transplant patients that include 4 living donor (LD) and 22 deceased donor (DD) biopsies that later developed no rejection (Ctrl, n = 7), delayed graft function (DGF, n = 4), cellular (T-cell mediated rejection; TCMR, n = 8), or antibody-mediated rejection (ABMR, n = 7), we analyzed gene expression profiles for different types of subsequent renal transplant complication. To this end, RNA was isolated from formalin-fixed, paraffin-embedded (FFPE) sections and gene expression profiles were quantified. Results were correlated with transplant data and B-cell, and plasma cell infiltration was assessed by immunofluorescence microscopy. Both principal component analysis and clustering analysis of gene expression data revealed marked separation between LDs and DDs. Differential expression analysis identified 185 significant differentially expressed genes (adjusted p < 0.05). The expression of 68% of these genes significantly correlated with cold ischemia time (CIT). Furthermore, immunoglobulins were differentially expressed in zero-time biopsies from transplants later developing rejection (TCMR + ABMR) compared to non-rejected (Ctrl + DGF) transplants. In addition, immunoglobulin expression did not correlate with CIT but was increased in transplants with previous acute renal failure (ARF). In conclusion, gene expression profiles in zero-time biopsies derived from LDs are markedly different from those of DDs. Pre-transplant ARF increased immunoglobulin expression, which might be involved in triggering later rejection events. However, these findings must be confirmed in larger cohorts and the role of early immunoglobulin upregulation in zero-biopsies needs further clarification.

Tackling Chronic Kidney Transplant Rejection: Challenges and Promises

Despite advances in post-transplant management, the long-term survival rate of kidney grafts and patients has not improved as approximately forty percent of transplants fails within ten years after transplantation. Both immunologic and non-immunologic factors contribute to late allograft loss. Chronic kidney transplant rejection (CKTR) is often clinically silent yet progressive allogeneic immune process that leads to cumulative graft injury, deterioration of graft function. Chronic active T cell mediated rejection (TCMR) and chronic active antibody-mediated rejection (ABMR) are classified as two principal subtypes of CKTR. While significant improvements have been made towards a better understanding of cellular and molecular mechanisms and diagnostic classifications of CKTR, lack of early detection, differential diagnosis and effective therapies continue to pose major challenges for long-term management. Recent development of high throughput cellular and molecular biotechnologies has allowed rapid development of new biomarkers associated with chronic renal injury, which not only provide insight into pathogenesis of chronic rejection but also allow for early detection. In parallel, several novel therapeutic strategies have emerged which may hold great promise for improvement of long-term graft and patient survival. With a brief overview of current understanding of pathogenesis, standard diagnosis and challenges in the context of CKTR, this mini-review aims to provide updates and insights into the latest development of promising novel biomarkers for diagnosis and novel therapeutic interventions to prevent and treat CKTR.

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.

Molecular Diversity of Clinically Stable Human Kidney Allografts

IMPORTANCE

Clinical decision and immunosuppression dosing in kidney transplantation rely on transplant biopsy tissue histology even though histology has low specificity, sensitivity, and reproducibility for rejection diagnosis. The inclusion of stable allografts in mechanistic and clinical studies is vital to provide a normal, noninjured comparative group for all interrogative studies on understanding allograft injury.

OBJECTIVE

To refine the definition of a stable allograft as one that is clinically, histologically, and molecularly quiescent using publicly available transcriptomics data.

DESIGN, SETTING, AND PARTICIPANTS

In this prognostic study, the National Center for Biotechnology Information Gene Expression Omnibus was used to search for microarray gene expression data from kidney transplant tissues, resulting in 38 studies from January 1, 2017, to December 31, 2018. The diagnostic annotations included 510 acute rejection (AR) samples, 1154 histologically stable (hSTA) samples, and 609 normal samples. Raw fluorescence intensity data were downloaded and preprocessed followed by data set merging and batch correction.

MAIN OUTCOMES AND MEASURES

The primary measure was area under the receiver operating characteristics curve from a set of feature selected genes and cell types for distinguishing AR from normal kidney tissue.

