Evaluation of gene expression change in eosinophilic gastroenteritis.

AIM: Screening differentially expressed genes (DEGs) related to Eosinophilic gastroenteritis (EG) to introduce possible biomarkers. BACKGROUND: EG as a rare gastrointestinal disorder is characterized with gastrointestinal bleeding, crampy generalized abdominal pain, diarrhea, nausea, vomiting, and weight loss. In this study gene expression profile of patients is analysis via protein-protein interaction (PPI) analysis to reveal new prospective of disease. METHODS: Top significant genes of gene expression profiles of 5 gastric antrum EG patients and 5gastric antrum control from GEO which were matched via boxplot analysis were screened via PPI network by using Cytoscape software and STRING database. Numbers of 20 top nodes of query DEGs based on degree value were introduced as central nodes which 7 critical central genes among them were identified. Gene ontology enrichment for the 20 central genes was done by using CluGO. Action map for the central genes was performed by applying CluePedia. RESULTS: Among 20 central nodes, TXN, PRDX2, NR3C1, GRB2, PIK3C3, AP2B1 and REPS1 were recognized as critical central genes. Nine biological terms were determined that most of them were involved in the transport processes. CONCLUSION: The introduced possible biomarkers can be used in the differential diagnosis of the disease and also in treatment of disorder.

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

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.

Barrett's esophagus transits to a cancer condition via potential biomarkers.

AIM: In this study, the transcriptome profile of Barrett's esophagus (BE) was examined for identification potential related biomarkers in view of interacting charactering. BACKGROUND: Since BE is known as a precursor of esophageal cancer, the molecular studies of this condition could be essential. METHODS: Gene expression data of BE in comparison with normal cases, GSE34619 was retrieved from Gene Expression Omnibus. Differentially expressed genes (DEGs) were determined applying GEO2R online software. The DEGs then were analyzed in terms of centrality properties via constructing an interaction network. RESULTS: The data indicate that there are two sets of hub-bottlenecks panels with distinguishable values in BE. The first group shows that BE is very susceptible to develop cancer, and the second one implied on central characteristic of some DEGs as previously were also reported for BE pathogenicity. In addition, these genes are also implicated in cancer shift from certain conditions. CONCLUSION: On the whole, taking together these findings explain and support the cancerous origin of BE and introduced a panel of nominated biomarkers that could be more specific for BE rather than other types of esophageal problems. However, a complementary study to support this claim is suggested.