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Analysis and verification of the HMGB1 signaling pathway

Gong, H and Zuliani, P and Komuravelli, A and Faeder, JR and Clarke, EM (2010) Analysis and verification of the HMGB1 signaling pathway. BMC Bioinformatics, 11 (SUPPL.).

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Background: Recent studies have found that overexpression of the High-mobility group box-1 (HMGB1) protein, in conjunction with its receptors for advanced glycation end products (RAGEs) and toll-like receptors (TLRs), is associated with proliferation of various cancer types, including that of the breast and pancreatic.Results: We have developed a rule-based model of crosstalk between the HMGB1 signaling pathway and other key cancer signaling pathways. The model has been simulated using both ordinary differential equations (ODEs) and discrete stochastic simulation. We have applied an automated verification technique, Statistical Model Checking, to validate interesting temporal properties of our model.Conclusions: Our simulations show that, if HMGB1 is overexpressed, then the oncoproteins CyclinD/E, which regulate cell proliferation, are overexpressed, while tumor suppressor proteins that regulate cell apoptosis (programmed cell death), such as p53, are repressed. Discrete, stochastic simulations show that p53 and MDM2 oscillations continue even after 10 hours, as observed by experiments. This property is not exhibited by the deterministic ODE simulation, for the chosen parameters. Moreover, the models also predict that mutations of RAS, ARF and P21 in the context of HMGB1 signaling can influence the cancer cell's fate - apoptosis or survival - through the crosstalk of different pathways. © 2010 Gong etal; licensee BioMed Central Ltd.


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Item Type: Article
Status: Published
CreatorsEmailPitt UsernameORCID
Gong, H
Zuliani, P
Komuravelli, A
Faeder, JRfaeder@pitt.eduFAEDER
Clarke, EM
Date: 15 October 2010
Date Type: Publication
Journal or Publication Title: BMC Bioinformatics
Volume: 11
Number: SUPPL.
DOI or Unique Handle: 10.1186/1471-2105-11-s7-s10
Schools and Programs: School of Medicine > Computational Biology
School of Medicine > Computational and Systems Biology
Refereed: Yes
Date Deposited: 15 Nov 2016 20:15
Last Modified: 04 Jul 2023 10:55


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