Cancer phenotype as the outcome of an evolutionary game between normal and malignant cells

Abstract

BACKGROUND: There is variability in the cancer phenotype across individuals: two patients with the same tumour may experience different disease life histories, resulting from genetic variation within the tumour and from the interaction between tumour and host. Until now, phenotypic variability has precluded a clear-cut identification of the fundamental characteristics of a given tumour type. METHODS: Using multiple myeloma as an example, we apply the principles of evolutionary game theory to determine the fundamental characteristics that define the phenotypic variability of a tumour. RESULTS: Tumour dynamics is determined by the frequency-dependent fitness of different cell populations, resulting from the benefits and costs accrued by each cell type in the presence of others. Our study shows how the phenotypic variability in multiple myeloma bone disease can be understood through the theoretical approach of a game that allows the identification of key genotypic features in a tumour and provides a natural explanation for phenotypic variability. This analysis also illustrates how complex biochemical signals can be translated into cell fitness that determines disease dynamics. CONCLUSION: The present paradigm is general and extends well beyond multiple myeloma, and even to non-neoplastic disorders. Furthermore, it provides a new perspective in dealing with cancer eradication. Instead of trying to kill all cancer cells, therapies should aim at reducing the fitness of malignant cells compared with normal cells, allowing natural selection to eradicate the tumour.

Cooperation among cancer cells as public goods games on Voronoi networks

“…Tomlinson [1997] and Tomlinson & Bodmer [1997] used the hawk-dove game, to explain why game theory can be used to understand conflict and cooperation between cancer cells; subsequent papers [Bach et al 2001, Dingli et al 2009, Basanta et al 2008a,b, 2011, 2012, Gerstung et al 2011 have extended that model to up to 4 strategies. 2-player games, however, are not appropriate to study collective interactions and can lead to misunderstandings [Archetti & Scheuring 2012].…”

Public goods in relation to competition, cooperation, and spite

“…At the other extreme of biological organization, endogenous pathogen cells produce metabolites that represent a public good, e.g., during cancer progression (17); treating cancer progression as a game between normal and malignant cells is thus natural (18,19) and was already suggested nearly a decade ago by Axelrod et al (20). Cancer itself of course represents a breakdown in cooperation and the maintenance of a public good (21), so the idea of developing new strategies for treating cancer-e.g., by attacking the public goods that allow cancers to thrive-seems an appropriate turnabout (17,22,23).…”

The ecology of cancer from an evolutionary game theory perspective

“…Such a coexistence between MM and OC (figure 5c) will prevail even if d ¼ 0 (MM and OB are neutral with respect to each other). However, changes in d may have a significant impact on the life history of the disease and associated progression time [47].…”

“…Let us denote by x i (t), the relative frequencies of the cell types: x 1 (t) (OC cells), x 2 (t) (OB cells) and x 3 (t) (MM cells The benefits and costs resulting from the interacting cell populations are captured in the initial pay-off matrix (1.2), here associated with matrix A ij . We may reduce this matrix to the minimal pay-off matrix (4.3) by taking into account that the nature of the fixed points of the evolutionary dynamics (though not their location) remains unaffected under a projective transformation of the relative cells frequencies [10], leading to [47] b ¼ c/e and d ¼ dc/be. Note further, that the REs and associated dynamics remain unaffected if we add an arbitrary constant to each column of the pay-off matrix.…”