Identifying potential novel insights for COVID-19 pathogenesis and therapeutics using an integrated bioinformatics analysis of host transcriptome

Abstract The molecular mechanisms underlying the pathogenesis of COVID-19 has not been fully discovered. This study aims to decipher potentially hidden parts of the pathogenesis of COVID-19, potential novel drug targets, and to identify potential drug candidates. Two gene expression profiles (GSE147507-GSE153970) were analyzed and overlapping differentially expressed genes (DEGs) were selected for which top enriched transcription factors and kinases were identified and pathway analysis was performed. Protein-protein interaction (PPI) of DEGs was constructed, hub genes were identified and module analysis was also performed. DGIdb database was used to identify drugs for the potential targets (hub genes and the most enriched transcription factors and kinases for DEGs). A drug-potential target network was constructed and drugs are ranked according to the degree. L1000FDW web-based utility was used to identify drugs that can reverse transcriptional profiles of COVID-19. We identified drugs currently in clinical trials and novel potential 8 drugs. Besides the well-known pathogenic pathways, It was found that axon guidance is a potential pathogenic pathway. Sema7A, which may exacerbate hypercytokinemia, is considered a potential novel drug target. Another potential novel pathway is related to TINF2 overexpression which may induce potential telomere dysfunction and hence DNA damage that may exacerbate lung fibrosis.

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SMC4, CCNB1 and CKS1B as potential targets and new critical biomarkers for the prognosis of human bladder cancer

10.21203/rs.3.rs-595148/v1 ◽

2021 ◽

Author(s):

Hongpeng Fang ◽

Zhansen Huang ◽

Xianzi Zeng ◽

Jiaming Wan ◽

Jieying Wu ◽

...

Keyword(s):

Gene Expression ◽

Bladder Cancer ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Gene Expression Omnibus ◽

Transcriptional Level ◽

Hub Genes ◽

Kaplan Meier ◽

High Form

Abstract Background As a common malignant cancer of the urinary system, the precise molecular mechanisms of bladder cancer remain to be illuminated. The purpose of this study was to identify core genes with prognostic value as potential oncogenes for the diagnosis, prognosis or novel therapeutic targets of bladder cancer. Methods The gene expression profiles GSE3167 and GSE7476 were available from the Gene Expression Omnibus (GEO) database. Next, PPI network was built to filter the hub gene through the STRING database and Cytoscape software and GEPIA and Kaplan-Meier plotter were implemented. Frequency and type of hub genes and sub groups analysis were performed in cBioportal and ULCAN database. Finally,We used RT-qPCR to confirm our results. Results Totally, 251 DEGs were excavated from two datasets in our study. We only founded high expression of SMC4, TYMS, CCNB1, CKS1B, NUSAP1 and KPNA2 was associated with worse outcomes in bladder cancer patients and no matter from the type of mutation or at the transcriptional level of hub genes, the tumor showed a high form of expression. However, only the expression of SMC4,CCNB1and CKS1B remained changed between the cancer and the normal samples in our results of RT-qPCR. Conclusion In conclusion,These findings indicate that the SMC4,CCNB1 and CKS1B may serve as critical biomarkers in the development and poor prognosis.

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Identification of Potential Key Genes and Molecular Mechanisms of Medulloblastoma Based on Integrated Bioinformatics Approach

BioMed Research International ◽

10.1155/2022/1776082 ◽

2022 ◽

Vol 2022 ◽

pp. 1-17

Author(s):

Md. Rakibul Islam ◽

Lway Faisal Abdulrazak ◽

Mohammad Khursheed Alam ◽

Bikash Kumar Paul ◽

Kawsar Ahmed ◽

...

