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Identification of Candidate Biomarkers for Idiopathic Thrombocytopenic Purpura by Bioinformatics Analysis of Microarray Data Publisher



Gilanchi S1 ; Zali H2, 3 ; Faranoush M4 ; Tavirani MR2 ; Shahriary K5 ; Daskareh M6
Authors
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Authors Affiliations
  1. 1. Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  2. 2. Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Science, Tehran, Iran
  3. 3. School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  4. 4. Pediatric Growth and Development Research Center, Institute of Endocrinology, Iran University of Medical Sciences, Tehran, Iran
  5. 5. West Coast University PharmD campus, Los Angeles, CA, United States
  6. 6. Department of Radiology, Ziyaian Hospital, Tehran University of Medical Sciences, Tehran, Iran

Source: Iranian Journal of Pharmaceutical Research Published:2020


Abstract

Idiopathic Thrombocytopenic Purpura (ITP) is a multifactorial disease with decreased count of platelet that can lead to bruising and bleeding manifestations. This study was intended to identify critical genes associated with chronic ITP. The gene expression profile GSE46922 was downloaded from the Gene Expression Omnibus database to recognize Differentially Expressed Genes (DEGs) by R software. Gene ontology and pathway analyses were performed by DAVID. The biological network was constructed using the Cytoscape. Molecular Complex Detection (MCODE) was applied for detecting module analysis. Transcription factors were identified by the PANTHER classification system database and the gene regulatory network was constructed by Cytoscape. One hundred thirty-two DEGs were screened from comparison newly diagnosed ITP than chronic ITP. Biological process analysis revealed that the DEGs were enriched in terms of positive regulation of autophagy and prohibiting apoptosis in the chronic phase. KEGG pathway analysis showed that the DEGs were enriched in the ErbB signaling pathway, mRNA surveillance pathway, Estrogen signaling pathway, and Notch signaling pathway. Additionally, the biological network was established, and five modules were extracted from the network. ARRB1, VIM, SF1, BUB3, GRK5, and RHOG were detected as hub genes that also belonged to the modules. SF1 also was identified as a hub-TF gene. To sum up, microarray data analysis could perform a panel of genes that provides new clues for diagnosing chronic ITP. © 2020, Iranian Journal of Pharmaceutical Research. All rights reserved.