scholarly journals Circulating miR-132-3p as a Candidate Diagnostic Biomarker for Malignant Mesothelioma

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Daniel G. Weber ◽  
Katarzyna Gawrych ◽  
Swaantje Casjens ◽  
Alexander Brik ◽  
Martin Lehnert ◽  
...  
Keyword(s):  
Malignant Mesothelioma ◽  
Smoking Status ◽  
Expression Profiles ◽  
Plasma Samples ◽  
Diagnostic Biomarker ◽  
Quantitative Real Time Pcr ◽  
Specific Expression ◽  
Circulating Micrornas ◽  
Diagnosis Of Cancer ◽  
Potential Biomarkers

The use of circulating microRNAs as biomarkers has opened new opportunities for diagnosis of cancer because microRNAs exhibit tumor-specific expression profiles. The aim of this study was the identification of circulating microRNAs in human plasma as potential biomarkers for the diagnosis of malignant mesothelioma. For discovery, TaqMan Low Density Array Human MicroRNA Cards were used to analyze 377 microRNAs in plasma samples from 21 mesothelioma patients and 21 asbestos-exposed controls. For verification, individual TaqMan microRNA assays were used for quantitative real-time PCR in plasma samples from 22 mesothelioma patients and 44 asbestos-exposed controls. The circulating miR-132-3p showed different expression levels between mesothelioma patients and asbestos-exposed controls. For discrimination, sensitivity of 86% and specificity of 61% were calculated. Circulating miR-132-3p in plasma was not affected by hemolysis and no impact of age or smoking status on miR-132-3p levels could be observed. For the combination of miR-132-3p with the previously described miR-126, sensitivity of 77% and specificity of 86% were calculated. The results of this study indicate that miR-132-3p might be a new promising diagnostic biomarker for malignant mesothelioma. It is indicated that the combination of miR-132-3p with other individual biomarkers improves the biomarker performance.

scholarly journals Combined detection of miR-21-5p, miR-30a-3p, miR-30a-5p, miR-155-5p, miR-216a and miR-217 for screening of early heart failure diseases

2020 ◽  
Vol 40 (3) ◽  
Author(s):  
Han Ding ◽  
Yin Wang ◽  
Longgang Hu ◽  
Sheng Xue ◽  
Yu Wang ◽  
...  
Keyword(s):  
Heart Failure ◽  
Expression Profiles ◽  
Healthy Controls ◽  
Diagnostic Biomarker ◽  
Specific Expression ◽  
Circulating Micrornas ◽  
Heart Failure Patients ◽  
Real Time Quantitative Pcr ◽  
Combined Detection ◽  
Normal Controls

Abstract The use of circulating microRNAs as biomarkers opens up new opportunities for the diagnosis of cardiovascular diseases because of their specific expression profiles. The aim of the present study was to identify circulating microRNAs in human plasma as potential biomarkers of heart failure and related diseases. We used real-time quantitative PCR to screen microRNA in plasma samples from 62 normal controls and 62 heart failure samples. We found that circulating miR-21-5p, miR-30a-3p, miR-30a-5p, miR-155-5p, miR-216a and miR-217 expressed differently between healthy controls and heart failure patients. Plasma levels of miR-21-5p, miR-30a-3p, miR-30a-5p, miR-155-5p, miR-216a and miR-217 were unaffected by hemolysis. Correlation analysis showed any two of these miRNAs possess a strong correlation, indicating a possibility of combined analysis. MiR-21-5p, miR-30a-3p, miR-30a-5p, miR-155-5p, miR-216a and miR-217 could be combined in two or three or more combinations. The results suggest that miR-21-5p, miR-30a-3p, miR-30a-5p, miR-155-5p, miR-216a and miR-217 may be a new diagnostic biomarker for heart failure and related diseases.

