Computational quantification of global effects induced by mutations and drugs in signaling networks of colorectal cancer cells

Abstract

Colorectal cancer (CRC) is one of the most deadly and commonly diagnosed tumors worldwide. Several genes are involved in its development and progression. The most frequent mutations concern APC, KRAS, SMAD4, and TP53 genes, suggesting that CRC relies on the concomitant alteration of the related pathways. However, with classic molecular approaches, it is not easy to simultaneously analyze the interconnections between these pathways. To overcome this limitation, recently these pathways have been included in a huge chemical reaction network (CRN) describing how information sensed from the environment by growth factors is processed by healthy colorectal cells. Starting from this CRN, we propose a computational model which simulates the effects induced by single or multiple concurrent mutations on the global signaling network. The model has been tested in three scenarios. First, we have quantified the changes induced on the concentration of the proteins of the network by a mutation in APC, KRAS, SMAD4, or TP53. Second, we have computed the changes in the concentration of p53 induced by up to two concurrent mutations affecting proteins upstreams in the network. Third, we have considered a mutated cell affected by a gain of function of KRAS, and we have simulated the action of Dabrafenib, showing that the proposed model can be used to determine the most effective amount of drug to be delivered to the cell. In general, the proposed approach displays several advantages, in that it allows to quantify the alteration in the concentration of the proteins resulting from a single or multiple given mutations. Moreover, simulations of the global signaling network of CRC may be used to identify new therapeutic targets, or to disclose unexpected interactions between the involved pathways.

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

“…For example, a LoF mutation, which results in the reduction or even the cancellation of the function of a specific protein, is implemented by projecting the initial concentration values describing the physiological cell onto a new initial state in which the concentrations of the mutated protein and the corresponding compounds are set to zero. On the other hand, a GoF mutation, which enhances the expression of a specific protein, is implemented by setting equal to zero the reaction coefficients corresponding to the equations representing the de-activation reactions for that protein (Sommariva et al, 2021b).…”

“…In particular, a GoF of KRAS is realized by a modification of the stoichiometric matrix in (1), which, from a chemical viewpoint, corresponds to removing from the CRN all reactions involved in the de-activation of that protein. A study of global effects of the GoF of KRAS on the proteomic profile of a colorectal cancer cell has been studied by (Sommariva et al, 2021b) via the computation of…”

“…An analysis of local effects of mutations may lead to a more direct connection with the physiology of the signaling network. A few items have already been examined in (Sommariva et al, 2021b), mainly focused on the study of the effects of various single-gene mutations on the concentration values of p53. Here we present a further set of complementary results on the MAPK pathway.…”

“…A rich plethora of information can be derived from the analysis of the solutions of the dynamical systems associated to the original CR-CRN and to its mutated forms. For example, feedback effects naturally emerge by comparing the time-courses of the individual protein concentrations or by studying the corresponding time-varying reaction fluxes (Sommariva et al, 2021b). More importantly, local and global effects induced on the network by LoF and GoF mutations can be quantified by computing the relative difference between the protein concentrations at the equilibrium point of the original CR-CRN and that at the equilibrium of the network obtained by applying the proper projection operator(s) (Sommariva et al, 2021a).…”

“…The proposed model has been used to simulate the functional alterations induced on the CR-CRN by some of the mutations more commonly found in CRC, including the GoF of PI3K, KRAS, and BRAF, and the LoF of PTEN, AKT, and TGFβRII (Sommariva et al, 2021a,b;Biddau et al, 2023), and a first attempt in modelling the action of Dabrafenib, a drug targeting BRAF, has been performed by (Sommariva et al, 2021b). The obtained results have been extensively compared with results previously published in literature.…”