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Despite improvement on outcomes post liver transplantation (LT), complications such as HCV recurrence (HCV-rec) and acute cellular rejection (ACR) continue to be a challenge for transplant physicians. Accurate diagnostic tools to better dissect between those complications post-LT are crucial for prompt and correct diagnosis and treatment. It is well known that the overlapping features of clinical and histo-pathological characteristics between these conditions turn difficult the appropriate differential diagnosis. Recently, new technological advances had supported the field of biomarker discovery in many diseases. Disease biomarkers capable to differentiate ACR versus HCV-rec post-LT is a long waited task in the transplant community. This editorial describes and discusses potential biomarkers of disease differentiation including recent reports in the field of genomics, proteomics, immunohistochemistry among other technologies.

Noninvasive, cost-effective biomarkers that allow accurate monitoring of graft function are needed in kidney transplantation. Since microRNAs (miRNAs) have emerged as promising disease biomarkers, we sought to establish an miRNA signature in urinary cell pellets comparing kidney transplant patients diagnosed with chronic allograft dysfunction (CAD) with interstitial fibrosis and tubular atrophy and those recipients with normal graft function. Overall, we evaluated 191 samples from 125 deceased donor primary kidney transplant recipients in the discovery, initial validation, and the longitudinal validation studies for noninvasive monitoring of graft function. Of 1733 mature miRNAs studied using microarrays, 22 were found to be differentially expressed between groups. Ontology and pathway analyses showed inflammation as the principal biological function associated with these miRNAs. Twelve selected miRNAs were longitudinally evaluated in urine samples of an independent set of 66 patients, at two time points after kidney transplant. A subset of these miRNAs was found to be differentially expressed between groups early after kidney transplant before histological allograft injury was evident. Thus, a panel of urine miRNAs was identified as potential biomarkers for monitoring graft function and anticipating progression to CAD in kidney transplant patients.

Background Ischemia-reperfusion (I/R) injury is a multifactorial phenomenon that occurs during the transplant event and frequently compromises early graft function after liver transplantation (LT). Current comprehension of molecular mechanisms and regulation processes of I/R injury lacks clarity. MicroRNA (miRNA) regulation results critical in several biological processes. Methods This study evaluated gene expression and miRNA expression profiles using microarrays in 34 graft biopsies collected at preimplantation (L1) and at 90 min postreperfusion (L2) from consecutives deceased-donor LT recipients. miRNA profiles were first analyzed. Data integration analysis (gene expression/miRNA expression) aimed to identify potential target genes for each identified miRNA from the L1/L2 differential gene expression profile. Results Pairwise comparison analyses identified 40 miRNAs and 3168 significantly differentially expressed genes at postreperfusion time compared with preimplantation time. Pathway analysis of miRNAs associated these profiles with antiapoptosis, inhibition of cellular proliferation, and proinflammatory processes. Target analysis identified an miRNA-associated molecular profile of 2172 genes involved in cellular growth and proliferation modulation by cell cycle regulation, cell death and survival, and proinflammatory and anti-inflammatory processes. miRNA-independent genes involved proinflammatory molecules. Conclusion We identified a miRNA profile involved in posttranscriptional regulatory mechanisms in I/R injury post-LT. A better understanding of these molecular processes involved in I/R may contribute to develop new strategies to minimize graft injury.

BACKGROUND Severe liver steatosis is a known risk factor for increased ischemia-reperfusion injury (IRI) and poor outcomes after liver transplantation (LT). This study aimed to identify steatosis-related molecular mechanisms associated with IRI exacerbation after LT. METHODS Paired graft biopsies (n = 60) were collected before implantation (L1) and 90 minutes after reperfusion (L2). The LT recipients (n = 30) were classified by graft macrosteatosis: without steatosis (WS) of 5% or less (n = 13) and with steatosis (S) of 25% or greater (n = 17). Plasma samples were collected at L1, L2, and 1 day after LT (postoperative [POD]1) for cytokines evaluation. Tissue RNA was isolated for gene expression microarrays. Probeset summaries were obtained using robust multiarray average algorithm. Pairwise comparisons were fit using 2-sample t test. P values 0.01 or less were significant (false discovery rate