RESULTS

Within the 28 data sets, the feature selection procedure identified a set of 6 genes (KLF4, CENPJ, KLF2, PPP1R15A, FOSB, TNFAIP3) (area under the curve [AUC], 0.98) and 5 immune cell types (CD4+ T-cell central memory [Tcm], CD4+ T-cell effector memory [Tem], CD8+ Tem, natural killer [NK] cells, and Type 1 T helper [TH1] cells) (AUC, 0.92) that were combined into 1 composite Instability Score (InstaScore) (AUC, 0.99). The InstaScore was applied to the hSTA samples: 626 of 1154 (54%) were found to be immune quiescent and redefined as histologically and molecularly stable (hSTA/mSTA); 528 of 1154 (46%) were found to have molecular evidence of rejection (hSTA/mAR) and should not have been classified as stable allografts. The validation on an independent cohort of 6 months of protocol biopsy samples in December 2019 showed that hSTA/mAR samples had a significant change in graft function (r = 0.52, P < .001) and graft loss at 5-year follow-up (r = 0.17). A drop by 10 mL/min/1.73m2 in estimated glomerular filtration rate was estimated as a threshold in allograft transitioning from hSTA/mSTA to hSTA/mAR.

CONCLUSIONS AND RELEVANCE

The results of this prognostic study suggest that the InstaScore could provide an important adjunct for comprehensive and highly quantitative phenotyping of protocol kidney transplant biopsy samples and could be integrated into clinical care for accurate estimation of subsequent patient clinical outcomes.

Avoidance of CNI and steroids using belatacept-Results of the Clinical Trials in Organ Transplantation 16 trial

Immunosuppression devoid of corticosteroids has been investigated to avoid long-term comorbidities. Likewise, alternatives to calcineurin inhibitors have been investigated as a strategy to improve long-term kidney function following transplanion. Costimulatory blockade strategies that include corticosteroids have recently shown promise, despite their higher rates of early acute rejection. We designed a randomized clinical trial utilizing depletional induction therapy to mitigate early rejection risk while limiting calcineurin inhibitors and corticosteroids. This trial, Clinical Trials in Organ Transplantation 16 (CTOT-16), sought to evaluate novel belatacept-based strategies employing tacrolimus and corticosteroid avoidance. Sixty-nine kidney transplant recipients were randomized from 4 US transplant centers comparing a control group of with rabbit antithymocyte globulin (rATG) induction, rapid steroid taper, and maintenance mycophenolate and tacrolimus, to 2 arms using maintenance belatacept. There were no graft losses but there were 2 deaths in the control group. However, the trial was halted early because of rejection in the belatacept treatment groups. Serious adverse events were similar across groups. Although rejection was not uniform in the belatacept maintenance therapy groups, the frequency of rejection limits the practical implementation of this strategy to avoid both calcineurin inhibitors and corticosteroids at this time.

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.

Advances in Detection of Kidney Transplant Injury

Early detection of graft injury after kidney transplantation is key to maintaining long-term good graft function. Graft injury could be due to a multitude of factors including ischaemia reperfusion injury, cell or antibody-mediated rejection, progressive interstitial fibrosis and tubular atrophy, infections and toxicity from the immunosuppressive drugs themselves. The current gold standard for assessing renal graft dysfunction is renal biopsy. However, biopsy is usually late when triggered by a change in serum creatinine and of limited utility in diagnosis of early injury when histological changes are equivocal. Therefore, there is a need for timely, objective and non-invasive diagnostic techniques with good early predictive value to determine graft injury and provide precision in titrating immunosuppression. We review potential novel plasma and urine biomarkers that offer sensitive new strategies for early detection and provide major insights into mechanisms of graft injury. This is a rapidly expanding field, but it is likely that a combination of biomarkers will be required to provide adequate sensitivity and specificity for detecting graft injury.

Bioinformatics analyses on the immune status of renal transplant patients, a systemic research of renal transplantation

BACKGROUND

Kidney transplantation is the most effective treatment for end-stage renal disease. Allograft rejections severely affect survivals of allograft kidneys and recipients.

METHODS

Using bioinformatics approaches, the present study was designed to investigate immune status in renal transplant recipients. Fifteen datasets from Gene Expression Omnibus (GEO) were collected and analysed. Analysis of gene enrichment and protein-protein interactions were also used.

RESULTS

There were 40 differentially expressed genes (DEGs) identified in chronic rejection group when compared with stable recipients, which were enriched in allograft rejection module. There were 135 DEGs identified in acute rejection patients, compared with stable recipients, in which most genes were enriched in allograft rejection and immune deficiency. There were 288 DEGs identified in stable recipients when compared to healthy subjects. Most genes were related to chemokine signalling pathway. In integrated comparisons, expressions of MHC molecules and immunoglobulins were increased in both acute and chronic rejection; expressions of LILRB and MAP 4 K1 were increased in acute rejection patients, but not in stable recipients. There were no overlapping DEGs in blood samples of transplant recipients.

