Publications by authors named "Sina Rezaei Tavirani"

16 Publications

  • Page 1 of 1

Evaluation of long-term consumption of omeprazole disadvantages: a network analysis.

Gastroenterol Hepatol Bed Bench 2020 ;13(Suppl1):S98-S105

Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Aim: Evaluation of deregulated genes after long-term consuming of omeprazole via network analysis.

Background: Proton pump inhibitors (PPIs) are used to inhibit gastric high rate of acid secretion in patients. Omeprazole as a PPI is a common drug in this regard. Evaluation of long-term consumption of omeprazole is studied in the present study via its effects on the gene expression of "human coronary artery endothelial cells".

Methods: Net effect of the presence of omeprazole on gene expression profiles of "human coronary artery endothelial cells" was evaluated through data from gene expression omnibus (GEO). Results of protein-protein interaction (PPI) network analysis were assessed via biological process examination to find the critical deregulated genes after long-term consumption of omeprazole.

Results: "Negative regulation of muscle cell apoptotic process", "negative regulation of DNA binding", "telencephalon cell migration", "forebrain cell migration" "response to cadmium ion", "cell-cell recognition", "positive regulation of protein targeting to mitochondrion", and "central nervous system neuron development" were the clusters of biological processes that were associated to the long -term presence of omeprazole. The final critical deregulated genes were JAK2, PTK2, and NRG1.

Conclusion: It can be concluded that cell cycle, proliferation, and apoptosis and several essential biological processes are affected and nervous system is a possible target related to the long-term consumption of omeprazole.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881401PMC
January 2020

Introducing GATA3 as a prominent player in Crohn's disease.

Gastroenterol Hepatol Bed Bench 2020 ;13(Suppl1):S53-S59

Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Aim: This study was aimed at gene assessment of Crohn's disease (CD) through protein-protein interaction (PPI) network analysis to find crucial genes.

Background: CD is a major subtype of inflammatory bowel diseases (IBD), which affects gastrointestinal tract. PPI network analysis is a suitable tool to clarify a critical gene as a drug target or diagnostic biomarker for these types of diseases.

Methods: Gene expression profile GSE126124 of 20 CD patients and 20 healthy controls was obtained from the Gene Expression Omnibus (GEO) database. RNA profile of peripheral blood mononuclear cells (PBMCs) and colon biopsy samples of the studied groups was investigated. Crucial genes were selected and analyzed via the PPI network by Cytoscape software. Gene ontology enrichment for the hubs, bottlenecks, and hub-bottlenecks was performed via CluGO plugin of Cytoscape software.

Results: Eighty-one differentially expressed genes (DEGs) among 250 initial DEGs were highlighted as significant by FC>2 and p-value ≤ 0.05, and 69 significant DEGs were used for PPI network construction. The network was characterized by poor connections, so 20 top neighbors were added to form a scale-free network. The main connected component included 39 query DEGs and 20 added first neighbors. Three clusters of biological processes associated with crucial genes were identified and discussed.

Conclusion: The results of this study indicated that GATA3 has a key role in CD pathogenesis and could be a possible drug target or diagnostic biomarker for Crohn's disease.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7881413PMC
January 2020

Immunological reactions by T cell and regulation of crucial genes in treated celiac disease patients.

Gastroenterol Hepatol Bed Bench 2020 ;13(2):155-160

Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Aim: To assess the immunological reactions and gene expression level in the celiac disease (CD) patients under a gluten-free diet (GFD).

Background: CD is an autoimmune disorder in genetic susceptible individuals and lifelong gluten free diet is the effective treatment method. It seems that treated patients will experience a normal life style though there are documents about some potential damages.

Methods: Gene expression profiles of treated CD patients and healthy samples were obtained from Gene Expression Omnibus (GEO) and compared to find the differentially expressed genes (DEGs). The identified DEGs were introduced in the network and gene ontology (GO) analysis.

