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MicroRNAs (miRNAs) are post-transcriptional regulatory RNAs that can modulate cell signaling and play key roles in cell state transitions. Epstein-Barr virus (EBV) expresses >40 viral miRNAs that manipulate both viral and cellular gene expression patterns and contribute to reprogramming of the host environment during infection. Here, we identified a subset of EBV miRNAs that desensitize cells to B cell receptor (BCR) stimuli, and attenuate the downstream activation of NF-kappaB or AP1-dependent transcription. Bioinformatics and pathway analysis of Ago PAR-CLIP datasets identified multiple EBV miRNA targets related to BCR signal transduction, including GRB2, SOS1, MALT1, RAC1, and INPP5D, which we validated in reporter assays. BCR signaling is critical for B cell activation, proliferation, and differentiation, and for EBV, is linked to reactivation. In functional assays, we demonstrate that EBV miR-BHRF1-2-5p contributes to the growth of latently infected B cells through GRB2 regulation. We further determined that activities of EBV miR-BHRF1-2-5p, EBV miR-BART2-5p, and a cellular miRNA, miR-17-5p, directly regulate virus reactivation triggered by BCR engagement. Our findings provide mechanistic insight into some of the key miRNA interactions impacting the proliferation of latently infected B cells and importantly, governing the latent to lytic switch. [ABSTRACT FROM AUTHOR]

Background: Endometrial cancer is the most common malignancy of the female genital tract worldwide, and endometrial endometrioid adenocarcinoma (EEC) is the major histological type of endometrial cancer. There is a great need for better markers with high sensitivity and specificity to permit early diagnosis and proper management of EEC. The aim of our study is to identify a miRNA classifier within plasma as a noninvasive biomarker for EEC diagnosis. Methods: This study was a retrospective case-control analysis which contained two independent cohorts including 93 participants. First, we screened 375 miRNAs in 29 plasma samples. 9 of the miRNAs were selected to be evaluated their expression by quantitative reverse-transcriptase polymerase chain reaction. A stepwise logistic regression model was then used to establish a new classifier in the validation cohort. Area under the receiver operating characteristic curve was used to evaluate the diagnostic accuracy. Co-expression analysis was used to verify the independence of results. Results: miR-15b, -27a, and -223 were found to be differentially expressed in the EEC plasma between the two cohorts and had few connections with other miRNAs. The areas under the curve (AUC) were 0.768, 0.813, and 0.768 for miR-15b, -27a, and 223, respectively. miR-27a and CA125 can be combined as a potential non-invasive biomarker for detecting EEC, with the AUC of 0.894. Conclusion: Our study demonstrated three miRNAs, including miR-15b, -27a, and -233 have a good clinical value in EEC diagnosis. The classifier, including miR-27a and CA125, demonstrated a high accuracy in the diagnosis of EEC and might serve as a novel non-invasive biomarker in the future. [ABSTRACT FROM AUTHOR]

Background: Sensitive and specific detection of liver cirrhosis is an urgent need for optimal individualized management of disease activity. Substantial studies have identified circulation miRNAs as biomarkers for diverse diseases including chronic liver diseases. In this study, we investigated the plasma miRNA signature to serve as a potential diagnostic biomarker for silent liver cirrhosis. Methods: A genome-wide miRNA microarray was first performed in 80 plasma specimens. Six candidate miRNAs were selected and then trained in CHB-related cirrhosis and controls by qPCR. A classifier, miR-106b and miR-181b, was validated finally in two independent cohorts including CHB-related silent cirrhosis and controls, as well as non−CHB-related cirrhosis and controls as validation sets, respectively. Results: A profile of 2 miRNAs (miR-106b and miR-181b) was identified as liver cirrhosis biomarkers irrespective of etiology. The classifier constructed by the two miRNAs provided a high diagnostic accuracy for cirrhosis (AUC = 0.882 for CHB-related cirrhosis in the training set, 0.774 for CHB-related silent cirrhosis in one validation set, and 0.915 for non−CHB-related cirrhosis in another validation set). Conclusion: Our study demonstrated that the combined detection of miR-106b and miR-181b has a considerable clinical value to diagnose patients with liver cirrhosis, especially those at early stage. [ABSTRACT FROM AUTHOR]