Assessment of colon cancer molecular mechanism: a system biology approach

Babak Arjmand; Mahmood Khodadoost; Somayeh Jahani Sherafat; Mostafa Rezaei Tavirani; Nayebali Ahmadi; Maryam Hamzeloo Moghadam; Sina Rezaei Tavirani; Binazir Khanabadi; Majid Iranshahi

Assessment of colon cancer molecular mechanism: a system biology approach

Gastroenterol Hepatol Bed Bench. 2021 Fall;14(Suppl1):S51-S57.

Authors

Babak Arjmand¹, Mahmood Khodadoost², Somayeh Jahani Sherafat³, Mostafa Rezaei Tavirani⁴, Nayebali Ahmadi⁴, Maryam Hamzeloo Moghadam⁵, Sina Rezaei Tavirani⁶, Binazir Khanabadi⁶, Majid Iranshahi⁶

Affiliations

¹ Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
² School of Traditional Medicine Shahid, Beheshti University of Medical Sciences, Tehran, Iran.
³ Laser Application in Medical Sciences Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
⁴ Proteomics Research Center, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
⁵ Traditional Medicine and Materia Medica Research Center, School of Traditional Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
⁶ Gastroenterology and Liver Diseases Research Center, Research Institute for Gastroenterology and Liver Diseases, Shahid Beheshti University of Medical Sciences, Tehran, Iran.

PMID: 35154602
PMCID: PMC8817753

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.

Keywords: Bioinformatics; Colon cancer; Human; Network analysis; Protein expression.