Microarray Analysis Identifies Key Differentially Expressed Circular RNAs in Aged Mice With Postoperative Cognitive Dysfunction

Postoperative cognitive dysfunction (POCD) is a common complication in elderly patients. Circular RNAs (circRNAs) may contribute to neurodegenerative diseases. However, the role of circRNAs in POCD in aged mice has not yet been reported. This study aimed to explore the potential circRNAs in a POCD model. First, a circRNA microarray was used to analyze the expression profiles. Differentially expressed circRNAs were validated using quantitative real-time polymerase chain reaction. A bioinformatics analysis was then used to construct a competing endogenous RNA (ceRNA) network. The database for annotation, visualization, and integrated discovery was used to perform Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of circRNA-related genes. Moreover, protein-protein interactions were analyzed to predict the circRNA-regulated hub genes using the STRING and molecular complex detection plug-in of Cytoscape. Microarray screen 124 predicted circRNAs in the POCD of aged mice. We found that the up/downregulated circRNAs were involved in multiple signaling pathways. Hub genes, including Egfr and Prkacb, were identified and may be regulated by ceRNA networks. These results suggest that circRNAs are dysexpressed in the hippocampus and may contribute to POCD in aged mice.

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Bioinformatics-Based Study to Investigate Potential Differentially Expressed Genes and miRNAs in Hashimoto’s Thyroiditis

10.21203/rs.3.rs-1023446/v1 ◽

2021 ◽

Author(s):

Li Guoquan ◽

Du Junwei ◽

He Qi ◽

Fu Xinghao ◽

Ji Feihong ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Genes ◽

Inflammatory Responses ◽

Expression Profiles ◽

Treatment Options ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Chronic Lymphocytic Thyroiditis ◽

Hub Genes

Abstract BackgroundHashimoto's thyroiditis (HT), also known as chronic lymphocytic thyroiditis, is a common autoimmune disease, which mainly occurs in women. The early manifestation was hyperthyroidism, however, hypothyroidism may occur if HT was not controlled for a long time. Numerous studies have shown that multiple factors, including genetic, environmental, and autoimmune factors, were involved in the pathogenesis of the disease, but the exact mechanisms were not yet clear. The aim of this study was to identify differentially expressed genes (DEGs) by comprehensive analysis and to provide specific insights into HT. MethodsTwo gene expression profiles (GSE6339, GSE138198) about HT were downloaded from the Gene Expression Omnibus (GEO) database. The DEGs were assessed between the HT and normal groups using the GEO2R. The DEGs were then sent to the Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. The hub genes were discovered using Cytoscape and CytoHubba. Finally, NetworkAnalyst was utilized to create the hub genes' targeted microRNAs (miRNAs). ResultsA total of 62 DEGs were discovered, including 60 up-regulated and 2 down-regulated DEGs. The signaling pathways were mainly engaged in cytokine interaction and cytotoxicity, and the DEGs were mostly enriched in immunological and inflammatory responses. IL2RA, CXCL9, IL10RA, CCL3, CCL4, CCL2, STAT1, CD4, CSF1R, and ITGAX were chosen as hub genes based on the results of the protein-protein interaction (PPI) network and CytoHubba. Five miRNAs, including mir-24-3p, mir-223-3p, mir-155-5p, mir-34a-5p, mir-26b-5p, and mir-6499-3p, were suggested as likely important miRNAs in HT. ConclusionsThese hub genes, pathways and miRNAs contribute to a better understanding of the pathophysiology of HT and offer potential treatment options for HT.

