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Assessment of Colon Cancer Molecular Mechanism: A System Biology Approach Publisher



Arjmand B1 ; Khodadoost M2 ; Sherafat SJ3 ; Tavirani MR4 ; Ahmadi N4 ; Moghadam MH5 ; Tavirani SR6 ; Khanabadi B6 ; Iranshahi M6
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Authors Affiliations
  1. 1. Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
  2. 2. School of Traditional Medicine Shahid, Beheshti University of Medical Sciences, Tehran, Iran
  3. 3. Laser Application in Medical Sciences Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  4. 4. Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  5. 5. Traditional Medicine, Materia Medica Research Center, School of Traditional Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
  6. 6. Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran

Source: Gastroenterology and Hepatology from Bed to Bench Published:2021


Abstract

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. ©2021 RIGLD, Research Institute for Gastroenterology and Liver Diseases
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