Plasma checkpoint protein 1 (Chk1) as a potential diagnostic biomarker for opisthorchiasis and cholangiocarcinoma

2021 ◽  
pp. 1-13
Author(s):  
Teva Phanaksri ◽  
Yodying Yingchutrakul ◽  
Sittiruk Roytrakul ◽  
Sattrachai Prasopdee ◽  
Anthicha Kunjantarachot ◽  
...  
Keyword(s):  
Diagnostic Methods ◽  
Protein Network ◽  
Enzyme Linked Immunosorbent Assay ◽  
Plasma Samples ◽  
Diagnostic Biomarker ◽  
Checkpoint Protein ◽  
Venn Diagrams ◽  
Network Prediction ◽  
Candidate Protein ◽  
Potential Biomarkers

BACKGROUND: Patients infected with a parasite often develop opisthorchiasis viverrini, which often progresses into cholangiocarcinoma (CCA) due to the asymptomatic nature of the infection. Currently, there are no effective diagnostic methods for opisthorchiasis or cholangiocarcinoma. OBJECTIVE: The aim of this study was to identify the host-responsive protein that can be developed as a diagnostic biomarker of opisthorchiasis and cholangiocarcinoma. METHODS: Plasma samples were collected from non-OVCCA, OV, and CCA subjects, and the proteomes were investigated by LC-MS/MS. Venn diagrams and protein network prediction by STITCH were used to identify the potential biomarkers. The level of candidate protein, the plasma checkpoint protein 1 (Chk1), was measured by indirect enzyme-linked immunosorbent assay (ELISA). RESULTS: Chk1 was present in the center of the protein network analysis in both the OV and CCA groups. In addition, the plasma Chk1 levels were significantly increased in both groups (P< 0.05). The sensitivity of the opisthorchiasis viverrini and cholangiocarcinoma was 59.38% and 65.62%, respectively, while the specificity of both was 85.71%. CONCLUSION: Chk1 was identified by differential plasma proteomes and was increased in O. viverrini-infected and cholangiocarcinoma-derived plasma samples. Higher levels of plasma Chk1 levels may serve as a potential diagnostic biomarker for opisthorchiasis and cholangiocarcinoma.

scholarly journals Profiles of Circulating miRNAs Following Metformin Treatment in Patients with Type 2 Diabetes

2018 ◽  
Vol 0 (0) ◽  
Author(s):  
İbrahim Halil Demirsoy ◽  
Duygu Yolal Ertural ◽  
Şenay Balci ◽  
Ümit Çınkır ◽  
Kerem Sezer ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Metabolic Pathways ◽  
Expression Profiles ◽  
Metformin Treatment ◽  
Plasma Samples ◽  
Circulating Mirnas ◽  
Quantitative Real Time Pcr ◽  
Increase Insulin Sensitivity ◽  
Reduce Blood Glucose

Summary Background: Metformin, a widely used biguanide class of anti-diabetic drug, has potential to increase insulin sensitivity and reduce blood glucose to treat type 2 diabetes (T2D). It has been reported that metformin has an activity on regulation of miRNAs by targeting several downstream genes in metabolic pathways. However, molecular mechanism underlying the process is still not fully known. In this study, it was aimed to identify differential expression profiles of plasma derived miRNAs following 3 months metformin treatment in patients with T2D. Methods: The plasma samples of 47 patients with T2D (received no anti-diabetic treatments) and plasma samples of same 47 patients received 3 months metformin treatment was recruited to the study. Total RNAs were isolated from plasma and reverse transcribed into cDNA. Profiles of differential expressions of miRNAs in plasma were assessed by using of micro-fluidic based multiplex quantitative real time -PCR (BioMarkTM 96.96 Dynamic Array). Results: Our results showed that expression profiles of 13 candidate miRNAs; hsa-let-7e-5p, hsa-let-7f-5p, hsa-miR- 21-5p, hsa-miR-24-3p, hsa-miR-26b-5p, hsa-miR-126-5p, hsa-miR-129-5p, hsa-miR-130b-3p, hsa-miR-146a-5p, hsamiR- 148a-3p, hsa-miR-152-3p, hsa-miR-194-5p, hsa-miR- 99a-5p were found significantly downregulated following metformin treatments in patients with T2D (p<0.05). Conclusions: In conclusion, our finding could provide development of better and more effective miRNAs based therapeutic strategies against T2D.

scholarly journals Profiles of Circulating miRNAs Following Metformin Treatment in Patients with Type 2 Diabetes

2018 ◽  
Vol 37 (4) ◽  
pp. 499-506 ◽  
Author(s):  
İbrahim Halil Demirsoy ◽  
Duygu Yolal Ertural ◽  
Şenay Balci ◽  
Ümit Çınkır ◽  
Kerem Sezer ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Metabolic Pathways ◽  
Expression Profiles ◽  
Metformin Treatment ◽  
Plasma Samples ◽  
Circulating Mirnas ◽  
Quantitative Real Time Pcr ◽  
Increase Insulin Sensitivity ◽  
Reduce Blood Glucose

