scholarly journals LINC00184 involved in the regulatory network of ANGPT2 via ceRNA mediated miR-145 inhibition.

2019 ◽  
Vol 5 (suppl) ◽  
pp. 17-17
Author(s):  
Haiyan Piao
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Regulatory Network ◽  
Poor Prognosis ◽  
Differentially Expressed ◽  
Competing Endogenous Rna ◽  
Carcinogenic Effect ◽  
Study Methods ◽  
Non Coding Rnas ◽  
Potential Biomarkers

17 Background: Abnormal gene expression is closely related to the development and poor prognosis of gastric cancer (GC). Since gene does not work alone, we are aimed to elucidate the potential networks between mRNA and non-coding RNAs (ncRNAs) in this study. Methods: Based on the TCGA database, we obtained the differentially expressed RNAs and constructed the competing endogenous RNA (ceRNA) regulatory network. Results: We found a regulatory network based on ANGPT2. We observed ANGPT2 is overexpressed in GC cells and tissues and associated with poor prognosis. ANGPT2 promotes proliferation, invasion, and EMT in GC cells, which could be abolished by miR-145. In addition, LINC00184 can be used as a ceRNA to inhibit the expression of miR-145, thus enhancing the carcinogenic effect of ANGPT2. Conclusions: Our results suggested that LINC00184/miR-145/ANGPT2 axis plays an important role in the occurrence and development of GC and may be potential biomarkers and targets for the treatment of GC.

scholarly journals Identification of Key Genes and MicroRNAs in Gastric Cancer via miRNA-mRNA Regulatory Network

2020 ◽  
Author(s):  
Chao Huang ◽  
Xiaojian Zhu ◽  
Jiefeng Zhao ◽  
Fanqin Bu ◽  
Jun Huang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Molecular Markers ◽  
Expression Profiling ◽  
Regulatory Network ◽  
Molecular Mechanisms ◽  
Critical Role ◽  
Differentially Expressed ◽  
Expression Levels ◽  
Receptor Interactions

Abstract Background Gastric cancer (GC) is a malignant tumor with high mortality. MicroRNAs (miRNAs) participate in various biological processes and disease pathogenesis by targeting messenger RNA (mRNA). The purpose of this study was to identify potential prognostic molecular markers of GC and to characterize the molecular mechanisms of GC. Methods A gene expression profiling dataset (GSE54129) and miRNA expression profiling dataset (GSE113486) were downloaded from the Gene Expression Omnibus (GEO) database. A miRNA-mRNA interaction network was established. Functional and pathway enrichment analyses were performed for differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) using FunRich, the clusterProfiler package, and DIANA-mirPath. Survival analysis of key molecular markers was performed using the online tool Kaplan-Meier Plotter and the database OncomiR. Finally, experiments were carried out to verify the expression levels and biological functions of a key gene. Results A total of 390 DEMs and 341 DEGs were identified. Ultimately, 45 genes and 31 miRNAs were selected to establish a miRNA-mRNA regulatory network. Four hub genes (ZFPM2, FUT9, NEUROD1 and LIPH) and six miRNAs (hsa-let-7d-5p, hsa-miR-23b-3p, hsa-miR-23a-3p, hsa-miR-133b, hsa-miR-130a-3p and hsa-miR-124-3p) were identified in the network. DEGs and DEMs were associated with ECM-receptor interactions and metabolic pathways. Two genes (ZFPM2 and LIPH) and two miRNAs (hsa-miR-23a-3p and hsa-miR-130a-3p) were observed to be related to the prognosis of GC. ZFPM2 was highly expressed in GC tissues and various GC cell lines and could promote the proliferation, invasion and migration of GC cells. Conclusion The expression levels of ZFPM2, LIPH, hsa-miR-23a-3p and hsa-miR-130a-3p were closely related to the prognosis of GC. ZFPM2 may serve as a potential molecular marker and therapeutic target for GC. ECM receptor interactions and metabolic abnormalities play a critical role in the GC progression.

