The novel serine protease tumor-associated differentially expressed gene-14 (KLK8/Neuropsin/Ovasin) is highly overexpressed in cervical cancer

AbstractRNA-sequencing (RNA-seq) data analysis of the different stages of root nodules formation in peanut Arachis hypogaea investigate the genetic features. Genes related to the root nodules formations in this plant are extensively studied [1] [2] [3] [4] [5], but less information is present for their relations with long noncoding RNAs (lncRNAs). Bioinformatics techniques are utilised here to identify the novel lncRNAs present in the publically available RNA-seq data reported [6] for the different stages of root nodules formation in this plant. Highly correlated, significant, and Differentially Expressed (DE) gene-lncRNA pairs are also detected to understand the epigenetic control of lncRNA. These pairs are further differentiated between cis and trans antisense lncRNAs and lincRNAs based on their functions and positions from the genes. Obtained results are the catalogue for the highly correlated and significant DE gene-lncRNA pairs related to root nodules formation in A. hypogaea.

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TET2 is differentially expressed in coronavirus infections.

10.31219/osf.io/bt9r4 ◽

2020 ◽

Author(s):

Shahan Mamoor

Keyword(s):

Differentially Expressed Gene ◽

Host Cells ◽

Differentially Expressed ◽

The Novel ◽

Public Data ◽

Transcriptional Changes ◽

One Year ◽

Novel Coronavirus ◽

Human Coronavirus 229E ◽

Coronavirus Infections

The novel coronavirus SARS-CoV-2 has infected nearly 20,000,000 in less than one year (1, 2). We mined published and public data (3-8) to discover the most significant transcriptional changes induced in host cells and tissues following coronavirus infections. We identified the ten eleven (TET) methylcytosine dioxygenase TET2 as a differentially expressed gene following infection of human cells with the Middle East Respiratory Syndrome (MERS) coronavirus, Human Coronavirus 229E, and in the lungs of mice infected with the Severe Acute Respiratory Syndrome (SARS) coronavirus SARS-CoV-1. TET2 may be a relevant target of study for understanding coronavirus pathogenesis.

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Integrative Systems Biology Approaches to Identify Potential Biomarkers and Pathways of Cervical Cancer

10.20944/preprints202103.0197.v1 ◽

2021 ◽

Author(s):

Arafat Rahman Oany ◽

Mamun Mia ◽

Tahmina Pervin ◽

Salem A. Alyami ◽

Mohammad Ali Moni

Keyword(s):

Cervical Cancer ◽

Systems Biology ◽

Target Identification ◽

Differentially Expressed Gene ◽

Vital Role ◽

Regulatory Genes ◽

Differentially Expressed ◽

Hub Genes ◽

Cancer Pathways ◽

Potential Biomarkers

Nowadays, cervical cancer (CC) is treated as the leading cancer among women throughout the world. Despite effective vaccination and improved surgery and treatment, CC remains its fatality rate about half of the infected populations globally. The major screening biomarkers and therapeutic target identification have now become a global concern. The present study, we have employed systems biology approaches to retrieve the potential biomarkers and pathways from the transcriptomic profiling. Initially, we have identified 76 of each up-regulated and down-regulated gene from a total of 4,643 differentially expressed genes. The up-regulatory genes are mainly concentrating on immune-inflammatory response and the down-regulatory genes are on receptor binding and gamma-glutamyltransferase. The involved pathways associated with these genes were also assessed through pathway enrichment and they were mainly focused on different cancer pathways, immunoresponse, and cell cycle pathways. After the subsequent enrichment of these genes, we have identified 12 hub genes, which play a crucial role in CC. Furthermore, the survival of the hub genes was also assessed, and among them, finally, CXCR4 has identified as one of the most potential differentially expressed gene that might play a vital role to the survival of CC patients. Thus CXCR4 could be used as a prognostic biomarker and development of a drug target for CC.

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Decoding Psoriasis: Integrated Bioinformatics Approach to Understand Hub Genes and Involved Pathways

Current Pharmaceutical Design ◽

10.2174/1381612826666200311130133 ◽

2020 ◽

Vol 26 (29) ◽

pp. 3619-3630

Author(s):

Saumya Choudhary ◽

Dibyabhaba Pradhan ◽

Noor S. Khan ◽

Harpreet Singh ◽

George Thomas ◽

...

