scholarly journals Differentially Expressed Functional LncRNAs in Human Subjects With Metabolic Syndrome Reflect a Competing Endogenous RNA Network in Circulating Extracellular Vesicles

2021 ◽  
Vol 8 ◽  
Author(s):  
Yongxin Li ◽  
Yu Meng ◽  
Yuanhang Liu ◽  
Andre J. van Wijnen ◽  
Alfonso Eirin ◽  
...  
Keyword(s):  
Metabolic Syndrome ◽  
Extracellular Vesicles ◽  
Disease Risk ◽  
Human Subjects ◽  
Inflammatory Marker ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cerna Network

Metabolic syndrome (MetS), a collective cluster of disease risk factors that include dyslipidemia, obesity, inflammation, hypertension, and insulin resistance, affects numerous people worldwide. Accumulating studies have shown that long non-coding RNAs (lncRNAs) serve as competing endogenous RNAs (ceRNAs) to play essential roles in regulating gene expression in various diseases. To explore the role of lncRNAs as ceRNAs in MetS, we examined a MetS-associated network in circulating extracellular vesicles (EVs) collected from the systemic blood of MetS and control patients (n = 5 each). In total, 191 differentially expressed lncRNAs, 1,389 mRNAs, and 138 miRNAs were selected for further analysis. Biological processes and pathway functional enrichment analysis were performed based on the Database for Annotation, Visualization, and Integrated Discovery (DAVID). The lncRNA/mRNA/miRNA ceRNA network was constructed by Cytoscape v3.8 based on the DE-RNAs and included 13 lncRNAs, 8 miRNAs, and 64 mRNAs. MetS patients showed elevated body weight, glucose, blood pressure, insulin, liver injury, and inflammatory marker levels. We found that lncRNAs reflect a ceRNA network that may regulate central cellular processes and complications of MetS, including cancer. These findings suggest that MetS alters the interactions among the ceRNA network components in circulating EVs and that this cargo of circulating EVs may have potential translational ramifications for MetS.

scholarly journals Construction of ceRNA Coexpression Network and Screening of Molecular Targets in Colorectal Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Zhao Hui ◽  
Wang Zhanwei ◽  
Yang Xi ◽  
Liu Jin ◽  
Zhuang Jing ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Protein Interactions ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Normal Tissues ◽  
Cerna Network ◽  
Cancer Tissues

Objective. To screen some RNAs that correlated with colorectal cancer (CRC). Methods. Differentially expressed miRNAs, lncRNAs, and mRNAs between cancer tissues and normal tissues in CRC were identified using data from the Gene Expression Omnibus (GEO) database. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interactions (PPIs) were performed to do the functional enrichment analysis. And a lncRNA-miRNA-mRNA network was constructed which correlated with CRC. RNAs in this network were subjected to analyze the relationship with the patient prognosis. Results. A total of 688, 241, and 103 differentially expressed genes (diff-mRNA), diff-lncRNA, and diff-miRNA were obtained between cancer tissues and normal tissues. A total of 315 edges were obtained in the ceRNA network. lncRNA RP11-108K3.2 and mRNA ONECUT2 correlated with prognosis. Conclusion. The identified RNAs and constructed ceRNA network could provide great sources for the researches of therapy of the CRC. And the lncRNA RP11-108K3.2 and mRNA ONECUT2 may serve as a novel prognostic predictor of CRC.

scholarly journals Competitive Endogenous RNA (ceRNA) Regulation Network of lncRNA–miRNA–mRNA in wilms tumor

2019 ◽  
Author(s):  
fucai tang ◽  
zechao Lu ◽  
jiamin wang ◽  
zhibiao Li ◽  
weijia Wu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Regulatory Network ◽  
Wilms Tumor ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Survival Prognosis ◽  
Cerna Network ◽  
Competitive Endogenous Rna

Abstract Background Competitive endogenous RNA (ceRNA) have revealed a new mechanism of interaction between RNAs. However, such comprehension of the ceRNA regulatory network in wilms tumor remains limited. Methods Raw RNA sequencing profiles regarding mRNAs, miRNAs and lncRNAs on wilms tumor samples and normal samples were obtained from Therapeutically Applicable Research to Generate Effective Treatment (TARGET). EdgeR package was applied to identify differentially expressed lncRNAs, miRNAs and mRNAs. Functional enrichment analysis were conducted via DAVID database and the ClusterProfile R package. The lncRNA–miRNA–mRNA interaction ceRNA network was established in Cytoscape according to the identified lncRNAs–miRNAs and miRNAs–mRNAs interactions. Subsequently, correlation between ceRNA network and overall survival prognosis were analyzed. Results A total of 2,037 lncRNAs, 154 miRNAs and 3,609 mRNAs were identified as differentially expressed RNAs in wilms tumor. 205 lncRNAs, 26 miRNAs and 143 mRNAs were included in ceRNA regulatory network. Analysis results showed that 14 out of the 205 lncRNAs, 1 out of 26 miRNAs and 8 out of 143 mRNAs were associated with overall survival in wilms tumor patients (P < 0.05). Conclusions CeRNA networks played an important role in wilms tumor. This might provide effective bioinformatics basis and novel insights for further understanding of the mechanisms underlying wilms tumor.