scholarly journals Construction of asthma related competing endogenous RNA network revealed novel long non-coding RNAs and potential new drugs

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Yifang Liao ◽  
Ping Li ◽  
Yanxia Wang ◽  
Hong Chen ◽  
Shangwei Ning ◽  
...  
Keyword(s):  
Gene Expression ◽  
Drug Repositioning ◽  
New Drugs ◽  
Differentially Expressed ◽  
Interaction Data ◽  
Competing Endogenous Rna ◽  
Non Coding Rna ◽  
Competing Endogenous Rna Network ◽  
Non Coding Rnas ◽  
Long Non Coding Rna

Abstract Background Asthma is a heterogeneous disease characterized by chronic airway inflammation. Long non-coding RNA can act as competing endogenous RNA to mRNA, and play significant role in many diseases. However, there is little known about the profiles of long non-coding RNA and the long non-coding RNA related competing endogenous RNA network in asthma. In current study, we aimed to explore the long non-coding RNA-microRNA-mRNA competing endogenous RNA network in asthma and their potential implications for therapy and prognosis. Methods Asthma-related gene expression profiles were downloaded from the Gene Expression Omnibus database, re-annotated with these genes and identified for asthma-associated differentially expressed mRNAs and long non-coding RNAs. The long non-coding RNA-miRNA interaction data and mRNA-miRNA interaction data were downloaded using the starBase database to construct a long non-coding RNA-miRNA-mRNA global competing endogenous RNA network and extract asthma-related differentially expressed competing endogenous RNA network. Finally, functional enrichment analysis and drug repositioning of asthma-associated differentially expressed competing endogenous RNA networks were performed to further identify key long non-coding RNAs and potential therapeutics associated with asthma. Results This study constructed an asthma-associated competing endogenous RNA network, determined 5 key long non-coding RNAs (MALAT1, MIR17HG, CASC2, MAGI2-AS3, DAPK1-IT1) and identified 8 potential new drugs (Tamoxifen, Ruxolitinib, Tretinoin, Quercetin, Dasatinib, Levocarnitine, Niflumic Acid, Glyburide). Conclusions The results suggested that long non-coding RNA played an important role in asthma, and these novel long non-coding RNAs could be potential therapeutic target and prognostic biomarkers. At the same time, potential new drugs for asthma treatment have been discovered through drug repositioning techniques, providing a new direction for the treatment of asthma.

Identification of novel autoantibodies in ascites of relapsed paclitaxel-resistant gastric cancer with peritoneal metastasis using immunome protein microarrays and proteomics

2021 ◽  
pp. 1-10
Author(s):  
Zhongyin Yang ◽  
Chao Yan ◽  
Wentao Liu ◽  
Wei Xu ◽  
Chen Li ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Effective Treatment ◽  
Peritoneal Metastasis ◽  
Quantitative Proteomics ◽  
Poor Prognosis ◽  
Protein Microarrays ◽  
Tandem Mass ◽  
Tandem Mass Tag ◽  
Resistant Group ◽  
Potential Biomarkers

BACKGROUND: Gastric cancer (GC) patients with peritoneal metastasis usually have extremely poor prognosis. Intraperitoneal infusion of paclitaxel (PTX) provides an effective treatment, but relapse and PTX-resistance are unavoidable disadvantages, and it is difficult to monitor the occurrence of PTX-resistance. OBJECTIVE: The aim of this study was to explore novel autoantibodies in the ascites of individuals with relapsed PTX-resistant GC with peritoneal metastasis. METHODS: Ascites samples were collected before PTX infusion and after the relapse in 3 GC patients. To determine the expression of significantly changed proteins, we performed autoantibody profiling with immunome protein microarrays and tandem mass tag (TMT) quantitative proteomics, and then, the overlapping proteins were selected. RESULTS: Thirty-eight autoantibodies that were differentially expressed between the ascites in the untreated group and relapsed PTX-resistant group were identified. For confirmation of the results, TMT quantitative proteomics was performed, and 842 dysregulated proteins were identified. Four proteins, TPM3, EFHD2, KRT19 and vimentin, overlapped between these two assays. CONCLUSIONS: Our results first revealed that TPM3, EFHD2, KRT19 and vimentin were novel autoantibodies in the ascites of relapsed PTX-resistant GC patients. These autoantibodies may be used as potential biomarkers to monitor the occurrence of PTX-resistance.