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Predicting functional circular RNA-based competitive endogenous RNA network in gastric carcinoma using novel bioinformatics analysis

Experimental Biology and Medicine ◽

10.1177/15353702211048757 ◽

2021 ◽

pp. 153537022110487

Author(s):

Zirui Zhu ◽

Rui Huang ◽

Baojun Huang

Keyword(s):

Messenger Rna ◽

Expression Profiles ◽

Clinical Stage ◽

Interaction Network ◽

Enrichment Analysis ◽

Rank Aggregation ◽

Circular Rnas ◽

Pathway Enrichment Analysis ◽

Hub Genes ◽

Competitive Endogenous Rna

Gastric cancer (GC) remains one of the most prevalent types of malignancies worldwide, and also one of the most reported lethal tumor-related diseases. Circular RNAs (circRNAs) have been certified to be trapped in multiple aspects of GC pathogenesis. Yet, the mechanism of this regulation is mostly undefined. This research is designed to discover the vital circRNA-microRNA (miRNA)-messenger RNA (mRNA) regulatory network in GC. Expression profiles with diverse levels including circRNAs, miRNAs, and mRNAs were all determined using microarray public datasets from Gene Expression Ominous (GEO). The differential circRNAs expressions were recognized against the published robust rank aggregation algorithm. Besides, a circRNA-based competitive endogenous RNA (ceRNA) interaction network was visualized via Cytoscape software (version 3.8.0). Functional and pathway enrichment analysis associated with differentially expressed targeted mRNAs were conducted using Cytoscape and an online bioinformatics database. Furthermore, an interconnected protein–protein interaction association network which consisted of 51 mRNAs was predicted, and hub genes were screened using STRING and CytoHubba. Then, several hub genes were chosen to explore their expression associated with survival rate and clinical stage in GEPIA and Kaplan-Meier Plotter databases. Finally, a carefully designed circRNA-related ceRNA regulatory subnetwork including four circRNAs, six miRNAs, and eight key hub genes was structured using the online bioinformatics tool.

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Bioinformatics analysis of potential core genes for glioblastoma

Bioscience Reports ◽

10.1042/bsr20201625 ◽

2020 ◽

Vol 40 (7) ◽

Author(s):

Yu Zhang ◽

Xin Yang ◽

Xiao-Lin Zhu ◽

Jia-Qi Hao ◽

Hao Bai ◽

...

Keyword(s):

Survival Analysis ◽

Protein Interactions ◽

Poor Prognosis ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Normal Brain ◽

Hub Genes ◽

Potential Core ◽

Core Genes

Abstract Background: Glioblastoma (GBM) has a high degree of malignancy, aggressiveness and recurrence rate. However, there are limited options available for the treatment of GBM, and they often result in poor prognosis and unsatisfactory outcomes. Materials and methods: In order to identify potential core genes in GBM that may provide new therapeutic insights, we analyzed three gene chips (GSE2223, GSE4290 and GSE50161) screened from the GEO database. Differentially expressed genes (DEG) from the tissues of GBM and normal brain were screened using GEO2R. To determine the functional annotation and pathway of DEG, Gene Ontology (GO) and KEGG pathway enrichment analysis were conducted using DAVID database. Protein interactions of DEG were visualized using PPI network on Cytoscape software. Next, 10 Hub nodes were screened from the differentially expressed network using MCC algorithm on CytoHubba software and subsequently identified as Hub genes. Finally, the relationship between Hub genes and the prognosis of GBM patients was described using GEPIA2 survival analysis web tool. Results: A total of 37 up-regulated and 187 down-regulated genes were identified through microarray analysis. Amongst the 10 Hub genes selected, SV2B appeared to be the only gene associated with poor prognosis in glioblastoma based on the survival analysis. Conclusion: Our study suggests that high expression of SV2B is associated with poor prognosis in GBM patients. Whether SV2B can be used as a new therapeutic target for GBM requires further validation.

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Potential function and molecular mechanism of circRNAs involved in idiopathic pulmonary fibrosis

10.21203/rs.3.rs-15519/v1 ◽

2020 ◽

Author(s):

Fangwei Li ◽

Hong Wang ◽

Hongyan Tao ◽

Fanqi Wu ◽

Dan Wang ◽

...