Summary Background: Metformin, a widely used biguanide class of anti-diabetic drug, has potential to increase insulin sensitivity and reduce blood glucose to treat type 2 diabetes (T2D). It has been reported that metformin has an activity on regulation of miRNAs by targeting several downstream genes in metabolic pathways. However, molecular mechanism underlying the process is still not fully known. In this study, it was aimed to identify differential expression profiles of plasma derived miRNAs following 3 months metformin treatment in patients with T2D. Methods: The plasma samples of 47 patients with T2D (received no anti-diabetic treatments) and plasma samples of same 47 patients received 3 months metformin treatment was recruited to the study. Total RNAs were isolated from plasma and reverse transcribed into cDNA. Profiles of differential expressions of miRNAs in plasma were assessed by using of micro-fluidic based multiplex quantitative real time -PCR (BioMarkTM 96.96 Dynamic Array). Results: Our results showed that expression profiles of 13 candidate miRNAs; hsa-let-7e-5p, hsa-let-7f-5p, hsa-miR- 21-5p, hsa-miR-24-3p, hsa-miR-26b-5p, hsa-miR-126-5p, hsa-miR-129-5p, hsa-miR-130b-3p, hsa-miR-146a-5p, hsamiR- 148a-3p, hsa-miR-152-3p, hsa-miR-194-5p, hsa-miR- 99a-5p were found significantly downregulated following metformin treatments in patients with T2D (p<0.05). Conclusions: In conclusion, our finding could provide development of better and more effective miRNAs based therapeutic strategies against T2D.

Label-Free Mass Spectrometry-Based Plasma Proteomics Identified LY6D, DSC3, CDSN, SERPINB12, and SLURP1,as Novel Protein Biomarkers For Pulmonary Tuberculosis

2019 ◽  
Vol 17 ◽  
Author(s):  
Xiaoli Yu ◽  
Lu Zhang ◽  
Na Li ◽  
Peng Hu ◽  
Zhaoqin Zhu ◽  
...  
Keyword(s):  
Pulmonary Tuberculosis ◽  
Search Algorithm ◽  
Differentially Expressed ◽  
P Value ◽  
Plasma Samples ◽  
Label Free ◽  
Protein Biomarkers ◽  
Protein Database ◽  
Leave One Out ◽  
Potential Biomarkers

Aim: We aimed to identify new plasma biomarkers for the diagnosis of Pulmonary tuberculosis. Background: Tuberculosis is an ancient infectious disease that remains one of the major global health problems. Until now, effective, convenient, and affordable methods for diagnosis of Pulmonary tuberculosis were still lacked. Objective: This study focused on construct a label-free LC-MS/MS based comparative proteomics between six tuberculosis patients and six healthy controls to identify differentially expressed proteins (DEPs) in plasma. Method: To reduce the influences of high-abundant proteins, albumin and globulin were removed from plasma samples using affinity gels. Then DEPs from the plasma samples were identified using a label-free Quadrupole-Orbitrap LC-MS/MS system. The results were analyzed by the protein database search algorithm SEQUEST-HT to identify mass spectra to peptides. The predictive abilities of combinations of host markers were investigated by general discriminant analysis (GDA), with leave-one-out cross-validation. Results: A total of 572 proteins were identified and 549 proteins were quantified. The threshold for differentially expressed protein was set as adjusted p-value < 0.05 and fold change ≥1.5 or ≤0.6667, 32 DEPs were found. ClusterVis, TBtools, and STRING were used to find new potential biomarkers of PTB. Six proteins, LY6D, DSC3, CDSN, FABP5, SERPINB12, and SLURP1, which performed well in the LOOCV method validation, were termed as potential biomarkers. The percentage of cross-validated grouped cases correctly classified and original grouped cases correctly classified is greater than or equal to 91.7%. Conclusion: We successfully identified five candidate biomarkers for immunodiagnosis of PTB in plasma, LY6D, DSC3, CDSN, SERPINB12, and SLURP1. Our work supported this group of proteins as potential biomarkers for pulmonary tuberculosis, and be worthy of further validation.