Abstract 286: Long Noncoding RNAs Are Differentially Expressed in Heart Failure

2012 ◽  
Vol 111 (suppl_1) ◽  
Author(s):  
Emma L Robinson ◽  
Syed Haider ◽  
Hillary Hei ◽  
Richard T Lee ◽  
Roger S Foo
Keyword(s):  
Gene Expression ◽  
Heart Failure ◽  
Significant Proportion ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Control Of Gene Expression ◽  
Failing Heart ◽  
Novel Transcripts ◽  
Non Coding Rnas

Heart failure comprises of clinically distinct inciting causes but a consistent pattern of change in myocardial gene expression supports the hypothesis that unifying biochemical mechanisms underlie disease progression. The recent RNA-seq revolution has enabled whole transcriptome profiling, using deep-sequencing technologies. Up to 70% of the genome is now known to be transcribed into RNA, a significant proportion of which is long non-coding RNAs (lncRNAs), defined as polyribonucleotides of ≥200 nucleotides. This project aims to discover whether the myocardium expression of lncRNAs changes in the failing heart. Paired end RNA-seq from a 300-400bp library of ‘stretched’ mouse myocyte total RNA was carried out to generate 76-mer sequence reads. Mechanically stretching myocytes with equibiaxial stretch apparatus mimics pathological hypertrophy in the heart. Transcripts were assembled and aligned to reference genome mm9 (UCSC), abundance determined and differential expression of novel transcripts and alternative splice variants were compared with that of control (non-stretched) mouse myocytes. Five novel transcripts have been identified in our RNA-seq that are differentially expressed in stretched myocytes compared with non-stretched. These are regions of the genome that are currently unannotated and potentially are transcribed into non-coding RNAs. Roles of known lncRNAs include control of gene expression, either by direct interaction with complementary regions of the genome or association with chromatin remodelling complexes which act on the epigenome.Changes in expression of genes which contribute to the deterioration of the failing heart could be due to the actions of these novel lncRNAs, immediately suggesting a target for new pharmaceuticals. Changes in the expression of these novel transcripts will be validated in a larger sample size of stretched myocytes vs non-stretched myocytes as well as in the hearts of transverse aortic constriction (TAC) mice vs Sham (surgical procedure without the aortic banding). In vivo investigations will then be carried out, using siLNA antisense technology to silence novel lncRNAs in mice.

scholarly journals Expression of LOX Suggests Poor Prognosis in Gastric Cancer

2021 ◽  
Vol 8 ◽  
Author(s):  
Jinfeng Zhu ◽  
Chen Luo ◽  
Jiefeng Zhao ◽  
Xiaojian Zhu ◽  
Kang Lin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gastric Cancer ◽  
Logistic Regression ◽  
Regression Analysis ◽  
Poor Prognosis ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
High Expression ◽  
Expression Level ◽  
Cox Regression Analysis