Results: Ten differentially expressed genes (DEGs) including CCR2, IRF4, FASLG, CCR4, ICOS, TNFSF18, BACH2, LTF, PRM1, and PRM2 were investigated via network analysis. Seven clusters of biological processes (BP) were determined as the affected BP. PThe finding led to introduction of CCR2, IRF4, FASLG, CCR4, and ICOS as the potential immunological markers that are still active despite GFD in the treated CD patients.

Conclusion: The results of this study indicated that the immune system is already active in treated CD patients despite GFD treatment and exposure to gluten causes potential immunological reactions in these patients.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7149810PMC
January 2020

Introducing Critical Pain-related Genes: A System Biology Approach.

Basic Clin Neurosci 2019 Jul-Aug;10(4):401-408. Epub 2019 Jul 1.

Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.32598/bcn.9.10.310DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7101522PMC
July 2019

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

Gastroenterol Hepatol Bed Bench 2019 ;12(Suppl1):S130-S135

Firoozabadi Clinical Research Development Unit, Iran University of Medical Sciences, Tehran, Iran.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7011064PMC
January 2019

Introducing tumor necrosis factor as a prominent player in celiac disease and type 1 diabetes mellitus.

Gastroenterol Hepatol Bed Bench 2019 ;12(Suppl1):S123-S129

Laser Application in Medical Sciences Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Aim: This study aimed to screen the common genes between celiac disease (CD) and type 1 diabetes mellitus to find critical ones.

Background: Celiac disease is a chronic autoimmune disorder which is correlated to type 1 diabetes mellitus (T1DM) in several molecular pathways. Understanding the clear common molecular mechanism of both diseases is of interest to scientists.

Methods: The related genes to the CD and T1DM were obtained from disease query of STRING and included in two separated PPI networks by Cytoscape software version 3.7.1. The networks were analyzed by network analyzer and the hub nodes were determined. The common hubs between the two networks were selected for further analysis and enriched via gene ontology using ClueGO plugin of Cytoscape software. Also, an action map was provided by Cluepedia application of Cytoscape software.

Results: Two separated networks of 2000 and 430 genes were constructed related to T1DM and CD, respectively. A total of 84 and 28 hubs were determined for T1DM and CD, respectively. There were 11 common hubs between the two networks. The first top hubs of Type 1 Diabetes Mellitus and CD networks were insulin (INS) and tumor necrosis factor (TNF), respectively. Also, 77 biological terms and pathways (in five clusters) were related to the common hubs. Action map revealed a close relationship between hubs.

Conclusion: The result of this study indicated that TNF is key mediator of immune reactions in celiac disease and type 1 diabetes mellitus.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7011075PMC
January 2019

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

J Lasers Med Sci 2019 1;10(Suppl 1):S1-S6. Epub 2019 Dec 1.

Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

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. 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. 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. The laser affected the main biological processes and simultaneously issued side effects.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://dx.doi.org/10.15171/jlms.2019.S1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6983861PMC
December 2019

The critical role of dysregulation of antioxidant activity and carbohydrate metabolism in celiac disease.

Gastroenterol Hepatol Bed Bench 2019 ;12(4):340-347

Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Aim: Identification of the important processes and the related genes that are dis-regulated in the celiac disease (CD) was the aim of this study.

Background: Celiac disease is an autoimmune disorder which is characterized by immune reaction response mostly to wheat gluten. The gluten-free diet is the best-known treatment of the patients.

Methods: Significant differentially expressed proteins (DEPs) related to the CD are extracted from a published proteomics study and are included in protein-protein interaction PPI) network analysis by Cytoscape software and its applications. The central proteins and related processes are identified and discussed.

Results: Among 53 queried genes, 51 individuals were recognized by the database, and after network construction, 48 ones included in the network, and three genes remained as isolated nodes. Following 50 neighbors, the network was analyzed, and eight central genes were identified as dis-regulated elements. Related processes and the role of the central genes in celiac are discussed in detail.

