Modern medicine and treatments for bacterial infections and cancer
have significantly increased life spans and improved quality-of-life.
However, many drugs eventually fail because of the outgrowth and
survival of treatment-resistant populations.
models, a collaborative team of
researchers from Moffitt Cancer Center's Integrated Mathematical
Oncology (IMO) Program have explained how bacteria and cancer cells exploit an evolutionary
process known as bet-hedging to resist medical intervention.
‘Bet-hedging naturally emerges in organisms and contributes to bacterial and cancer treatment resistance.’
"Treatment resistance occurs partly because cell populations are
heterogeneous - consisting of a mixture of cells with differing
characteristics, some of which are impervious to therapy," said Alexander Anderson. "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."
Where this heterogeneity arises through mechanisms other than
genetic mutation, it is referred to as bet-hedging. Bet-hedging has been
identified previously as a mechanism of drug resistance in both
bacterial infections and a number of cancers.
It is unclear how the phenomenon of bet-hedging first evolved or how
it continues to persist where catastrophic events are rare, as natural
selection should theoretically drive its loss in a population. The IMO
team performed mathematical modeling, coupled with extensive
simulations, to predict the evolutionary origin and fate of
bet-hedging. Mathematical modeling allows scientists to study complex
biological systems and processes that could not feasibly be studied with
common laboratory and clinical experimental approaches.
The researchers report that biological redundancy can lead to
bet-hedging through the introduction of random genetic mutations that
initially have no impact on the characteristics of a species.
Additionally, the molecular mechanism that controls bet-hedging can slow
the rate of its loss. Combined, these mechanisms can ensure that
bet-hedging is not lost even where catastrophic events do not occur.
These results have important implications for the treatment of
diseases that are associated with drug resistance due to bet-hedging.
The study's lead author, Dan Nichol from Oxford University, said, "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
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.
The IMO team suggests that these strategies could be ineffective in
the long-term as redundancy can render single genetic targets
ineffective. Instead, they suggest that it may be possible to identify
multiple targets whose combination will prevent bet-hedging, or shift
the proportion of resistant cells to a manageable level - allowing
treatment with traditional chemotherapeutic drugs or resulting in
controlled, rather than expanding, disease.