scholarly journals Integrated analysis of lncRNA-miRNA-mRNA ceRNA network in human aortic dissection

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Hao Zhang ◽  
Ce Bian ◽  
Simei Tu ◽  
Fanxing Yin ◽  
Panpan Guo ◽  
...  
Keyword(s):  
Aortic Dissection ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Down Regulation ◽  
Tissue Samples ◽  
Cerna Network

Abstract Background Many studies on long chain non-coding RNAs (lncRNAs) are published in recent years. But the roles of lncRNAs in aortic dissection (AD) are still unclear and should be further examined. The present work focused on determining the molecular mechanisms underlying lncRNAs regulation in aortic dissection on the basis of the lncRNA-miRNA-mRNA competing endogenous RNA (ceRNA) network. Methods This study collected the lncRNAs (GSE52093), mRNAs (GSE52093) and miRNAs (GSE92427) expression data within human tissue samples with aortic dissection group and normal group based on Gene Expression Omnibus (GEO) database. Results This study identified three differentially expressed lncRNAs (DELs), 19 differentially expressed miRNAs (DEmiRs) and 1046 differentially expressed mRNAs (DEGs) identified regarding aortic dissection. Furthermore, we constructed a lncRNA-miRNA-mRNA network through three lncRNAs (including two with up-regulation and one with down-regulation), five miRNAs (five with up-regulation), as well as 211 mRNAs (including 103 with up-regulation and 108 with down-regulation). Simultaneously, we conducted functional enrichment and pathway analyses on genes within the as-constructed ceRNA network. According to our PPI/ceRNA network and functional enrichment analysis results, four critical genes were found (E2F2, IGF1R, BDNF and PPP2R1B). In addition, E2F2 level was possibly modulated via lncRNA FAM87A-hsa-miR-31-5p/hsa-miR-7-5p or lncRNA C9orf106-hsa-miR-7-5p. The expression of IGF1R may be regulated by lncRNA FAM87A-hsa-miR-16-5p/hsa-miR-7-5p or lncRNA C9orf106-hsa-miR-7-5p. Conclusion In conclusion, the ceRNA interaction axis we identified is a potentially critical target for treating AD. Our results shed more lights on the possible pathogenic mechanism in AD using a lncRNA-associated ceRNA network.

scholarly journals Building a Competing Endogenous RNA Network to Find Potential Long Non-Coding RNA Biomarkers for Pheochromocytoma

2018 ◽  
Vol 51 (6) ◽  
pp. 2916-2924 ◽  
Author(s):  
Ying-Chun Liang ◽  
Yu-Peng Wu ◽  
Dong-Ning Chen ◽  
Shao-Hao Chen ◽  
Xiao-Dong Li ◽  
...  
Keyword(s):  
Digital Gene Expression ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Competing Endogenous Rna ◽  
Cerna Network ◽  
Competing Endogenous Rna Network ◽  
Patient Prognosis

Background/Aims: Accumulating evidence has shown that long non-coding RNAs (lncRNAs) in competing endogenous RNA (ceRNA) networks play crucial roles in tumor survival and patient prognosis; however, studies investigating ceRNA networks in pheochromocytoma (PCC) are lacking. In this study, we investigated the pathogenesis of PCC and whether lncRNAs acting through ceRNAs networks were associated with prognosis. Methods: A total of 183 PCC samples and 3 control samples from The Cancer Genome Atlas database were analyzed. The Empirical Analysis of Digital Gene Expression Data package in R (edgeR) was used to analyze differentially expressed RNAs. Biological processes and pathways functional enrichment analysis were performed based on the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database. LncRNA/mRNA/miRNA ceRNA network was constructed by Cytoscape v3.0 software based on the differentially expressed RNAs Survival package in R was used to perform survival analysis. Results: In total, 554 differentially expressed lncRNAs, 1775 mRNAs and 40 miRNAs were selected for further analysis. Subsequently, 23 lncRNAs, 22 mRNAs, and 6 miRNAs were included in the constructed ceRNA network. Meanwhile, two of the 23 lncRNAs (C9orf147 and BSN-AS2) were identified as independent predictors of overall survival in PCC patients (P< 0.05). Conclusion: This study improves the understanding of lncRNA-related ceRNA networks in PCC and suggests that the lncRNAs C9orf147 and BSN-AS2 could be independent prognostic biomarkers and potential therapeutic targets for PCC.