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Interaction Network ◽

Enrichment Analysis ◽

Clinical Information ◽

Gene Expression Omnibus ◽

Hub Genes ◽

New Treatments

Background. Medulloblastoma (MB) is the most occurring brain cancer that mostly happens in childhood age. This cancer starts in the cerebellum part of the brain. This study is designed to screen novel and significant biomarkers, which may perform as potential prognostic biomarkers and therapeutic targets in MB. Methods. A total of 103 MB-related samples from three gene expression profiles of GSE22139, GSE37418, and GSE86574 were downloaded from the Gene Expression Omnibus (GEO). Applying the limma package, all three datasets were analyzed, and 1065 mutual DEGs were identified including 408 overexpressed and 657 underexpressed with the minimum cut-off criteria of ∣ log fold change ∣ > 1 and P < 0.05 . The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and WikiPathways enrichment analyses were executed to discover the internal functions of the mutual DEGs. The outcomes of enrichment analysis showed that the common DEGs were significantly connected with MB progression and development. The Search Tool for Retrieval of Interacting Genes (STRING) database was used to construct the interaction network, and the network was displayed using the Cytoscape tool and applying connectivity and stress value methods of cytoHubba plugin 35 hub genes were identified from the whole network. Results. Four key clusters were identified using the PEWCC 1.0 method. Additionally, the survival analysis of hub genes was brought out based on clinical information of 612 MB patients. This bioinformatics analysis may help to define the pathogenesis and originate new treatments for MB.

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Identification of Differential Gene Expression and Related Signaling Pathways In SARS-COV-2 Infected Human Cells

10.21203/rs.3.rs-794267/v1 ◽

2021 ◽

Author(s):

Tian-Ao Xie ◽

Hou-He Li ◽

Zu-En Lin ◽

Xiao-Ye Lin ◽

Xin Meng ◽

...

Keyword(s):

Gene Expression ◽

Vaccine Development ◽

Virus Disease ◽

Expression Profiles ◽

Biological Significance ◽

Gene Expression Profiles ◽

Gene Expression Omnibus ◽

Human Cells ◽

Hub Genes ◽

Protein Protein Interaction

Abstract Background: The Corona Virus Disease 2019 (COVID-19) pandemic poses a serious public health threat to the survival and health of people all over the world. We analyzed related mRNA data and gene expression profiles of human cell lines infected with SARS-CoV-2 obtained from GEO (GSE148729), using bioinformatics tools. Differentially expressed genes (DEGs) of human cells infected with SARS-CoV-2 were identified.Method: The GSE148729 datasets were downloaded from the Gene Expression Omnibus (GEO) database. To explore the Biological significance of DEGs, Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment of the DEGs was performed. Protein-protein interaction (PPI) networks of the DEGs were constructed by using the STRING database. The hub genes were selected using the Cytoscape Software, and a t-test was performed to validate the hub genes.Result: A total of 1241 DEGs were screened, including 1049 up-regulated genes and 192 down-regulated genes. Besides, 10 hub genes were obtained from the PPI network, among which the expression level of CXCL2, Etv7, and HIST1H2BG was found to be statistically significant.Conclusion: In conclusion, bioinformatics analysis reveals genes and cellular pathways that are significantly altered in SARS-CoV-2 infected cells. This is conducive to further guide the clinical study of SARS-CoV-2 and provides new perspectives for vaccine development.

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Nr4a2 Transcription Factor in Hippocampal Synaptic Plasticity, Memory and Cognitive Dysfunction: A Perspective Review

Frontiers in Molecular Neuroscience ◽

10.3389/fnmol.2021.786226 ◽

2021 ◽

Vol 14 ◽

Author(s):

Judit Català-Solsona ◽

Alfredo J. Miñano-Molina ◽

José Rodríguez-Álvarez

Keyword(s):

Transcription Factor ◽

Transcription Factors ◽

Synaptic Plasticity ◽

Nuclear Receptor ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Memory Formation ◽

Synaptic Dysfunction ◽

Hippocampal Synaptic Plasticity

Long-lasting changes of synaptic efficacy are largely mediated by activity-induced gene transcription and are essential for neuronal plasticity and memory. In this scenario, transcription factors have emerged as pivotal players underlying synaptic plasticity and the modification of neural networks required for memory formation and consolidation. Hippocampal synaptic dysfunction is widely accepted to underlie the cognitive decline observed in some neurodegenerative disorders including Alzheimer’s disease. Therefore, understanding the molecular pathways regulating gene expression profiles may help to identify new synaptic therapeutic targets. The nuclear receptor 4A subfamily (Nr4a) of transcription factors has been involved in a variety of physiological processes within the hippocampus, ranging from inflammation to neuroprotection. Recent studies have also pointed out a role for the activity-dependent nuclear receptor subfamily 4, group A, member 2 (Nr4a2/Nurr1) in hippocampal synaptic plasticity and cognitive functions, although the underlying molecular mechanisms are still poorly understood. In this review, we highlight the specific effects of Nr4a2 in hippocampal synaptic plasticity and memory formation and we discuss whether the dysregulation of this transcription factor could contribute to hippocampal synaptic dysfunction, altogether suggesting the possibility that Nr4a2 may emerge as a novel synaptic therapeutic target in brain pathologies associated to cognitive dysfunctions.