Keyword(s):

Idiopathic Pulmonary Fibrosis ◽

Pulmonary Fibrosis ◽

Molecular Mechanism ◽

Target Genes ◽

Expression Profiles ◽

Enrichment Analysis ◽

Differentially Expressed ◽

Circular Rnas

Abstract Background: Recent studies have found a regulatory role of circular RNAs (circRNAs) in the pathogenesis of idiopathic pulmonary fibrosis (IPF). However, the function and underlying molecular mechanism of circRNAs involved in IPF are uncertain and incomplete. This study aimed to further provide some critical information for the circRNA function in IPF using bioinformatic analysis. Methods: We searched in the NCBI (National Center for Biotechnology Information) Gene Expression Omnibus (GEO) database to find the circRNA expression profiles of human IPF. The microarray data GSE102660 was obtained and differentially expressed circRNAs were identified through R software. Results: 6 significantly up-regulated and 13 significantly down-regulated circRNAs were identified involved in the pathogenesis of IPF. The binding sites of miRNAs for each differentially expressed circRNA were also predicted and circRNA-miRNA-mRNA networks were constructed for the most up-regulated hsa_circ_0004099 and down-regulated hsa_circ_0029633. In addition, GO and KEGG enrichment analysis revealed the molecular function and enriched pathways of the target genes of circRNAs in IPF.Conclusion: These findings suggest that candidate circRNAs might serve an important role in the pathogenesis of IPF. Therefore, these circRNAs might be potential biomarkers for diagnosis and promising targets for treatment of IPF, which still need further veriﬁcation in vivo and in vitro.

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Identification of hub genes and pathways in nonalcoholic steatohepatitis by integrated bioinformatics analysis

10.1101/2021.09.10.459743 ◽

2021 ◽

Author(s):

Pegah Einaliyan ◽

Ali Owfi ◽

Mohammadamin Mahmanzar ◽

Taha Aghajanzadeh ◽

Morteza Hadizadeh ◽

...

Keyword(s):

Gene Expression ◽

Protein Interactions ◽

Expression Profiles ◽

Principal Component ◽

Gene Expression Omnibus ◽

P Value ◽

Protein Protein Interactions ◽

Hub Genes ◽

Alcoholic Fatty Liver ◽

Critical Pathways

AbstractBackgroundCurrently, non-alcoholic fatty liver disease (NAFLD) is one of the most common chronic liver diseases in the world. Forecasting the short-term, up to 2025, NASH due to fibrosis is one of the leading causes of liver transplantation. Cohort studies revealed that non-alcoholic steatohepatitis (NASH) has a higher risk of fibrosis progression among NAFLD patients. Identifying differentially expressed genes helps to determine NASH pathogenic pathways, make more accurate diagnoses, and prescribe appropriate treatment.Methods and ResultsIn this study, we found 11 NASH datasets by searching in the Gene Expression Omnibus (GEO) database. Subsequently, NASH datasets with low-quality control scores were excluded. Four datasets were analyzed with packages of R/Bioconductor. Then, all integrated genes were Imported into Cytoscape to illustrate the protein-protein interactions network. All hubs and nodes degree has been calculated to determine the hub genes with critical roles in networks.Possible correlations between expression profiles of mutual DEGs were identified employing Principal Component Analysis (PCA). Primary analyzed data were filtered based on gene expression (logFC > 1, logFC < −1) and adj-P-value (<0.05). Ultimately, among 379 DEGs, we selected the top 10 genes (MYC, JUN, EGR1, FOS, CCL2, IL1B, CXCL8, PTGS2, IL6, SERPINE1) as candidates among up and down regulated genes, and critical pathways such as IL-6, IL-17, TGF β, and TNFα were identified.ConclusionThe present study suggests an important DEGs, biological processes, and critical pathways involved in the pathogenesis of NASH disease. Further investigations are needed to clarify the exact mechanisms underlying the development and progression of NASH disease.