Systems Biology Approaches Reveal a Multi-stress Responsive WRKY Transcription Factor and Stress Associated Gene Co-expression Networks in Chickpea

2019 ◽  
Vol 14 (7) ◽  
pp. 591-601 ◽  
Author(s):  
Aravind K. Konda ◽  
Parasappa R. Sabale ◽  
Khela R. Soren ◽  
Shanmugavadivel P. Subramaniam ◽  
Pallavi Singh ◽  
...  
Keyword(s):  
Expression Pattern ◽  
Gene Networks ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Wrky Transcription Factor ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Callose Deposition ◽  
Significant Probability

Background: Chickpea is a nutritional rich premier pulse crop but its production encounters setbacks due to various stresses and understanding of molecular mechanisms can be ascribed foremost importance. Objective: The investigation was carried out to identify the differentially expressed WRKY TFs in chickpea in response to herbicide stress and decipher their interacting partners. Methods: For this purpose, transcriptome wide identification of WRKY TFs in chickpea was done. Behavior of the differentially expressed TFs was compared between other stress conditions. Orthology based cofunctional gene networks were derived from Arabidopsis. Gene ontology and functional enrichment analysis was performed using Blast2GO and STRING software. Gene Coexpression Network (GCN) was constructed in chickpea using publicly available transcriptome data. Expression pattern of the identified gene network was studied in chickpea-Fusarium interactions. Results: A unique WRKY TF (Ca_08086) was found to be significantly (q value = 0.02) upregulated not only under herbicide stress but also in other stresses. Co-functional network of 14 genes, namely Ca_08086, Ca_19657, Ca_01317, Ca_20172, Ca_12226, Ca_15326, Ca_04218, Ca_07256, Ca_14620, Ca_12474, Ca_11595, Ca_15291, Ca_11762 and Ca_03543 were identified. GCN revealed 95 hub genes based on the significant probability scores. Functional annotation indicated role in callose deposition and response to chitin. Interestingly, contrasting expression pattern of the 14 network genes was observed in wilt resistant and susceptible chickpea genotypes, infected with Fusarium. Conclusion: This is the first report of identification of a multi-stress responsive WRKY TF and its associated GCN in chickpea.

scholarly journals Exploration of the Proteomic Landscape of Small Extracellular Vesicles in Serum as Biomarkers for Early Detection of Colorectal Neoplasia

2021 ◽  
Vol 11 ◽  
Author(s):  
Li-Chun Chang ◽  
Yi-Chiung Hsu ◽  
Han-Mo Chiu ◽  
Koji Ueda ◽  
Ming-Shiang Wu ◽  
...  
Keyword(s):  
Extracellular Vesicles ◽  
Normal Control ◽  
Early Stage ◽  
Colorectal Neoplasia ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Data Matrix ◽  
Advanced Adenoma ◽  
Advanced Neoplasia

BackgroundPatient participation in colorectal cancer (CRC) screening via a stool test and colonoscopy is suboptimal, but participation can be improved by the development of a blood test. However, the suboptimal detection abilities of blood tests for advanced neoplasia, including advanced adenoma (AA) and CRC, limit their application. We aimed to investigate the proteomic landscape of small extracellular vesicles (sEVs) from the serum of patients with colorectal neoplasia and identify specific sEV proteins that could serve as biomarkers for early diagnosis.Materials and MethodsWe enrolled 100 patients including 13 healthy subjects, 12 non-AAs, 13 AAs, and 16 stage-I, 15 stage-II, 16 stage-III, and 15 stage-IV CRCs. These patients were classified as normal control, early neoplasia, and advanced neoplasia. The sEV proteome was explored by liquid chromatography-tandem mass spectrometry. Generalized association plots were used to integrate the clustering methods, visualize the data matrix, and analyze the relationship. The specific sEV biomarkers were identified by a decision tree via Orange3 software. Functional enrichment analysis was conducted by using the Ingenuity Pathway Analysis platform.ResultsThe sEV protein matrix was identified from the serum of 100 patients and contained 3353 proteins, of which 1921 proteins from 98 patients were finally analyzed. Compared with the normal control, subjects with early and advanced neoplasia exhibited a distinct proteomic distribution in the data matrix plot. Six sEV proteins were identified, namely, GCLM, KEL, APOF, CFB, PDE5A, and ATIC, which properly distinguished normal control, early neoplasia, and advanced neoplasia patients from each other. Functional enrichment analysis revealed that APOF+ and CFB+ sEV associated with clathrin-mediated endocytosis signaling and the complement system, which have critical implications for CRC carcinogenesis.ConclusionPatients with colorectal neoplasia had a distinct sEV proteome expression pattern in serum compared with those patients who were healthy and did not have neoplasms. Moreover, the six identified specific sEV proteins had the potential to discriminate colorectal neoplasia between early-stage and advanced neoplasia. Collectively, our study provided a six-sEV protein biomarker panel for CRC diagnosis at early or advanced stages. Furthermore, the implication of the sEV proteome in CRC carcinogenesis via specific signaling pathways was explored.

