Mathematical models of cancer metabolism

Abstract

Metabolism is essential for life, and its alteration is implicated in multiple human diseases. The transformation from a normal to a cancerous cell requires metabolic changes to fuel the high metabolic demands of cancer cells, including but not limited to cell proliferation and cell migration. In recent years, there have been a number of new discoveries connecting known aberrations in oncogenic and tumour suppressor pathways with metabolic alterations required to sustain cell proliferation and migration. However, an understanding of the selective advantage of these metabolic alterations is still lacking. Here, we review the literature on mathematical models of metabolism, with an emphasis on their contribution to the identification of the selective advantage of metabolic phenotypes that seem otherwise wasteful or accidental. We will show how the molecular hallmarks of cancer can be related to cell proliferation and tissue remodelling, the two major physiological requirements for the development of a multicellular structure. We will cover different areas such as genome-wide gene expression analysis, flux balance models, kinetic models, reaction diffusion models and models of the tumour microenvironment. We will also highlight current challenges and how their resolution will help to achieve a better understanding of cancer metabolism and the metabolic vulnerabilities of cancers.

Loss of GINS2 inhibits cell proliferation and tumorigenesis in human gliomas

“…Cell proliferation is one of the core hallmarks of tumors . In this study, we tested the proliferation of glioma cell strains U87 and U251 via CCK‐8 assay after inhibiting GINS2 expression (Figure A).…”

“…Cell proliferation is one of the core hallmarks of tumors. 24 In this study, we tested the proliferation of glioma cell strains U87 and U251 via CCK-8 assay after inhibiting GINS2 expression ( Figure 3A). The normalized optical density value of U87 cells was 0.81 ± 0.06, which was significantly lower than that of the control group.…”

Metabolite and Microbiome Interplay in Cancer Immunotherapy

“…Recent reviews highlight various types of mathematical models applied to cancer metabolism [45] and host-microbial metabolomics [46]. Markert and Vazquez highlight several different types of models, including flux balance models [47], which have been successfully applied to study cellular metabolism under steady state conditions and are being expanded to include kinetic data.…”

Computational Model Predicts the Effects of Targeting Cellular Metabolism in Pancreatic Cancer

“…These are steady state stoichiometric models that can predict the flux distributions, but fail to capture the kinetic aspects (time course of metabolite concentrations) in the system or time-varying heterogeneities that arise due to environmental fluctuations. When considering processes that are inherently transient, such as the effects of reprogramming of cancer metabolism, kinetic modeling is required to understand the dynamic relationship between metabolic fluxes and metabolite concentrations (Markert and Vazquez, 2015). Therefore, models that represent the metabolic pathways using a system of nonlinear ordinary differential equations (ODEs) are of particular importance.…”