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Aim: The current study aimed to introduce the key proteins involved in liver ischemia/reperfusion (I/R) injury through protein-protein interaction (PPI) analysis. Background: Liver transplantation (LT) is a well-known treatment for liver diseases that threaten patients with mortality. LT is a complex operation, and several risks, including liver I/R injury, affect its success. Improving LT requires detection of its molecular mechanism. Experiments have revealed that high throughput methods such as proteomics in combination with bioinformatics are useful tools for analyzing the molecular mechanism of disease. Methods: The differentially expressed proteins (DEPs) involved in liver I/R injury were extracted from the literature. The queried DEPs plus the first 100 neighbors were included in a network through STRING database using Cytoscape software. Degree, betweenness centrality, closeness centrality, and stress were considered to determine the central nodes. The queried DEPs were assessed by action map analysis using the CluePedia application of Cytoscape software. The key proteins were identified by comparing network analysis and action map evaluation results. Results: Six proteins, namely ALB, INS, GAPDH, CAT, IL6, and TNF, among the added first neighbors were determined as the central first neighbors. MPO, CRP, MMP9, and HMOX1 were selected as central DEPs among the queried proteins. Action map analysis confirmed the PPI findings. The final evaluation revealed that MMP9 in combination with CRP and HMOX1 plays a critical role in liver I/R injury. Conclusion: The significant role of MMP9 in liver I/R injury was detected in this study. Two central proteins (CRP and HMOX1) were shown to have a regulatory effect on MMP9; CRP activated MMP9, while HMXO1 downregulated it. [ABSTRACT FROM AUTHOR]

Introduction: It is reported that migraine may be a risk factor for brain cancers. Since one of the best ways to assess this possible relationship is to study the molecular mechanism, here the common central dysregulated proteins between these diseases are investigated via network analysis. Methods: The dysregulated proteins of migraine and gliosarcoma are extracted from the STRING database and interacted via Cytoscape software, version 3.7.2. to form two separate networks. Central nodes of the networks are compared to find the common central district proteins. First neighbors of the common central proteins are studied. Results: The number of 11 hub bottlenecks was identified for each of the migraine and gliosarcoma cancer networks. Albumin (ALB) and interleukin 6 (IL6) were introduced as common differentially expressed central proteins. Kininogen 1 (KNG1), vascular endothelial growth factor A (VEGFA), and neurofibromatosis type I (NF1) the first neighbors of ALB-IL6 were connected to the central nodes of networks of the two studied diseases. Conclusion: ALB and IL6 can be considered molecular links between migraine and brain cancers. [ABSTRACT FROM AUTHOR]

Introduction: Cold physical plasma is a growing tool in medicine which 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 treatment at the cellular level. Detection of related biological terms via gene ontology is suggested. [ABSTRACT FROM AUTHOR]

Aim: The current study aimed to assess and compare colon cancer dysregulated genes from the GEO and STRING databases. Background: Colorectal cancer is known as the third most common kind of cancer and the second most important reason for global cancer-related mortality rates. There have been many studies on the molecular mechanism of colon cancer Methods: From the STRING database, 100 differentially expressed proteins related to colon cancers were retrieved and analyzed by network analysis. The central nodes of the network were assessed by gene ontology. The findings were compared with a GSE from GEO. Results: Based on data from the STRING database, TP53, EGFR, HRAS, MYC, AKT1, GAPDH, KRAS, ERBB2, PTEN, and VEGFA were identified as central genes. The central nodes were not included in the significant DEGs of the analyzed GSE. Conclusion: A combination of different database sources in system biology investigations provides useful information about the studied diseases. [ABSTRACT FROM AUTHOR]

Aim: To assess the effects of omeprazole on the human cardiovascular system is the main aim of this study. Background: Omeprazole as a proton pump inhibitor is widely consumed to inhibit gastric acid secretion. Methods: Gene expression profiles of "human coronary artery endothelial cells" in the absence and presence of omeprazole were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) interacted as an interactome, and the hub nodes are determined. The DEGs were enriched via gene ontology (GO) analysis. The critical hubs were identified based on the GO findings. Results: Among 103 queried DEGs, 61 individuals were included in the main connected component. CTNNB1, HNRNPA1, SRSF4, TRA2A, SFPQ, and RBM5 genes were identified as critical hub genes. Six clusters of biological terms were introduced as deregulated elements in the presence of omeprazole. Conclusion: In conclusion, long-term consumption of omeprazole may be accompanied with undesirable effects, however more evidence is required. [ABSTRACT FROM AUTHOR]

