Assessment of Cytokine-Mediated Signaling Pathway Dysregulation in Arm Skin After CO2 Laser Therapy.

Introduction: Laser therapy is known as an efficient approach in dermatology surgery. CO2 laser therapy is a gold standard treatment in skin surgery. This study aimed to evaluate the interferons change after CO2 laser surgery Methods: Significant differentially-expressed genes (DEGs) of arm skin after 7 days of treatment by the CO2 laser relative to the controls are downloaded from Gene Expression Omnibus (GEO) and are included in the protein-protein interaction network via a STRING database (an application of Cytoscape software). The central DEGs were identified and enriched via gene ontology by using Clue GO software. Results: A network including 78 DEGs and 100 neighbors was constructed and STAT1, MX1, ISG15, OAS1, IFIT1, IRF8, OASL, OAS2, and RSAD2 as hubs and STAT1, PTPRC, MX1, IRF8, ISG15, IL6, RORC, SAMSN1, and IFIT1 as bottlenecks were introduced. The cytokine-mediated signaling pathway, interferon gamma signaling, hepatitis C, interferon alpha/beta signaling, and the type I interferon signaling pathway were identified as 5 clusters of biological terms which are related to the central nodes. Conclusion: It can be concluded that the cytokine-mediated signaling pathway is the major pathway that is dysregulated after laser application in the treated skin.

Analysis of Laser Therapy Effects on Squamous Cell Carcinoma Patients: A System Biology Study.

Introduction: The Mechanism of laser therapy and also its safety are 2 important features of the application of different types of lasers in medicine. This study aims to investigate the critically affected genes after the treatment of squamous cell carcinoma patients. Methods: The gene expression profiles of 4 squamous cell carcinoma patients that were treated via chemoradiotherapy (CRT) plus the laser and 3 similar patients without laser exposure from Gene Expression Omnibus (GEO) were downloaded and were screened to find critical genes via network analysis. The STRING database, Cytoscape software, and the Clue GO plug-in of Cytoscape software were used. Results: The genes HSX70 and NCC27 were determined as neighbors and HSPA1B, CLIC1, RAB13, PPIF, and LCE3D as hub genes. The over-expression of LCE3D was interpreted as the side effect of laser therapy. Apoptosis and the cell cycle were the dominant biological processes regulated by the HSP molecules in the laser-treated patients. Conclusion: The laser affected the main biological processes and simultaneously issued side effects.

The Highlighted Role of GAPDH and Nitric-Oxide Synthase Regulator Activity in Proton Beam Irradiated Melanoma BLM Cells.

Introduction: The human melanoma is a type of invasive tumor the treatment of which is challenging. To better understand the proton irradiation mechanisms as one of the widely applied therapy for this type of cancer, bioinformatics analysis of proteomics outcome could be beneficial. Methods: Protein-protein interaction network analysis of the differentially expressed proteins (DEPs) of melanoma BLM (BRO lung metastasis) cells in the treatment of 3 Gy dosage proton therapy was performed in this study via Cytoscape V.3.7.2. and its integrated plug-ins. Results: Eighteen DEPs were searched for network constructions and limited numbers of query +neighbor proteins were found central. The hub-bottlenecks (i.e. central nodes) were GAPDH, ACTB, ALB, AKT1, TP53, and EGFR. The fist mentioned proteins were from DEPs. The enrichment analysis of these elements identified nitric-oxide synthase regulator activity and the positive regulation of the norepinephrine uptake that may be the key to the mechanisms of proton therapy. Conclusion: In conclusion, the identified central nodes (EGFR, TP53, ALB, AKT1, GAPDH, and ACTB) and the related biological terms are the critical affected genes and biological terms in the irradiated melanoma cells.

Effects of high fat medium conditions on cellular gene expression profile: a network analysis approach.

AIM: This study aimed to evaluate high fat medium (HFM) effect on the gene expression profile of human Sk-hep1 cells and to determine critical differential proteins. BACKGROUND: There is a correlation between high fat diet (HFD), obesity, and non-alcoholic fatty liver disease. Despite wide range of investigations, understanding molecular mechanism of HFD effect on onset and progression of NAFLD warrants further examination. In this study, network analysis is applied to obtain a clear perspective about HFD effects and NAFLD. METHODS: Gene expression profiles of human Sk-hep1 cells treated with HFM versus controls were extracted from GEO. Data were analyzed by GEO2R where the significant and characterized DEGs were included in the PPI network. The top 10 nodes of query DEGs based on four centrality parameters were selected to determine central nodes. The common hub nodes with at least other one central group were identified as central nodes. Action map was provided for the introduced central nodes. RESULTS: Heterogeneous nuclear ribonucleoprotein family including A1, A2/B1, D, R, and D-like, and five proteins (PRPF40A, SRSF1, PCF11, LSM8, and HSP90AA1) were introduced as differential proteins. CONCLUSION: mRNA processing and several biological terms including hypoxia and oxidative stress, apoptosis, regulation of cell morphology and cytoskeletal organization, and differentiation of micro tubes were introduced as dysregulated terms under HFM condition.

Comparative study of gastric cancer and chronic gastritis via network analysis.

AIM: In this study the significant differentially expressed genes (DEGs) related to gastric cancer (GC) and chronic gastritis were screened to introduce common and distinctive genes between the two diseases. BACKGROUND: Diagnosis of gastric cancer as a mortal disease and chronic gastritis the stomach disorder which can be considered as risk factor of GCs required safe and effective molecular biomarkers. METHODS: Microarray profiles were downloaded from Gene Expression Omnibus (GEO) and analyzed via GEO2R. The candidate DEGs plus relevant genes from STRING database were interacted by Cytoscape software version 3.6.0 the central nodes were determined and analyzed. RESULTS: JUN, GAPDH, FOS, TP53, PRDM10, VEGFA, and CREB1 as central nodes and TFF1 and ERG1 as the top changed expressed genes were determined as critical nodes related to gastric cancer. GAPDH, PRDM10, TP53, JUN, AKT1, EGFR, MAPK1, EGF, DECR1, and MYC were identified as common remarkable genes between GC and chronic gastritis. CONCLUSION: Identification of distinctive and common genes between GC and chronic gastritis can be useful in the early stage detection of disease and reducing risk of GCs.

Barrett's esophagus network analysis revealed that arginine, alanine, aspartate, glutamate, valine, leucine and isoleucine can be biomarkers.

AIM: Identification of crucial genes and possible biomarkers which are involved in Barrett's esophagus (BE) disease was aim of this study. BACKGROUND: BE is diagnosed by endoscopy and biopsy and is characterized by esophageal columnar metaplastic epithelium. BE can convert into dysplasia that finally results cancer condition. METHODS: Gene expression profiles of BE and normal gastric cardia which are characterized by GSE34619 and GPL6244 platform (1) were retrieved from gene expression omnibus (GEO). The significant differentially expressed genes (DEGs) were analyzed via protein-protein interaction network (PPI) analysis. The nodes of network were enriched via gene ontology (GO) to find biological terms. Action map of network elements was provided. RESULTS: Among 250 top DEGs, 100 ones were included in PPI network and KIT, CFTR, IMPDH2, MYB, FLT1, ATP4A, and CPS1 were recognized as prominent genes related to BE. Seven amino acids including arginine, alanine, aspartate, glutamate, valine, leucine and isoleucine which are related to BE were highlighted. CONCLUSION: In conclusion five central DEGs; KIT, CFTR, IMPDH2, MYB, and FLT1 were proposed as possible biomarkers for BE. However, validation and more experimental information is require to finalize the findings.