Key driver genes as potential therapeutic targets in renal allograft rejection.

Acute rejection (AR) in renal transplantation is an established risk factor for reduced allograft survival. Molecules with regulatory control among immune pathways of AR that are inadequately suppressed, despite standard-of-care immunosuppression, could serve as important targets for therapeutic manipulation to prevent rejection. Here, an integrative, network-based computational strategy incorporating gene expression and genotype data of human renal allograft biopsy tissue was applied, to identify the master regulators - the key driver genes (KDGs) - within dysregulated AR pathways. A 982-meta-gene signature with differential expression in AR versus non-AR was identified from a meta-analysis of microarray data from 735 human kidney allograft biopsy samples across 7 data sets. Fourteen KDGs were derived from this signature. Interrogation of 2 publicly available databases identified compounds with predicted efficacy against individual KDGs or a key driver-based gene set, respectively, which could be repurposed for AR prevention. Minocycline, a tetracycline antibiotic, was chosen for experimental validation in a murine cardiac allograft model of AR. Minocycline attenuated the inflammatory profile of AR compared with controls and when coadministered with immunosuppression prolonged graft survival. This study demonstrates that a network-based strategy, using expression and genotype data to predict KDGs, assists target prioritization for therapeutics in renal allograft rejection.

A Peripheral Blood Gene Expression Signature to Diagnose Subclinical Acute Rejection.

BACKGROUND: In kidney transplant recipients, surveillance biopsies can reveal, despite stable graft function, histologic features of acute rejection and borderline changes that are associated with undesirable graft outcomes. Noninvasive biomarkers of subclinical acute rejection are needed to avoid the risks and costs associated with repeated biopsies. METHODS: We examined subclinical histologic and functional changes in kidney transplant recipients from the prospective Genomics of Chronic Allograft Rejection (GoCAR) study who underwent surveillance biopsies over 2 years, identifying those with subclinical or borderline acute cellular rejection (ACR) at 3 months (ACR-3) post-transplant. We performed RNA sequencing on whole blood collected from 88 individuals at the time of 3-month surveillance biopsy to identify transcripts associated with ACR-3, developed a novel sequencing-based targeted expression assay, and validated this gene signature in an independent cohort. RESULTS: Study participants with ACR-3 had significantly higher risk than those without ACR-3 of subsequent clinical acute rejection at 12 and 24 months, faster decline in graft function, and decreased graft survival in adjusted Cox analysis. We identified a 17-gene signature in peripheral blood that accurately diagnosed ACR-3, and validated it using microarray expression profiles of blood samples from 65 transplant recipients in the GoCAR cohort and three public microarray datasets. In an independent cohort of 110 transplant recipients, tests of the targeted expression assay on the basis of the 17-gene set showed that it identified individuals at higher risk of ongoing acute rejection and future graft loss. CONCLUSIONS: Our targeted expression assay enabled noninvasive diagnosis of subclinical acute rejection and inflammation in the graft and may represent a useful tool to risk-stratify kidney transplant recipients.

Pretransplant transcriptomic signature in peripheral blood predicts early acute rejection.

Commonly available clinical parameters fail to predict early acute cellular rejection (EAR, occurring within 6 months after transplant), a major risk factor for graft loss after kidney transplantation. We performed whole-blood RNA sequencing at the time of transplant in 235 kidney transplant recipients enrolled in a prospective cohort study (Genomics of Chronic Allograft Rejection [GoCAR]) and evaluated the relationship of pretransplant transcriptomic profiles with EAR. EAR was associated with downregulation of NK and CD8+ T cell gene signatures in pretransplant blood. We identified a 23-gene set that predicted EAR in the discovery (n = 81, and AUC = 0.80) and validation (n = 74, and AUC = 0.74) sets. Exclusion of recipients with 5 or 6 HLA donor mismatches increased the AUC to 0.89. The risk score derived from the gene set was also significantly associated with acute cellular rejection after 6 months, antibody-mediated rejection and/or de novo donor-specific antibodies, and graft loss in a cohort of 154 patients, combining the validation set and additional GoCAR patients with surveillance biopsies between 6 and 24 months (n = 80) posttransplant. This 23-gene set is a potentially important new tool for determination of the recipient's immunological risk before kidney transplantation, and facilitation of an individualized approach to immunosuppressive therapy.

The causes, significance and consequences of inflammatory fibrosis in kidney transplantation: The Banff i-IFTA lesion.