CONCLUSION

By performing bioinformatics analysis on the immune status of kidney transplant patients, the present study reports several DEGs in the renal biopsy of transplant recipients, which are requested to be validated in clinical practice.

Peripheral blood transcriptome analysis and development of classification model for diagnosing antibody-mediated rejection vs accommodation in ABO-incompatible kidney transplant

The major obstacle to successful ABO blood group-incompatible kidney transplantation (ABOi KT) is antibody-mediated rejection (AMR). This study aimed to investigate transcriptional profiles through RNA sequencing and develop a minimally invasive diagnostic tool for discrimination between accommodation and early acute AMR in ABOi KT. Twenty-eight ABOi KT patients were selected: 18 with accommodation and 10 with acute AMR at the 10th day posttransplant protocol biopsy. Complete transcriptomes of their peripheral blood were analyzed by RNA sequencing. Candidate genes were selected by bioinformatics analysis, validated with quantitative polymerase chain reaction, and used to develop a classification model to diagnose accommodation. A total of 1385 genes were differentially expressed in accommodation compared with in AMR with P-adjusted < .05. Functional annotation and gene set enrichment analysis identified several immune-related and immunometabolic pathways. A 5-gene classification model including COX7A2L, CD69, CD14, CFD, and FOXJ3 was developed by logistic regression analysis. The model was further validated with an independent cohort and discriminated between accommodation and AMR with 92.7% sensitivity, 85.7% specificity, and 91.7% accuracy. Our study suggests that a classification model based on peripheral blood transcriptomics may allow minimally invasive diagnosis of acute AMR vs accommodation and subsequent patient-tailored immunosuppression in ABOi KT.

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.

A urinary Common Rejection Module (uCRM) score for non-invasive kidney transplant monitoring

A Common Rejection Module (CRM) consisting of 11 genes expressed in allograft biopsies was previously reported to serve as a biomarker for acute rejection (AR), correlate with the extent of graft injury, and predict future allograft damage. We investigated the use of this gene panel on the urine cell pellet of kidney transplant patients. Urinary cell sediments collected from patients with biopsy-confirmed acute rejection, borderline AR (bAR), BK virus nephropathy (BKVN), and stable kidney grafts with normal protocol biopsies (STA) were analyzed for expression of these 11 genes using quantitative polymerase chain reaction (qPCR). We assessed these 11 CRM genes for their abundance, autocorrelation, and individual expression levels. Expression of 10/11 genes were elevated in AR when compared to STA. Psmb9 and Cxcl10could classify AR versus STA as accurately as the 11-gene model (sensitivity = 93.6%, specificity = 97.6%). A uCRM score, based on the geometric mean of the expression levels, could distinguish AR from STA with high accuracy (AUC = 0.9886) and correlated specifically with histologic measures of tubulitis and interstitial inflammation rather than tubular atrophy, glomerulosclerosis, intimal proliferation, tubular vacuolization or acute glomerulitis. This urine gene expression-based score may enable the non-invasive and quantitative monitoring of AR.

Urinary CXCL10 Chemokine Is Associated With Alloimmune and Virus Compartment-Specific Renal Allograft Inflammation

BACKGROUND

Urinary CXC chemokine ligand 10 (CXCL10) is a promising biomarker for subclinical tubulointerstitial inflammation, but limited data exist regarding its correlation with (micro)vascular inflammation. Furthermore, no study has evaluated whether concomitant serum CXCL10 improves the discrimination for (micro)vascular inflammation.

METHODS

We investigated whether serum/urinary CXCL10 reflect subclinical inflammation within different renal compartments. Patients (n = 107) with 107 surveillance biopsies were classified as: normal histology (n = 47), normal histology with polyomavirus BK (BKV) or cytomegalovirus (CMV) viremia (n = 17), moderate-severe tubulointerstitial inflammation (tubulitis ≥2, n = 18), pure microvascular inflammation (n = 15), and isolated v lesions (n = 10). Serum and urinary CXCL10 Enzyme-linked Immunosorbent Assay was performed. An independent validation set was evaluated for urine CXCL10: normal histology (n = 14), normal histology with BKV or CMV viremia (n = 19), tubulitis ≥2 (n = 15), pure microvascular inflammation (n = 41), and isolated v lesions (n = 14).

