181 - Viewing cancer through an evolutionary lens: a radically different approach to treatment

1. 0:00 – 0:10

   intro

   1. PAPeter Attia0:00

      [upbeat music] Hey, everyone. Welcome to "The Drive" podcast. I'm your host, Peter Attia. [upbeat music] Hey, Bob.

2. 0:10 – 12:30

   Bob’s unlikely path to medicine and his disappointment with his medical school experience

   1. PAPeter Attia0:10

      Thanks so much for making time to chat today. I've, I've been looking forward to this one for, for quite some time.

   2. RGRobert Gatenby0:15

      Thanks for having me.

   3. PAPeter Attia0:17

      So, um, I'll tell you, I kind of stumbled across your work in preparing actually for another podcast. So I was doing another podcast some time ago, and in the process of it, uh, actually came across an article in Wired about you, um, which we'll obviously link to in the show notes, and that whole concept just quickly captivated me such that I, I kind of made a note to my team and said, "Hey, at, at some point, this is someone I'm gonna wanna interview, and I'm gonna wanna talk about this entire, um, approach to cancer." And, and lo and behold, that led us to reach out to you, and that's, um, that's how it came about. But it's interesting that it really started with, you know, th- the sort of rabbit hole you can easily find yourself on in Google where you're trying to find out about this treatment for this type of cancer and this treatment and da, da, da, da, da, and then all of a sudden you see something. And I don't know what led me to read that whole article, but I was very captivated by it. Um, and I guess part of it is my own bias, which is, um, my background is very similar to yours. So, so tell folks a little bit about your, your background 'cause your path to medicine was not, uh, I guess the standard path.

   4. RGRobert Gatenby1:28

      Uh, uh, no. I, I guess I, I... When I went to college, uh, I wanted to be a physicist and, um, spent most of that time really thinking that I, I should do that. Um, and then, uh, I, I had some great physicists, uh, as, as mentors and s- kind of came to the conclusion I'm not smart enough to do this. [chuckles] And, and I gotta s- I gotta find something else to do. A- and, um, and of course, that was in the great humanist, uh, you know, the Vietnam War era, and going to medical school was considered, uh, something that was really, you know, for humanity and something that I, I decided I would, I would do, um, to, to my, to my regret by the way, but, but I did, I did end up doing it.

   5. PAPeter Attia2:13

      So you were at Princeton as an undergrad in the late '60s?

   6. RGRobert Gatenby2:17

      Uh, late '60s, early '70s. Uh, yes.

   7. PAPeter Attia2:20

      And y- you know, Richard Feynman of course also did-

   8. RGRobert Gatenby2:22

      Mm-hmm

   9. PAPeter Attia2:22

      ... his undergrad at, um-

   10. RGRobert Gatenby2:24

       Mm-hmm

   11. PAPeter Attia2:24

       ... at Pr- Actually, no, no. Did he do his PhD at Princeton and his undergrad at MIT-

   12. RGRobert Gatenby2:28

       Yes

   13. PAPeter Attia2:28

       ... right?

   14. RGRobert Gatenby2:28

       Mm-hmm. Yes.

   15. PAPeter Attia2:29

       So was there still the shadow of Feynman there in the late '60s? 'Cause he had just won his Nobel Prize in about '66, right?

   16. RGRobert Gatenby2:36

       Absolutely. Um, and, and Wheeler was still the department chair, and he was, you know, one of the great physicists of his generation. Um, and, uh, a- actually my, my, uh, TA, uh, was, um, t- turned out to, uh, uh, won a Field Medal, um-

   17. PAPeter Attia2:55

       Wow

   18. RGRobert Gatenby2:55

       ... subsequently. A- and so, uh, you know, I was surrounded by really smart people a- and, uh, and it was a very, um, enriching time. I mean, it was just, just very stimulating and, and, uh, intellectually exciting to, to be there at the time.

   19. PAPeter Attia3:11

       And for people who don't know, the Fields Medal is like the Nobel Prize for mathematics. The-

   20. RGRobert Gatenby3:15

       Yes. Yeah

   21. PAPeter Attia3:15

       ... mathematics does not have a Nobel Prize. The Fields Medal is a substitute-

   22. RGRobert Gatenby3:19

       Yes

   23. PAPeter Attia3:19

       ... although it comes with two caveats. One, the recipient has to be, I believe, under 40, correct?

   24. RGRobert Gatenby3:23

       Mm-hmm. Yes.

   25. PAPeter Attia3:24

       And the second caveat is it's only awarded, I believe, every four years instead of annually.

   26. RGRobert Gatenby3:29

       Yeah. So, um, yeah, and his, i- and this was Witten, Dr. Witten, who, uh, has been very involved in string theory.

   27. PAPeter Attia3:37

       So, um, you, you decide to, uh, to, to take this detour into medicine. Aside from the altruism and the feeling that you weren't brilliant enough to win a Nobel Prize in physics, what, what else drew you to medicine?

   28. RGRobert Gatenby3:51

       Uh, um, y- well, yeah, th- that was pret- pretty much it. You know, it seemed like, uh, um, kind of the right thing to do. It was, uh, again, that era was full of, uh, wanting to help the humanity and, and, you know, those kinds of exalted ideas about, uh, changing the world. So it's, it... I, I guess I entered medical school, uh, with those things in mind, assuming that I would, um, link the science, uh, there to, to, to helping people.

   29. PAPeter Attia4:23

       But, but now given that, you know, the space race of the 1960s, um, probably attracted some of the best and brightest people into engineering, which you were already in, did, did you at some point consider, you know, staying in engineering but not, uh, pursuing physics?

   30. RGRobert Gatenby4:44

       Um, uh, no. I, and I don't know why. I, I can't quite tell you that. Um, somehow medicine, uh, just kind of drew me. The idea of it was so compelling that I felt like it was, I don't know, something I wanted to do. Now, I will tell you that I hated every minute of medical school and, uh, almost from the beginning began looking at graduate schools [chuckles] to do something else, um, and, and ultimately decided to stay in it, but, uh, but, but was disappointed, uh, by what I found there.
3. 12:30 – 29:27

   Rethinking the approach to cancer: using first principles and applying mathematical models

   1. RGRobert Gatenby12:30

      [laughs]

   2. PAPeter Attia12:32

      So when you were in medical school, um, what drew you to radiology? Or at, at the time, did you go into radiology first and then radiation oncology, or how did you, um, how did you make that choice?

