Biddau, G. | Search bioRxiv

bioRxiv2023

In-silico modelling of the mitogen-activated kinase (MAPK) pathway in colorectal cancer: mutations and targeted therapy

Chemical reaction networks are powerful tools for computing the complex nature of cancers onset, progression, and therapy. The main reason for their effectiveness is in the fact that these networks can be rather naturally encoded as a dynamical system whose asymptotic solution mimics the proteins concentration profile at equilibrium. The paper relies on this mathematical approach to investigate global and local effects on the chemical reaction network of the colorectal cancer, triggered by partial and complete mutations occurring in its mitogen-activated kinase (MAPK) pathway. Further, this same approach allowed the in-silico modelling and dosage of a multi-target therapeutic intervention that utilizes MAPK as its molecular target.

systems biology↗

bioRxiv2023

SSI: A Statistical Sensitivity Index for Chemical Reaction Networks in cancer

SO_SCPLOWUMMARYC_SCPLOWAt the cellular level, cancer is triggered by mutations of the proteins involved in signalling networks made of hundreds of reacting species. The corresponding mathematical model consists of a large system of non-linear Ordinary Differential Equations for the unknown proteins concentrations depending on a consistently large number of kinetic parameters and initial concentrations. For this model, the present paper considers the problem of assessing the impact of each parameter and initial concentration on the systems output. More specifically, we introduced a statistical sensitivity index whose values can be easily computed by means of principal component analysis, and which leads to the partition of the parameters and initial concentrations sets into sensible and non-sensible families. This approach allows the identification of those kinetic parameters and initial concentrations that mostly impact the mutation-driven modification of the proteomic profile at equilibrium, and of those pathways in the network that are mostly affected by the presence of mutations in the cancer cell.

systems biology↗