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Identification of potential core genes in Kawasaki disease using bioinformatics analysis

Journal of International Medical Research ◽

10.1177/0300060519862057 ◽

2019 ◽

Vol 47 (9) ◽

pp. 4051-4058

Author(s):

Wenbin Wu ◽

Keyou You ◽

Jinchan Zhong ◽

Zhanwei Ruan ◽

Bubu Wang

Keyword(s):

Gene Expression ◽

Gene Ontology ◽

Kawasaki Disease ◽

Protein Interactions ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Humoral Response ◽

Hub Genes ◽

Potential Core

Objective The present study aimed to elucidate the underlying pathogenesis of Kawasaki disease (KD) and to identify potential biomarkers for KD. Methods Gene expression profiles for the GSE68004 dataset were downloaded from the Gene Expression Omnibus database. The pathways and functional annotations of differentially expressed genes (DEGs) in KD were examined by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses using the Database for Annotation, Visualization and Integrated Discovery (DAVID) tool. Protein–protein interactions of the above-described DEGs were investigated using the Search Tool for the Retrieval of Interacting Genes (STRING). Results Gene Ontology analysis revealed that DEGs in KD were significantly enriched in biological processes, including the inflammatory response, innate immune response, defense response to Gram-positive bacteria, and antibacterial humoral response. In addition, 10 hub genes with high connectivity were selected from among these DEGs ( ITGAM, MPO, MAPK14, SLC11A1, HIST2H2BE, ELANE, CAMP, MMP9, NTS, and HIST2H2AC). Conclusion The identification of several novel hub genes in KD enhances our understanding of the molecular mechanisms underlying the progression of this disease. These genes may be potential diagnostic biomarkers and/or therapeutic molecular targets in patients with KD. ITGAM inhibitors in particular may be potential targets for KD therapy.

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Meta-Analyses of Multiple Gene Expression Profiles to Screen Hub Genes Related to Osteoarthritis

Public Health Genomics ◽

10.1159/000517308 ◽

2021 ◽

Vol 24 (5-6) ◽

pp. 267-279

Author(s):

Xianyang Zhu ◽

Wen Guo

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Meta Analysis ◽

Wnt Signaling Pathway ◽

Gene Expression Profiles ◽

Enrichment Analysis ◽

Receptor Interaction ◽

Ppi Network ◽

Hub Genes

Background: This study aimed to screen and validate the crucial genes involved in osteoarthritis (OA) and explore its potential molecular mechanisms. Methods: Four expression profile datasets related to OA were downloaded from the Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) from 4 microarray patterns were identified by the meta-analysis method. The weighted gene co-expression network analysis (WGCNA) method was used to investigate stable modules most related to OA. In addition, a protein-protein interaction (PPI) network was built to explore hub genes in OA. Moreover, OA-related genes and pathways were retrieved from Comparative Toxicogenomics Database (CTD). Results: A total of 1,136 DEGs were identified from 4 datasets. Based on these DEGs, WGCNA further explored 370 genes included in the 3 OA-related stable modules. A total of 10 hub genes were identified in the PPI network, including AKT1, CDC42, HLA-DQA2, TUBB, TWISTNB, GSK3B, FZD2, KLC1, GUSB, and RHOG. Besides, 5 pathways including “Lysosome,” “Pathways in cancer,” “Wnt signaling pathway,” “ECM-receptor interaction” and “Focal adhesion” in CTD and enrichment analysis and 5 OA-related hub genes (including GSK3B, CDC42, AKT1, FZD2, and GUSB) were identified. Conclusion: In this study, the meta-analysis was used to screen the central genes associated with OA in a variety of gene expression profiles. Three OA-related modules (green, turquoise, and yellow) containing 370 genes were identified through WGCNA. It was discovered through the gene-pathway network that GSK3B, CDC42, AKT1, FZD2, and GUSB may be key genes related to the progress of OA and may become promising therapeutic targets.

