Publisher: Research Institute for Gastroenterology and Liver Diseases (RIGLD)
  • Register
  • Login

Gastroenterology and Hepatology from Bed to Bench

  • Home
  • Issues
    • Current
    • Archives
  • About
    • About the Journal
    • Aims and Scope
    • Editorial Team
    • Privacy Statement
    • Contact
  • For Authors
    • Submissions
    • Author Guidelines
    • Peer Review Process
  • Indexing & Abstracting
  • Announcements
Advanced Search
  1. Home
  2. Archives
  3. Vol 16, No 2 (2023): Spring
  4. Original Article

ISSN: 2008-2258

Vol 16, No 2 (2023): Spring

Network Analysis of Liver Cancer: A System Biology Approach

  • Babak Arjmand
  • Somayeh Jahani Sherafat
  • Mostafa Rezaei –Tavirani
  • Maryam Hamzeloo Moghadam
  • Mohammad Amin Abbasi

Gastroenterology and Hepatology from Bed to Bench, ,
https://doi.org/10.22037/ghfbb.v16i2.2514 Published 30 April 2023

  • View Article
  • Cite
  • References
  • Statastics
  • Share

Abstract

Background: Liver cancer as a common health problem is characterized by difficulties in early diagnosis and rapid progression. Due to lack of targeted drugs and the other features of disease the survival rate for patients is extremely low


Aim: Determining critical dysregulated proteins in liver cancer is the main aim of this study.


Methods: The related dysregulated proteins for liver cancer were retrieved from STRING database. The queried proteins were included in a network by cytoscape software and the central nodes of the network were enriched via gene ontology.  


Results: Among 11 introduced central nodes (GAPDH, TP53, EGFR, MYC, INS, ALB, IL6, AKT1, VEGFA, CDH1, and HRAS), HRAS and AKT1 were highlighted as critical dysregulated proteins which can be considered as possible biomarkers.


Conclusion: Analysis revealed that AKT1 and HRAS and the related biochemical pathways (specially “HIF-1 signaling pathway”) are the possible diagnostic and therapeutic agents of liver cancer. 

Keywords:
  • Liver cancer; AKT1; HRAS; Biomarker; Gene ontology

How to Cite

Arjmand , B., Jahani Sherafat, S., Rezaei –Tavirani, M., Hamzeloo Moghadam, M., & Abbasi, M. A. (2023). Network Analysis of Liver Cancer: A System Biology Approach . Gastroenterology and Hepatology from Bed to Bench, 16(2). https://doi.org/10.22037/ghfbb.v16i2.2514
  • ACM
  • ACS
  • APA
  • ABNT
  • Chicago
  • Harvard
  • IEEE
  • MLA
  • Turabian
  • Vancouver
  • Endnote/Zotero/Mendeley (RIS)
  • BibTeX