scholarly journals Identification of a prognostic long non-coding RNA signature in breast cancer

2020 ◽  
Author(s):  
Gaochen Lan ◽  
Xiaoling Yu ◽  
Yanna Zhao ◽  
Jinjian Lan ◽  
Wan Li ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Cox Regression ◽  
Prognostic Biomarker ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Cox Regression Analysis

Abstract Background: Breast cancer is the most common malignant disease among women. At present, more and more attention has been paid to long non-coding RNAs (lncRNAs) in the field of breast cancer research. We aimed to investigate the expression profiles of lncRNAs and construct a prognostic lncRNA for predicting the overall survival (OS) of breast cancer.Methods: The expression profiles of lncRNAs and clinical data with breast cancer were obtained from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs were screened out by R package (limma). The survival probability was estimated by the Kaplan‑Meier Test. The Cox Regression Model was performed for univariate and multivariate analysis. The risk score (RS) was established on the basis of the lncRNAs’ expression level (exp) multiplied regression coefficient (β) from the multivariate cox regression analysis with the following formula: RS=exp a1 * β a1 + exp a2 * β a2 +……+ exp an * β an. Functional enrichment analysis was performed by Metascape.Results: A total of 3404 differentially expressed lncRNAs were identified. Among them, CYTOR, MIR4458HG and MAPT-AS1 were significantly associated with the survival of breast cancer. Finally, The RS could predict OS of breast cancer (RS=exp CYTOR * β CYTOR + exp MIR4458HG * β MIR4458HG + exp MAPT-AS1 * β MAPT-AS1). Moreover, it was confirmed that the three-lncRNA signature could be an independent prognostic biomarker for breast cancer (HR=3.040, P=0.000).Conclusions: This study established a three-lncRNA signature, which might be a novel prognostic biomarker for breast cancer.

scholarly journals Identifcation of The Ferroptosis-Related Gene Signature In Placenta of Patients With Early-Onset Preeclampsia

2021 ◽  
Author(s):  
Nana Yang ◽  
Qianghua Wang ◽  
Biao Ding ◽  
Yinging Gong ◽  
Yue Wu ◽  
...  
Keyword(s):  
Iron Homeostasis ◽  
Molecular Mechanisms ◽  
Late Onset ◽  
Expression Profiles ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Ppi Network ◽  
Network Analyses

Abstract Background: The accumulation of ROS resulting from upregulated levels of oxidative stress is commonly implicated in preeclampsia (PE). Ferroptosis is a novel form of iron-dependent cell death instigated by lipid peroxidation likely plays important role in PE pathogenesis. This study aims to investigate expression profiles and functions of the ferroptosis-related genes (FRGs) in early- and late-onset preeclampsia.Methods: The gene expression data and clinical information were downloaded from GEO database. The “limma” R package was used for screening differentially expressed genes. GO(Gene Ontology), Kyoto Encyclopedia of Genes and Genomes(KEGG) and protein protein interaction (PPI) network analyses were conducted to investigate the bioinformatics functions and molecular interactions of significantly different FRGs. Quantitative real-time reverse transcriptase PCR was used to verify the expression of hub FRGs in PE.Results: A total number of 4,215 DEGs were identified between EOPE and preterm cases and 3,356 DEGs were found between EOPE and LOPE subtypes. 20 significantly different FRGs were identified in EOPE, while only 3 in LOPE. Functional enrichment analysis revealed that the differentially expressed FRGs was mainly involved in EOPE and enriched in hypoxia- and iron-related pathways, such as response to hypoxia, iron homeostasis and iron ion binding process. The PPI network analysis and verification by RT-qPCR resulted in the identification of the following six interesting FRGs: FTH1, HIF1A, FTL, IREB2, MAPK8 and PLIN2. Conclusions: EOPE and LOPE owned distinct underlying molecular mechanisms and ferroptosis may be mainly implicated in pathogenesis of EOPE. Further studies are necessary for deeper inquiry into placental ferroptosis and its role in the pathogenesis of EOPE.

