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Background. Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide with high mortality, and there is an urgent need of new diagnosis measures. This study is aimed at investigating whether circulating exosomal miRNAs could act as biomarkers for the diagnosis of HCC. Methods. A four-stage strategy was adopted in this study. Candidate miRNA was selected by comprehensive analysis of four GEO datasets and TCGA database. The expression of candidate miRNAs in serum exosomal samples were examined through qRT-PCR. The diagnostic utility of the final validated miRNAs was examined by receiver operating characteristic (ROC) curve analysis. Results. After synthetical analysis of four GEO datasets, six miRNAs were selected as candidates due to their higher differential fold change. miR-101 and miR-125b were selected as candidate miRNAs to further investigate their potential as biomarkers for HCC due to their differential fold change and their influence on overall survival based on the TCGA database. As a result, miR-101 and miR-125b expressions were remarkably downregulated in both tissues and serum exosomes of patients with HCC. The area under the ROC curves (AUCs) of circulating exosomal miR-101 and miR-125b were 0.894 (95% CI, 0.793–0.994) and 0.812 (95% CI, 0.675–0.950), respectively. The combination of the two miRNAs presented higher diagnostic utility for HCC ( AUC = 0.953 ). Conclusion. The exosomal miR-101 and miR-125b panel in the serum may act as a noninvasive biomarker for HCC detection.

Abstract Background Triple negative breast cancer (TNBC) is the most aggressive subtype of breast cancer (BC). Treatment options for TNBC patients are limited and further insights into disease aetiology are needed to develop better therapeutic approaches. microRNAs’ ability to regulate multiple targets could hold a promising discovery approach to pathways relevant for TNBC aggressiveness. Thus, we address the role of miRNAs in controlling three signalling pathways relevant to the biology of TNBC, and their downstream phenotypes. Methods To identify miRNAs regulating WNT/β-catenin, c-Met, and integrin signalling pathways, we performed a high-throughput targeted proteomic approach, investigating the effect of 800 miRNAs on the expression of 62 proteins in the MDA-MB-231 TNBC cell line. We then developed a novel network analysis, Pathway Coregulatory (PC) score, to detect miRNAs regulating these three pathways. Using in vitro assays for cell growth, migration, apoptosis, and stem-cell content, we validated the function of candidate miRNAs. Bioinformatic analyses using BC patients’ datasets were employed to assess expression of miRNAs as well as their pathological relevance in TNBC patients. Results We identified six candidate miRNAs coordinately regulating the three signalling pathways. Quantifying cell growth of three TNBC cell lines upon miRNA gain-of-function experiments, we characterised miR-193b as a strong and consistent repressor of proliferation. Importantly, the effects of miR-193b were stronger than chemical inhibition of the individual pathways. We further demonstrated that miR-193b induced apoptosis, repressed migration, and regulated stem-cell markers in MDA-MB-231 cells. Furthermore, miR-193b expression was the lowest in patients classified as TNBC or Basal compared to other subtypes. Gene Set Enrichment Analysis showed that miR-193b expression was significantly associated with reduced activity of WNT/β-catenin and c-Met signalling pathways in TNBC patients. Conclusions Integrating miRNA-mediated effects and protein functions on networks, we show that miRNAs predominantly act in a coordinated fashion to activate or repress connected signalling pathways responsible for metastatic traits in TNBC. We further demonstrate that our top candidate, miR-193b, regulates these phenotypes to an extent stronger than individual pathway inhibition, thus emphasizing that its effect on TNBC aggressiveness is mediated by the coordinated repression of these functionally interconnected pathways.