Background: Lysyl oxidase (LOX) is a key enzyme for the cross-linking of collagen and elastin in the extracellular matrix. This study evaluated the prognostic role of LOX in gastric cancer (GC) by analyzing the data of The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) dataset.Methods: The Wilcoxon rank-sum test was used to calculate the expression difference of LOX gene in gastric cancer and normal tissues. Western blot and immunohistochemical staining were used to evaluate the expression level of LOX protein in gastric cancer. Kaplan-Meier analysis was used to calculate the survival difference between the high expression group and the low expression group in gastric cancer. The relationship between statistical clinicopathological characteristics and LOX gene expression was analyzed by Wilcoxon or Kruskal-Wallis test and logistic regression. Univariate and multivariate Cox regression analysis was used to find independent risk factors affecting the prognosis of GC patients. Gene set enrichment analysis (GSEA) was used to screen the possible mechanisms of LOX and GC. The CIBERSORT calculation method was used to evaluate the distribution of tumor-infiltrating immune cell (TIC) abundance.Results: LOX is highly expressed in gastric cancer tissues and is significantly related to poor overall survival. Wilcoxon or Kruskal-Wallis test and Logistic regression analysis showed, LOX overexpression is significantly correlated with T-stage progression in gastric cancer. Multivariate Cox regression analysis on TCGA and GEO data found that LOX (all p < 0.05) is an independent factor for poor GC prognosis. GSEA showed that high LOX expression is related to ECM receptor interaction, cancer, Hedgehog, TGF-beta, JAK-STAT, MAPK, Wnt, and mTOR signaling pathways. The expression level of LOX affects the immune activity of the tumor microenvironment in gastric cancer.Conclusion: High expression of LOX is a potential molecular indicator for poor prognosis of gastric cancer.

Integrated analysis profiles of long non–coding RNAs reveal potential biomarkers across brain regions in post–traumatic stress disorder

2020 ◽  
Author(s):  
Yaoyao Bian ◽  
Lili Yang ◽  
Zhongli Wang ◽  
Wen Li ◽  
Qing Wang ◽  
...  
Keyword(s):  
Post Traumatic Stress Disorder ◽  
Traumatic Stress ◽  
Stress Disorder ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Post Traumatic Stress ◽  
Post Traumatic ◽  
Non Coding Rnas ◽  
Potential Biomarkers

Abstract Background Post–traumatic stress disorder (PTSD) is characterized by impaired fear extinction, excessive anxiety and depression. However, underlying mechanisms, especially the function roles of long non–coding RNAs (lncRNAs) involved in PTSD is still unclear. We argued that the lncRNAs, co–expressed mRNAs, as well as the associated pathways, are altered and may thus serve as potential biomarkers and key pathways related to PTSD.Methods The gene expression profiles of GSE68077 was downloaded from the GEO database, and the differentially expressed lncRNAs and mRNAs were identified. Gene ontology (GO) and Kyto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis were performed. Subsequently, protein–protein interaction (PPI) network was analyzed, and module analysis of the differentially expressed mRNAs was performed with Cytoscape software. Finally, lncRNAs–mRNAs co–expression network was constructed and core pair lncRNAs involved in PTSD were mapped.Results A total of 45 differentially expressed lncRNAs and 726 differentially expressed mRNAs were obtained. Among of which, 17 lncRNAs and 86 mRNAs were inter–regulated, and most of the lncRNAs–mRNAs co–expression showed positive correlations. The lncRNAs–mRNAs co–expressed network suggested the potentially functional roles of lncRNAs, regulated mRNAs and related pathways in PTSD. By implication of the core pair network, lncRNA–NONMMUT010120.2 synergistically up–regulated Ppargc1a and down–regulated Cir1, Slc38a9, Atp6v0a2. Moreover, lncRNA–NONMMUT023440.2, NONMMUT034155.2, NONMMUT105407.1 and NONMMUT149972.1 were co–expressed with 10 co–expressed mRNAs, which indicated that lncRNAs involved in PTSD might work by regulating the co–expressed mRNAs.

scholarly journals Identification of Differentially Expressed Genes and miRNAs Associated with Esophageal Squamous Cell Carcinoma by Integrated Analysis of Microarray Data

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Lemeng Zhang ◽  
Jianhua Chen ◽  
Tianli Cheng ◽  
Hua Yang ◽  
Changqie Pan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Squamous Cell Carcinoma ◽  
Survival Analysis ◽  
Esophageal Squamous Cell Carcinoma ◽  
Cell Carcinoma ◽  
Differentially Expressed Genes ◽  
Microarray Data ◽  
Regulatory Network ◽  
Differentially Expressed ◽  
Pathway Enrichment