RESULTS

Elevated urinary CXCL10 reflected inflammation within the tubulointerstitial (urinary CXCL10/creatinine, 1.23 ng/mmol vs 0.46 ng/mmol; P = 0.02; area under the curve, 0.69; P = 0.001) and microvascular compartments (urinary CXCL10/creatinine, 1.72 ng/mmol vs 0.46 ng/mmol; P = 0.03; area under the curve, 0.69; P = 0.02) compared to normal histology. Intriguingly, urinary CXCL10 was predominantly elevated with peritubular capillaritis, but not glomerulitis (P = 0.04). Furthermore, urinary CXCL10 corresponded with BKV, but not CMV viremia (P = 0.02). These urine CXCL10 findings were confirmed in the independent validation set. Finally, serum CXCL10 was elevated with BKV and CMV viremia but was not associated with microvascular or vascular inflammation (P ≥ 0.19).

CONCLUSIONS

Urinary CXCL10 reflects subclinical inflammation within the tubulointerstitial and peritubular capillary spaces, but not the vascular/systemic compartments; this was consistent with BKV (tubulointerstitial) and CMV viremia (systemic). Serum CXCL10 was not a useful marker for (micro)vascular inflammation.

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.

Mechanisms and biomarkers of immune quiescence in kidney transplantation

This review discusses the current understanding of biomarkers of immune quiescence based on reviews of published literature in kidney transplant operational tolerance and mechanistic studies based on a better characterization of the stable, well-functioning renal allograft.

Targeted Transcriptional Profiling of Kidney Transplant Biopsies

Introduction

Studies are needed to assess the quality of transcriptome analysis in paired human tissue samples preserved by different methods and different gene amplification platforms to enable data comparisons across experimenters.

Methods

RNA was extracted from kidney biopsies, either submerged in RNA-stabilizing solution (RSS) or stored in formalin-fixed, paraffin-embedded (FFPE) blocks. RNA quality and integrity were compared. Gene expression of the common rejection module and other immune cell genes were quantified for both tissue preservation methods in the same sample using conventional quantitative polymerase chain reaction (QPCR) by 2 different commercial platforms, (fluidigm [FD]) or barcoded-oligos (nanostring [NS]).

Results

RNA quality was inferior in FFPE tissues. Despite this, gene expression for 19 measured genes on the same sample, stored in FFPE or RSS, were strongly correlated on the FD (r = 0.81) or NS platforms (r = 0.82). For the same samples, interplatform gene expression correlations were excellent (r = 0.80) for RSS and moderate (r = 0.66) for FFPE. Significant differences in gene expression were confirmed on both platforms (FD: P = 1.1E-03; NS: P = 2.5E-04) for biopsy-confirmed acute rejection.

Conclusion

Our study provided supportive evidence that despite a low RNA quality of archival FFPE kidney transplantation tissue, small quantities of this tissue can be obtained from existing paraffin blocks to provide a viable and rich biospecimen source for focused gene expression assays. In addition, reliable and reproducible gene expression evaluation can be performed on these FFPE tissues using either a QPCR-based or a barcoded-oligo approach, which provides opportunities for collaborative analytics.

Polyomavirus BK Nephropathy-Associated Transcriptomic Signatures: A Critical Reevaluation

Background

Recent work using DNA microarrays has suggested that genes related to DNA replication, RNA polymerase assembly, and pathogen recognition receptors can serve as surrogate tissue biomarkers for polyomavirus BK nephropathy (BKPyVN).

Methods

We have examined this premise by looking for differential regulation of these genes using a different technology platform (RNA-seq) and an independent set 25 biopsies covering a wide spectrum of diagnoses.

Results

RNA-seq could discriminate T cell–mediated rejection from other common lesions seen in formalin fixed biopsy material. However, overlapping RNA-seq signatures were found among all disease processes investigated. Specifically, genes previously reported as being specific for the diagnosis of BKPyVN were found to be significantly upregulated in T cell–mediated rejection, inflamed areas of fibrosis/tubular atrophy, as well as acute tubular injury.