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Comprehensive Bioinformatics Analysis Identifies POLR2I as a Key Gene in the Pathogenesis of Hypertensive Nephropathy

Frontiers in Genetics ◽

10.3389/fgene.2021.698570 ◽

2021 ◽

Vol 12 ◽

Author(s):

Shilong You ◽

Jiaqi Xu ◽

Boquan Wu ◽

Shaojun Wu ◽

Ying Zhang ◽

...

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Gene Expression Omnibus ◽

Chronic Hypertension ◽

Hub Genes ◽

Hypertensive Nephropathy ◽

Protein Levels

Hypertensive nephropathy (HN), mainly caused by chronic hypertension, is one of the major causes of end-stage renal disease. However, the pathogenesis of HN remains unclarified, and there is an urgent need for improved treatments. Gene expression profiles for HN and normal tissue were obtained from the Gene Expression Omnibus database. A total of 229 differentially co-expressed genes were identified by weighted gene co-expression network analysis and differential gene expression analysis. These genes were used to construct protein–protein interaction networks to search for hub genes. Following validation in an independent external dataset and in a clinical database, POLR2I, one of the hub genes, was identified as a key gene related to the pathogenesis of HN. The expression level of POLR2I is upregulated in HN, and the up-regulation of POLR2I is positively correlated with renal function in HN. Finally, we verified the protein levels of POLR2I in vivo to confirm the accuracy of our analysis. In conclusion, our study identified POLR2I as a key gene related to the pathogenesis of HN, providing new insights into the molecular mechanisms underlying HN.

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Comprehensive transcriptional analysis reveals salt stress-regulated key pathways, hub genes and time-specific responsive gene categories in common bermudagrass (Cynodon dactylon (L.) Pers.) roots

BMC Plant Biology ◽

10.1186/s12870-021-02939-1 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

An Shao ◽

Wei Wang ◽

Shugao Fan ◽

Xiao Xu ◽

Yanling Yin ◽

...

Keyword(s):

Transcription Factors ◽

Salt Stress ◽

Molecular Mechanisms ◽

Cynodon Dactylon ◽

Expression Profiles ◽

Transcriptional Analysis ◽

Salt Treatment ◽

Hub Genes ◽

Salt Response ◽

Common Bermudagrass

Abstract Background Despite its good salt-tolerance level, key genes and pathways involved with temporal salt response of common bermudagrass (Cynodon dactylon (L.) Pers.) have not been explored. Therefore, in this study, to understand the underlying regulatory mechanism following the different period of salt exposure, a comprehensive transcriptome analysis of the bermudagrass roots was conducted. Results The transcripts regulated after 1 h, 6 h, or 24 h of hydroponic exposure to 200 mM NaCl in the roots of bermudagrass were investigated. Dataset series analysis revealed 16 distinct temporal salt-responsive expression profiles. Enrichment analysis identified potentially important salt responsive genes belonging to specific categories, such as hormonal metabolism, secondary metabolism, misc., cell wall, transcription factors and genes encoded a series of transporters. Weighted gene co-expression network analysis (WGCNA) revealed that lavenderblush2 and brown4 modules were significantly positively correlated with the proline content and peroxidase activity and hub genes within these two modules were further determined. Besides, after 1 h of salt treatment, genes belonging to categories such as signalling receptor kinase, transcription factors, tetrapyrrole synthesis and lipid metabolism were immediately and exclusively up-enriched compared to the subsequent time points, which indicated fast-acting and immediate physiological responses. Genes involved in secondary metabolite biosynthesis such as simple phenols, glucosinolates, isoflavones and tocopherol biosynthesis were exclusively up-regulated after 24 h of salt treatment, suggesting a slightly slower reaction of metabolic adjustment. Conclusion Here, we revealed salt-responsive genes belonging to categories that were commonly or differentially expressed in short-term salt stress, suggesting possible adaptive salt response mechanisms in roots. Also, the distinctive salt-response pathways and potential salt-tolerant hub genes investigated can provide useful future references to explore the molecular mechanisms of bermudagrass.

