Question: Is it possible to delay, steer, and even reverse the development of chemotherapeutic resistance in a tumor?
Our group is developing evolutionary game theory models, along with optimal and adaptive control theory methods, to design multi-drug schedules that steer the evolution of a tumor
It is widely appreciated that chemo- resistance is the primary reason for recurrence of cancer in patients undergoing treatment and remains one of the primary challenges in the field of oncology. As a tumor grows, and even as tumor cells spread throughout the system and metastasis ensues, standard prescheduled chemotherapeutic protocols such as maximum tolerated dose (MTD) and low-dose metronomic schedules (LDM) often show early success as the tumor regresses temporarily. The development of chemotherapeutic resistance resulting in tumor relapse is largely the consequence of the mechanism of competitive release (aka ecological release) of pre-existing resistant tumor cells selected for regrowth after chemotherapeutic agents attack the previously dominant chemo-sensitive population. Because of the genetic and cellular heterogeneity of a typical tumor, instead of killing all of the cancer cells and thereby eliminating the tumor, the chemotherapeutic regimen actually selects for a resistant phenotype. The diversity of cells within a tumor effectively protects the tumor from single-line or prescheduled chemotherapeutic assaults by allowing for the elimination of the chemo-sensitive population in order to accomplish the subsequent release of the chemoresistant population. By reducing the relative fitness of the sensitive cells, chemotherapy acts as the primary mechanism of natural selection that selects specifically against rapidly dividing cells.
Our lab is developing mathematical and computational models based on evolutionary game theory in the form of the replicator dynamical system and Moran processes to develop adaptive chemotherapy dosing schedules that keep the subpopulations of cells making up the tumor in balance, competing with each other indefinitely, without any one of the cancerous subpopulations dominating the landscape. The basic goal is to shape the evolutionary landscape of the tumor and to impose no more selection than necessary.
Here are four papers you can read to learn more about our approach. See full publication list for others.
- J. West, L. You, J. Zhang, R.A. Gatenby, J.S. Brown, P.K. Newton, A.R.A. Anderson, Towards multi-drug adaptive therapy (pdf) Cancer Research (2020)
- PK Newton, Y Ma, Nonlinear adaptive control of competitive release and chemotherapeutic resistance Phys. Rev. E 99 022404 (2019)
- J West, Y Ma, PK Newton, Capitalizing on competition: An evolutionary model of competitive release in metastatic castration-resistant prostate cancer treatment, J. Theo. Bio. 455 249-260 (2018)
- J West, Z Hasnain, P Macklin, PK Newton, An evolutionary model of tumor cell kinetics and the emergence of molecular heterogeneity driving Gompertzian growth SIAM Review 58(4) 716-736 (2016)
