TANAFFOS (Respiration)

TANAFFOS (Respiration)

Network Analysis of Severe Asthma in Female Patients to Find Possible Drug Targets

Document Type : Original Article

Authors
1 Skin Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
2 Laser Application in Medical Sciences Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
3 Clinical Tuberculosis and Epidemiology Research Center, National Research Institute of Tuberculosis and Lung Diseases (NRITLD), Shahid Beheshti University of Medical Sciences, Tehran, Iran
4 Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
5 Iranian Cancer Control Center (MACSA), Tehran, Iran
6 Celiac Disease and Gluten Related Disorders Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran
7 Proteomics Research Center, System Biology Institute, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Abstract
Background: Severe asthma (SA) has been a challenging health issue worldwide. In this view, a complementary study of gene expression profiles could be helpful. Protein-protein interaction network analysis could help better understand the molecular changes and, ultimately, the underlying mechanisms of treatment approaches. The identification of the critical genes involved in severe asthma is the main aim of this study.
Materials and Methods: Data were retrieved from the Gene Expression Omnibus (GEO) database and pre-evaluated via GEO2R to find the significantly differentially expressed genes (DEGs). Cytoscape software and its plugin were used to facilitate protein-protein interaction (PPI) network analysis and gene ontology enrichment.
Results: A total of 30 significant DEGs were identified as the genes that differentiate severe asthma from control samples. PPI network analysis led to the identification of four hub-bottlenecks, including TP53, AKT1, ACTB, and EGFR, and two hubs (GAPDH and PTEN). DLG4 was highlighted as a bottleneck node. “Nitric-oxide synthase”, “lymphocyte apoptotic process”, “regulation of cyclin-dependent protein serine/threonine kinase activity”, and “positive regulation of miRNA maturation” biological processes were linked to the central genes.
Conclusion: AKT1 and EGFR, and the related biological processes, can be considered as the possible drug targets for severe asthma.
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