Introduction: Genomics and bioinformatics are useful methods for exploring unclear aspects of radiation effects on biological systems. Many radiation-induced alterations in irradiated samples are post-radiation time-dependent. This study aims to evaluate the post-irradiation effects of the gamma ray on human Jurkat cells. Methods: Gene expression profiles of the samples harvested 6 and 24 hours after radiation to find the critical differential expressed genes and the related pathways. Samples are provided from Gene Expression Omnibus (GEO) and analyzed by ClueGO. Results: Twnety-nine critical genes were determined as the important affected genes and 7 classes of related pathways were introduced. CCNE2, PSMD11, CDC25C, ANAPC1, PLK1, AURKA, and CCNB1 that were associated with more than 6 pathways were related to one of the determined pathway groups. Conclusion: Cell protecting pathways were associated with the genes (HSPA5, HSPA8, HSP90B1, HMMR, CEBPB, RXRA, and PSMD11) which were related to the minimum numbers of pathways. The finding of this study corresponds to repair processes which depend on post-radiation time. It seems these sets of genes are suitable candidates for further investigation. [ABSTRACT FROM AUTHOR]

Introduction: Low-level laser therapy (LLLT) is accompanied by protein expression change in the body. There are many efforts to find a clear relationship between the differentially expressed proteins. This study aims to find the central differentiated expressed proteins of plasma after LLLT. Methods: Six proteins are extracted from a proteomics study and the network including these query proteins plus 100 first neighbors was constructed. The central proteins were determined based on degree value, betweenness centrality, closeness centrality (CC), and stress (The centrality parameters). Results: Among 106 nodes of the network, 10 proteins were characterized with the most values of degree, betweenness centrality, CC, and stress. These proteins were determined as central proteins in response to LLLT in plasma. Conclusion: Three query proteins, AHSG, FGG, and SERPINA1, plus 7 first neighbors, namely FGA, ALB, KNG1, FN1, APP, TIMP1, and F5, were identified as central proteins which were dysregulated. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Introduction: Pain is valuable in diagnosis and also warning of the patients. Many molecular reagents are introduced which are related to pain. In this research, the pain-related genes are screened to identify the critical ones. Methods: First, the pain-related genes were pulling out from the STRING database, and Cytoscape software was used to make the interactome unit. Then the central genes and their neighbors were analyzed. Finally, the genes were clustered, and the essential genes were introduced. Results: After analyzing 159 genes of the network, FOS, IL6, TNF, TAC1, IL8, and KNG1 were identified as the essential genes. Further analysis revealed that 88 genes are directly connected to the central genes. More resolution led to ignoring TNF and IL8 and considering SCN-alpha and PAICS as additional critical nodes. Conclusion: Six critical genes related to pain were identified. They can be potentially considered as new drug targets. Further investigation is required to introduce the central genes as a pain killer. [ABSTRACT FROM AUTHOR]

Aim: Identifying crucial genes related to colorectal cancers via protein-protein interaction (PPI) network analysis is the aim of this study. Background: colorectal cancer as major reason of mortality is evaluated by genetic and proteomic approaches to find suitable biomarkers. Chromosomal instability plays crucial role in CRC. Expression change of large numbers of genes is reported. Methods: Differentially expressed genes related to CRCs which obtained from different proteomic methods were extracted from a review article of Paula Álvarez-Chaver et al. The genes interacted by Cytoscape software via STRING database. The central nodes determined and were enriched for biological terms by ClueGO. Action map for central genes was illustrated by CluePedia. The critical genes in CRC were introduced. Results: Among 123 query genes, 114 one recognized by software and were included in the network. SRC, EGFR, PCNA, IL8, CTNNB1, TIMP1, CDH1, and HSPD1 were determined as central genes. After gene ontology analysis SRC, EGFR, and CDH1 were identified as critical genes related to CRC. Conclusion: It seems that SRC, EGFR, and CDH1 and the related pathways are possible biomarkers for CRC. [ABSTRACT FROM AUTHOR]

Aim: Gene expression profile analysis of colon cancer grade II into grade III transition by using system biology. Background: Colon cancer is one of lethal cancer in men and women. Treatment in advanced colon cancer is difficult and survival rate is low. Methods: Gene expression profiles of children patients with non-preforated appendicitis in comparison with the samples with non-appendicitis abdominal pain are analysis via protein - protein interaction PPI and the critical compounds are introduced by STITCH. Results: Six critical genes including MAPK3, AKT1, SRC, TP53, GAPDH, and ALB were identified as a possible biomarker panel related to colon cancer grade II to III transition. Among these critical genes roles of MAPK3, AKT1, SRC, TP53 are highlighted. Conclusion: It was concluded that target therapy to regulate SRC and TP53 may be the effective therapeutic way to treatment of colon cancer and more researches in necessary to design drugs for these purposes. [ABSTRACT FROM AUTHOR]