Objective: This study aims to identify differentially expressed salivary miRNAs and validate the diagnostic potential for idiopathic Parkinson's disease (PD). Also, the disease specificity of candidate miRNAs was evaluated between PD, multiple system atrophy (MSA), and essential tremor (ET).Methods: We collected salivary samples from 50 PD, 20 ET, and 20 MSA patients, as well as 30 healthy controls (HCs). In the discovery phase, salivary miRNA microarray analysis was performed. In-silico analysis was used to investigate the target genes of differentially expressed miRNAs and clustered pathways. In validation phase, RT-qPCR was performed with samples from 30 PD patients and 30 HCs. Subsequently, we investigated candidate miRNAs in all recruited subjects. Receiver operating characteristic curve and Spearman correlation analysis was performed to determine diagnostic usefulness.Results: We identified 43 miRNAs that were differentially expressed between 5 PD patients and 5 HCs by miRNA microarray analysis. Computational analysis revealed the target genes were clustered in the pathways associated with ubiquitin protein ligase activity. The result of RT-qPCR showed that the miR-29a-3p and miR-29c-3p were found to be significantly downregulated (p = 0.004, p = 0.027), whereas the miR-6756-5p was significantly upregulated in 30 PD patients compared with 30 HCs (p = 0.032). The miR-29a-3p expression level in PD patients was significantly lower than ET patients (p = 0.035), but higher than MSA patients (p < 0.0001). The diagnostic efficacy reached a little higher when the combination of miR-29a-3p and miR-29c-3p.Conclusion: The miRNA combination of salivary miR-29a-3p and miR-29c-3p has potential to be a diagnostic biomarker for idiopathic PD.

Cyclical changes in hormone profiles across the menstrual cycle are associated with alterations in metabolic control. MicroRNAs (miRNA) contribute to regulating metabolic control, including adipose tissue metabolism. How fluctuations in hormonal profiles across the menstrual cycle affect adipose tissue miRNA expression remain unknown. Eleven healthy, regularly menstruating females underwent four sampling visits across their menstrual cycle. Subcutaneous abdominal adipose tissue and venous blood samples were collected each at sampling visit. Luteinizing hormone (LH) tests, calendar counting, and serum hormone concentrations were used to determine menstrual cycle phases: early-follicular (EF); late-follicular (LF); post-ovulatory (PO) and mid-luteal (ML). Serum follicle-stimulating hormone, LH, estrogen, progesterone and testosterone were determined using multiplex magnetic bead panels and enzyme-linked immunosorbent assays. Global adipose tissue miRNA expression levels were determined via microarray in a subset of participants (N=8) and 17 candidate miRNAs validated by RT-qPCR in the whole cohort (N=11). Global analysis of adipose tissue miRNA expression identified 33 miRNAs significantly altered across the menstrual cycle; however, no significant differences remained after correcting for multiple testing (p>0.05). RT-qPCR analysis of candidate miRNAs revealed miR-497-5p expression was significantly altered across the menstrual cycle (np2=0.18, p=0.03); however, post-hoc tests did not reveal any significant differences between menstrual cycle phases (p> 0.05). miR-30c-5p associated with testosterone concentration (R2=0.13, p=0.033). These pilot data indicate differences in adipose tissue miRNAs in healthy women across the menstrual cycle and a weak association with ovarian hormones. Further research in larger sample sizes is required to confirm regulation of miRNA expression across the menstrual cycle.

Abstract Background: Micro RNA (miRNA), a class of endogenous small RNAs with a length of about 20-24 nucleotides, have been played a variety of important regulatory roles in cells and have attracted the attention of researchers because involvement of initiation and progression of diverse kinds of human diseases, especially cancer. However, the regulatory role of miRNA in triple negative breast cancer (TNBC), its clinical significance and potential mechanism are still largely unknown.Methods: In this study, the differentially expressed miRNAs were analyzed using GEO2R from GSE57897 and GSE97811 of the Gene Expression Omnibus (GEO). Then, we performed the overall survival (OS) analysis of four candidate miRNAs. And the expressions of four candidate miRNAs in TNBC and non-TNBC tissues were tested by Quantitative real-time PCR. We determined the level and prognostic values of hsa-miR-3616-3p in TNBC patients. Then, TNBC cells migration and invasion were studied in vitro with hsa-miR-3616-3p by using wounding heal assays and transwell assays. Next, target genes and transcription factors of hsa-miR-3616-3p enrichment analysis, were performed by the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway.Results: Based on GSE57897 and GSE97811, we found 962 differentially expressed miRNAs including 943 up-regulated miRNAs and 19 down-regulated miRNAs. We selected top2 up-regulated miRNAs as hsa-miR-4428 and hsa-miR-575, and top2 down-regulated miRNAs as hsa-miR-3616-3p and hsa-miR-3909, and then we found that low expression of 4 candidated miRNAs had a worse prognosis in TNBC subtype. Next, we verified that the expression of hsa-miR-3616-3p was the most downregulated in TNBC tissues compared with matched surrounding tissues by qRT-PCR. Moerover, our results showed that overexpression of hsa-miR-3616-3p inhibited TNBC cells migration, and invasion in vitro.Conclusions: Our study might reveal important roles of hsa-miR-3616-3p plays in TNBC migration and invasion.

