ArticleInternational journal of molecular medicine2019
Bioinformatics-based study to detect chemical compounds that show potential as treatments for pulmonary thromboembolism.
Article in International journal of molecular medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 6 citations in OpenAlex.
- Construction and validation of risk prediction models for pulmonary embolism in hospitalized patients based on different machine learning methods.Frontiers in cardiovascular medicine · 2024Article
- Clinical Characteristics of Patients with Pulmonary Thromboembolism Based on Computer Statistical Analysis.Journal of healthcare engineering · 2022Article
- Integrated bioinformatics analysis of core regulatory elements involved in keloid formation.BMC medical genomics · 2021Article
- Lateral rectus muscle differentiation potential in paralytic esotropia patients.BMC ophthalmology · 2021Article
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Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The objectives of the present study comprised the recognition of major genes related to pulmonary thromboembolism (PTE) and the evaluation of their functional enrichment levels, in addition to the identification of small chemical molecules that may offer potential for use in PTE treatment. The RNA expression profiling of GSE84738 was obtained from the Gene Expression Omnibus database. Following data preprocessing, the differently expressed genes (DEGs) between the PTE group and the control group were identified using the Linear Models for Microarray package. Subsequently, the protein‑protein interaction (PPI) network of these DEGs was examined using the Search Tool for the Retrieval of Interacting Genes/Proteins database, visualized via Cytoscape. The most significantly clustered modules in the network were identified using Multi Contrast Delayed Enhancement, a plugin of Cytoscape. Subsequently, functional enrichment analysis of the DEGs was performed, using the Database for Annotation Visualization and Integrated Discovery tool. Furthermore, the chemical‑target interaction networks were investigated using the Comparative Toxicogenomics Database as visualized via Cytoscape. A total of 548 DEGs (262 upregulated and 286 downregulated) were identified in the PTE group, compared with the control group. The upregulated and downregulated genes were enriched in Gene Ontology terms related to inflammation and eye sarcolemma, respectively. Tumor necrosis factor (TNF) and erb‑b2 receptor tyrosine kinase 2 (ERBB2) were upregulated genes that ranked higher in the PPI network (47 and 40 degrees, respectively) whereas C‑JUN was the most downregulated gene (46). Small chemical molecules ethinyl (135), cyclosporine (126), thrombomodulin precursor (113) and tretinoin (111) had >100 degrees in the DEG‑chemical interaction network. In addition, ethinyl targeted to TNF, whereas TNF and ERBB2 were targeted by cyclosporine, and tretinoin was a targeted chemical of ERBB2. Therefore, cyclosporine, ethinyl, and tretinoin may be potential targets for PTE treatment.
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