   3. RGRobert Gatenby12:44

      Um, y- you know, I like the, the radiology was a minimum game puzzle. You know, y- y- a minimum in- information puzzle where you, you know, sort of get bits and pieces of things and try to put it together, and, and I, I really like that as an intellectual exercise. I, I don't know, somehow it appealed to me. Uh, um, and, uh, to be honest, I mean, I, I, you know, I was a very shy, uh, kind of retiring kid. Dealing with patients was very difficult for me. Um, it was a lot easier to work, [laughs] to work with films. Um, and so it, it just, it, it intellectually and psychologically met the kinds of things that I, I like to do. So, um, it just, it just felt like the right thing, and, um, and I'm happy I did it because that, that was really one of the few things in medical school that I liked. So-

   4. PAPeter Attia13:36

      Which I think is very common for people with our background. I, I had decided early on that I was going to go into surgery, um, [clears throat] and, and one of the drawbacks, I guess, of deciding early on what you're gonna do is it makes some of the other rotations you go through less enjoyable. Um, but that wasn't true for radiology because once I got to my month of radiology, I was, I mean, categorically obsessed with this field because, first of all, all of the residents I met were basically engineers, mathematicians, and physicists, so it heavily selects for those people. An understanding of math and physics gave you an understanding of how the MRI machine worked in a way that you, you simply couldn't understand that without the background. And I remember thinking, "God, I wish there was a way to do both surgery and radiology."

   5. RGRobert Gatenby14:28

      [laughs] Yeah. So it, yeah, it was... I found it very appealing, and, uh, and, and enjoyed the residency and did enjoy people that I, I began working with in that, in that setting.

   6. PAPeter Attia14:39

      So where was it in your, um, radiology career, if not sooner, that you began to, um, start to think about cancer in a different way?

   7. RGRobert Gatenby14:50

      Well, my first job outside of training was at the Fox Chase Cancer Center in Philadelphia, and, um, I hadn't really thought about cancer very much, and of course, uh, you know, we, we kind of had these very dogmatic views of cancer i- in what training I did get, and, uh, but when you work in a cancer center, I mean, y- you just wanna help. I mean, I mean, it just, it felt like you wanna make a contribution because this disease is just so awful. And so, um, so I decided I would, I would spend more time learning about cancer, and I would, uh, you know, really just get textbooks and read it. And, uh, um, one of the things I started reading was the, the, the journal Cancer Research, which is the flagship journal of the ACR, and one of the things I found was that I would read an article and say, "Well, this is really a good article, and that's really interesting and important," and then I would read another article and have the same response. But then I would try to think of, "Well, how do these fit together? How do these relate to one another?" A- and, and I couldn't see that. And, and there, there was no organizing principles that was involved. I mean, they, they, the authors themselves were not trying to, to put these together. They were simply making a sequence of observations. Each were really quite separate. And, and, and as you know, um, in the physics world, these things had happened. The planetary motions, for example, um, you know, Tycho Brahe and others pretty much had the data, but the data was overwhelming and complicated. Um, you know, Kepler developed a kind of geometric, um, i- interaction, and then ultimately it was Newton who developed first principles that could put all this together. And, you know, similar with the Balmer lines, uh, i- in the, uh, early 20th century, the particle zoo in the, in the mid-20th century, all of those required, um, theoretical mastery of it. You know, you needed to-

   8. PAPeter Attia16:46

      You could even make the case with, with Einstein's work around, um, the photoelectric effect. I mean, most people think Einstein won the Nobel Prize for relativity, but it was actually for the photoelectric effect, photoelectric effect.

   9. RGRobert Gatenby16:58

      Yeah.

   10. PAPeter Attia16:58

       And he was not the first person to make the observation. He was simply the first person to put it all together.

   11. RGRobert Gatenby17:05

       Yeah.

   12. PAPeter Attia17:05

       And, and I've always found that to be a very illustrative case of what really, what genius really is. It's that ability to assimilate information, um, and pattern from what others can't see, and that, you know, that, and Einstein and others are the examples.

   13. RGRobert Gatenby17:21

       So, so I decided that maybe w- where I could contribute is to focus on developing first principles, developing a, uh, a, a kind of framework of understanding but recognizing that it really had to be mathematical. And so I, um, I actually spent about a year relearning the mathematics. Um, I'd forgotten it all by then. And, um, then, uh, worked on developing, you know, so what are the first principles, and I, I, I decided it, it would, you know, it'd have to be evolution and ecology, that, that all living systems essentially obey the laws of Darwin, and, and therefore cancer must do the same. A- and so I sat down, and I started writing, um, uh, population, uh, dynamic equations looking at, um, at cancer, looking at the interaction of cancer with, with normal cells and then the cancers with each other, cancer cells with each other and competing them and, and, and that sort of thing. And so that was, um, how I, I started it. Um-

   14. PAPeter Attia18:21

       Now, why, why were you so convinced, Bob, that this had to be done mathematically as opposed to theoretically but without the, the, the quote unquote cumbersome mathematics that comes with it?

   15. RGRobert Gatenby18:33

       I think that, that, um, I brought with it an appreciation of nonlinearity, um, that human beings think linearly, and when complex systems have nonlinear things like feedback loops that, uh, you know, so the linear thinking is if you do one, you get two, you get two, you do two, you get four, you get four, you do eight. Uh, you know, that we're real good. The human brain is very good at that. But nonlinear dynamics, we're, we're really not good at all. And, and, uh, a great example, which is also from Philadelphia, uh, was, uh, Benjamin Franklin wanted to see the, uh, a, a lunar eclipse one evening. And, um, but a nor'easter came in. Now, a nor'easter, if you live in Philadelphia, you're, you're familiar with these. They, wind's coming from the nor'east, northeast, hence the name. And this, uh, you know, these are often violent storms, and so it rolled in and he couldn't see the, the, the, the lunar eclipse. Now, Franklin, like all scientists of his day, thought that the wind carried the storm. In effect, if you ask a child, "How do you, what, how do you think storms move?" They will say, "Well, it must be the wind blowing it," 'cause it, it, it makes sense. It, it's intuitively obvious that that's the case. But when he learned, when he talked to his brother in Boston about the eclipse, it turned out that the storm arrived in Boston after the eclipse was over. So in fact, the storm was going in the opposite direction of the wind, and he was really the first, uh, scientist to be, to, to recognize that that's, that, that, that, that obvious, that, that, that something that's intuitively clear must be happening is also wrong. And, and so I think that, um, in cancers, we see nonlinearities all the time, and, and again, the feedback, the evolutionary dynamics of, of resistance, for example, is a good example of that. A- and we can't intuitively predict those things. We, we need to actually understand first principles and the underlying mathematics to, to, to capture that piece of it. A- and so I guess I was very involved in that kind of thing, and it, to me, it seemed obvious that we needed to do the math because, um, what, what, the things that were, were being done in, in cancer treatment were often intuitively obvious but were clearly not working [chuckles] . Um, so, uh, so I don't know. I mean, I don't, uh, I mean, I may be putting retrospective, you know, analysis on that, but at the time it seemed that it really had to be understood mathematically. And of course, from a physics background, that's just kind of a natural, you know, the theory has to be fundamentally about mathematics, so.

   16. PAPeter Attia21:09

       Just, this is m- ju- just sort of a fun aside question. Why do you think that evolution, um, gave us as humans the ability to understand linear systems quite well and absolutely no capability to understand [chuckles] nonlinear systems? So for example, um, it's clear that we don't understand hyperbolic discounting.

