Metabolic reprogramming dynamics in tumor spheroids: Insights from a multicellular, multiscale model

Abstract

Mathematical modeling provides the predictive ability to understand the metabolic reprogramming and complex pathways that mediate cancer cells’ proliferation. We present a mathematical model using a multiscale, multicellular approach to simulate avascular tumor growth, applied to pancreatic cancer. The model spans three distinct spatial and temporal scales. At the extracellular level, reaction diffusion equations describe nutrient concentrations over a span of seconds. At the cellular level, a lattice-based energy driven stochastic approach describes cellular phenomena including adhesion, proliferation, viability and cell state transitions, occurring on the timescale of hours. At the sub-cellular level, we incorporate a detailed kinetic model of intracellular metabolite dynamics on the timescale of minutes, which enables the cells to uptake and excrete metabolites and use the metabolites to generate energy and building blocks for cell growth. This is a particularly novel aspect of the model. Certain defined criteria for the concentrations of intracellular metabolites lead to cancer cell growth, proliferation or death. Overall, we model the evolution of the tumor in both time and space. Starting with a cluster of tumor cells, the model produces an avascular tumor that quantitatively and qualitatively mimics experimental measurements of multicellular tumor spheroids. Through our model simulations, we can investigate the response of individual intracellular species under a metabolic perturbation and investigate how that response contributes to the response of the tumor as a whole. The predicted response of intracellular metabolites under various targeted strategies are difficult to resolve with experimental techniques. Thus, the model can give novel predictions as to the response of the tumor as a whole, identifies potential therapies to impede tumor growth, and predicts the effects of those therapeutic strategies. In particular, the model provides quantitative insight into the dynamic reprogramming of tumor cells at the intracellular level in response to specific metabolic perturbations. Overall, the model is a useful framework to study targeted metabolic strategies for inhibiting tumor growth.

Role of Glutathione in Cancer: From Mechanisms to Therapies

“…Current approaches for multi-cellular system modeling for cancer have been recently reviewed [ 176 ] and give an interesting basis for future analysis of glutathione’s role in these systems. An example of modeling tumor spheroids by combining multiscale and multicellular models was recently presented by Roy and Finley [ 177 ]. The model includes detailed kinetic representation of intracellular metabolism linked within the cluster of tumor cells that simulates tumor spheroid systems.…”

PCK2:A potential Therapeutic Target and Biomarker for Hepatocellular Carcinoma Based on Weighted Gene Co-Expression Network Analysis

“…PCK2 and its co-expressed genes were then functionally examined by performing GO and KEGG enrichment analyses, which showed a strong enrichment in metabolic related biological processes. In tumors, metabolic reprogramming is an important feature, with the metabolism playing an important role in tumor anti-oxidative stress, energy production and biosynthesis [22].Therefore, key metabolic genes may play an important role in regulating metabolic networks and may affect various biological processes associated with tumors. Furthermore, PCK2 overexpression in HCC cell lines was shown to reduce cell proliferation, thus further suggesting that PCK2 may be a key gene that affects HCC occurrence and development.…”

SARS-COV-2 infection and lung tumor microenvironment

“…SARS-CoV-2 proteins might interact with the components of TME and may support tumor growth or cause resistance to the ongoing therapy. A detailed proteomic analysis of host cell (SARS-CoV-2 infected colon carcinoma cell line) after the infection was performed [ 49 ]. The SARS-CoV-2 infection affected several pathways.…”

“…This increased utilization of glutamine is supported by viral infections [ 52 ]. SARS-CoV-2 infected colon cancer cells have shown that a set of genes involved in the metabolic pathways get altered by this infection [ 49 ]. Also, the TME is usually hypoxic and nutrient deprived which supports suppressed immune response providing a favorable environment for viral growth.…”