Balbo, Gianfranco

Beccuti, Marco

Calogero, Raffaele Adolfo

Cordero, Francesca

Fornari, Chiara

English

Institutional Research Information System University of Turin

The multi-level view to investigate the cancer progressionFrancesca Cordero, Chiara Fornari, Marco Beccuti, Gianfranco BalboDepartment of Computer Science, University of Torinofornari@di.unito.it, fcordero@di.unito.it, beccuti@di.unito.it, balbo@di.unito.itRaffaele A. Calogero,Department of Molecular Biotechnology and Life Sciences, University of Torinoraffaele.calogero@unito.itOne of the most challenging problem in systems biology is to build a mathematical modelable to reproduce a detailed biological systems. To have a functional model generating newhypothesis, one starts by describing the structure of the model (i.e. biochemical reactionsor entity interactions), then defines the parameters (i.e. concentrations and reaction rates)to obtain temporal behaviors of these entities. A less explored dimension is the integrationof different levels of detail generating a multi-level model able to represent a more realisticand predictive description of cancer.In this work we investigated the effects of vaccination on a cancer hierarchical structurethrough a multi-level model [1]. In particular, we propose a new approach which exploitsspecific interdependencies among population and molecular levels. The overall organizationof the method consists of four main steps. (i) Model definition, the population level ismodeled by a system of Ordinary Differential Equations (ODE) describing the progressionof malignant tumors, assuming the validity the cancer stem cells theory [3]. Instead, themolecular level is modeled using the Petri Net (PN) formalism [2] to detail part of theproliferation pathway. (ii) Model consistency and correctness, we take advantage from thestructural proprieties of PN formalism in order to check if the mass conservation lawsare respected. Moreover, we use the model checking techniques to verify if well-knownproprieties of the model are modeled in the correct way.(iii) Multi-level model interactions,to link populations proliferation parameters with regulation events we identify for each levela set of interaction points, i.e protein playing a pivotal role in proliferation (molecular level)and proliferation rate (population level). (iv) Model dynamics, we derive a set of ODEs fromthe PN model and we analyzed the temporal dynamics of the proteins which play a criticalrole in cell proliferation through numerical integration. Hence, the obtained quantities areused as parameters in the ODE system modeling the cell proliferation, and it is solved bynumerical integration.In this work we proposed a multi-level approach in which molecular networks are used toestimate parameters of population level. Using this method we have been able to reproduceat a qualitative level the effect of anti-ErbB2 chronic vaccination in BALB-neuT model.References[1] F. Cordero, M. Beccuti, C. Fornari, S. Lanzardo, L. Conti, F. Cavallo, G. Balbo and RA. Calogero,Multi-level model for the investigation of oncoantigen-driven vaccination effect. BMC Bioinformatics,In press[2] V. Reddy, M. Mavrovouniotis, M. Liebman, Petri net representation in metabolic pathways. In Proc.Int. Conf. Intelligent Systems for Molecular Biology 1993 328336.[3] C. Fornari, F. Cordero, D. Manini, R.A. Calogero, G. Balbo Mathematical approach to predict thedrug effects on cancer stem cell models, Proceedings of the CS2Bio 2nd International Workshop onInteractions between Computer Science and Biology, Reykjavik, Iceland, 2011.

The multi-level view to investigate the cancer progression

https://iris.unito.it/bitstream/2318/138382/1/mathwaysCordero.pdf

The multi-level view to investigate the cancer progression

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