Volume 7, Issue 4 (3-2021)
jhbmi 2021, 7(4): 453-465 |
Back to browse issues page
Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:
Allahyari Fard N, Davari A, Karbalaei A, Zamani M R. Investigation of Network of Proteins Effective in Esophageal, Gastric and Colon Cancers and Determination of Key Common Proteins Using In Silico Method. jhbmi 2021; 7 (4) :453-465
URL: http://jhbmi.ir/article-1-472-en.html
URL: http://jhbmi.ir/article-1-472-en.html
Ph.D. in Biology-Molecular Genetics, Assistant Professor, Systems Biotechnology Dept., National Institute of Genetic Engineering & Biotechnology (NIGEB), Tehran, Iran
Abstract: (2087 Views)
Introduction: The prevalence of gastrointestinal cancers, especially gastric and colorectal cancers, is increasing. Gastric cancer is the most common gastrointestinal cancer in Iran and the age of esophageal and colon cancers onset has decreased in Iran. Therefore, it is important to study the factors and proteins involved in these cancers. Use of computational tools is an effective way to study protein networks and identify the important proteins involved in these diseases.
Method: At first identified proteins from esophageal, gastric and colon cancers were extracted from relevant databases and articles; then, the Protein-Protein Interaction (PPI) networks were mapped and analyzed for cross-linking and determination of key proteins using servers and software such as STRING 11.0, Cytoscape 3.7.3, NDEx 2.4.3, and UniProt. The CentiScaPe 2.2 plugin was used by examining the centrality indices (Betweenness, Closeness, Degree) and the CytoHubba plugin was used by different centrality indices for determination of the key nodes and the central common proteins. Finally, after investigation of the expression profiles of proteins with high centrality indices using GTEx v8, Expression Atlas, and GEPIA2, the final common proteins were determined in all three cancers.
Results: The results showed that PLK1, CCNB1, CCNA2, BUB1B, and CDK1 proteins are the central common proteins in all three tissues. These proteins are highly correlated (R => 0.8) with each other and have significant expression differences in normal and cancerous tissues.
Conclusion: PLK1, CCNB1, CCNA2, BUB1B, and CDK1 proteins can be used as diagnostic and therapeutic markers for esophageal, gastric, and colon cancers. Further studies on these proteins will have a bright future for the treatment of various types of gastrointestinal cancer.
Method: At first identified proteins from esophageal, gastric and colon cancers were extracted from relevant databases and articles; then, the Protein-Protein Interaction (PPI) networks were mapped and analyzed for cross-linking and determination of key proteins using servers and software such as STRING 11.0, Cytoscape 3.7.3, NDEx 2.4.3, and UniProt. The CentiScaPe 2.2 plugin was used by examining the centrality indices (Betweenness, Closeness, Degree) and the CytoHubba plugin was used by different centrality indices for determination of the key nodes and the central common proteins. Finally, after investigation of the expression profiles of proteins with high centrality indices using GTEx v8, Expression Atlas, and GEPIA2, the final common proteins were determined in all three cancers.
Results: The results showed that PLK1, CCNB1, CCNA2, BUB1B, and CDK1 proteins are the central common proteins in all three tissues. These proteins are highly correlated (R => 0.8) with each other and have significant expression differences in normal and cancerous tissues.
Conclusion: PLK1, CCNB1, CCNA2, BUB1B, and CDK1 proteins can be used as diagnostic and therapeutic markers for esophageal, gastric, and colon cancers. Further studies on these proteins will have a bright future for the treatment of various types of gastrointestinal cancer.
Keywords: Esophageal Cancer, Gastric Cancer, Colon Cancer, Interactive Protein Network, Central Protein, Systems Biology
Audio File [MP3 2204 KB] (59 Download)
Send email to the article author
| Rights and permissions | |
 |
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. |
