- Researchers examined cancer treatment as a game played by the physician and tumor cells.
- The physician, as a leader in the game, can regularly monitor cancer responses during each treatment cycle.
- This approach combined with a mathematical model could provide useful data to enhance the results of subsequent cycles.
Cancer can be treated by radiation therapy, chemotherapy, surgery, synthetic lethality, and various other methods. It depends on what type of cancer a patient has and how advanced it is. Most patients receive a combination of treatment, such as surgery followed by radiation therapy or chemotherapy.
Now, a research team Moffitt Cancer Center and Maastricht University have come up with a new theory that challenges the decades-old standard-treatment of metastatic cancers. Metastasis is a medical term for cancer that starts from one particular part and spreads to other parts of the body. In this case, drugs are delivered at the MTD (maximum tolerated dose) until the tumor advances.
The researchers used a mathematical model to examine cancer treatment as a game played by the physician and tumor cells. Oncologists can continuously monitor cancer’s dynamics and adjust drugs/doses to prevent or delay tumor progression. For each single adjustment, oncologists update data on the tumor’s response.
Physician Have Advantages Over Cancer Cell Opponents
In this game, the physician is rational whereas the tumor cells aren’t. Physicians have knowledge of evolution dynamics of cancers and that’s why they can predict tumor’s response. Tumors, on the other hand, can never anticipate the physician’s next move (adjustments in treatment).
Physicians also have another benefit of always ‘playing’ first. Tumor can’t start to evolve resistance until the physicians conduct a therapy. Because of this sequence, we can consider the process of tumor treatment as a game theoretic model known as “Stackelberg” for “leader-follower” game.
The leader in a Stackelberg game has a significant advantage of making the first move, which limits the following responses of cancer cells. Moreover, the leader can use his own experience/knowledge to predict and steer cancer’s vulnerabilities and evolution.
The MTD strategy will only be beneficial if the tumor is made up of same types of cells that aren’t strong enough to adapt and evolve rapidly, but this is rarely the case. Therefore, we need this kind of approach (game theory) to predict, steer and exploit evolutionary responses of cancer cells.
Artistic image of cancer cell | Credit: Raj Creationzs/Shutterstock
The researchers propose that physicians can start adjusting treatment by establishing a goal: whether to prolong life or cure the patient. This will enable them to efficiently balance the advantages of therapy against the possible harmful effects on the patient’s health.
Reference: JAMA Oncology | doi:10.1001/jamaoncol.2018.3395 | Moffitt Cancer Center
If the objective is to prolong life, physicians can utilize evolutionary strategies to reduce the resistant cells’ growth while limiting the harmful side effects. If the objective is to cure, then resistance cells must be killed or prevented.
Ultimately, the physician, as a leader in the game, can regularly monitor cancer responses during each treatment cycle. With the help of a mathematical model known as Bellman equation, this approach can provide useful data to enhance the results of subsequent cycles.
Implementing Theoretical Study
To implement their approach, researches suggested precision medicine to deal with resistance cancer cells. The physicians should develop a Resistance Management Plan for each individual. They also recommended examinations of each patient’s report to improve personalized oncology.
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Although the strategy is developed for fatal metastatic cancers, the complete dynamics of leader-follower games haven’t yet been rigorously studied. However, as they proceed further, researchers believe that their investigation will uncover effective methodologies that could increase the chances of curing even advanced, heterogeneous tumors.