Background: Astrocytomas (sub-group of gliomas) are central neuron system malignant diseases, which are originated from astrocytes. There are several documents about molecular mechanism of astrocytomas and many related genes are introduced. Here, gene expression profile alteration for grade III relative to grade II of astrocytoma is analyzed via protein-protein interaction (PPI) network to screen and introduce critical differentially expressed genes (DEGs). Methods: The significant DEGs were extracted from gene expression omnibus (GEO) database and included in a PPI network by Cytoscape software. The common significant DEGs and central nodes of the network were selected and enriched by ClueGO to find related biological terms. Results: Twenty critical genes including zinc finger protein 765 (ZNF765), zinc finger protein 540 (ZNF540), Zeste white 10 (ZW10) ZW10interacting kinetochore protein (ZWINT), collagen type XVIII alpha 1 chain (COL18A1), protamine 2 (RRM2), kinesin familymember 23 (KIF23), minichromosome maintenance 10 (MCM10), anaphase promoting complex subunit 7 (ANAPC7), NADPH oxidase activator 1 (NOXA1), ryanodine receptor 2 (RYR2), myozenin 3 (MYOZ3), myosin binding protein C (MYBPC2), fast type, keratin 17 (KRT17), zinc phosphodiesterase ELAC protein 2 (ELAC2), Abelson helper integration site 1 (AHI1), latent transforming growth factor beta binding protein 1 (LTBP1), kaptin (actin binding protein) (KPTN), BEN domain containing 3 (BEND3), cysteine and histidine rich 1 (CYHR1), and hyaluronoglucosaminidase 2 (HYAL2) were identified. Eight class of biological terms related to the critical genes were determined and discussed. Conclusions: A wide range of the introduced significant genes indicates that there are several possible therapeutic ways to challenge astrocytoma. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Aim: Aim of this study is screen of the large numbers of related genes of CD to find the key ones. Background: Celiac disease (CD) is known as a gluten sensitive and immune system dependent disease. There are several high throughput investigations about CD but it is necessary to clarify new molecular aspects mechanism of celiac. Methods: Whole-genome profile (RNA) of the human peripheral blood mononuclear cells (PBMCs) as Gene expression profile GSE113469 was retrieved Gene Expression Omnibus (GEO) database. The significant genes were selected and analyzed via proteinprotein interaction (PPI) network by Cytoscape software. The key genes were introduced and enriched via ClueGO to find the related biochemical pathways. Results: Among 250 significant genes 47 genes with expressed change above 2 fold change (FC) were interacted and the constructed network were analyzed. The network characterized by poor connections so it was promoted by addition 50 related nodes and 18 crucial nodes were introduced. Two clusters of biochemical pathways were identified and discussed. Conclusion: There is an obvious conflict between microarray finding and the well-known related genes of CD. This problem can be solve by more attention to the interpretation of PPI ntwork analysis results. [ABSTRACT FROM AUTHOR]

Background: Gliosarcoma (GS) is a rare primary neoplasm of the central nervous system. It is a subtype of glioblastoma and has a biphasic pattern consisting of glial and malignant mesenchymal elements. Its onset is between the fourth and sixth decade of life. Objectives: Since protein - protein interaction (PPI) network analysis can provide useful information about molecular aspects of diseases, the aim of this study is GS protein analysis via PPI network and gene ontology assessment. Methods: The related genes to GS were gathered from STRING DB and organized in the interacted network by Cytoscape software version 3.6.0. The network was analyzed based on topological parameters and the central nodes were introduced. The significant clusters were identified by ClusterONE and the cluster included more key genes enriched via gene ontology by ClueGO. Results: Nine crucial genes including TP53, EGFR, PTEN, EGR1, VEGFA, HSP90AA1, IL2, KNG1, and HSP90AB1 were introduced as related key genes to GS. Two significant clusters contain most of central genes. Twenty - one elements of cluster - 1, which included 7 key genes, were enriched via gen ontology and 115 related terms were determined and discussed. Conclusions: The nine introduced central genes may play main roles in pathology of GS. However, experimental investigation is proposed to validate the findings. [ABSTRACT FROM AUTHOR]

Aim: Pathway analysis of gastric atrophy to find new molecular prospective of disease. Background: Gastric atrophy as a process which is accompanied with "loss of glans" in stomach can be considered as a risk factor of gastric cancer. Here, the correlated biochemical pathways to the disorder have been analyzed via protein-protein interaction (PPI) network analysis. Methods: The genes related to gastric atrophy were retrieved by STRING database and organized in a network by Cytoscape. Three significant clusters were determined by ClusterONE plug-in of Cytoscape. The elements of cluster-2 which contained all central nodes of the network were enriched by ClueGO and the biochemical pathways discussed in details. Results: The number of seven central nodes (which are included in cluster-2); INS, TP53, IL6, TNF, SRC, MYC, and IL8 were identified. The biochemical pathways related to the elements of cluster-2 were determined and clustered in nine groups. The pathways were discussed in details. Conclusion: Pathway analysis indicates that the introduced central genes of the network can be considered as biomarkers of gastric atrophy. [ABSTRACT FROM AUTHOR]