Despite the advances in immunosuppression, renal allograft attrition over time remains unabated due to chronic allograft dysfunction (CAD) with interstitial fibrosis (IF) and tubular atrophy (TA). We aimed to evaluate microRNA (miRNA) signatures in CAD with IF/TA and appraise correlation with paired urine samples and potential utility in prospective evaluation of graft function. MicroRNA signatures were established between CAD with IF/TA vs. normal allografts by microarray. Validation of the microarray results and prospective evaluation of urine samples was performed using RT-qPCR. Fifty-six miRNAs were identified in samples with CAD-IF/TA. Five miRNAs were selected for further validation based on: array fold change, p-value and in silico predicted mRNA targets. We confirmed the differential expression of these 5 miRNAs by RT-qPCR using an independent set of samples. Differential expression was detected for miR-142-3p, miR-204, miR-107, and miR-211 (P<0.001) and miR-32 (p<0.05). Furthermore, differential expression of miR-142-3p (p<0.01), miR-204 (p<0.01) and miR-211 (p<0.05) was also observed between patient groups in urine samples. A characteristic miRNA signature for IF/TA that correlates with paired urine samples was identified. These results support the potential use of miRNAs as non-invasive markers of IF/TA and for monitoring graft function.

In this study, we used the Affymetrix HG-U133A version 2.0 GeneChips to identify genes capable of distinguishing cirrhotic liver tissues with and without hepatocellular carcinoma by modeling the high-dimensional dataset using an L 1 penalized logistic regression model, with error estimated using N-fold cross-validation. Genes identified by gene expression microarray included those that have important links to cancer development and progression, including VAMP2, DPP4, CALR, CACNA1C, and EGR1. In addition, the selected molecular markers in the multigenic gene expression classifier were subsequently validated using reverse transcriptasereal time PCR, and an independently acquired gene expression microarray dataset was downloaded from Gene Expression Omnibus. The multigenetic classifier derived herein did similarly or better than standard abdominal ultrasonography and serum α-fetoprotein, which are currently used for hepatocellular carcinoma surveillance. Because early hepatocellular carcinoma diagnosis increases survival by increasing access to therapeutic options, these molecular markers may prove useful for early diagnosis of hepatocellular carcinoma, especially if prospectively validated and translated into gene products that can be reproducibly and reliably tested noninvasively. (Cancer Epidemiol

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 of >45 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 (P < 0.01), 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.

Introductiont The increased disparity between organ supply and need has led to the use of extended criteria donors (ECD) and donation-after-cardiac-death (DCD) donors with other comorbidities. Methods We have examined the pre-implantation transcriptome of 112 kidney transplant recipient (KTRs) samples from 100 deceased donor (DD) kidneys by microarray profiling. Subject groups were segregated based on estimated glomerular filtration rate at 1-month post-transplantation (post-KTx): the GFR-high group (N=74) included patients with eGFR >45 mL/min/1.73m2 while the GFR-low group (N=35) included patients with eGFR ≤45 mL/min/1.73m2. Results Gene expression profiling identified higher expression of 160 probesets (140 genes) in the GFR-low group while expression of 37 probesets (33 genes) was higher in the GFR-high group (p<0.01, FDR<0.2). Four genes (CCL5, CXCR4, ITGB2, and EGF) were selected based on fold change and p-value and further validated using an independent set of samples. A random forest analysis identified three of these genes (CCL5, CXCR4, and ITGB2) as important predictors of graft function post-transplant. Conclusions Inclusion of pre-transplant molecular gene expression profiles in donor quality assessment systems may provide the necessary information for better donor organ selection and function prediction. These biomarkers would further allow a more objective and complete assessment of procured renal allografts at pre transplantation time.

Supplementary Table 2 from Identifying Genes for Establishing a Multigenic Test for Hepatocellular Carcinoma Surveillance in Hepatitis C Virus-Positive Cirrhotic Patients