scholarly journals Comparative Transcriptome Analysis Suggests Key Roles for 5-Hydroxytryptamlne Receptors in Control of Goose Egg Production

Genes ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 455 ◽  
Author(s):  
Qingyuan Ouyang ◽  
Shenqiang Hu ◽  
Guosong Wang ◽  
Jiwei Hu ◽  
Jiaman Zhang ◽  
...  
Keyword(s):  
Egg Production ◽  
Expression Profiles ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Production Performance ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Anser Anser

To date, research on poultry egg production performance has only been conducted within inter or intra-breed groups, while those combining both inter- and intra-breed groups are lacking. Egg production performance is known to differ markedly between Sichuan white goose (Anser cygnoides) and Landes goose (Anser anser). In order to understand the mechanism of egg production performance in geese, we undertook this study. Here, 18 ovarian stromal samples from both Sichuan white goose and Landes goose at the age of 145 days (3 individuals before egg production initiation for each breed) and 730 days (3 high- and low egg production individuals during non-laying periods for each breed) were collected to reveal the genome-wide expression profiles of ovarian mRNAs and lncRNAs between these two geese breeds at different physiological stages. Briefly, 58, 347, 797, 777, and 881 differentially expressed genes (DEGs) and 56, 24, 154, 105, and 224 differentially expressed long non-coding RNAs (DElncRNAs) were found in LLD vs. HLD (low egg production Landes goose vs. high egg production Landes goose), LSC vs. HSC (low egg production Sichuan White goose vs. high egg production Sichuan white goose), YLD vs. YSC (young Landes goose vs. young Sichuan white goose), HLD vs. HSC (high egg production Landes goose vs. high egg production Sichuan white goose), and LLD vs. LSC (low egg production Landes goose vs. low egg production Sichuan white goose) groups, respectively. Functional enrichment analysis of these DEGs and DElncRNAs suggest that the “neuroactive ligand–receptor interaction pathway” is crucial for egg production, and particularly, members of the 5-hydroxytryptamine receptor (HTR) family affect egg production by regulating ovarian metabolic function. Furthermore, the big differences in the secondary structures among HTR1F and HTR1B, HTR2B, and HTR7 may lead to their different expression patterns in goose ovaries of both inter- and intra-breed groups. These results provide novel insights into the mechanisms regulating poultry egg production performance.

scholarly journals LnCeVar: a comprehensive database of genomic variations that disturb ceRNA network regulation

2019 ◽  
Author(s):  
Peng Wang ◽  
Xin Li ◽  
Yue Gao ◽  
Qiuyan Guo ◽  
Shangwei Ning ◽  
...  
Keyword(s):  
Cox Regression ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Data Sets ◽  
Genomic Variations ◽  
Cancer Hallmarks ◽  
Cerna Network ◽  
Comprehensive Database ◽  
User Friendly

Abstract LnCeVar (http://www.bio-bigdata.net/LnCeVar/) is a comprehensive database that aims to provide genomic variations that disturb lncRNA-associated competing endogenous RNA (ceRNA) network regulation curated from the published literature and high-throughput data sets. LnCeVar curated 119 501 variation–ceRNA events from thousands of samples and cell lines, including: (i) more than 2000 experimentally supported circulating, drug-resistant and prognosis-related lncRNA biomarkers; (ii) 11 418 somatic mutation–ceRNA events from TCGA and COSMIC; (iii) 112 674 CNV–ceRNA events from TCGA; (iv) 67 066 SNP–ceRNA events from the 1000 Genomes Project. LnCeVar provides a user-friendly searching and browsing interface. In addition, as an important supplement of the database, several flexible tools have been developed to aid retrieval and analysis of the data. The LnCeVar–BLAST interface is a convenient way for users to search ceRNAs by interesting sequences. LnCeVar–Function is a tool for performing functional enrichment analysis. LnCeVar–Hallmark identifies dysregulated cancer hallmarks of variation–ceRNA events. LnCeVar–Survival performs COX regression analyses and produces survival curves for variation–ceRNA events. LnCeVar–Network identifies and creates a visualization of dysregulated variation–ceRNA networks. Collectively, LnCeVar will serve as an important resource for investigating the functions and mechanisms of personalized genomic variations that disturb ceRNA network regulation in human diseases.

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