Keyword(s):

Gene Expression ◽

Differentially Expressed Gene ◽

Therapeutic Targets ◽

Interaction Network ◽

Gene Expression Omnibus ◽

Differentially Expressed ◽

Keratinocyte Differentiation ◽

Hub Genes ◽

Lesional Skin ◽

Ncbi Gene Expression Omnibus

Background: Psoriasis is a chronic immune mediated skin disorder with global prevalence of 0.2- 11.4%. Despite rare mortality, the severity of the disease could be understood by the accompanying comorbidities, that has even led to psychological problems among several patients. The cause and the disease mechanism still remain elusive. Objective: To identify potential therapeutic targets and affecting pathways for better insight of the disease pathogenesis. Method: The gene expression profile GSE13355 and GSE14905 were retrieved from NCBI, Gene Expression Omnibus database. The GEO profiles were integrated and the DEGs of lesional and non-lesional psoriasis skin were identified using the affy package in R software. The Kyoto Encyclopaedia of Genes and Genomes pathways of the DEGs were analyzed using clusterProfiler. Cytoscape, V3.7.1 was utilized to construct protein interaction network and analyze the interactome map of candidate proteins encoded in DEGs. Functionally relevant clusters were detected through Cytohubba and MCODE. Results: A total of 1013 genes were differentially expressed in lesional skin of which 557 were upregulated and 456 were downregulated. Seven dysregulated genes were extracted in non-lesional skin. The disease gene network of these DEGs revealed 75 newly identified differentially expressed gene that might have a role in development and progression of the disease. GO analysis revealed keratinocyte differentiation and positive regulation of cytokine production to be the most enriched biological process and molecular function. Cytokines -cytokine receptor was the most enriched pathways. Among 1013 identified DEGs in lesional group, 36 DEGs were found to have altered genetic signature including IL1B and STAT3 which are also reported as hub genes. CCNB1, CCNA2, CDK1, IL1B, CXCL8, MKI 67, ESR1, UBE2C, STAT1 and STAT3 were top 10 hub gene. Conclusion: The hub genes, genomic altered DEGs and other newly identified differentially dysregulated genes would improve our understanding of psoriasis pathogenesis, moreover, the hub genes could be explored as potential therapeutic targets for psoriasis.

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Identification of the Differentially Expressed Genes Involved in the Synergistic Neurotoxicity of an HIV Protease Inhibitor and Methamphetamine

Current HIV Research ◽

10.2174/1570162x17666190924200354 ◽

2019 ◽

Vol 17 (4) ◽

pp. 290-303

Author(s):

Sangsang Li ◽

Yanfei Li ◽

Bingpeng Deng ◽

Jie Yan ◽

Yong Wang

Keyword(s):

Protease Inhibitor ◽

Growth Inhibition ◽

Quantitative Polymerase Chain Reaction ◽

Differentially Expressed Gene ◽

Antiretroviral Drugs ◽

Differentially Expressed ◽

Hiv Protease ◽

Hiv Protease Inhibitor ◽

Dopaminergic Cells ◽

Immunodeficiency Syndrome

Background: The abuse of psychostimulants such as methamphetamine (METH) is common in human immunodeficiency virus (HIV)-infected individuals. Acquired immunodeficiency syndrome (AIDS) patients taking METH and antiretroviral drugs could suffer severe neurologic damage and cognitive impairment. Objective: To reveal the underlying neuropathologic mechanisms of an HIV protease inhibitor (PI) combined with METH, growth-inhibition tests of dopaminergic cells and RNA sequencing were performed. Methods: A combination of METH and PI caused more growth inhibition of dopaminergic cells than METH alone or a PI alone. Furthermore, we identified differentially expressed gene (DEG) patterns in the METH vs. untreated cells (1161 genes), PI vs. untreated cells (16 genes), METH-PI vs. PI (3959 genes), and METH-PI vs. METH groups (14 genes). Results: The DEGs in the METH-PI co-treatment group were verified in the brains of a mouse model using quantitative polymerase chain reaction and were involved mostly in the regulatory functions of cell proliferation and inflammation. Conclusion: Such identification of key regulatory genes could facilitate the study of their neuroprotective potential in the users of METH and PIs.

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Gene Set Correlation Analysis and Visualization Using Gene Expression Data

Current Bioinformatics ◽

10.2174/1574893615999200629124444 ◽

2020 ◽

Vol 15 ◽

Author(s):

Chen-An Tsai ◽

James J. Chen

Keyword(s):

