“Latest Insights from Applying Evolutionary Theory to the Treatment Strategies of Cancer Patients”

“Latest Insights from Applying Evolutionary Theory to the Treatment Strategies of Cancer Patients” (Bob Gatenby, MD) [#154] Brad Power July 30, 2025 “Typically, the design of clinical trials is ‘seat of the pants’. It's intuitive. One of the things that we know about complex dynamic systems, which is a mathematical description of cancer, is that there are nonlinear dynamics.

Human intuition, which is linear, is not really good at those kinds of things. I want to emphasize the need to have formal mathematical modeling to make any of these decisions, especially if you're going to do something that's really far from conventional treatment.

” – Bob Gatenby, MD “If you think about cancer as a game between the oncologist who plays the game by applying a therapy, and the cancer which plays the game by evolving a resistance, the oncologist has two major advantages. One is that he or she always plays first because the cancer cannot make its move until the oncologist has applied a treatment.

That's the equivalent of playing the white pieces in chess. It's called a Stackelberg game, and it gives an inherent advantage to the person who's leading the game. More importantly, is that the oncologist is sentient. The oncologist can anticipate what the cancer is going to do and plan for that; whereas, like any evolving population, the cancer cells can never anticipate the future.

They can never adapt to something they have not seen before. The problem is that when we use the standard approach, which is maximum tolerated continuously until progression, with some adjustments only for toxicity, the oncologist is playing the same move at each cycle, so the cancer cells can simply respond as they have before. There's no additional burden placed on them.

Because the oncologist changes treatment only when the cancer progresses, the oncologist has ceded control of the game to the cancer. What we want to do is have the oncologist playing a far more active and informed kind of game.

” – Bob Gatenby, MD Meeting Summary Cancer patients and their caregivers face an explosion of testing and treatment options that is increasing the complexity of decision-making. For some patients, there are too many options, while other patients are faced with very few good treatment options.

The typical approach is to look to the evidence-based standard of care and find your best treatment option. A drug is selected, often a chemotherapy or targeted therapy, and it is applied at the maximum tolerable dose until it fails, and you move on to your next treatment. A more complex approach is to look long-term and strategically.

This approach considers combining therapies, personalized (often low) doses, and sequencing treatments. For example, should you start with chemotherapy to eradicate or shrink your cancer, or get immunotherapy as a first line of treatment while your immune system is strong?

onalized (often low) doses, and sequencing treatments. For example, should you start with chemotherapy to eradicate or shrink your cancer, or get immunotherapy as a first line of treatment while your immune system is strong? If you have several possible treatment options, should you consider combining them?

Bob Gatenby, MD, Moffitt Cancer Center, Co-Director, Center of Excellence for Evolutionary Therapy, and Department Chair, Diagnostic Imaging, is uniquely qualified to lead a discussion on the big picture strategy you should use to manage your cancer treatment.

“Latest Insights from Applying Evolutionary Theory to the Treatment Strategies of Cancer Patients” (Bob Gatenby, MD) [#154] mathematical simulation, mechanistic mathematical models, evolutionary and game theory, and experimental models to treatment decisions.

Bob advocates using “adaptive therapy”: rather than continuously applying the maximum tolerable dose until resistance: you treat enough to knock the tumor back a little bit, and then pull the treatment away, allowing the tumor to grow back.

But since the sensitive cells do not have the burden of the resistance mechanisms that the resistant cells have, the sensitive cells have a fitness advantage in the absence of therapy, and outcompete the resistant cells. The strategy is to use the sensitive cells that you can control to control the resistant cells that you cannot control.

Other principles: ●Combinations (first strike second strike): This strategy emerges from investigations of Anthropogenic (human-induced) extinctions. Generally, we think about species extinctions in terms of the dinosaurs - a single massive application of evolutionary force. Arguably, the high dose density therapy in cancer is built upon this conceptual model.

