Identification of Targeted Central Genes (IGF1 and HMOX1) by Indirect Cold Physical Plasma in Human Melanocytes: Identification of Targeted Central Genes by Indirect Cold Physical Plasma
نویسندگان
1 Laser Application in Medical Sciences Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
2 Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
3 Proteomics Research Center, 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 Traditional Medicine and Materia Medica Research Center, School of Traditional Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
6 Laser Application in Medical Sciences Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
doi
40191چکیده
Introduction: Cold physical plasma is a growing tool in medicine that is applied for the treatment of different cancers. In the present study, the gene profiles of human melanocytes exposed to indirect cold physical plasma versus control individuals are analyzed via protein-protein interaction (PPI) network analysis.Methods: The gene expression profiles were derived from Gene Expression Omnibus (GEO), and the significant differentially expressed genes (DEGs) were decoded via “Expression Atlas”. PPI network analysis was applied to find the targeted central genes by indirect cold physical plasma.Results: The main connected component of the constructed network including 74 queried DEGs and 50 added first neighbors was analyzed. Considering degree value, betweenness centrality, closeness centrality, and stress, IGF1 and HMOX1 were introduced as the central nodes.Conclusion: The finding of this study indicates that the down-regulation of IGF1 and the upregulation of HMOX are the prominent events in response to indirect cold physical plasma treatmentat the cellular level. Detection of related biological terms via gene ontology is suggested.