   17. RGRobert Gatenby21:33

       Mm.

   18. PAPeter Attia21:33

       Like, we, we just can't do it. Is it simply that evolution wasn't optimizing for that problem?

   19. RGRobert Gatenby21:39

       Yeah.

   20. PAPeter Attia21:39

       And it really didn't, when it came down to reproduction and survival, linearity was sufficient?

   21. RGRobert Gatenby21:46

       Th- that would be my guess, that, that what we need to know to survive and, and, and proliferate is, is linear, is sufficiently linear that we can probably, that's probably all that was needed. Uh, but I, I, y- y- you know, I, um, I'd have to think more about that. I mean, what's, what's linear in the world that, um, is so important? But, but my sense is that, um, relatively simple things that, that are related to, you know, eating and running away from, uh, predators and that sort of thing and ru- running after mates are probably sufficiently linear that that was really the, all that was necessary.

   22. PAPeter Attia22:22

       So as you're getting deeper into the mathematics of, um, of, of, of, of, um, of the biology, you're probably struck by the fact that you don't have a lot of colleagues in this space, right? There's not a conference for theoretical biologists, right?

   23. RGRobert Gatenby22:39

       No. No. No, and, and to s- and similar to the, the response of your colleagues to your model, um, pretty much everybody, all, pretty much all of my colleagues hated it. Um, f- thought the whole thing was ridiculous.

   24. PAPeter Attia22:53

       But did they, were they even qualified to understand it?

   25. RGRobert Gatenby22:57

       N- probably not, but, but just, uh, on an intuitive level, it was, um, they just couldn't understand why you would do this. A- and it's funny because if I, if I had a dollar for every time someone said to me that cancer is too complicated to model, I, I, you know, I wouldn't have to apply for grants anymore, uh, because that was kind of the prevailing wisdom. And, and I mean, the irony of that is that the argument itself is self, i- i- is self-defeating. If it's that complicated, then you have to have mathematics. I mean, you, you, there's, there's no way that the, that the human brain is gonna understand complex systems without sufficient, you know, mathematics. I, unfortunately, I think in there, uh, w- was a certain arrogance that you're also taught as physicians, which is that, uh, well, it's too complicated to model, but my superior intellect will be able to sort of master this a- and, and figure it out. I mean, I, I always got the feeling that there was that, that second clause in that statement that, that was, that went unsaid, uh, but was part of this kind of idea that this confidence that, um, we can understand this and, and, you know, we step back and w- and we can take care of this without the mathematics. Um, and so, so I think it takes some humility to say, "No, I, I really need to look at the math models and, and the computer simulations to understand how I think this is gonna happen." I don't know that we physicians have been taught humility with, with sufficiently well, uh, to, um, you know, to accept that.

   26. PAPeter Attia24:32

       Y- yeah, and, and, and another great example of that is look at other incredibly complex systems like, um, economics. Um, and of course, uh, uh, I don't know what the stats would be, but certainly a sufficient number of the Nobel Prizes awarded in that field are, you know, in their fun- are fundamentally based on mathematics, right?

   27. RGRobert Gatenby24:54

       So absolutely.

   28. PAPeter Attia24:54

       Whether it be game theory or otherwise. Uh, obviously a lot of them are behavioral as well, but nevertheless, I don't think anybody is suggesting that the models are sufficient in economics. In other words, that you can take an economic model, you can plug in all of the initial conditions, and it will tell you the answer. If unemployment is this, if the rate of home price appreciation is this, if inflation is this, here are 50, you know, starting variables, put them in the model and it will spit out, you know, GDP growth 10 years from now. I don't think anybody's so delusional to believe that that's true, but it still doesn't minimize what the model can do for your understanding of the system.

   29. RGRobert Gatenby25:33

       Yeah. We, we like to talk about, uh, hurricane modeling, um, you know, and, and weather modeling in general, which is, which is a, a classic example of how to master a complex dynamic system. Um, and you know, you can, you can pretty much, you can be pretty sure that you can predict what's gonna happen in the next 24 hours. After that, the, the, um, the, the complexity as well as stochastic, uh, p- you know, changes are gonna degrade the, the accuracy. Uh, but that, that doesn't mean that-- So at each day, you, you, you, you get more data and you just keep predicting forward. Um, it's, it's not necessary, a-at least again, in, in, in sort of cancer modeling to say what's gonna happen 10 years from now. It's an, it's just you need to know what should I do to, what therapy should I use today, and, and for the next three months, say, and then after that, we'll, we'll get more data. We'll, we'll, we'll start again. Um, but, but sometimes people expect more of that, of it than that. And, uh, like you said, that's, uh, this idea that we should be able to predict the entire course is, is, is not realistic.

   30. PAPeter Attia26:44

       You know, I'm glad you brought up hurricanes and, and weather because as you note, they're some of the most complicated models out there.
4. 29:27 – 37:50

   Relating predator prey-models to cancer

   1. PAPeter Attia29:27

      So let's go back to, you know, that first year where you're, you've relearned the mathematics. Um, presumably at some point you say, "I want to look in nature and see where mathematics has already come up with an elegant way to describe a similar problem." Is that what led you to the study of predator prey-models?

   2. RGRobert Gatenby29:50

      Uh, yeah, it just-- The, um, uh, eco-evolutionary dynamics in general. Um, and, and bec- it's very appealing 'cause, of course, they're living systems. You know, these, the ecology of, of, uh, you know, swamps and that sort of thing is very complicated, and yet they can m-more or less master these, these, these complex relationships. And so that was appealing to me. Um, it was also appealing to me because, you know, when you work in a cancer center, um, the, the, uh, the cancer almost takes on a, a persona, a, a, like an evil entity kind of thing, uh, almost magical in its ability to, uh, to overcome anything that the physicians do. And, and, and if you talk to oncologists, many of them will, will, you know, have that... They, they may not say it, but they have that kind of sense of it. And to me Just saying that cancers have to obey Darwinian laws, that they're not magic, they're not unfathomable. They, they simply are really good evolutionary machines. And we can ma- we, we can master this. We, we, we understand evolution and, and we can get on top of this. This is, this is, you know, it's not, it's not something that we cannot understand. Because before that, it just felt like we have no basis to, to understand this. It, it just happens and we do this and then this happens and... So this to, to me, gave it some deterministic quality, some, some cause effect, uh, relationships that I, that at least to me, were comforting. Like I y- y- yeah, we could, we could deal with this.

   3. PAPeter Attia31:33

      So explain to folks how the standard relatively simple predator prey models work. So, um, the, the swamp is too complicated 'cause you-

   4. RGRobert Gatenby31:43

      Yeah

   5. PAPeter Attia31:43

      ... might have multiple predators-

   6. RGRobert Gatenby31:45

      Yeah

   7. PAPeter Attia31:45

      ... and multiple prey. But let's start with first order differential equations, second order differential equations where you've got one, you know, you've got an isolated ecosystem where you've got foxes and hares. How does that-

   8. RGRobert Gatenby31:57

      Sure

   9. PAPeter Attia31:57

      ... dynamic work?

