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Mathematical Model Explains Treatment Resistance by way of Evolutionary Bet-Hedging

Posted December 30, 2016

While it is safe to say that modern medical interventions designed to treat bacterial infections and cancer have led to longer life-spans and better quality-of-life, many drugs still eventually fail due to the outgrowth and survival of treatment-resistant populations.

Evolutionary bet-hedging protects bacteria and cancerous tissues from medical intervention. Image credit: skeeze via, CC0 Public Domain.

In part, treatment resistance develops because cell populations are often comprised of a mixture of cells with differing characteristics, some of which are impervious to therapy.

“Heterogeneity is found in all organisms, from bacteria and fungi, to plants, insects and cancer cells, and can serve as a survival mechanism to ensure that at least a portion of the population can survive a catastrophic environmental change”, said Alexander Anderson, PhD, from the Department of Integrated Mathematical Oncology at the Moffitt Cancer Center and Research Institute.

In biology, bet-hedging (or “non-genetic variation in phenotypes”), analogous to hedging in finance, occurs when organisms trade a degree of general fitness for increased fitness under novel, stressful conditions by retaining gene variants (alleles) that are neutral or slightly deleterious in the “normal” (customary) environment, but advantageous under new and unusual circumstances.

An example might be a population of plants which produce seeds that do not germinate on the same year, thereby protecting it from being wiped-out in case of a catastrophic event.

A key driving force behind this phenomenon is genetic drift, defined as fluctuations in the frequency of a gene variant within a given population, which arise due to the unpredictable nature of reproduction and other random events, and are not affected by natural selection due to being neutral in terms of fitness.

The question is how does bet-hedging persist where catastrophic conditions are rare, and what is the mechanism that drives it.

Using mathematical modeling, researchers from the Moffitt Cancer Center and Oxford University’s Department of Computer Science have found a molecular switch, itself subject to selection, that guides the process and retains it even where catastrophic events do not occur. This suggests that natural selection can plot adaptations that increase fitness over the long-term.

These results could also have implications for the treatment of diseases associated with drug-resistance due to bet-hedging. “One strategy with the potential to overcome resistance is called a treatment holiday, wherein a patient ceases treatment for a period of time to prevent strong selection for drug-resistant cells that will ultimately drive relapse.”

Researchers at Moffitt performed simulations showing that the underlying mechanism that controls bet-hedging determines whether a treatment holiday will be beneficial. Other strategies for overcoming bet-hedging-driven treatment-resistant diseases rely on discovering drugs that kill the resistant cells, or identifying targetable genetic mechanisms to prevent their emergence.

Sources: study,

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