Abstract Encapsulating peritoneal sclerosis (EPS) is a catastrophic complication of chronic peritoneal dialysis (PD). Late diagnosis is associated with high mortality. With the advancement of new diagnostic technologies, such as microRNA (miRNA), we attempted to develop a noninvasive test to assist in the diagnosis of EPS. The eight-hour PD effluents were collected from 71 non-EPS and 56 EPS patients. The screening set included 28 samples (20 of non-EPS vs. 8 of EPS). After analyzing the ratio values of two miRNA expression levels from the high-throughput real-time PCR-array of 377 miRNAs, eight candidate miRNAs were selected. The prediction model was conducted using 127 samples (71 of non-EPS vs 56 of EPS) to produce an area under the curve (AUC) value of the miRNA classifier. Candidate miRNAs were also verified by single real-time PCR. The ratios of the five miRNAs with the top five ROC values were selected to calculate the combined AUC by multiple logistic regression. The AUC value to detect EPS with the five miRNA ratios was 0.8929 with an accuracy of 78.7%. The accuracy of the EPS diagnosis was further optimized to 94.1% after considering clinical characteristics (AUC value 0.9931). A signature-based model of clinical characteristics and miRNA expression in PD effluents can efficiently assist in the diagnosis of EPS, thus preventing the catastrophic prognosis.

Abstract Background: Encapsulating peritoneal sclerosis (EPS) is a catastrophic complication of chronic peritoneal dialysis (PD). Late diagnosis is associated with high mortality. With the advancement of new diagnostic technologies, such as microRNA (miRNA), we attempted to develop a noninvasive test to assist in the diagnosis of EPS. Methods: MiRNA expression profiles of PD effluents from patients with or without EPS were examined by a high-throughput real-time PCR array to first screen candidate miRNAs. Candidate miRNAs were verified by single real-time PCR. The model for EPS prediction was evaluated by multiple logistic regression. Results: We collected eight-hour PD effluents from 71 non-EPS and 56 EPS patients. The screening set included 28 samples (20 of non-EPS vs. 8 of EPS). After analyzing the ratio values of two miRNA expression levels from the PCR-array of 377 miRNAs, eight candidate miRNAs were selected. The prediction model was conducted using 127 samples (71 of non-EPS vs 56 of EPS) to produce an area under the curve (AUC) value of the miRNA classifier. The ratios of the five miRNAs with the top five ROC values were selected to calculate the combined AUC by logistic regression. The AUC value to detect EPS with the five miRNA ratios was 0.8929 with an accuracy of 78.7%. The accuracy of the EPS diagnosis was further improved to 94.1% after considering clinical characteristics (AUC value 0.9931). Conclusions: A signature-based model of clinical characteristics and miRNA expression in PD effluents can efficiently assist in the diagnosis of EPS, thus preventing the catastrophic prognosis.