Conclusions

In conclusion, the search for virus specific molecular signatures is confounded by substantial overlap in pathogenetic mechanisms between BKPyVN and nonviral forms of allograft injury. Clinical heterogeneity, overlapping exposures, and different morphologic patterns and stage of disease are a source of substantial variability in “Omics” experiments. These variables should be better controlled in future biomarker studies on BKPyVN, T cell–mediated rejection, and other forms of allograft injury, before widespread implementation of these tests in the transplant clinic.

Biomarkers in renal transplantation: An updated review

Genomics, proteomics and molecular biology lead to tremendous advances in all fields of medical sciences. Among these the finding of biomarkers as non invasive indicators of biologic processes represents a useful tool in the field of transplantation. In addition to define the principal characteristics of the biomarkers, this review will examine the biomarker usefulness in the different clinical phases following renal transplantation. Biomarkers of ischemia-reperfusion injury and of delayed graft function are extremely important for an early diagnosis of these complications and for optimizing the treatment. Biomarkers predicting or diagnosing acute rejection either cell-mediated or antibody-mediated allow a risk stratification of the recipient, a prompt diagnosis in an early phase when the histology is still unremarkable. The kidney solid organ response test detects renal transplant recipients at high risk for acute rejection with a very high sensitivity and is also able to make diagnosis of subclinical acute rejection. Other biomarkers are able to detect chronic allograft dysfunction in an early phase and to differentiate the true chronic rejection from other forms of chronic allograft nephropathies no immune related. Finally biomarkers recently discovered identify patients tolerant or almost tolerant. This fact allows to safely reduce or withdrawn the immunosuppressive therapy.

Myocardial Gene Expression Profiling to Predict and Identify Cardiac Allograft Acute Cellular Rejection: The GET-Study

Aims

Serial invasive endomyocardial biopsies (EMB) remain the gold standard for acute cellular rejection (ACR) diagnosis. However histological grading has several limitations. We aimed to explore the value of myocardial Gene Expression Profiling (GEP) for diagnosing and identifying predictive biomarkers of ACR.

Methods

A case-control study nested within a retrospective heart transplant patients cohort included 126 patients with median (IQR) age 50 (41–57) years and 111 (88%) males. Among 1157 EMB performed, 467 were eligible (i.e, corresponding to either ISHLT grade 0 or ≥3A), among which 36 were selected for GEP according to the grading: 0 (C_ISHLT, n = 13); rejection ≥3A (R_ISHLT, n = 13); 0 one month before ACR (BR_ISHLT, n = 10).

Results

We found 294 genes differentially expressed between C_ISHLT and R_ISHLT, mainly involved in immune activation, and inflammation. Hierarchical clustering showed a clear segregation of C_ISHLT and R_ISHLT groups and heterogeneity of GEP within R_ISHLT. All EMB presented immune activation, but some R_ISHLT EMB were strongly subject to inflammation, whereas others, closer to C_ISHLT, were characterized by structural modifications with lower inflammation level. We identified 15 probes significantly different between BR_ISHLT and C_ISHLT, including the gene of the muscular protein TTN. This result suggests that structural alterations precede inflammation in ACR. Linear Discriminant Analysis based on these 15 probes was able to identify the histological status of every 36 samples.

Conclusion

Myocardial GEP is a helpful method to accurately diagnose ACR, and predicts rejection one month before its histological occurrence. These results should be considered in cardiac allograft recipients’ care.

Advances in diagnostics for transplant rejection

INTRODUCTION

Identification of allograft injury, including acute clinical and subclinical injury, is vital in increasing the longevity of the transplanted organ. Acute rejection, which occurs as a result of a variety of immune and non-immune factors including the infiltration of immune cells and antibodies to the donor specific epitopes, poses a significant risk to the organ. Recent years have marked an increase in the discovery of new genomic, transcriptomic, and proteomic biomarkers in molecular diagnostics, which offer better potential for personalized management of the transplanted organ by providing earlier detection of rejection episodes. Areas covered: This review was compiled from key word searches of full-text publications relevant to the field. Expert commentary: Many of the recent advancements in the molecular diagnostics of allograft injury show much promise, but before they can be fully realized further validation in larger sample sets must be conducted. Additionally, for better informed therapeutic decisions, more work must be completed to differentiate between different causes of injury. Moreover, the diagnostics field is looking at methodologies that allow for multiplexing, the ability to identify multiple targets simultaneously, in order to provide more robust biomarkers and better understanding.