However, because our species is consistently causing extinction of other species, we have had an opportunity to observe species extinctions in real time. It turns out that most extinctions are not the result of a single event but rather a series of different perturbations none of which, in itself, could cause extinction.

This has potential lessons for cancer therapy which, since the pioneering work of Ehrlich, focused on drug development to find “magic bullets” which are drugs that kill cancer cells but do not harm normal cells. The lessons from Anthropocene extinctions is that, lacking magic bullets, metastatic cancers can still theoretically be cured through a strategic combination of pretty good bullets.

None of these bullets could by themselves cure the cancer, but a sequence of strategically timed perturbations can generate synergistic dynamics (termed an “extinction vortex”) that can result in extinction. Interestingly, the current sequence of treatments that are curative in childhood leukemia represent a real world example of this treatment strategy.

ction vortex”) that can result in extinction. Interestingly, the current sequence of treatments that are curative in childhood leukemia represent a real world example of this treatment strategy. ●Sequencing (not a combination cocktail): If you have a combination cocktail, especially as a first strike, you're applying the therapy to the largest possible population.

The heterogeneity is such that almost certainly you will find tumor cells that can be resistant to the combination. It is better to hit the cancer with therapies in sequence, as each knocks the population down and can drive it to an extinction. Ideally, the sequence should generate an “evolutionary double bind”.

In this strategy, a treatment is applied that kills cancer cells but also results in predictable evolution of a specific adaptive mechanism. The second therapy induces cytotoxicity by specifically targeting the mechanism of resistance. An analogy is control of a rodent population in an agricultural setting. An effective “therapy” is the introduction of owls.

However, the rodents can adapt by hiding under bushes. This can be countered by introducing snakes. So, adaptation to one predator makes them vulnerable to the other and vice-versa. Evolution has a difficult time solving this conundrum and the typical result is a small stable population or complete eradication. This can be found in cancer treatment.

For example, we have found that cancer cells adapt to DNA damaging agents by upregulating DNA repair pathways and immunogenic cell stress pathways. The latter includes increased expression of membrane proteins recognized by Natural Killer cells.

“Latest Insights from Applying Evolutionary Theory to the Treatment Strategies of Cancer Patients” (Bob Gatenby, MD) [#154] If we add NK cells to prostate cancer cells that have adapted to radiation therapy, they are consistently eradicated.

●Focus on the mechanism of resistance by giving one therapy and anticipating the adaptive response, then following up with a treatment that specifically targets the evolved resistance mechanism. ●On-off cycling of treatments based on your response. How can mathematical models and evolutionary and game theory help you understand your complex cancer dynamics and improve your treatment strategy?

●Predict cancer cell evolution and resistance mechanisms ●Simulate treatment responses before clinical trials ●Optimize treatment timing and dosing strategies ●Develop personalized treatment plans based on your data ●Identify gaps in current understanding ●Develop more nuanced treatment approaches ●Move beyond intuitive, linear thinking and create more sophisticated, dynamic treatment strategies that anticipate your cancer's evolutionary responses What are the key considerations for individualizing dosing and monitoring strategies in the adaptive therapy approach, for example in prostate cancer?

t strategies that anticipate your cancer's evolutionary responses What are the key considerations for individualizing dosing and monitoring strategies in the adaptive therapy approach, for example in prostate cancer?

●Maintain a population of treatment-sensitive cells : prevent the dominance of resistant cells ●Test frequently: get consistent labs (weekly or bi-weekly) to track testosterone and PSA levels, observing rates of increase and decrease ●Track your cancer biomarker : monitor your PSA levels closely, allowing it to rise to about 50% of the pre-treatment value before stopping treatment.

●Track other markers (e.g., hormones) : ensure a rapid testosterone upsweep (within a few days) when coming off androgen deprivation therapy (ADT). A slow recovery can allow cancer cells to adapt.

