Analysis and verification of the HMGB1 signaling pathway

Abstract

BackgroundRecent 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.ResultsWe 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.ConclusionsOur 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.

Bayesian Statistical Model Checking with Application to Stateflow/Simulink Verification

“…In fact, we have recently applied both approaches to verify computational models of biological signaling pathways [20] and analog circuits [47]. In the systems biology application, models are inherently probabilistic because of the stochastic nature of the (quantum) physics underlying chemical reactions.…”

“…In particular, the pioneering work of Gillespie [19] showed that, under some reasonable assumptions, one can use continuous-time Markov chains to approximate the temporal evolution of chemical reaction networks. In our work [20] we used the BioNetGen rule-based language [26] to succinctly describe the reactions of an important signaling pathway in cancer. The model (i.e., the resulting continuous-time Markov chain) is then efficiently simulated by the BioNetGen simulator and verified against known behavioral properties expressed in BLTL.…”

HMGB1 Protein Does Not Mediate the Inflammatory Response in Spontaneous Spinal Cord Regeneration

“…Bioinformatic analysis has even revealed that overexpressed HMGB1 can influence cell fate, such as apoptosis or proliferation, through regulation of cell circle factors, including c-Myc, p53, pRb, Ras, etc. (79). The possibility of intracellular gHMGB1-mediated neuronal apoptosis may be caused by aberrant expression of these cell circle factors.…”

Immunogene Zelltodmarker HMGB1 und sRAGE als neue prädiktive und prognostische Serum Biomarker bei Tumorerkrankungen/Immunogenic cell death markers HMGB1 and sRAGE as new predictive and prognostic serum biomarkers in cancer disease

“…Au ß erdem bestehen Querverbindungen zu p53-MDM [61] , Rho-GTPasen [62] , Jak/STAT [63] und Mac-152 zudem spielt RAGE eine wichtige Rolle in der DNAabh ä ngigen Aktivierung von TLR9, sodass RAGE weniger als konventioneller Rezeptor sondern viel mehr als Adapter f ü r verschiedenste Signalwege gesehen werden kann [34] . HMGB1 aktiviert ü ber Bindung an RAGE dendritische Zellen und f ö rdert ihre Reifung, was zur Aussch ü ttung von proinflammatorischen Zytokinen wie IL-1-α , IL-6 und TNF-α f ü hrt.…”