Speaker
Description
Chemical Reaction Networks (CRNs) provide a rigorous mathematical framework to represent molecular interactions along signaling pathways by large systems of ordinary differential equations, exploiting the mass-action law. This framework enables a deeper understanding of the mechanisms underlying different diseases by analyzing the dynamics of the concentrations of the involved chemical species \cite{1}, capturing the steady-state behaviors through specific accurate root-finding methods \cite{2}, and observing the perturbation effects induced by genetic mutations and pharmacological treatments by implementing their action on the network \cite{3}.
We will present an application of this approach to the PI3K-AKT-mTOR axis to investigate the synergistic effect of two somatic activating mutations - MTOR p.S2215F and RPS6 p.R232H - documented in a patient with brain malformations and drug-resistant epilepsy \cite{4}. Single and combined mutations are implemented as parameter perturbations within the CRN to capture how altered signaling dynamics propagate along the pathway and shift the system toward pathological steady states. Furthermore, we simulate pharmacological inhibition via mTOR inhibitors to explore whether and how their administration attenuates the dysregulation of key cellular pathways that may be involved in aberrant neuronal migration, proliferation, and electrical activity, potentially providing new therapeutic avenues for patients refractory to conventional anti-epileptic drugs.
Acknowledgments
This research was partially found by Hub Life Science - Digital Health (LSH-DH) PNC-E3-2022-23683267 - Progetto DHEAL-COM - CUP: D33C22001980001, founded by Ministero della Salute within “Piano Nazionale Complementare al PNRR Ecosistema Innovativo della Salute - Codice univoco investimento:
PNC-E.3”
Bibliography
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title = {Gain and {Loss} of {Function} mutations in biological chemical reaction networks: a mathematical model with application to colorectal cancer cells},
shorttitle = {Gain and {Loss} of {Function} mutations in biological chemical reaction networks},
doi = {10.48550/ARXIV.2004.02632},
urldate = {2026-05-11},
publisher = {arXiv},
author = {Sommariva, Sara and Caviglia, Giacomo and Piana, Michele},
year = {2020},
}
@article{2,
title = {Combined {Newton}-{Gradient} {Method} for {Constrained} {Root}-{Finding} in {Chemical} {Reaction} {Networks}},
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issn = {0022-3239, 1573-2878},
doi = {10.1007/s10957-023-02323-z},
language = {en},
number = {1},
urldate = {2026-05-11},
journal = {Journal of Optimization Theory and Applications},
author = {Berra, Silvia and La Torraca, Alessandro and Benvenuto, Federico and Sommariva, Sara},
month = jan,
year = {2024},
pages = {404--427},
}
@article{3,
title = {In-silico modelling of the mitogen-activated protein kinase ({MAPK}) pathway in colorectal cancer: mutations and targeted therapy},
volume = {3},
issn = {2674-0702},
shorttitle = {In-silico modelling of the mitogen-activated protein kinase ({MAPK}) pathway in colorectal cancer},
doi = {10.3389/fsysb.2023.1207898},
urldate = {2026-05-11},
journal = {Frontiers in Systems Biology},
author = {Sommariva, Sara and Berra, Silvia and Biddau, Giorgia and Caviglia, Giacomo and Benvenuto, Federico and Piana, Michele},
month = aug,
year = {2023},
pages = {1207898},
}
@article{4,
title = {Somatic double-hit in {MTOR} and {RPS6} in hemimegalencephaly with intractable epilepsy},
volume = {28},
issn = {0964-6906, 1460-2083},
doi = {10.1093/hmg/ddz194},
language = {en},
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urldate = {2026-05-11},
journal = {Human Molecular Genetics},
author = {Pelorosso, Cristiana and Watrin, Françoise and Conti, Valerio and Buhler, Emmanuelle and Gelot, Antoinette and Yang, Xiaoxu and Mei, Davide and McEvoy-Venneri, Jennifer and Manent, Jean-Bernard and Cetica, Valentina and Ball, Laurel L and Buccoliero, Anna Maria and Vinck, Antonin and Barba, Carmen and Gleeson, Joseph G and Guerrini, Renzo and Represa, Alfonso},
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pages = {3755--3765},
}