Numerous experiments have proved that microRNAs (miRNAs) could be used as diagnostic biomarkers for many complex diseases. Thus, it is conceivable that predicting the unobserved associations between miRNAs and diseases is extremely significant for the medical field. Here, based on heterogeneous networks built on the information of known miRNA–disease associations, miRNA function similarity, disease semantic similarity, and Gaussian interaction profile kernel similarity for miRNAs and diseases, we developed a computing model of biased random walk with restart on multilayer heterogeneous networks for miRNA–disease association prediction (BRWRMHMDA) through enforcing degree-based biased random walk with restart (BRWR). Assessment results reflected that an AUC of 0.8310 was gained in local leave-one-out cross-validation (LOOCV), which proved the calculation algorithm’s good performance. Besides, we carried out BRWRMHMDA to prioritize candidate miRNAs for esophageal neoplasms based on HMDD v2.0. We further prioritize candidate miRNAs for breast neoplasms based on HMDD v1.0. The local LOOCV results and performance analysis of the case study all showed that the proposed model has good and stable performance.

Background: Amnestic mild cognitive impairment (aMCI) is a prodromal stage of Alzheimer’s disease (AD) involving imbalanced beta-site amyloid precursor protein cleaving enzyme 1 (BACE1). MicroRNAs (miRNAs) are associated with AD. Objective: This study aimed to investigated whether plasma miRNAs can predict prodromal AD or are associated with AD pathology. Methods: Participants in the discovery set (n = 10), analysis set (n = 30), and validation set (n = 80) were screened from the China Longitudinal Aging Study. RNA was extracted from the participants’ plasma. Microarray sequencing provided miRNA profiles and differentially expressed miRNAs (DEmiRNAs) in the discovery set included patients with 18F-Flutemetamol positron emission tomography scan-confirmed aMCI. Potential biomarkers were screened in the analysis set. The predict capability of candidate miRNAs was assessed in the validation set. Candidate miRNAs modulation of BACE1 expression was explored in rat and human hippocampal neurons in vitro. Results: We verified 46 significant DEmiRNAs between the aMCI and NC groups (p <  0.05), among which 33 were downregulated. In the analysis set, miR-1185-2-3p, miR-1909-3p, miR-22-5p, and miR-134-3p levels decreased significantly in the aMCI group. These miRNAs and previously identified miR-107 were selected as potential biomarkers. A prediction model comprising these five miRNAs showed outstanding accuracy (81.25%) to discriminate aMCI at cut-off value of 0.174. Except for miR-134-3p, the other four miRNAs significantly suppressed Bace1 expression in rat hippocampal neurons in vitro. BACE1 modulation of miR-1185-2-3p, miR-1909-3p, and miR-134-3p was confirmed in human hippocampal neurons in vitro. Conclusion: A predictive model consisting of five BACE1-related plasma miRNAs could be a novel biomarker for aMCI.

Abstract BackgroundEarly detection of hepatocellular carcinoma (HCC) will reduce morbidity and mortality rates of this poorly diagnosed widely-spread disease. Dysregulation in microRNA (miRNAs) expression is associated with HCC progression. MethodsThe objective is to identify a panel of differentially expressed miRNAs (DE-miRNAs) to enhance HCC early prediction in hepatitis C virus (HCV) infected patients. Candidate miRNAs were selected using bioinformatic analysis of microarray and RNA-sequencing datasets, resulting in nine DE- miRNAs (miR-142, miR-150, miR-183, miR-199a, miR-215, miR-217, miR-224, miR-424 and miR-3607). Their expressions were validated in the serum of 44 healthy individuals, 62 non-cirrhotic HCV patients, 67 cirrhotic-HCV and 72 HCV-associated HCC patients using real time PCR (qPCR).ResultsThere was a significant increase in serum concentrations of the nine-candidate miRNAs in HCC and HCV patients relative to healthy individuals. MiR-424, miR-199a, miR-142, and miR-224 expressions were significantly altered in HCC compared to non-cirrhotic patients. While miR-199a and miR-183 showed differential expression in cirrhotic relative to non-cirrhotic patients. A panel of 5 miRNAs improved sensitivity and specificity of HCC detection to 100% and 95.12% relative to healthy controls. Distinguishing HCC from HCV-treated patients was achieved by 70.8% sensitivity and 61.9% specificity using the combined panel, compared to alpha-fetoprotein (51.4% sensitivity and 60.67% specificity).ConclusionMiR-142, miR-183, miR-199a, miR-224 and miR-424 novel panel could serve as non-invasive biomarker for HCC early prediction in chronic HCV patients.