   10. RGRobert Gatenby31:59

       Uh, well, the, you know, the hares, uh, essentially turn, uh, convert, um, local vegetation to babies, uh, to baby hares, and so they reproduce. The foxes or whatever the predator is going to eat the, uh, the, um, the, the rabbits. Um, and of course, so then you get these, these population rises and falls because, uh, i- if the, uh, i- if the predator eats too many of the, of the prey, then its population will tend to decline. As its population declines, the predator population expands. A- and so you can see these, this cycling effect that goes on for prolonged periods of time. And there at least are some data that have suggested that this is the case. But as with everything that's, that's living, it's, it's always more complicated than that. There's always various factors that, that's come into play. But at least that was really, I think, probably if, probably the first of, uh, really kind of recognized, uh, population models that began to be applied to nature. Um, and so, uh, to, it's kind of, it's interesting to see that. And predator prey models are still are, are things that we use a little bit like for the immune system, where the, the immune system is kind of a predator a- and the, and it's chasing after the, the cancer cells. Um, but of course, there's, there's, there's important differences in that. The, the, uh, predator eats the prey and gains y- y- you know, substrate from that, whereas in, in the pre- in the immune system, it kills the, the, the cancer cells, but it, it loses substrate. It doesn't eat them up. And in fact, if anything, if anybody's eating anything, it's probably the cancer cells are s- are swooping up, um, you know, elements of their brethren that, you know, the macromolecules that they're, are getting spilled into the environment. So, so there's i- i- i- again, it's an app- one of those things that's an appealing model, the predator prey model t- in, in i- immunotherapy, and yet there are important distinctions that you have to recognize that, that make the biology different, and in some ways can give advantages to the prey that you don't really expect.

   11. PAPeter Attia34:16

       So when you move on to a more complicated system like the swamp, right? Where-

   12. RGRobert Gatenby34:20

       Mm-hmm

   13. PAPeter Attia34:20

       ... you've got, you know, you've got everything from algae to bacteria to, you know, small fish, and then you have to deal with how much sunlight is coming in, and what's the temperature. I mean, now it starts to look a little bit more like the human body, where why is there an algal, you know, bloom here-

   14. RGRobert Gatenby34:42

       Mm-hmm

   15. PAPeter Attia34:43

       ... that basically consumes all of the oxygen and rapidly kills all the fish-

   16. RGRobert Gatenby34:48

       Mm-hmm

   17. PAPeter Attia34:48

       ... versus a system that can be somewhat in a sustained setting where you never fully get rid of the algae, but the fish can live and there's-

   18. RGRobert Gatenby34:56

       Yeah

   19. PAPeter Attia34:56

       ... kind of a, a beautiful chain of carbon fixation that goes from algae to fish. Um-

   20. RGRobert Gatenby35:03

       Yeah

   21. PAPeter Attia35:03

       ... so to me, like, how did you get to the point where you could look at that and say, "We can now model this for human cancer, given that this is far more likely of how it behaves"?

   22. RGRobert Gatenby35:16

       Um, again, it's, you know, simplifying. Uh, it, it, it, it's, uh, you know, the best we can do is sort of a cartoon. And it's interesting to, to think about why. I mean, ecologists, uh, uh, that are looking at a new ecosystem will begin by asking a very simple question. What's the birth rate and death rate of each species that's present? We don't know that in the cancer. I mean, astonishingly enough, that's not data that we get. Um, what's the carbon cycle? What's the iron cycle? What's the sul- you know, nitrogen? What are all these cycles? How can we, can we watch these substrate pass through individuals and, and how does that work? We, we don't get that. So one of the, uh, pr- problems that, that... and so ecologists kind of turn pale when we, when they start asking these questions and realize that we have n- that, that the cancer biologists have never thought in those terms. I mean, something as simple as [laughs] what is the, what is the birth rate and the death rate of the cancer population? Um, you know, it's, it's astonishing to me that we, we don't know that. That, that... and, um, you know, things like that, that we, we, you know, what's the growth rate of the tumor? What are, what are we kind of dealing with e- even in a first order kind of, uh, estimate? Um, we, we o- we often don't do. Um, and it's kind of astounding to me it, it, that, that, um, we have, we do things very crudely in, in, in my, in my opinion, can... We don't, we, you know, the evolutionary biologists and ecologists are, you know, take a far more sophisticated view of these, of these interactions than we do. Even to the point, an interesting fact is that if you were a pesticide manufacturer, you are required by law to submit a, um, a, a resistance management plan. You have to identify how pests become resistant to your, you know, what are the mechanisms of resistance, a-and how do I plan to prevent that from occurring? We- we, you can, you can introduce cancer drugs ... Yeah, I mean, well, cancer drugs are routinely, um, uh, uh, approved without any knowledge, uh, of what the resistance mechanism is, much less how you're gonna manage that in a patient. Um, so again, this, this odd kind of disconnect that, um, w- in, in some ways, I think the ecologists, evolutionary biologists have, have pushed ahead of us, and we're just still trying to catch up with them in terms of, of understanding, of taking their sophisticated models and, and, and applying them to,

5. 37:50 – 47:27

   Insights into cancer gathered from ecological models of pests and pesticides

   1. RGRobert Gatenby37:50

      to cancer.

   2. PAPeter Attia37:51

      So let's talk about the ecologic models of, um, of pests and, um, pesticides 'cause that's-

   3. RGRobert Gatenby37:58

      Mm-hmm

   4. PAPeter Attia37:58

      ... something that I think gave you a big insight, correct?

   5. RGRobert Gatenby38:01

      Mm-hmm. Mm-hmm. Yes. So, uh, one of the things that I had, uh, run across was just a, a, a, a kind of a story on the, on the internet news somewhere about the diamondback moth. And, and it was, uh ... The, the story was that it was, that it, it, uh, was first recognized, I think it's in Indiana, somewhere in the Midwest, uh, in the, uh, mid-19th century. And, a-and this, this ... The diamondback moth has, has the, I guess, the, the, um, uh, the, the, uh, honor of having received and struck by every pesticide developed in the modern era. And, um, a-and what it has done is, is absolutely nothing. Uh, the, the ... In fact, it's spread all over ... The diamondback moth spread all over the country a- and, uh, to Europe and to Asia, and it's just everywhere. A-and in the 1980s, it was ... They, they were, uh, uncovering diamondback moths that were, uh, not susceptible to any known pesticide. I mean, they had become resistant to all of them. And, uh, to me, this was, it was interesting because ... So, so it, it ... You begin to sort of look at this, that, this whole process. And, and of course, farmers for, for centuries, um, used pesticides freely, and the idea is you dump as much of it on, uh, on the, the, uh, your fields as you can. You wanna, you know, get rid of as many of the pests as you can. Um, but what people realized is that by doing that, you're, you're selecting for resistance. And so, um-

   6. PAPeter Attia39:35

      Explain to people why that's true because it is counterintuitive. I think most people would say, "Well, gosh, if I'm a farmer and I've got my acre of corn here, and there are a million moths that have descended on this acre, I want to get every one of them eradicated. And the best odds of doing that, wouldn't that just be using all of the pesticide I can, just shy of killing my own crop?"