scholarly journals Lantern: an integrative repository of functional annotations for lncRNAs in the human genome

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Swapna Vidhur Daulatabad ◽  
Rajneesh Srivastava ◽  
Sarath Chandra Janga
Keyword(s):  
Human Genome ◽  
Cellular Localization ◽  
Expression Profiles ◽  
Free Text ◽  
Dynamic Visualization ◽  
Specific Expression ◽  
Web Resource ◽  
Functional Dynamics ◽  
Non Coding Rnas ◽  
Retrieval Engine

Abstract Background With advancements in omics technologies, the range of biological processes where long non-coding RNAs (lncRNAs) are involved, is expanding extensively, thereby generating the need to develop lncRNA annotation resources. Although, there are a plethora of resources for annotating genes, despite the extensive corpus of lncRNA literature, the available resources with lncRNA ontology annotations are rare. Results We present a lncRNA annotation extractor and repository (Lantern), developed using PubMed’s abstract retrieval engine and NCBO’s recommender annotation system. Lantern’s annotations were benchmarked against lncRNAdb’s manually curated free text. Benchmarking analysis suggested that Lantern has a recall of 0.62 against lncRNAdb for 182 lncRNAs and precision of 0.8. Additionally, we also annotated lncRNAs with multiple omics annotations, including predicted cis-regulatory TFs, interactions with RBPs, tissue-specific expression profiles, protein co-expression networks, coding potential, sub-cellular localization, and SNPs for ~ 11,000 lncRNAs in the human genome, providing a one-stop dynamic visualization platform. Conclusions Lantern integrates a novel, accurate semi-automatic ontology annotation engine derived annotations combined with a variety of multi-omics annotations for lncRNAs, to provide a central web resource for dissecting the functional dynamics of long non-coding RNAs and to facilitate future hypothesis-driven experiments. The annotation pipeline and a web resource with current annotations for human lncRNAs are freely available on sysbio.lab.iupui.edu/lantern.

scholarly journals MiRNA Expression in Neuroendocrine Neoplasms of Frequent Localizations

2021 ◽  
Vol 7 (3) ◽  
pp. 38
Author(s):  
Alexandra Korotaeva ◽  
Danzan Mansorunov ◽  
Natalya Apanovich ◽  
Anna Kuzevanova ◽  
Alexander Karpukhin
Keyword(s):  
Mirna Expression ◽  
Malignant Tumors ◽  
Neuroendocrine Neoplasms ◽  
Specific Expression ◽  
Clinical Biomarkers ◽  
Different Types ◽  
Functional Features ◽  
First Time ◽  
Potential Biomarkers

Neuroendocrine neoplasms (NEN) are infrequent malignant tumors of a neuroendocrine nature that arise in various organs. They occur most frequently in the lungs, intestines, stomach and pancreas. Molecular diagnostics and prognosis of NEN development are highly relevant. The role of clinical biomarkers can be played by microRNAs (miRNAs). This work is devoted to the analysis of data on miRNA expression in NENs. For the first time, a search for specificity or a community of their functional characteristics in different types of NEN was carried out. Their properties as biomarkers were also analyzed. To date, more than 100 miRNAs have been characterized as differentially expressed and significant for the development of NEN tumors. Only about 10% of the studied miRNAs are expressed in several types of NEN; differential expression of the remaining 90% was found only in tumors of specific localizations. A significant number of miRNAs have been identified as potential biomarkers. However, only a few miRNAs have values that characterized their quality as markers. The analysis demonstrates the predominant specific expression of miRNA in each studied type of NEN. This indicates that miRNA’s functional features are predominantly influenced by the tissue in which they are formed.

scholarly journals Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Ping Yan ◽  
Zuotian Huang ◽  
Tong Mou ◽  
Yunhai Luo ◽  
Yanyao Liu ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Malignant Tumors ◽  
Expression Profiles ◽  
Clinical Information ◽  
Gene Expression Omnibus ◽  
The Cancer Genome Atlas ◽  
High Rate ◽  
Competing Endogenous Rna ◽  
Tissue Samples ◽  
Potential Biomarkers

Abstract Background Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers. Methods We first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively. Results With the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The ‘upregulated’ ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the ‘downregulated’ network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients. Conclusions In conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

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