To identify candidate key genes and miRNAs associated with esophageal squamous cell carcinoma (ESCC) development and prognosis, the gene expression profiles and miRNA microarray data including GSE20347, GSE38129, GSE23400, and GSE55856 were downloaded from the Gene Expression Omnibus (GEO) database. Clinical and survival data were retrieved from The Cancer Genome Atlas (TCGA). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of differentially expressed genes (DEGs) was analyzed via DAVID, while the DEG-associated protein-protein interaction network (PPI) was constructed using the STRING database. Additionally, the miRNA target gene regulatory network and miRNA coregulatory network were constructed, using the Cytoscape software. Survival analysis and prognostic model construction were performed via the survival (version 2.42-6) and rbsurv R packages, respectively. The results showed a total of 2575, 2111, and 1205 DEGs, and 226 differentially expressed miRNAs (DEMs) were identified. Pathway enrichment analyses revealed that DEGs were mainly enriched in 36 pathways, such as the proteasome, p53, and beta-alanine metabolism pathways. Furthermore, 448 nodes and 1144 interactions were identified in the PPI network, with MYC having the highest random walk score. In addition, 7 DEMs in the microarray data, including miR-196a, miR-21, miR-205, miR-194, miR-103, miR-223, and miR-375, were found in the regulatory network. Moreover, several reported disease-related miRNAs, including miR-198a, miR-103, miR-223, miR-21, miR-194, and miR-375, were found to have common target genes with other DEMs. Survival analysis revealed that 85 DEMs were related to prognosis, among which hsa-miR-1248, hsa-miR-1291, hsa-miR-421, and hsa-miR-7-5p were used for a prognostic survival model. Taken together, this study revealed the important roles of DEGs and DEMs in ESCC development, as well as DEMs in the prognosis of ESCC. This will provide potential therapeutic targets and prognostic predictors for ESCC.

scholarly journals Identification of Potential Biomarkers and Biological Pathways in Juvenile Dermatomyositis Based on miRNA-mRNA Network

2019 ◽  
Vol 2019 ◽  
pp. 1-9 ◽  
Author(s):  
Cheng-Cheng Qiu ◽  
Qi-Sheng Su ◽  
Shang-Yong Zhu ◽  
Ruo-Chuan Liu
Keyword(s):  
Regulatory Network ◽  
Messenger Rna ◽  
Target Genes ◽  
Juvenile Dermatomyositis ◽  
Type I Diabetes ◽  
Differentially Expressed ◽  
Pathway Enrichment Analysis ◽  
Type I ◽  
Ppi Network ◽  
Potential Biomarkers

Objective. The aim of this study is to explore the potential pathogenesis of juvenile dermatomyositis by bioinformatics analysis of gene chips, which would screen the hub genes, identify potential biomarkers, and reveal the development mechanism of juvenile dermatomyositis. Material and Methods. We retrieved juvenile dermatomyositis’s original expression microarray data of message RNAs (mRNAs) and microRNAs (miRNAs) from NCBI’s Gene Expression Omnibus database (GEO, http://www.ncbi.nlm.nih.gov/geo/); through the R package of limma in Bioconductor, we can screen the differentially expressed miRNAs and mRNAs, and then we further analyzed the predicted target genes by the methods such as Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis and miRNA-mRNA regulatory network construction and protein-protein interaction (PPI) network using Cytoscape 3.6.1. Results. Compared with normal juvenile skin tissues, 6 upregulated microRNAs and 5 downregulated microRNAs were identified from 166 downregulated microRNAs and 58 upregulated microRNAs in juvenile dermatomyositis tissues. The enrichment pathways of differentially expressed microRNAs include cell adhesion molecules (CAMs), autoimmune thyroid disease, Type I diabetes mellitus, antigen and presentation, viral myocardium, graft-versus-host disease, and Kaposi sarcoma-associated herpes virus infection. By screening of microRNA-messenger RNA regulatory network and construction of PPI network map, three target miRNAs were identified, namely, miR-193b, miR-199b-5p, and miR-665. Conclusion. We identified mir-193b, mir-199b-5p, and mir-6653 target miRNAs by exploring the miRNA-mRNA regulation network mechanism related to the pathogenesis of juvenile dermatomyositis, which will be of great significance for further study on the pathogenesis and targeted therapy of juvenile dermatomyositis.

