Does Cancer Biology Rely on Parrondo's Principles?

Abstract

Many aspects of cancer biology remain puzzling, including the proliferative and survival success of malignant cells in spite of their high genetic and epigenetic instability as well as their ability to express migrating phenotypes and/or enter dormancy despite possible fitness loss. Understanding the potential adaptive value of these phenotypic traits is confounded by the fact that, when considered separately, they seem to be rather detrimental at the cell level, at least in the short term. Here, we argue that cancer's biology and success could frequently be governed by processes underlying Parrondo's paradox, whereby combinations of intrinsically losing strategies may result in winning outcomes. Oncogenic selection would favor Parrondo's dynamics because, given the environmental adversity in which malignant cells emerge and evolve, alternating between various less optimal strategies would represent the sole viable option to counteract the changing and deleterious environments cells are exposed to during tumorigenesis. We suggest that malignant processes could be viewed through this lens, and we discuss how Parrondo's principles are also important when designing therapies against cancer.

Keywords: Parrondo’s paradox; cancer; dormancy; metastasis; therapy.

Figure 1

Parrondo’s original game, involving two games, A and B (adapted from [32]). See Box 1 for details.

Figure 2

Hypothetical dynamics illustrating that (a) the co-existence of relatively stable cell populations and cell populations exhibiting stochasticity rely on the Parrondo’s paradox (adapted from [34]), (b) the co-existence of a relatively stable cell subpopulation (game A) and a cell subpopulation exhibiting stochasticity (game B) is necessary for tumoral growth (i.e., relying on Parrondo’s paradox). Tumor growth is impaired when the size of one subpopulation exceeds (or goes below) an optimal threshold of representation. The slope of the decrease depends on which unique strategy is overrepresented (small arrows). Also, the optimal ratio between the two strategies may vary during tumorigenesis, explaining the different slopes for the same ratios at different times.