   7. RGRobert Gatenby40:05

      Yes, and that, that's one of those things that is intuitively appealing but not necessarily true.

   8. PAPeter Attia40:11

      [clears throat]

   9. RGRobert Gatenby40:12

      And, and the reason is that you're, you're dealing with, uh, a very large population, and this is not a uniform population. Uh, it's the ... This is biology, which means that there's, there's heterogeneity within that population, and there are moths in that population that are extremely sensitive to the pesticide, and there's gonna be moths in that, that population that are not very sensitive to the pesticide.

   10. PAPeter Attia40:36

       Okay, so let's put some numbers to it. So then I just gave you a million moths. You dump the best pesticide imaginable on them. What if we assume that there's a spectrum and, you know, 20% of them die at the first whiff of the pesticide, 60% of them, eh, eventually get clubbed to death, but 20% of them, I don't know, they, they seem somewhat immune. Is that-

   11. RGRobert Gatenby41:03

       Yeah.

   12. PAPeter Attia41:04

       Let's just use those numbers.

   13. RGRobert Gatenby41:05

       Yeah.

   14. PAPeter Attia41:05

       Right?

   15. RGRobert Gatenby41:05

       Sure. Sure.

   16. PAPeter Attia41:06

       Um-

   17. RGRobert Gatenby41:06

       And then so short-term, you did good. I mean-

   18. PAPeter Attia41:10

       Because you got rid of-

   19. RGRobert Gatenby41:10

       Yeah. You, you got rid of-

   20. PAPeter Attia41:11

       You got rid of 80%. Yeah

   21. RGRobert Gatenby41:12

       ... Right. Right. Now dump pesticide on them again, and now, you know, maybe one ... So that population that's, that's, that's, that 20% now has a whole field that's open to it. Um, it has no competitors, um, so it can rapidly expand. Um, and it's taking its genome with it, and so it's, uh, uh, you know, the, the ... Its offspring will also be somewhat heterogeneous, but they will definitely be shifted more toward the, um, the resistant one. So you now, you, you dump your, your massive amounts of pesticide, and maybe you get 5% of them that die, and maybe you get 20% of them that, you know, eventually die, but 80% of them don't, and, and you just keep doing. So f- year one or w- you know, season one, um, looks good, and, and again, the [chuckles] intuitively, you know, like a really good idea. But the long-term effect is that now you've got pests that you can't control anymore. You're, you're, you, you have a pesticide that doesn't work. Um, and so in, in the longer term, what you've done is you've created a species you can no longer control. Um, now you have to find a new pesticide, and, um, you know, there's always some cross-resistance. A-and, and in any large biological population, there's sufficient heterogeneity that it's most likely that you're gonna have resistance. So if it worked, and, and, and part of this is say, well, yeah, okay, the ... but how do you know that, uh, there's resistance? And, and it's simple If it worked, there wasn't resistance. But you know from, from experience, you know, from, from that, and over and over and over again, what, what you found was that you use this large, you know, dose pesticides, you can, you can get a short-term gain, but in the long term it doesn't work. Um, so believe y- you know, your, your eyes. And so it, it... And so this actually, uh, you know, again, ecologists that we sh- uh, [laughs] you know, were, were way ahead of us here. Uh, they said, "Well, okay, that doesn't... This, this has gotta... There's gotta be something different to this." And so, uh, in the Nixon administrations, this is a long time ago, same time that they started the war on cancer, um, the, this, this, the, the using large doses of pesticide was essentially, um, uh, n- not allowed. And they started to do this thing they called integrated pest management. And the idea with this is that w- you, you, you recognize that you can't eradicate the pest, that, that, that there's simply no, um, just historically, there's nothing that's ever done that before, so let's assume that's not gonna happen this time. Let's give enough pesticide that we're gonna knock th- this population low enough that, that, that they're not gonna do very much crop damage, uh, but don't do more than that. And, and, um, there's a number of ways you can do that. So for example, um, they would take a field and they would, they would put pesticide on three quarters of the field and leave one quarter alone. These, you know, you would knock this population down, but you would not... You... To this last quarter of the field, you're applying no selection for resistance. And so these guys would then, um, move out to the rest of the field and, you know, you would eventually get to this low population, uh, but you're not selecting for resistance. Um, there, there's a, there's a, a- another bit of this, and that is that the resistance costs something. Um, you know, to be able to deal with a toxic, uh, uh, pesticide or toxic drug, you know, you have to have the molecular machinery necessary to deal with it. You have to be able to repair your me- your, your, your DNA if it's, if it's damaged. You have to be able to pump it out, which is what, what a lot of them do. I mean, there's a number of different mechanisms. But all those mechanisms have a cost. It doesn't necessarily have to be a big cost, but, uh, but, but... And, and in the cost-benefit ratio, w- when you've got a lot of this drug around, those guys are clearly the, you know, the, the benefit greatly outweighs the cost. But when there's no drug present, the, the, then the cost does not, uh, it, it, it does not outweigh the be- I'm sorry, the benefit does not outweigh the cost. And so now the guys that are not resistant don't have to carry that machinery around with them, are m- more fit. And so there's this then subtle competition that goes on. So you, you'll be selecting for resistance in, let's say, the three quarters of the field, but when the o- when the ones that are sensitive move into that area, they have a benefit, uh, they have the benefit of not having this, uh, pesticide being applied to them anymore. There's no selection for resistance, and their fitness advantage will, will be such that the, that when the, uh, when, when the pest population comes back to something close to what it was at the beginning, it's as sensitive as it was in the be- in the beginning. And so this actually then-

   22. PAPeter Attia46:23

       Will it eventually get better? I mean, is, is there a, is there a scenario here under which, if I'm understanding you correctly-

   23. RGRobert Gatenby46:28

       Yeah

   24. PAPeter Attia46:28

       ... the moths that will, um, be able to best resist the pesticide, they, that comes at a cost. And the cost is-

   25. RGRobert Gatenby46:38

       Mm-hmm

   26. PAPeter Attia46:38

       ... molecular machinery-

   27. RGRobert Gatenby46:40

       Yeah

   28. PAPeter Attia46:40

       ... that is only there to allow them to survive the toxicity of the pesticide-

   29. RGRobert Gatenby46:47

       Yeah

   30. PAPeter Attia46:47

       ... but not reproduce better or acquire food better. So the, the more quickly you can get non-pesticide resistant moths back into their ecosystem, who presumably, in the absence of pesticide, now have a fitness advantage over them because they don't have the extra baggage they don't need in a non-pesticide world, they'll actually out-compete them. So is there a scenario where in year one, 20% of the moths are resistant to the pesticide, but if you manage it correctly, in year five, that number is 10% because they have actually been out-competed by the other moths?