Conclusion: CAT, ENO1, PCK2, ACO2, ALDOOB, GALM, ADA, and ACTBADA as critical genes and Antioxidant activity, carbohydrate metabolism, inflammation, cell growth processes are highlighted as the dis-regulated individuals in CD.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6820838PMC
January 2019

Highlighted role of VEGFA in follow up of celiac disease.

Gastroenterol Hepatol Bed Bench 2019 ;12(3):254-259

Firoozabadi Clinical Research Development Unit (FACRDU), Iran University of Medical Sciences, Tehran, Iran.

Aim: Evolution of gene expression change of intestine tissue in celiac patients to find a new molecular prospective of disease is the aim of this study.

Background: Celiac disease (CD) as an autoimmune disease is known as an immune reaction response to the gluten in patients. It is reported that genetic and environmental conditions are important in onset and progress of CD.

Methods: gene expression profiles of intestinal tissue in 12 celiac patients and 12 healthy controls from gene expression omnibus (GEO) were downloaded and verified by boxplot analysis. The significant and selected differentially expressed genes (DEGs) were included protein-protein interaction (PPI) network analysis. The central nodes were identified by network analyzer.

Results: The network was constructed from 161 query DEGs and 50 additional neighbors. GTF2H1, VEGFA, SUMO1, RAD51, MED21, BBP4, LEP, and MAP2K7 as potent hub nodes LRP5, RABGEF1, BCAS2, DYRK1B, AOC3, RABL2A, CRTAP, VEGFA, and SPOPL as potent bottlenecks are introduced as crucial nodes.

Conclusion: Among the crucial DEGs, Vascular endothelial growth factor A (VEGFA) was highlighted as an important biomarker candidate for follow up of celiac patients.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6668760PMC
January 2019

Gene screening of colorectal cancers via network analysis.

Gastroenterol Hepatol Bed Bench 2019 ;12(2):149-154

Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

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 . 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6536014PMC
January 2019

Gene expression profile analysis of colon cancer grade II into grade III transition by using system biology.

Gastroenterol Hepatol Bed Bench 2019 ;12(1):60-66

Skin Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6441480PMC
January 2019

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

Gastroenterol Hepatol Bed Bench 2018 ;11(Suppl 1):S98-S104

Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6347987PMC
January 2018

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

Gastroenterol Hepatol Bed Bench 2018 ;11(4):343-351

Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6204252PMC
January 2018

Celiac disease microarray analysis based on System Biology Approach.

Gastroenterol Hepatol Bed Bench 2018 ;11(3):216-224

Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

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 protein-protein 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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6040039PMC
January 2018

Biochemical pathway analysis of gastric atrophy.

Gastroenterol Hepatol Bed Bench 2018 ;11(2):118-124

Faculty of Medicine, Iran University of Medical Sciences, Tehran, Iran.

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.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5990925PMC
January 2018

Pancreatic adenocarcinoma protein-protein interaction network analysis.

Gastroenterol Hepatol Bed Bench 2017 ;10(Suppl1):S85-S92

Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

Aim: Gene assessment of pancreatic adenocarcinoma disease via protein-protein interaction (PPI) Network Analysis.

Background: Diagnosis, especially early detection of pancreatic adenocarcinoma as a lethal disease implies more investigation. PPI Network Analysis is a suitable tool to discover new aspects of molecular mechanism of diseases.

Methods: In the present study the related genes to pancreatic adenocarcinoma are studied in the interactome unit and the key genes are highlighted. The significant clusters were introduced by Cluster-ONE application of Cytoscape software 3.4.0. The genes are retrieved from STRING date base and analyzed by Cytoscape software. The crucial genes based on analysis of central parameters were determined and enriched by ClueGO v2.3.5 via gene ontology.

Results: The number of 24 key genes among 794 initial genes were highlighted as crucial nodes in relationship with pancreatic adenocarcinoma. All of the key genes were organized in a cluster including 216 nodes. The main related pathways and cancer diseases were determined.

Conclusion: It was concluded that the introduced 24 genes are possible biomarker panel of pancreatic adenocarcinoma.
View Article and Find Full Text PDF

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5838186PMC
January 2017