References

1. Fu J, Wang H. Precision diagnosis and treatment of liver cancer in China. Cancer letters. 2018;412:283-8.
2. Billington S, Ray AS, Salphati L, Xiao G, Chu X, Humphreys WG, et al. Transporter expression in noncancerous and cancerous liver tissue from donors with hepatocellular carcinoma and chronic hepatitis C infection quantified by LC-MS/MS proteomics. Drug Metabolism and Disposition. 2018;46(2):189-96.
3. Jiang Y, Sun A, Zhao Y, Ying W, Sun H, Yang X, et al. Proteomics identifies new therapeutic targets of early-stage hepatocellular carcinoma. Nature. 2019;567(7747):257-61.
4. Liu J, Dang H, Wang XW. The significance of intertumor and intratumor heterogeneity in liver cancer. Experimental & molecular medicine. 2018;50(1):e416-e.
5. Carulli JP, Artinger M, Swain PM, Root CD, Chee L, Tulig C, et al. High throughput analysis of differential gene expression. Journal of Cellular Biochemistry. 1998;72(S30‒31):286-96.
6. Büssow K, Nordhoff E, Lübbert C, Lehrach H, Walter G. A human cDNA library for high-throughput protein expression screening. Genomics. 2000;65(1):1-8.
7. Wu J, Vallenius T, Ovaska K, Westermarck J, Mäkelä TP, Hautaniemi S. Integrated network analysis platform for protein-protein interactions. Nature methods. 2009;6(1):75-7.
8. Ideker T, Sharan R. Protein networks in disease. Genome research. 2008;18(4):644-52.
9. Zhang Q, Ma C, Gearing M, Wang PG, Chin L-S, Li L. Integrated proteomics and network analysis identifies protein hubs and network alterations in Alzheimer’s disease. Acta neuropathologica communications. 2018;6(1):1-19.
10. Zotenko E, Mestre J, O'Leary DP, Przytycka TM. Why do hubs in the yeast protein interaction network tend to be essential: reexamining the connection between the network topology and essentiality. PLoS computational biology. 2008;4(8):e1000140.
11. Kar G, Gursoy A, Keskin O. Human cancer protein-protein interaction network: a structural perspective. PLoS computational biology. 2009;5(12):e1000601.
12. Zamanian-Azodi M, Rezaei-Tavirani M, Rahmati-Rad S, Hasanzadeh H, Tavirani MR, Seyyedi SS. Protein-Protein Interaction Network could reveal the relationship between the breast and colon cancer. Gastroenterology and Hepatology from bed to bench. 2015;8(3):215.
13. Rezaei-Tavirani M, Mansouri V, Tavirani MR, Rostami-Nejad M, Bashash D, Azodi MZ. Gene and Biochemical Pathway Evaluation of Burns Injury via Protein-Protein Interaction Network Analysis. Galen Medical Journal. 2019;8:e1257.
14. Nguyen TB, Do DN, Nguyen-Thanh T, Tatipamula VB, Nguyen HT. Identification of Five Hub Genes as Key Prognostic Biomarkers in Liver Cancer via Integrated Bioinformatics Analysis. Biology. 2021;10(10):957.
15. Azodi MZ, khatoon Hajisayyah S, Razzaghi Z, Tavirani MR. Introducing physical exercise as a potential strategy in liver cancer prevention and development. Gastroenterology and Hepatology from Bed to Bench. 2021.
16. Szklarczyk D, Gable AL, Nastou KC, Lyon D, Kirsch R, Pyysalo S, et al. The STRING database in 2021: customizable protein–protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic acids research. 2021;49(D1):D605-D12.
17. Asadzadeh-Aghdaei H, Okhovatian F, Razzaghi Z, Heidari M, Vafaee R, Nikzamir A. Radiation Therapy in Patients With Brain Cancer: Post-proteomics Interpretation. Journal of lasers in medical sciences. 2019;10(Suppl 1):S59.
18. Azodi MZ, Arjmand B, Zali A, Razzaghi M. Introducing APOA1 as a key protein in COVID-19 infection: a bioinformatics approach. Gastroenterology and Hepatology From Bed to Bench. 2020;13(4):367.
19. Lu X, Paliogiannis P, Calvisi DF, Chen X. Role of the mammalian target of rapamycin pathway in liver cancer: from molecular genetics to targeted therapies. Hepatology. 2021;73:49-61.
20. Lu SC. Dysregulation of glutathione synthesis in liver disease. Liver Research. 2020;4(2):64-73.
21. Reyes-Gordillo K, Shah R, Arellanes-Robledo J, Cheng Y, Ibrahim J, Tuma PL. Akt1 and Akt2 isoforms play distinct roles in regulating the development of inflammation and fibrosis associated with alcoholic liver disease. Cells. 2019;8(11):1337.
22. Xu Z, Xu M, Liu P, Zhang S, Shang R, Qiao Y, et al. The mTORC2‐Akt1 cascade is crucial for c‐Myc to promote hepatocarcinogenesis in mice and humans. Hepatology. 2019;70(5):1600-13.
23. Zhao J-X, Yuan Y-W, Cai C-F, Shen D-Y, Chen M-L, Ye F, et al. Aldose reductase interacts with AKT1 to augment hepatic AKT/mTOR signaling and promote hepatocarcinogenesis. Oncotarget. 2017;8(40):66987.
24. Park J-C, Jeong W-J, Seo SH, Choi K-Y. WDR76 mediates obesity and hepatic steatosis via HRas destabilization. Scientific reports. 2019;9(1):1-12.
25. Pecenka V, Pajer P, Karafiat V, Kasparova P, Dudlova J, Dvorak M. HRAS, EGFR, MET, and RON genes are recurrently activated by provirus insertion in liver tumors induced by the retrovirus myeloblastosis-associated virus 2. Journal of virology. 2017;91(20):e00467-17.
26. Xin B, Yamamoto M, Fujii K, Ooshio T, Chen X, Okada Y, et al. Critical role of Myc activation in mouse hepatocarcinogenesis induced by the activation of AKT and RAS pathways. Oncogene. 2017;36(36):5087-97.
27. Han J, He Y, Zhao H, Xu X. Hypoxia inducible factor‐1 promotes liver fibrosis in nonalcoholic fatty liver disease by activating PTEN/p65 signaling pathway. Journal of cellular biochemistry. 2019;120(9):14735-44.
28. Chiu DK-C, Tse AP-W, Law C-T, Xu IM-J, Lee D, Chen M, et al. Hypoxia regulates the mitochondrial activity of hepatocellular carcinoma cells through HIF/HEY1/PINK1 pathway. Cell death & disease. 2019;10(12):1-16.
29. Bubendorf L, Schöpfer A, Wagner U, Sauter G, Moch H, Willi N, et al. Metastatic patterns of prostate cancer: an autopsy study of 1,589 patients. Human pathology. 2000;31(5):578-83.
  • Abstract Viewed: 0 times

Download Statastics

  • Linkedin
  • Twitter
  • Facebook
  • Google Plus
  • Telegram
Open Journal Systems
Keywords
Current Issue
  • Atom logo
  • RSS2 logo
  • RSS1 logo
  • Home
  • Archives
  • Submissions
  • About the Journal
  • Editorial Team
  • Contact

GHFBB journal is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0).

Print ISSN: 2008-2258
Online ISSN: 2008-4234

Support Contact: ghfbb.journal@gmail.com

 

GHFBB is an open-access journal and does not charge fees for authors who submit their articles and for readers who access PDF files of published articles.

The template of this website is designed by Sinaweb