Microenvironmental cooperation promotes early spread and bistability of a Warburg-like phenotype

Abstract

We introduce an in silico model for the initial spread of an aberrant phenotype with Warburg-like overflow metabolism within a healthy homeostatic tissue in contact with a nutrient reservoir (the blood), aimed at characterizing the role of the microenvironment for aberrant growth. Accounting for cellular metabolic activity, competition for nutrients, spatial diffusion and their feedbacks on aberrant replication and death rates, we obtain a phase portrait where distinct asymptotic whole-tissue states are found upon varying the tissue-blood turnover rate and the level of blood-borne primary nutrient. Over a broad range of parameters, the spreading dynamics is bistable as random fluctuations can impact the final state of the tissue. Such a behaviour turns out to be linked to the re-cycling of overflow products by non-aberrant cells. Quantitative insight on the overall emerging picture is provided by a spatially homogeneous version of the model.

Characterizing steady states of genome-scale metabolic networks in continuous cell cultures

“…Although many complications must be considered in this case, including circadian oscillations, heterogeneous cell populations and spatial structure (Ref. [ 60 ] presents an attempt to deal with the later two), some of the conclusions derived in this manuscript could still be relevant in this context. For example, it would be very interesting to explore if the metabolic profile of cells from different tissues can be correlated to the ratio between cell density and average perfusion rate experienced at the tissue site ( i.e , the ξ parameter defined in this work).…”

“…To gain insight into the kind of solutions expected, we examined first a simple metabolic network that admits an analytic solution. It is based on the simplified network studied by A. Vazquez et al to explain the Warburg effect [ 58 ], and serves as a minimal model of metabolic transitions in the cell [ 58 – 60 ].…”

Maximum entropy and population heterogeneity in continuous cell cultures

“…This simplified model or close variations have been extensively discussed in the literature, e.g . [ 13 , 43 , 45 , 46 ].…”

Spin Glass Theory of Interacting Metabolic Networks

“…For example, if reaction r represents consumption of a nutrient such as glucose, then there is an evolutionary pressure favoring competition between cells i and j for this nutrient. On the contrary if J rij < 0, cells i and j tend to carry opposite fluxes on reaction r. If reaction r represents an exchange of a byproduct, such as lactate, it means then that cell i tends to produce lactate and cell j to consume it (or vice versa), establishing a so called lactate shuttle [22,[36][37][38]). In this case we say that cells cooperate.…”

“…This results necessarily in direct or indirect relations between the metabolism of different cells [21]. However, most of the theoretical work on interacting metabolic networks has been characterized by i) the study of competing/cooperating populations after drastic simplifications of their metabolism [22][23][24][25][26], and ii) the study of the interaction between two individual cells with identical or nearly identical complex metabolism [8-10, 27, 28]. When populations of cells are described by complex metabolic networks, interacting between them or with the environment, simulations have been the main research tool [29][30][31][32].…”