Acute cellular rejection (ACR) and hepatitis C virus (HCV) recurrence (HCVrec) are common complications after liver transplantation (LT) in HCV patients, who share common clinical and histological features, making a differential diagnosis difficult. Fifty-three liver allograft samples from unique HCV LT recipients were studied using microarrays, including a training set (n = 32) and a validation set (n = 19). Two no-HCV-ACR samples from LT recipients were also included. Probe set intensity values were obtained using the robust multiarray average method (RMA) method. Analysis of variance identified statistically differentially expressed genes (P ≤ 0.005). The limma package was used to fit the mixed-effects models using a restricted maximum likelihood procedure. The last absolute shrinkage and selection operator (LASSO) model was fit with HCVrec versus ACR as the dependent variable predicted. N-fold cross-validation was performed to provide an unbiased estimate of generalization error. A total of 179 probe sets were differentially expressed among groups, with 71 exclusive genes between HCVrec and HCV-ACR. No differences were found within ACR group (HCV-ACR vs. no-HCV-ACR). Supervised clustering analysis displayed two clearly independent groups, and no-HCV-ACR clustered within HCV-ACR. HCVrec-related genes were associated with a cytotoxic T-cell profile, and HCV-ACR-related genes were associated with the inflammatory response. The best-fitting LASSO model classifier accuracy, including 15 genes, has an accuracy of 100% in the training set. N-fold cross-validation accuracy was 78.1%, and sensitivity, specificity and positive and negative predictive values were 50.0%, 90.9%, 71.4% and 80.0%, respectively. Arginase type II (ARG2), ethylmalonic encephalopathy 1 (ETHE1), transmembrane protein 176A (TMEM176A) and TMEM176B genes were significantly confirmed in the validation set. A molecular signature capable of distinguishing HCVrec and ACR in HCV LT recipients was identified and validated.

The molecular basis of calcineurin inhibitor toxicity (CNIT) in kidney transplantation (KT) and its contribution to chronic allograft dysfunction (CAD) with interstitial fibrosis (IF) and tubular atrophy (TA) were evaluated by: (1) identifying specific CNIT molecular pathways that associate with allograft injury (cross-sectional study) and (2) assessing the contribution of the identified CNIT signature in the progression to CAD with IF/TA (longitudinal study). Kidney biopsies from well-selected transplant recipients with histological diagnosis of CNIT (n = 14), acute rejection (n = 13) and CAD with IF/TA (n = 10) were evaluated. Normal allografts (n = 18) were used as controls. To test CNIT contribution to CAD progression, an independent set of biopsies (n = 122) from 61 KT patients collected at 3 and ~12 months post-KT (range = 9-18) were evaluated. Patients were classified based on 2-year post-KT graft function and histological findings as progressors (n = 30) or nonprogressors to CAD (n = 31). Molecular signatures characterizing CNIT samples were identified. Patients classified as progressors showed an overlap of 7% and 22% with the CNIT signature at 3 and at ~12 months post-KT, respectively, while the overlap was

UNLABELLED The increased disparity between organ supply and need has led to the use of extended criteria donors and donation after cardiac death donors with other comorbidities. METHODS We have examined the preimplantation transcriptome of 112 kidney transplant recipient samples from 100 deceased-donor kidneys by microarray profiling. Subject groups were segregated based on estimated glomerular filtration rate (eGFR) at 1 month after transplantation: the GFR-high group (n=74) included patients with eGFR 45 mL/min per 1.73 m(2), whereas the GFR-low group (n=35) included patients with eGFR 45 mL/min or less per 1.73 m(2). RESULTS Gene expression profiling identified higher expression of 160 probe sets (140 genes) in the GFR-low group, whereas expression of 37 probe sets (33 genes) was higher in the GFR-high group (P

Background The use of expanded criteria donor kidneys (ECD) had been associated with worse outcomes. Whole gene expression of pre-implantation allograft biopsies from deceased donor kidneys (DDKs) was evaluated to compare the effect of pulsatile pump preservation (PPP) vs. cold storage preservation (CSP) on standard and ECD kidneys. Methodology/Principal Findings 99 pre-implantation DDK biopsies were studied using gene expression with GeneChips. Kidneys transplant recipients were followed post transplantation for 35.8 months (range = 24–62). The PPP group included 60 biopsies (cold ischemia time (CIT) = 1,367+/−509 minutes) and the CSP group included 39 biopsies (CIT = 1,022+/−485 minutes) (P

Robust biomarkers are needed to identify donor kidneys with poor quality associated with inferior early and longer-term outcome. The occurrence of delayed graft function (DGF) is most often used as a clinical outcome marker to capture poor kidney quality. Gene expression profiles of 92 preimplantation biopsies were evaluated in relation to DGF and estimated glomerular filtration rate (eGFR) to identify preoperative gene transcript changes associated with short-term function. Patients were stratified into those who required dialysis during the first week (DGF group) versus those without (noDGF group) and subclassified according to 1-month eGFR of45 mL/min (eGFR(hi)) versus eGFR of ≤45 mL/min (eGFR(lo)). The groups and subgroups were compared in relation to clinical donor and recipient variables and transcriptome-associated biological pathways. A validation set was used to confirm target genes. Donor and recipient characteristics were similar between the DGF versus noDGF groups. A total of 206 probe sets were significant between groups (P0.01), but the gene functional analyses failed to identify any significantly affected pathways. However, the subclassification of the DGF and noDGF groups identified 283 probe sets to be significant among groups and associated with biological pathways. Kidneys that developed postoperative DGF and sustained an impaired 1-month function (DGF(lo) group) showed a transcriptome profile of significant immune activation already preimplant. In addition, these kidneys maintained a poorer transplant function throughout the first-year posttransplant. In conclusion, DGF is a poor marker for organ quality and transplant outcome. In contrast, preimplant gene expression profiles identify "poor quality" grafts and may eventually improve organ allocation.