Recognition of Differentially Expressed Molecular Signatures and Pathways Associated with COVID-19 Poor Prognosis in Glioblastoma Patients
Glioblastoma (GBM) is a type of brain cancer that is typically very aggressive and difficult to treat. Glioblastoma cases have been reported to have increased during COVID-19. The mechanisms underlying this comorbidity, including genomic interactions, tumor differentiation, immune responses, and hos...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-02-01
|
| Series: | International Journal of Molecular Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1422-0067/24/4/3562 |
| _version_ | 1797620530050760704 |
|---|---|
| author | Faisal A. Alzahrani Mohd Faheem Khan Varish Ahmad |
| author_facet | Faisal A. Alzahrani Mohd Faheem Khan Varish Ahmad |
| author_sort | Faisal A. Alzahrani |
| collection | DOAJ |
| description | Glioblastoma (GBM) is a type of brain cancer that is typically very aggressive and difficult to treat. Glioblastoma cases have been reported to have increased during COVID-19. The mechanisms underlying this comorbidity, including genomic interactions, tumor differentiation, immune responses, and host defense, are not completely explained. Therefore, we intended to investigate the differentially expressed shared genes and therapeutic agents which are significant for these conditions by using in silico approaches. Gene expression datasets of GSE68848, GSE169158, and GSE4290 studies were collected and analyzed to identify the DEGs between the diseased and the control samples. Then, the ontology of the genes and the metabolic pathway enrichment analysis were carried out for the classified samples based on expression values. Protein–protein interactions (PPI) map were performed by STRING and fine-tuned by Cytoscape to screen the enriched gene module. In addition, the connectivity map was used for the prediction of potential drugs. As a result, 154 overexpressed and 234 under-expressed genes were identified as common DEGs. These genes were found to be significantly enriched in the pathways involved in viral diseases, NOD-like receptor signaling pathway, the cGMP-PKG signaling pathway, growth hormone synthesis, secretion, and action, the immune system, interferon signaling, and the neuronal system. STAT1, CXCL10, and SAMDL were screened out as the top 03 out of the top 10 most critical genes among the DEGs from the PPI network. AZD-8055, methotrexate, and ruxolitinib were predicted to be the possible agents for the treatment. The current study identified significant key genes, common metabolic signaling networks, and therapeutic agents to improve our perception of the common mechanisms of GBM–COVID-19. |
| first_indexed | 2024-03-11T08:42:50Z |
| format | Article |
| id | doaj.art-4df39a2512cf412c99de15fd37bfdc92 |
| institution | Directory Open Access Journal |
| issn | 1661-6596 1422-0067 |
| language | English |
| last_indexed | 2024-03-11T08:42:50Z |
| publishDate | 2023-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | International Journal of Molecular Sciences |
| spelling | doaj.art-4df39a2512cf412c99de15fd37bfdc922023-11-16T21:01:48ZengMDPI AGInternational Journal of Molecular Sciences1661-65961422-00672023-02-01244356210.3390/ijms24043562Recognition of Differentially Expressed Molecular Signatures and Pathways Associated with COVID-19 Poor Prognosis in Glioblastoma PatientsFaisal A. Alzahrani0Mohd Faheem Khan1Varish Ahmad2Department of Biochemistry, Faculty of Science, Embryonic Stem Cell Unit, King Fahad Center for Medical Research, King Abdulaziz University, Jeddah 21589, Saudi ArabiaDepartment of Biotechnology, Khandelwal College of Management Science and Technology (KCMT), Mahatma Jyotiba Phule Rohilkhand University, Bareilly 243006, IndiaHealth Information Technology Department, The Applied College, King Abdulaziz University, Jeddah 21589, Saudi ArabiaGlioblastoma (GBM) is a type of brain cancer that is typically very aggressive and difficult to treat. Glioblastoma cases have been reported to have increased during COVID-19. The mechanisms underlying this comorbidity, including genomic interactions, tumor differentiation, immune responses, and host defense, are not completely explained. Therefore, we intended to investigate the differentially expressed shared genes and therapeutic agents which are significant for these conditions by using in silico approaches. Gene expression datasets of GSE68848, GSE169158, and GSE4290 studies were collected and analyzed to identify the DEGs between the diseased and the control samples. Then, the ontology of the genes and the metabolic pathway enrichment analysis were carried out for the classified samples based on expression values. Protein–protein interactions (PPI) map were performed by STRING and fine-tuned by Cytoscape to screen the enriched gene module. In addition, the connectivity map was used for the prediction of potential drugs. As a result, 154 overexpressed and 234 under-expressed genes were identified as common DEGs. These genes were found to be significantly enriched in the pathways involved in viral diseases, NOD-like receptor signaling pathway, the cGMP-PKG signaling pathway, growth hormone synthesis, secretion, and action, the immune system, interferon signaling, and the neuronal system. STAT1, CXCL10, and SAMDL were screened out as the top 03 out of the top 10 most critical genes among the DEGs from the PPI network. AZD-8055, methotrexate, and ruxolitinib were predicted to be the possible agents for the treatment. The current study identified significant key genes, common metabolic signaling networks, and therapeutic agents to improve our perception of the common mechanisms of GBM–COVID-19.https://www.mdpi.com/1422-0067/24/4/3562hub genesCOVID-19GBMco-expression networkprotein–protein interaction network |
| spellingShingle | Faisal A. Alzahrani Mohd Faheem Khan Varish Ahmad Recognition of Differentially Expressed Molecular Signatures and Pathways Associated with COVID-19 Poor Prognosis in Glioblastoma Patients International Journal of Molecular Sciences hub genes COVID-19 GBM co-expression network protein–protein interaction network |
| title | Recognition of Differentially Expressed Molecular Signatures and Pathways Associated with COVID-19 Poor Prognosis in Glioblastoma Patients |
| title_full | Recognition of Differentially Expressed Molecular Signatures and Pathways Associated with COVID-19 Poor Prognosis in Glioblastoma Patients |
| title_fullStr | Recognition of Differentially Expressed Molecular Signatures and Pathways Associated with COVID-19 Poor Prognosis in Glioblastoma Patients |
| title_full_unstemmed | Recognition of Differentially Expressed Molecular Signatures and Pathways Associated with COVID-19 Poor Prognosis in Glioblastoma Patients |
| title_short | Recognition of Differentially Expressed Molecular Signatures and Pathways Associated with COVID-19 Poor Prognosis in Glioblastoma Patients |
| title_sort | recognition of differentially expressed molecular signatures and pathways associated with covid 19 poor prognosis in glioblastoma patients |
| topic | hub genes COVID-19 GBM co-expression network protein–protein interaction network |
| url | https://www.mdpi.com/1422-0067/24/4/3562 |
| work_keys_str_mv | AT faisalaalzahrani recognitionofdifferentiallyexpressedmolecularsignaturesandpathwaysassociatedwithcovid19poorprognosisinglioblastomapatients AT mohdfaheemkhan recognitionofdifferentiallyexpressedmolecularsignaturesandpathwaysassociatedwithcovid19poorprognosisinglioblastomapatients AT varishahmad recognitionofdifferentiallyexpressedmolecularsignaturesandpathwaysassociatedwithcovid19poorprognosisinglioblastomapatients |