scholarly journals Construction and Comprehensive Analysis of Dysregulated Long Noncoding RNA-Associated Competing Endogenous RNA Network in Moyamoya Disease

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Xuefeng Gu ◽  
Dongyang Jiang ◽  
Yue Yang ◽  
Peng Zhang ◽  
Guoqing Wan ◽  
...  
Keyword(s):  
Moyamoya Disease ◽  
Cerebral Artery ◽  
Regulatory Network ◽  
Noncoding Rna ◽  
Expression Profiles ◽  
Differentially Expressed ◽  
Competing Endogenous Rna ◽  
Cerna Network ◽  
And Control ◽  
Control Samples

Background. Moyamoya disease (MMD) is a rare cerebrovascular disease characterized by chronic progressive stenosis or occlusion of the bilateral internal carotid artery (ICA), the anterior cerebral artery (ACA), and the middle cerebral artery (MCA). MMD is secondary to the formation of an abnormal vascular network at the base of the skull. However, the etiology and pathogenesis of MMD remain poorly understood. Methods. A competing endogenous RNA (ceRNA) network was constructed by analyzing sample-matched messenger RNA (mRNA), long non-coding RNA (lncRNA), and microRNA (miRNA) expression profiles from MMD patients and control samples. Then, a protein-protein interaction (PPI) network was constructed to identify crucial genes associated with MMD. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were employed with the DAVID database to investigate the underlying functions of differentially expressed mRNAs (DEmRNAs) involved in the ceRNA network. CMap was used to identify potential small drug molecules. Results. A total of 94 miRNAs, 3649 lncRNAs, and 2294 mRNAs were differentially expressed between MMD patients and control samples. A synergistic ceRNA lncRNA-miRNA-mRNA regulatory network was constructed. Core regulatory miRNAs (miR-107 and miR-423-5p) and key mRNAs (STAT5B, FOSL2, CEBPB, and CXCL16) involved in the ceRNA network were identified. GO and KEGG analyses indicated that the DEmRNAs were involved in the regulation of the immune system and inflammation in MMD. Finally, two potential small molecule drugs, CAY-10415 and indirubin, were identified by CMap as candidate drugs for treating MMD. Conclusions. The present study used bioinformatics analysis of candidate RNAs to identify a series of clearly altered miRNAs, lncRNAs, and mRNAs involved in MMD. Furthermore, a ceRNA lncRNA-miRNA-mRNA regulatory network was constructed, which provides insights into the novel molecular pathogenesis of MMD, thus giving promising clues for clinical therapy.

scholarly journals Study strategies for long non-coding RNAs and their roles in regulating gene expression

2015 ◽  
Vol 20 (2) ◽  
Author(s):  
Dan Qin ◽  
Cunshuan Xu
Keyword(s):  
Gene Expression ◽  
Regulatory Network ◽  
Experimental Methods ◽  
Study Strategies ◽  
Mechanisms Of Action ◽  
Cellular Processes ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale ◽  
Non Coding Rnas

AbstractLong non-coding RNAs (lncRNAs) have attracted considerable attention recently due to their involvement in numerous key cellular processes and in the development of various disorders. New high-throughput methods enable their study on a genome-wide scale. Numerous lncRNAs have been identified and characterized as important members of the biological regulatory network, with significant roles in regulating gene expression at the epigenetic, transcriptional and post-transcriptional levels. This paper summarizes the diverse mechanisms of action of these lncRNAs and looks at the study strategies in this field. A major challenge in future study is to establish more effective bioinformatics and experimental methods to explore the functions, detailed mechanisms of action and structures deciding the functional diversity of lncRNAs, since the vast majority remain unresolved.

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