Modeling and Simulation of a miRNA Regulatory Network of the PTEN Gene

Gionmattia Carancini, Margherita Carletti and Giulia Spaletta ()
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Gionmattia Carancini: School of Biotechnology, University of Urbino Carlo Bo, 61029 Urbino, Italy
Margherita Carletti: Department of Pure and Applied Sciences, University of Urbino Carlo Bo, 61029 Urbino, Italy

Mathematics, 2021, vol. 9, issue 15, 1-16

Abstract: The PTEN onco-suppressor gene is likely to play an important role in the onset of brain cancer, namely glioblastoma multiforme. Consequently, the PTEN regulatory network, involving microRNAs and competitive endogenous RNAs, becomes a crucial tool for understanding the mechanism related to low levels of expression in cancer patients. This paper introduces a novel model for the regulation of PTEN whose solution is approximated by a high-dimensional system of ordinary differential equations under the assumption that the Law of Mass Action applies. Extensive numerical simulations are presented that mirror parts of the biological subtext that lies behind various alterations. Given the complexity of processes involved in the acquisition of empirical data, initial conditions and reaction rates were inferred from the literature. Despite this, the proposed model is shown to be capable of capturing biologically reasonable behaviors of inter-species interactions, thus representing a positive result, which encourages pursuing the possibility of experimenting on data hopefully provided by omics disciplines.

Keywords: numerical modeling; ordinary differential equations; LSODA method; stoichiometric matrix; propensity function; PTEN onco-suppressor gene; gene regulatory network (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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