Gene Expression ◽

Correlation Analysis ◽

Gene Expression Data ◽

Differentially Expressed Gene ◽

Differentially Expressed ◽

Superior Performance ◽

Expression Data ◽

Gene Set ◽

Gene Sets ◽

Set Correlation

Background: Gene set enrichment analyses (GSEA) provide a useful and powerful approach to identify differentially expressed gene sets with prior biological knowledge. Several GSEA algorithms have been proposed to perform enrichment analyses on groups of genes. However, many of these algorithms have focused on identification of differentially expressed gene sets in a given phenotype. Objective: In this paper, we propose a gene set analytic framework, Gene Set Correlation Analysis (GSCoA), that simultaneously measures within and between gene sets variation to identify sets of genes enriched for differential expression and highly co-related pathways. Methods: We apply co-inertia analysis to the comparisons of cross-gene sets in gene expression data to measure the costructure of expression profiles in pairs of gene sets. Co-inertia analysis (CIA) is one multivariate method to identify trends or co-relationships in multiple datasets, which contain the same samples. The objective of CIA is to seek ordinations (dimension reduction diagrams) of two gene sets such that the square covariance between the projections of the gene sets on successive axes is maximized. Simulation studies illustrate that CIA offers superior performance in identifying corelationships between gene sets in all simulation settings when compared to correlation-based gene set methods. Result and Conclusion: We also combine between-gene set CIA and GSEA to discover the relationships between gene sets significantly associated with phenotypes. In addition, we provide a graphical technique for visualizing and simultaneously exploring the associations of between and within gene sets and their interaction and network. We then demonstrate integration of within and between gene sets variation using CIA and GSEA, applied to the p53 gene expression data using the c2 curated gene sets. Ultimately, the GSCoA approach provides an attractive tool for identification and visualization of novel associations between pairs of gene sets by integrating co-relationships between gene sets into gene set analysis.

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Integrative Systems Biology Approaches to Identify Potential Biomarkers and Pathways of Cervical Cancer

Journal of Personalized Medicine ◽

10.3390/jpm11050363 ◽

2021 ◽

Vol 11 (5) ◽

pp. 363

Author(s):

Arafat Rahman Oany ◽

Mamun Mia ◽

Tahmina Pervin ◽

Salem Ali Alyami ◽

Mohammad Ali Moni

Keyword(s):

Cervical Cancer ◽

Systems Biology ◽

Differentially Expressed Genes ◽

Inflammatory Responses ◽

Profile Analysis ◽

Target Identification ◽

Regulatory Genes ◽

Differentially Expressed ◽

Hub Genes ◽

Potential Biomarkers

Nowadays, cervical cancer (CC) is treated as the leading cancer among women throughout the world. Despite effective vaccination and improved surgery and treatment, CC retains its fatality rate of about half of the infected population globally. The major screening biomarkers and therapeutic target identification have now become a global concern. In the present study, we have employed systems biology approaches to retrieve the potential biomarkers and pathways from transcriptomic profiling. Initially, we have identified 76 of each up-regulated and down-regulated gene from a total of 4643 differentially expressed genes. The up-regulatory genes mainly concentrate on immune-inflammatory responses, and the down-regulatory genes are on receptor binding and gamma-glutamyltransferase. The involved pathways associated with these genes were also assessed through pathway enrichment, and we mainly focused on different cancer pathways, immunoresponse, and cell cycle pathways. After the subsequent enrichment of these genes, we have identified 12 hub genes, which play a crucial role in CC and are verified by expression profile analysis. From our study, we have found that genes LILRB2 and CYBB play crucial roles in CC, as reported here for the first time. Furthermore, the survivability of the hub genes was also assessed, and among them, finally, CXCR4 has been identified as one of the most potential differentially expressed genes that might play a vital role in the survival of CC patients. Thus, CXCR4 could be used as a prognostic and/or diagnostic biomarker and a drug target for CC.

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Alpha-1 antitrypsin inhibits TMPRSS2 protease activity and SARS-CoV-2 infection

Nature Communications ◽

10.1038/s41467-021-21972-0 ◽

2021 ◽

Vol 12 (1) ◽

Author(s):

Lukas Wettstein ◽

Tatjana Weil ◽

Carina Conzelmann ◽

Janis A. Müller ◽

Rüdiger Groß ◽

...

Keyword(s):

Serine Protease ◽

Immune Defense ◽

Innate Immune ◽

Respiratory Pathogen ◽

The Novel ◽

Airway Epithelial ◽

Protein Library ◽

Epithelial Cultures ◽

Alpha 1 Antitrypsin ◽

Novel Coronavirus

AbstractSARS-CoV-2 is a respiratory pathogen and primarily infects the airway epithelium. As our knowledge about innate immune factors of the respiratory tract against SARS-CoV-2 is limited, we generated and screened a peptide/protein library derived from bronchoalveolar lavage for inhibitors of SARS-CoV-2 spike-driven entry. Analysis of antiviral fractions revealed the presence of α1-antitrypsin (α1AT), a highly abundant circulating serine protease inhibitor. Here, we report that α1AT inhibits SARS-CoV-2 entry at physiological concentrations and suppresses viral replication in cell lines and primary cells including human airway epithelial cultures. We further demonstrate that α1AT binds and inactivates the serine protease TMPRSS2, which enzymatically primes the SARS-CoV-2 spike protein for membrane fusion. Thus, the acute phase protein α1AT is an inhibitor of TMPRSS2 and SARS-CoV-2 entry, and may play an important role in the innate immune defense against the novel coronavirus. Our findings suggest that repurposing of α1AT-containing drugs has prospects for the therapy of COVID-19.

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