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Integrated analysis of the expression, involved functions, and regulatory network of RUNX3 in melanoma

Combinatorial Chemistry & High Throughput Screening ◽

10.2174/1386207324666210816121833 ◽

2021 ◽

Vol 24 ◽

Author(s):

Yanxin Liu ◽

Zhang Feng ◽

Huaxia Chen

Keyword(s):

Protein Interactions ◽

Enrichment Analysis ◽

Functional Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Functional Enrichment ◽

Differentially Expressed ◽

Integrated Analysis ◽

Protein Protein Interactions ◽

Nf Kappab ◽

Microarray Datasets

Background: As a tumor suppressor or oncogenic gene, abnormal expression of RUNX family transcription factor 3 (RUNX3) has been reported in various cancers. Introduction: This study aimed to investigate the role of RUNX3 in melanoma. Methods: The expression level of RUNX3 in melanoma tissues was analyzed by immunohistochemistry and the Oncomine database. Based on microarray datasets GSE3189 and GSE7553, differentially expressed genes (DEGs) in melanoma samples were screened, followed by functional enrichment analysis. Gene Set Enrichment Analysis (GSEA) was performed for RUNX3. DEGs that co-expressed with RUNX3 were analyzed, and the transcription factors (TFs) of RUNX3 and its co-expressed genes were predicted. The protein-protein interactions (PPIs) for RUNX3 were analyzed utilizing the GeneMANIA database. MicroRNAs (miRNAs) that could target RUNX3 expression, were predicted. Results : RUNX3 expression was significantly up-regulated in melanoma tissues. GSEA showed that RUNX3 expression was positively correlated with melanogenesis and melanoma pathways. Eleven DEGs showed significant co-expression with RUNX3 in melanoma, for example, TLE4 was negatively co-expressed with RUNX3. RUNX3 was identified as a TF that regulated the expression of both itself and its co-expressed genes. PPI analysis showed that 20 protein-encoding genes interacted with RUNX3, among which 9 genes were differentially expressed in melanoma, such as CBFB and SMAD3. These genes were significantly enriched in transcriptional regulation by RUNX3, RUNX3 regulates BCL2L11 (BIM) transcription, regulation of I-kappaB kinase/NF-kappaB signaling, and signaling by NOTCH. A total of 31 miRNAs could target RUNX3, such as miR-326, miR-330-5p, and miR-373-3p. Conclusion: RUNX3 expression was up-regulated in melanoma and was implicated in the development of melanoma.

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Mesothelioma Interactome with 367 Novel Protein-Protein Interactions

10.1101/459065 ◽

2018 ◽

Author(s):

Kalyani B. Karunakaran ◽

Naveena Yanamala ◽

Gregory Boyce ◽

Madhavi K. Ganapathiraju

Keyword(s):

Protein Interactions ◽

Cellular Localization ◽

Expression Profiles ◽

Differentially Expressed ◽

Protein Protein Interactions ◽

Advanced Search ◽

Genomic Location ◽

One Year ◽

Approved Drugs ◽

Novel Protein

AbstractMalignant pleural mesothelioma (MPM) is an aggressive cancer of the thorax with a median survival of one year. We constructed an ‘MPM interactome’ with over 300 computationally predicted PPIs and over 1300 known PPIs of 62 literature-curated genes whose activity affects MPM. Known PPIs of the 62 MPM associated genes were derived from BioGRID and HPRD databases. Novel PPIs were predicted by applying the HiPPIP algorithm, which computes features of protein pairs such as cellular localization, molecular function, biological process membership, genomic location of the gene, gene expression in microarray experiments, protein domains and tissue membership, and classifies the pairwise features asinteractingornon-interactingbased on a random forest model. To our satisfaction, the interactome is significantly enriched with genes differentially expressed in MPM tumors compared with normal pleura, and with other thoracic tumors. The interactome is also significantly enriched with genes whose high expression has been correlated with unfavorable prognosis in lung cancer, and with genes differentially expressed on crocidolite exposure. 28 of the interactors of MPM proteins are targets of 147 FDA-approved drugs. By comparing differential expression profiles induced by drug to profiles induced by MPM, potentially repurposable drugs are identified from this drug list. Development of PPIs of disease-specific set of genes is a powerful approach with high translational impact – the interactome is a vehicle to piece together an integrated view on how genes associated with MPM through various high throughput studies are functionally linked, leading to clinically translatable results such as clinical trials with repurposed drugs. The PPIs are made available on a webserver, calledWiki-Pi MPMathttp://severus.dbmi.pitt.edu/wiki-MPMwith advanced search capabilities.One Sentence SummaryMesothelioma Interactome with 367 novel protein-protein interactions may shed light on the mechanisms of cancer genesis and progression