6. 47:27 – 55:25

   Bob’s pilot clinical trial: the advantages of adaptive therapy compared to standard prostate cancer treatment

   1. RGRobert Gatenby47:28

      Yeah. So where were you 20 years ago? Uh, because, um, when I, I... Only recently has this, has, has your scenario come up. And, um, uh, I, and I guess we're getting a little ahead of ourselves, but, but we, we've done a study now with, with, in men with prostate cancer where we've used a drug. A- and what we did was that this, we, we gave the drug until the tumor responded to 50% of its pre-treatment value, pulled it away, let the, let the tumor come back up. But again, similar to this, to what we talked about, the, the, um, there's no pesticide being applied, there's no drug being applied, there's no res- there's no, um, there's no sen- there's no selection for resistance. And so the sensitive guys are supposed to come back up, uh, and there is... And, and so grow at the expense of the resistance.

   2. PAPeter Attia48:18

      Yep.

   3. RGRobert Gatenby48:18

      Now, for a very long time, our models said that what would happen is that every time the sensitive population came down, the resistant population would go up a little bit, and when the sensitive population started going, we took the drug away, let the sensitive population grow, the, the resistant population would plateau. And what we then assumed is that at each cycle, you would, you would have this plateau. So stepwise, it would just keep going up, and at some point you would lose control inevitably. A- and all of our models said that if we did this Somewhere between 2 and 20 cycles, the treatment would fail.

   4. PAPeter Attia49:01

      Wow, that's, that's a, that's a huge variance though, 2 to 20 cycles. That could be the difference between a few months and a few years. Why such a, why such a difference?

   5. RGRobert Gatenby49:09

      Well, we, we didn't know the... At, at the time, we, we, we didn't know th- what the fraction of resistant population was at the, at the beginning. So that, that was probably the biggest thing. So if it's 1%, it's-

   6. PAPeter Attia49:22

      Yeah

   7. RGRobert Gatenby49:22

      ... you know, that takes longer than if it's, if it's, uh, let's say, 20 or 30%. Uh, um, a- and there are some other things like the, the, uh, we didn't, we weren't really entirely sure what the proliferation rate was, and a- again, I mean, things like birth and death. We didn't [chuckles] we just estimated those. Um, [clears throat] but so we, we've done... So we did this, um, trial on this, so just a, a r- um, a pilot trial to see if this worked. And, and so what we did was w- we then, so we gave this kind of intermittent therapy, a- and we compared it to patients that just got the standard maximum tolerated dose until progression. The, the difference between the groups was 16 months, so it was y- y- the median time progression for standard of care was 14 months, which is pretty much what's, what's, uh, in the literature. For the r- for the, the, um, adaptive therapy group, it was 30 months, um, which was, which was great. Uh, but then we said, "But o- of the 20, 4 patients are now out five years, and they're still cycling." That's not what we predicted.

   8. PAPeter Attia50:30

      And, and this is, this is patients with metastatic prostate cancer?

   9. RGRobert Gatenby50:33

      That's, that's correct. Um, so what the models said, and this is, this is now gets, this gets very nerdy, but, but the pr- perhaps the most important thing that came out of this trial was the number seven because the ratio of the fitness, uh, measure for the sensitive cells was sevenfold that of the resistant cells, and we had estimated it at two or three, so it's a big difference. And, and the reason that that-

   10. PAPeter Attia51:01

       And it's a big difference in favor of the healthy cell.

   11. RGRobert Gatenby51:04

       Exactly. And so what we see then is that when the sensitive cells, s- y- you have sensitive cells that go down, resistant cells go up, sensitive cells go up, we expected them to plateau.

   12. PAPeter Attia51:16

       But in fact, they're going down.

   13. RGRobert Gatenby51:17

       What... Seven, they go down.

   14. PAPeter Attia51:18

       Yep.

   15. RGRobert Gatenby51:19

       And what we found was that if you, in fact, had three cycles where you, you hit that sweet spot exactly, the, the resistant cells progressively went toward extinction.

   16. PAPeter Attia51:32

       So three successive cycles is a critical enough mass that you can drive that resistant cell to a, to a, presumably to a place where... And by the way, is it limited by substrate? Is that the most important factor that is creating the fitness differential?

   17. RGRobert Gatenby51:47

       Yes, we think. Now, it's, it's, it's gonna be they're competing for space and substrate. Um, and of course, in in- the tumor environment is, um, one in which usually the substrate delivery is very poor because the, the o- you know, the blood flow isn't very good. So substrate is probably the most limiting factor, but again, we don't know this. I mean, this is, again, one of those things that I wish we knew more about because we're, in, in some ways we're just working in the dark. Uh, but what's happened is, uh, that what we... And so when we go, went w- back and looked at these, these four patients that, that's, that, you know, have just, uh, have gone far beyond anything that you would expect, uh, for this treatment, I mean, uh, it's just, there's... very rare that someone would go five years, um, on this treatment using standard of care. Uh, what we found was that each of them had these three sequences-

   18. PAPeter Attia52:40

       Hmm

   19. RGRobert Gatenby52:40

       ... cycles where we th- where, where the model predicted that they drove the, the, the resistant population to extinction or, or something very close to extinction.

   20. PAPeter Attia52:49

       And none of the others had the three cycles?

   21. RGRobert Gatenby52:52

       No. None of... And, and, and that was the key thing that we learned from this, and which is one of the great advantages of having the math models because you can self-critique. Now, now you don't just take the, the results of the cohort and say, "Well, this is nice. We, we did 16 months better." We can also look at what we did and say, "What did we do right, and what did we do wrong?" And what the model said was that we had built into the, into the protocol some components that, that r- that as a result we did not hit those, those three consecutive cycles perfectly. Um, and, and we t- and universally, we overtreated. Um, if we had cut back on therapy-

   22. PAPeter Attia53:33

       Hmm

   23. RGRobert Gatenby53:33

       ... we would have done still better, uh, and the models predicted that every patient f- in both cohorts in this study could have had, we, we, we could have gained control of the tumor indefinitely.

   24. PAPeter Attia53:46

       What were the two... What was the other cohort?

   25. RGRobert Gatenby53:49

       The other cohort received standard of care, whi- which is maximum, uh-

   26. PAPeter Attia53:53

       Oh, oh, oh

   27. RGRobert Gatenby53:53

       ... the drug maximum

   28. PAPeter Attia53:53

       But this was, but this was not randomized.

   29. RGRobert Gatenby53:55

       Hmm.