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Bile Ductal Transcriptome Identifies Key Pathways and Hub Genes in Clonorchis sinensis-Infected Sprague-Dawley Rats

The Korean Journal of Parasitology ◽

10.3347/kjp.2020.58.5.513 ◽

2020 ◽

Vol 58 (5) ◽

pp. 513-525

Author(s):

Won Gi Yoo ◽

Jung-Mi Kang ◽

Huong Giang Lê ◽

Jhang Ho Pak ◽

Sung-Jong Hong ◽

...

Keyword(s):

Bile Ducts ◽

Expression Profiles ◽

Expression Patterns ◽

Clonorchis Sinensis ◽

Gene Expression Profiles ◽

Predictive Biomarkers ◽

Gene Interaction ◽

Sprague Dawley ◽

Hub Genes ◽

Protein Protein Interaction

Clonorchis sinensis is a food-borne trematode that infects more than 15 million people. The liver fluke causes clonorchiasis and chronical cholangitis, and promotes cholangiocarcinoma. The underlying molecular pathogenesis occurring in the bile duct by the infection is little known. In this study, transcriptome profile in the bile ducts infected with C. sinensis were analyzed using microarray methods. Differentially expressed genes (DEGs) were 1,563 and 1,457 at 2 and 4 weeks after infection. Majority of the DEGs were temporally dysregulated at 2 weeks, but 519 DEGs showed monotonically changing expression patterns that formed seven distinct expression profiles. Protein-protein interaction (PPI) analysis of the DEG products revealed 5 sub-networks and 10 key hub proteins while weighted co-expression network analysis (WGCNA)-derived gene-gene interaction exhibited 16 co-expression modules and 13 key hub genes. The DEGs were significantly enriched in 16 Kyoto Encyclopedia of Genes and Genomes pathways, which were related to original systems, cellular process, environmental information processing, and human diseases. This study uncovered a global picture of gene expression profiles in the bile ducts infected with C. sinensis, and provided a set of potent predictive biomarkers for early diagnosis of clonorchiasis.

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Identification of key genes related to heart failure by analysis of expression profiles

Archives of Medical Science ◽

10.5114/aoms/114896 ◽

2021 ◽

Author(s):

Che Wang ◽

Qingmin Li ◽

Honghui Yang ◽

Chuanyu Gao ◽

Qiubo Du ◽

...

Keyword(s):

Gene Expression ◽

Heart Failure ◽

Drug Targets ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Interaction Network ◽

Type I ◽

Ppi Network ◽

Hub Genes ◽

And Control

IntroductionTo elucidate the candidate biomarkers involved in the patho�genesis process of heart failure (HF) via analysis of differentially expressed genes (DEGs) of the dataset from the Gene Expression Omnibus (GEO).Material and methodsThe GSE76701 gene expression profiles regarding the HF and control subjects were respectively analysed. Briefly, DEGs were firstly identified and subjected to Cytoscape plug-in ClueGO + CluePedia and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. A protein-protein interaction (PPI) network was then built to analyse the in�teraction between DEGs, followed by the construction of an interaction net�work by combining with hub genes with the targeted miRNA genes of DEGs to identify the key molecules of HF. In addition, potential drugs targeting key DEGs were sought using the drug-gene interaction database (DGIdb), and a drug-mRNA-miRNA interaction network was also constructed.ResultsA total of 489 DEGs were verified between HF and control, which mainly enriched in type I interferon and leukocyte migration according to molecular function. Significantly increased levels of GAPDH, GALM1, MMP9, CCL5, and GNAL2 were found in the HF setting and were identified as the hub genes based on the PPI network. Furthermore, according to the drug-mRNA-miRNA network, FCGR2B, CCND1, and NF-κb, as well as corre�sponding miRNA-605-5p, miRNA-147a, and miRNA-671-5p were identified as the drug targets of HF.ConclusionsThe hub genes GAPDH, GALM1, MMP9, CCL5, and GNAL2 were significantly increased in HF. miRNA-605-5p, miRNA-147a, and miRNA-671-5p were predicted as the drug target-interacted gene-miRNA of HF.

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