Peto’s Paradox and why Elephants don’t get cancer
Many obstacles complicate the ability to successfully treat cancer; chemotherapy resistance is one of the most pressing. Chemotherapy consists of many different types of chemical drugs that kill fast-growing cells, including cancer cells. Since its discovery, these drugs have been some of the most essential treatments available for cancer. Chemotherapy resistance occurs when the cancerous cells within a patient are no longer killed by a chemotherapy drug, rendering this treatment ineffective. The emergence of chemotherapy resistance is an evolutionary problem. This means that finding ways to combat resistance requires evolutionary thinking. Here, we discuss one of several proposed solutions to chemotherapy resistance – adaptive therapy.
The logic behind adaptive therapy is based on two key principles – Somatic selection and Trade-offs.
Multiple levels of selections: somatic selection
Traditionally, doctors administer high doses in an attempt to kill as many cancerous cells as possible. If no resistant cells are present at the start of treatment, this high-dosage treatment should, theoretically, completely eliminate a cancerous tumor. However, this is rarely the case. Cells with some level of resistance are often present before treatment ever starts and are among the surviving cancer cells after high dosage treatment finishes. This reduces the size of the tumor, but simultaneously selects for any cells with resistance to the chemotherapy that was used. Importantly, with the susceptible cells gone, the growth of the resistant cell population is no longer hindered by competition with the susceptible cells. That is, the resistant cells can experience a competitive release.
So how does an adaptive therapy strategy exploit this trade-off and avoid competitive release? Small doses of chemotherapy are administered at intervals timed according to the growth of the cancer being treated (4, 5). The dose of chemotherapy should be high enough to shrink the tumor and mitigate the harm associated with cancer, but low enough to allow chemotherapy susceptible cells to survive. If done properly, it maintains a cellular ecology where resistant cells are always around to outcompete susceptible cells. Lowering the levels of chemotherapy administered has the added benefit of mitigating some of its notoriously harsh side effects.
Early clinical uses of adaptive therapy provide proof of concept. The first human clinical study of an adaptive therapy strategy includes 11 patients with prostate cancer. Compared to outcomes using traditional high dose therapies, the use of adaptive therapy has prolonged time to progression for patients in the trial (6). As the trial is ongoing, it is still unclear just how effective this strategy can be. However, adaptive therapy presents an innovative use of evolutionary theory that has progressed to the clinic. It can similarly be used as content within evolutionary biology curriculum.
Multiple levels of selection: somatic selection
Teaching somatic selection first requires students to have some understanding on the cell cycle, and how certain types of mutations can lead to cells that escape regulatory control of replication. Once this is covered, students can be asked to think about how tumors might progress. One way to do this is by having them draw visual models that indicate unique mutations among cells. Students can be asked to think through different scenarios. For example, what would the progression of cancer look if an early mutation led to lower fidelity DNA replication compared to a cancer where this did not occur?
Instructors can continue this exercise by providing similar illustrations of tumors that vary in the number of resistant cells, and the level of resistance among those cells. Students can then be asked to predict what might occur over time when chemotherapy is used. This same method can be used to have students to diagram the logic behind adaptive therapy.
Adaptive therapy is just one of many contexts that instructors can use to teach trade-offs, which are ubiquitous across biology. A strength of focusing on trade-offs when teaching adaptive therapy is that it requires students to apply this principle, not just understand its meaning. In doing so, students can go through different component ideas involved in trade-offs. Students can be asked to work through the impact of the local environment on trade-offs by explaining why the fitness of chemotherapy resistant cells compared to chemotherapy sensitive cells differs based on the presence or absence of chemotherapy. Instructors can have students focus on proximate reasons for trade-offs by having students discuss how known resistance mutations could result in a trade-off in the first place. Students can also learn about the evolutionary impacts of trade-offs, including how it can lead to selection that mitigates their costs. Instructors could propose a hypothetical situation where a compensatory mutation emerges within a resistant cell line, eliminating the cost of the trade-off.