   30. PAPeter Attia53:55

       Those were-
7. 55:25 – 1:03:29

   New avenues of cancer therapy: utilizing drug-sensitive cancer cells to control drug-resistant cancer cells

   1. PAPeter Attia55:25

      cells. Yeah.

   2. RGRobert Gatenby55:25

      To eradicate the cr- Now, I, you know, never thought about that. But this is now opening up whole new avenues of, uh, of, of therapy, at least theoretically. I mean, at least potentially. Because there's a lot of cases where, um, you, you know, the initial therapy for, for cancers gets great results. I mean, you know, they talk about remis- tumors going into remission. A- and of course, what happens is the tumor eventually comes back. Um, what we know then is, is that the s- the resistant cells are there, but they're there in a very small number. And you can then estimate that they must be way, way, way less fit than the sensitive cells in the absence of treatment. And that... So that fitness difference is, it must be very large. And so, um, using a number like seven as the ratio is not unreasonable. In fact, it's, it's highly likely. And so now we've got this situation where maybe we can, um, start to think about using these very effective th- therapies. So what, right now what we do is we, we give the therapy, you know, tumor kind of disappears, can't see it, and what do we do? Well, we keep giving the same therapy. We give it until progression. Well, b- as we're doing that, you know, we've knocked the tumor to the ground, but we just keep giving it the same treatment. And of course, what we're d- it's resisting

   3. PAPeter Attia56:52

      So we're just, we're closing the gap. We're re- we're reducing the fitness ratio from seven, six, five, four, three, two, one, and it'll flip on you.

   4. RGRobert Gatenby57:00

      Yeah, so now suddenly we've got, all we've got is resistant cells.

   5. PAPeter Attia57:03

      Yeah.

   6. RGRobert Gatenby57:04

      I can keep treating that all I want. That's not gonna work. Uh, but these are highly vulnerable to additional perturbations. So the, the thing is, instead of just giving this treatment, you know, putting the, the, the g- g- you know, getting the, um, ca- cancer populations to something that's very, very small, a- and then to just keep treating them, at that point, hit them again. Do the, do something different. Um, apply additional perturbations. Um, one of my colleagues likes to say this is... We, we, we're like, we're like boxing here. You know, you knock your opponent down, and what do you, you go to your, you go to your corner. And, you know, the referee counts, and when the, when the opponent's back up, then you start again. And, you know, this is, it's not a boxing match. It's a knife fight. You know, we, this is to the death. And, and that means that when you knock your opponent down, you don't stand back and wait. You go attack. And, and I think that we've... That's an approach, and we've called that an extinction approach, that we think is something that has not been, uh, explored yet. But it's interesting that if you look at Anthropocene extinctions, if you look at how our species has killed off other species, uh, this is the way it happens. There's usually a, an initial perturbation. But then after that, when you get a small population, you get a sequence of smaller perturbations that drive it to extinction. It's a two-step kind of process. What's interesting is that you cause extinction through a sequence of perturbations, none of which by itself could cause extinction. In cancer, we're always looking for the magic bullet, the one that will eradicate the cancer and not, and, and not the normal cells. And for de- for a century, we, we've been looking for magic bullets, but maybe all we need is a series of pretty good bullets. Um, and, and so that's a different sort of thinking process. But it, but it is hard to, to, to, to sell that, um, especially to a, a medical community in which new drug development is, is what's most incentivized. Um, so using the same drug, um... So the, the, in the, in the case of our, of our protocol, it's, it's using a drug called abiraterone, which is, which is off patent. Nobody's making any money on this, you know? So, um, it's not, there's no pharma, there's no pharma company that's gonna s- support, you know, the, the clinical trials. There's, it's really, it's kind of an orphan drug, so there's no, uh, there's, there's no natural supporter for this. And the same is true with a lot of these other things that we're really just talking about using drugs that already exist, about using them better. You know, again, there's just not a, a, there's not kind of a natural, um, support for it within the, you know, medical community.

   7. PAPeter Attia59:53

      I want to detour for a second, Bob, and talk about, um, how this logic fits into a, an area that frankly I've never considered until now. I've just taken it for granted, which is the use of antibiotics in bacteria. So standard thinking is you have a bacterial infection, you give the antibiotic, and, you know, there's some magic number, which is you're gonna give it for X number of days. It's a 10-day course. Now, three days into that 10-day course, the patient is defervesced, they feel completely better, the k- the tissue culture is negative, but we continue to give the antibiotic for seven more days because our fear is, or what we were told was, if you don't-

   8. RGRobert Gatenby1:00:36

      Yeah

   9. PAPeter Attia1:00:36

      ... you will generate resistance. But based on what you're telling me now, that might not be true. In fact, it might be that giving that seven additional days of antibiotic might be exactly the thing that is leading to resistance. Is that, am I misunderstanding?

   10. RGRobert Gatenby1:00:52

       Yes, I, uh, I think that's certainly true. I mean, I don't work with, um, infections, and there are, but there are, um, people that are, are looking at this exact issue. Um, how do we Uh, how do you prevent, uh, the development of resistance of bacteria? A- and worldwide, it's a big problem with malaria and tuberculosis and, and things like that. And so the World Health Organization actively uses evolution-based mathematical models, um, to plan how they, they deliver, uh, treatment. And a lot of it is, as, as I understand it, again, this isn't my area, is that they are trying to kind of, uh, do this kind of adaptive approach where you, like just keep the resistant population low. Um, the, the... Now, there are some exceptions where, where, uh, I, I... My understanding is some people have advocated regional attempts to eradicate a, uh, a population. So, so, and, and again, a little bit like the Anthropocene extinctions.

   11. PAPeter Attia1:01:56

       So Bob, is one difference, I guess as n- the more I think about this, between antibiotics and bacteria versus chemotherapy and cancer, technically a person can live with a billion cancer cells in their body and not... I mean, you could live with billions of cancer cells in your body and be totally-

   12. RGRobert Gatenby1:02:13

       Absolutely

   13. PAPeter Attia1:02:13

       ... fine. Is that true with, you know, bacteria? Is that true? Could you have a billion MRSA floating around your bloodstream and still be fine, or do we need complete extinction there in a way that we don't with cancer?

   14. RGRobert Gatenby1:02:27

       I, you know, I don't know. Uh, uh, we'll have to, we have to get a, uh, someone that's expert in this. Um, I, I think that the, the one thing to remember is that by the time you have a cancer, it's defeated your immune system, uh, whereas the bacteria often, uh, you know, are still very different-

   15. PAPeter Attia1:02:45

       Mm

   16. RGRobert Gatenby1:02:45

       ... from our normal cells.