●Monitor your symptoms : consider your symptoms alongside lab results, not just focusing on achieving the lowest possible PSA ●Personalize cycles : adjust treatment cycles based on your response, using mathematical models to guide decision-making Who should consider adaptive therapy and mathematical models to guide their treatment?

“Latest Insights from Applying Evolutionary Theory to the Treatment Strategies of Cancer Patients” (Bob Gatenby, MD) [#154] ●If you are willing to have frequent monitoring (PSA and testosterone), are comfortable with fluctuating biomarkers (PSA levels), want to reduce treatment costs, and are open to a more strategic, mathematically-guided treatment approach.

●If you have not responded well to standard continuous treatment How can you learn more and get help in making strategic testing and treatment decisions using mathematical models?

●Consult with doctors familiar with adaptive therapy and who collaborate with mathematical modeling teams ●Consider consulting with teams that specialize in an evolutionary approach to cancer treatment, like Bob Gatenby ( Robert.Gatenby@moffitt.org ) and his team at Moffitt Cancer Center which includes oncologists, mathematicians, and evolutionary biologists ●Consider contacting Dr.

Dawn Lemanne ( doctor@oregonio.

○The “Personalization Conundrum” (Brad Power) [#16] ○"Modeling Disease" (Michael Liebman) [#24] ○“Personalizing Treatments with Biosimulation" (Michael Castro, MD) [#88] ○"Simulations for Predicting Treatment Response" (Marc Birtwistle) [#20] ○"Bipolar Androgen Therapy" (Bryce Olson and Bob Gatenby) [#21] The information and opinions expressed on this website or platform, or during discussions and presentations (both verbal and written) are not intended as health care recommendations or medical advice by Cancer Patient Lab, its principals, presenters, participants, or representatives for any medical treatment, product, or course of action.

You should always consult a doctor about your specific situation before pursuing any health care program, treatment, product or other course of action that might affect your health. For the video recording of this conversation, please see here.

“Latest Insights from Applying Evolutionary Theory to the Treatment Strategies of Cancer Patients” (Bob Gatenby, MD) [#154] Meeting Notes KEYWORDS Cancer treatment, adaptive therapy, bipolar androgen therapy, prostate cancer, evolutionary biology, game theory, maximum tolerated dose, personalized dosing, testosterone levels, PSA ratio, mathematical models, oncology, resistance mechanisms, clinical trials, patient care.

SPEAKERS Bob Gatenby (68%), Brad Power (9%), Chase (6%), Jeff Krolick (6%), Paul Van Camp (4%), Allen Morris (4%), Rick Davis (1%), Bill Paseman (1%), Chris Apfel (1%) CHAT CONTRIBUTORS Ari Akerstein, Chris Apfel, Rick Davis, Chase, Russ Hollyer, Allen Morris, Raj Aji, Richard Anders, David Plunkett, Steve R, Len Sierra, Bill Paseman SUMMARY Bob Gatenby discussed his adaptive therapy approach for prostate cancer, emphasizing the importance of maintaining treatment-sensitive cells.

He highlighted a trial using Abiraterone, showing a 28-month overall survival difference and a $70,000 cost reduction per patient per year. The median time to progression exceeded 6 years, with patients receiving treatment only 46% of the time. He also introduced a directed evolution strategy using testosterone injections to target resistant cells.

He noted that mathematical models guide treatment decisions, aiming to maintain a stable chronic disease state with reduced toxicity and cost. OUTLINE Introduction and Background of Bob Gatenby ●Bob Gatenby has joined for two previous sessions on evolutionary biology and game theory in cancer care.

●He is recognized for his leadership in adaptive therapy, particularly bipolar androgen therapy in prostate cancer. ●Bob's strategic approach to cancer treatment is unique, especially in contrast to the typical "maximum tolerated dose until failure" approach of most doctors.

Overview of Cancer Evolution and Treatment Strategies ●Cancer death is often due to evolution, with cancer cells rapidly evolving resistance to treatments.