Myeloid‐derived suppressor cells (MDSC) are negative regulators of the immune response and are in part responsible for the inhibition of the T cell–mediated immune responses. While MDSC have been demonstrated to participate in the induction of prolonged allograft survival in animal models of transplantation, little is known about their immune regulatory function in human transplant recipients. Here, we report that two subsets of human MDSC expressing CD11b+, CD33+ and HLA‐DR− develop in renal patients posttransplantation. We found that CD14+ expressing monocytic MDSC isolated from transplant recipients were highly efficient in suppressing the proliferation of CD4+ T cells in mixed leukocyte reactions. In addition, we observed that CD11b+CD33+HLA‐DR− MDSC are capable of expanding Treg in vitro, and their accumulation overtime after transplantation linearly correlated with an increase in Treg in vivo. This is the first study to link the presence of MDSC with the emergence of Treg in vivo in transplant recipients, and to define the subpopulation of MDSC derived from transplant recipients responsible for generation of Treg. Further studies are necessary to determine the alloimmune regulatory function of MDSC in human transplant recipients.

Summary 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.

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BackgroundIn 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.MethodsWe 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.ResultsStudy 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.ConclusionsOur 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.

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 family tyrosine kinase, hematopoietic cell kinase (), as upregulated in allografts in CAI. Querying the Kinase Inhibitor Resource database revealed that dasatinib, a Food and Drug Administration-approved drug, potently binds with high selectivity., overexpression activated the pathway, whereas knockdown inhibited it. Treatment of tubular cells with dasatinib reduced the expression of Dasatinib also reduced proliferation and 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 is a key mediator of renal fibrosis and dasatinib could be developed as an antifibrotic drug.

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Three-dimensional protein structure determination is a costly process due in part to the low success rate within groups of potential targets. Conventional validation methods eliminate the vast majority of proteins from further consideration through a time-consuming succession of screens for expression, solubility, purification, and folding. False negatives at each stage incur unwarranted reductions in the overall success rate. We developed a semi-automated protocol for isotopically-labeled protein production using the Maxwell-16, a commercially available bench top robot, that allows for single-step target screening by 2D NMR. In the span of a week, one person can express, purify, and screen 48 different 15 N-labeled proteins, accelerating the validation process by more than 10-fold. The yield from a single channel of the Maxwell-16 is sufficient for acquisition of a high-quality 2D 1 H-15 N-HSQC spectrum using a 3-mm sample cell and 5-mm cryogenic NMR probe. Maxwell-16 screening of a control group of proteins reproduced previous validation results from conventional small-scale expression screening and large-scale production approaches currently employed by our structural genomics pipeline. Analysis of 18 new protein constructs identified two potential structure targets that included the second PDZ domain of human Par-3. To further demonstrate the broad utility of this production strategy, we solved the PDZ2 NMR structure using [U-15 N, 13 C] protein prepared using the Maxwell-16. This novel semi-automated protein production protocol reduces the time and cost associated with NMR structure determination by eliminating unnecessary screening and scale-up steps.

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