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Three novel circRNAs upregulated in tissue and plasma from hepatocellular carcinoma patients and their regulatory network

Cancer Cell International ◽

10.1186/s12935-021-01762-w ◽

2021 ◽

Vol 21 (1) ◽

Cited By ~ 1

Author(s):

Lianghai Wang ◽

Lisha Zhou ◽

Jun Hou ◽

Jin Meng ◽

Ke Lin ◽

...

Keyword(s):

Hepatocellular Carcinoma ◽

Regulatory Network ◽

Expression Profiles ◽

Interaction Network ◽

Enrichment Analysis ◽

Circular Rnas ◽

Pathway Enrichment Analysis ◽

Plasma Samples ◽

Hub Genes ◽

Protein Protein Interaction

Abstract Background The regulatory roles of circular RNAs (circRNAs) in tumorigenesis have attracted increasing attention. However, novel circRNAs with the potential to be used as serum/plasma biomarkers and their regulatory mechanism in the pathogenesis of hepatocellular carcinoma (HCC) remain explored. Methods CircRNA expression profiles of tumor tissues and plasma samples from HCC patients were compiled and jointly analyzed. CircRNA–miRNA–mRNA interactions were predicted by bioinformatics tools. The expression of interacting miRNAs and mRNA was verified in independent datasets. Survival analysis and pathway enrichment analysis were conducted on hub genes. Results We identified three significantly up-regulated circRNAs (hsa_circ_0009910, hsa_circ_0049783, and hsa_circ_0089172) both in HCC tissues and plasma samples. Two of them were validated to be indeed circular and could be excreted from hepatoma cells. We further revealed four miRNAs (hsa-miR-455-5p, hsa-miR-615-3p, hsa-miR-18a-3p, hsa-miR-4524a-3p) that targeting circRNAs and expressed in human HCC samples, and 95 mRNAs targeted by miRNAs and significantly up-regulated in two HCC cohorts. A protein-protein interaction network revealed 19 hub genes, 12 of them (MCM6, CCNB1, CDC20, NDC80, ZWINT, ASPM, CENPU, MCM3, MCM5, ECT2, CDC7, and DLGAP5) were associated with reduced survival in two HCC cohorts. KEGG, Reactome, and Wikipathway enrichment analysis indicated that the hub genes mainly functioned in DNA replication and cell cycle. Conclusions Our study uncovers three novel deregulated circRNAs in tumor and plasma from HCC patients and provides an insight into the pathogenesis from the circRNA–miRNA–mRNA regulatory network.

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Construction of ceRNA co-expression network and screening of molecular targets in colorectal cancer

10.21203/rs.2.17910/v1 ◽

2019 ◽

Author(s):

Hui Zhao ◽

Zhanwei Wang ◽

Xi Yang ◽

Jin Liu ◽

Jing Zhuang ◽

...

Keyword(s):

Colorectal Cancer ◽

Protein Interactions ◽

Enrichment Analysis ◽

Gene Expression Omnibus ◽

Differentially Expressed ◽

Protein Protein Interactions ◽

Normal Tissues ◽

Cerna Network ◽

Using Data ◽

Cancer Tissues

Abstract 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 functioal enrichment analysis. And a lncRNA-miRNA-mRNA network was constructed wich correlated with CRC. RNAs in this network were subjecte 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 reasearches of therapy the CRC. And the lncRNA RP11-108K3.2 and mRNA ONECUT2 may serve novel prognostic predictor of CRC.

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