Inflammation within areas of interstitial fibrosis and tubular atrophy (i-IFTA) is associated with adverse outcomes in kidney transplantation. We evaluated i-IFTA in 429 indication- and 2052 protocol-driven biopsy samples from a longitudinal cohort of 362 kidney-pancreas recipients to determine its prevalence, time course, and relationships with T cell-mediated rejection (TCMR), immunosuppression, and outcome. Sequential histology demonstrated that i-IFTA was preceded by cellular interstitial inflammation and followed by IF/TA. The prevalence and intensity of i-IFTA increased with developing chronic fibrosis and correlated with inflammation, tubulitis, and immunosuppression era (P < .001). Tacrolimus era-based immunosuppression was associated with reduced histologic inflammation in unscarred and scarred i-IFTA compartments, ameliorated progression of IF, and increased conversion to inactive IF/TA (compared with cyclosporine era, P < .001). Prior acute (including borderline) TCMR and subclinical TCMR were followed by greater 1-year i-IFTA, remaining predictive by multivariate analysis and independent of humoral markers. One-year i-IFTA was associated with accelerated IF/TA, arterial fibrointimal hyperplasia, and chronic glomerulopathy and with reduced renal function (P < .001 versus no i-IFTA). In summary, i-IFTA is the histologic consequence of active T cell-mediated alloimmunity, representing the interface between inflammation and tubular injury with fibrotic healing. Uncontrolled i-IFTA is associated with adverse structural and functional outcomes.

Genomic Analysis of Kidney Allograft Injury Identifies Hematopoietic Cell Kinase as a Key Driver of Renal Fibrosis.

Renal fibrosis is the common pathway of progression for patients with CKD and chronic renal allograft injury (CAI), but the underlying mechanisms remain obscure. We performed a meta-analysis in human kidney biopsy specimens with CAI, incorporating data available publicly and from our Genomics of Chronic Renal Allograft Rejection study. We identified an Src family tyrosine kinase, hematopoietic cell kinase (Hck), as upregulated in allografts in CAI. Querying the Kinase Inhibitor Resource database revealed that dasatinib, a Food and Drug Administration-approved drug, potently binds Hck with high selectivity. In vitro, Hck overexpression activated the TGF-ß/Smad3 pathway, whereas HCK knockdown inhibited it. Treatment of tubular cells with dasatinib reduced the expression of Col1a1 Dasatinib also reduced proliferation and α-SMA expression in fibroblasts. In a murine model with unilateral ureteric obstruction, pretreatment with dasatinib significantly reduced the upregulation of profibrotic markers, phosphorylation of Smad3, and renal fibrosis observed in kidneys pretreated with vehicle alone. Dasatinib treatment also improved renal function, reduced albuminuria, and inhibited expression of profibrotic markers in animal models with lupus nephritis and folic acid nephropathy. These data suggest that Hck is a key mediator of renal fibrosis and dasatinib could be developed as an antifibrotic drug.

Biopsy transcriptome expression profiling to identify kidney transplants at risk of chronic injury: a multicentre, prospective study.

BACKGROUND: Chronic injury in kidney transplants remains a major cause of allograft loss. The aim of this study was to identify a gene set capable of predicting renal allografts at risk of progressive injury due to fibrosis. METHODS: This Genomics of Chronic Allograft Rejection (GoCAR) study is a prospective, multicentre study. We prospectively collected biopsies from renal allograft recipients (n=204) with stable renal function 3 months after transplantation. We used microarray analysis to investigate gene expression in 159 of these tissue samples. We aimed to identify genes that correlated with the Chronic Allograft Damage Index (CADI) score at 12 months, but not fibrosis at the time of the biopsy. We applied a penalised regression model in combination with permutation-based approach to derive an optimal gene set to predict allograft fibrosis. The GoCAR study is registered with ClinicalTrials.gov, number NCT00611702. FINDINGS: We identified a set of 13 genes that was independently predictive for the development of fibrosis at 1 year (ie, CADI-12 ≥2). The gene set had high predictive capacity (area under the curve [AUC] 0·967), which was superior to that of baseline clinical variables (AUC 0·706) and clinical and pathological variables (AUC 0·806). Furthermore routine pathological variables were unable to identify which histologically normal allografts would progress to fibrosis (AUC 0·754), whereas the predictive gene set accurately discriminated between transplants at high and low risk of progression (AUC 0·916). The 13 genes also accurately predicted early allograft loss (AUC 0·842 at 2 years and 0·844 at 3 years). We validated the predictive value of this gene set in an independent cohort from the GoCAR study (n=45, AUC 0·866) and two independent, publically available expression datasets (n=282, AUC 0·831 and n=24, AUC 0·972). INTERPRETATION: Our results suggest that this set of 13 genes could be used to identify kidney transplant recipients at risk of allograft loss before the development of irreversible damage, thus allowing therapy to be modified to prevent progression to fibrosis. FUNDING: National Institutes of Health.

The Use of Genomics and Pathway Analysis in Our Understanding and Prediction of Clinical Renal Transplant Injury.

The development and application of high-throughput molecular profiling have transformed the study of human diseases. The problem of handling large, complex data sets has been facilitated by advances in complex computational analysis. In this review, the recent literature regarding the application of transcriptional genomic information to renal transplantation, with specific reference to acute rejection, acute kidney injury in allografts, chronic allograft injury, and tolerance is discussed, as is the current published data regarding other "omics" strategies-proteomics, metabolomics, and the microRNA transcriptome. These data have shed new light on our understanding of the pathogenesis of specific disease conditions after renal transplantation, but their utility as a biomarker of disease has been hampered by study design and sample size. This review aims to highlight the opportunities and obstacles that exist with genomics and other related technologies to better understand and predict renal allograft outcome.