   17. PAPeter Attia1:02:47

       Yeah

   18. RGRobert Gatenby1:02:47

       ... and therefore, uh, I think more targetable by the immune system. I think there's probably a slightly different dynamic in that, that, that may change things, but, but I, I would defer to the, uh, to the people that are, that are doing this. I, I, I could give you some names o- of, of people that are, um, interested in this topic. Um-

   19. PAPeter Attia1:03:06

       Well, and, and I'm glad to hear that people are studying this because-

   20. RGRobert Gatenby1:03:09

       Yes

   21. PAPeter Attia1:03:09

       ... antibiotic-resistant bacteria are a huge problem in the hospital, right? And we've heard it-

   22. RGRobert Gatenby1:03:14

       Yes

   23. PAPeter Attia1:03:14

       ... you know, again, we've heard about these superbugs. Um-

   24. RGRobert Gatenby1:03:17

       Mm

   25. PAPeter Attia1:03:17

       ... and you can't help but wonder based on what you're saying if a big part of the problem was we're creating them by over-treating in situations when we don't need to, uh, you know-

   26. RGRobert Gatenby1:03:26

       Sure

   27. PAPeter Attia1:03:26

       ... using, using a drug for a lot longer than,

8. 1:03:29 – 1:14:30

   The vulnerability of small populations of cancer cells and the problem with a “single strike” treatment approach

   1. PAPeter Attia1:03:29

      than we need to. Um, let's give people a sense of some numbers, 'cause I, you know, I remember when I was in medical school, I spent, uh, a few months at the NIH and the NCI, and I, I, I got all these amazing assignments to do, and what my favorite assignment to do as the medical student was to look up all of the literature on cancer growth rates. Um, and so, and they gave me this assignment because of my background in math, and so it was sort of like I could go digging in all the literature on, you know, every, you know, starting with the most trivial sort of logistic models to the, you know, Gompertz model and all of these other models. But one of the things that really is interesting is just how many cancer cells you need to actually even be detected, right? It's about a billion cells in a centimeter cubed, so you-

   2. RGRobert Gatenby1:04:20

      That's, uh, usually the number that's used, yeah.

   3. PAPeter Attia1:04:22

      Yeah, you couldn't even... There's no clinical, outside of what we now have as liquid biopsies, there's no clinical way to even detect cancer shy of about a billion cells. Um, and this speaks to the non-linearity, right? To go from a million to a billion versus a billion to a trillion. Like, these are-

   4. RGRobert Gatenby1:04:42

      Sure

   5. PAPeter Attia1:04:42

      ... uh, it's hard for people to wrap their head around what's involved in those things.

   6. RGRobert Gatenby1:04:45

      Yeah.

   7. PAPeter Attia1:04:45

      And, and both from a growth perspective, 'cause that's not linear, and a size perspective, because you're dealing with something that's growing with a cube power, not a square power.

   8. RGRobert Gatenby1:04:56

      Yeah.

   9. PAPeter Attia1:04:56

      Um, where do you see this being an issue? Because the numbers are so enormous, right? And this gets to your question of if we talked about the example I used earlier of there being, like, a million moths, well, the heterogeneity there is already significant. But once you're talking about tens of billions of cells, by definition, the heterogeneity is probably even more significant, correct?

   10. RGRobert Gatenby1:05:28

       Absolutely. I ca- I, a- and, and it's really important. I think there's two factors to think about. One is the, is stochasticity. If you have a small population, uh, small changes in birth and death rates, uh, can be quite significant. Um, you know, s- uh, small populations can go extinct, um, based on very small changes. Um, uh, the other thing is what's called the Allee effect, and that is that in a classic, uh, evolutionary model, as a population grows, the fitness should be decreasing because you're getting toward the, the carrying capacity of the environment. Uh, but Allee and others have found that it increases as y- And the reason is that there's an advantage in groups. Um, and, uh, i- in, in herds, for example, I mean, you, you can... The obvious advantage-

   11. PAPeter Attia1:06:19

       Yeah

   12. RGRobert Gatenby1:06:19

       ... is that they can gather themselves to, uh, to defeat, uh, predators. Uh, but they can also, there's, there's sort of leadership issues and, uh, and, and, and other things. In tumors, um, there, there's, there's a couple of things. One is they have to make blood vessels, and that means that there's small groups of them have to get together and make the angiogenic factors that they then send to the, uh, to the blood vessels to, to bring a blood vessel in. It's probably not a single cell that can do that. It has to be a loosely organized system. Uh, um, the development of extracellular matrix. The, you know, the tumors, it's, it's just not tumor cells. They make a uh, uh, collagen and other things that, that go in the, between the cells that provide a kind of a structure for them to, to live on, um, they have to make that, uh, and that it can't just be anything. They, they probably act together for that, and then they also probably act together to defeat the immune system. Um, they, they can secrete things, um, and, and they, they can... And, and so there's a number of things that, that they can act together on so that the, you know, tumor cells i- i- ... small populations may not grow as fast as, uh, large populations, and they may be more vulnerable to treatment. They may not be as able to deal with immunotherapy or targeted therapy or, or even chemotherapy, um, because they don't have the capacity to act together. Um, so those two things are, I think, important factors in understanding treatment, and this is a little bit why, um, you know, I was talking about when, you know, there are therapies now that can take large cancers and, and drive them down so that they become not detectable by CT scans, which means that their population has to be very small. Um, those guys are now vulnerable to dynamics related to stochasticity and allee effects that the larger populations are not necessarily, um, uh, you know, a- a- applicable, uh, are not necessarily, um, responsive to. And if you... And, and one of the things that's very interesting, if you take something like neoadjuvant therapy where you, where you take a big, uh, breast cancer, for example. You, you, you make it small and then take it out. What you find is that the tumor isn't a ball that just shrinks. So you don't... You gotta start with a big ball, you get a smaller ball. In fact, it fragments, and so what you get are little islands of tumor cells surrounded by, uh, fibrosis or necrosis or something like that. So these guys are islands. You know, this, these are highly vulnerable. Um, and so I think that, that this is when, uh, we, you know, we should crank it up and kill it. Uh, I, I think that the, this, I think tumors are vulnerable at this point, but I think that the way we've done things, which is this dogma, uh, in oncology, you know, continuous maximum tolerated dose until progression. And as you just said, you can't see it, the... I- if, if you're waiting for a progression, you, you won't see that until you have billions of cells. I mean, it has to be big enough that you can image or feel, and that's at least a CC of tumor, and it's probably two or three CCs. Um, by that time now, if you, when you change therapy, you're, you're, you're dealing with a [laughs] really big population, whereas you could have, uh, been dealing with a small fraction of it, you know, a few months earlier when you couldn't see it. Now, the oncologists always get, "Well, I, I have to be able to see something to be able to understand whether it's effective or not, you know, that my therapy's effective." Yeah, and, and that's... I, you know, I get that, but, but you're not be- gonna be able to do that in this setting. Um, what's interesting is that the pediatric oncologists learned this a long time ago. This is how they cure leukemia. Um, they give an, a- an induction therapy, and then they immediately change to a different therapy. So what they learned was that e- even after induction therapy when there was no apparent tumor in the bone marrow or in the blood, that if you didn't do anything, the kids would all relapse. And so, um, they hit it immediately with another d- with another group of drugs and then another group of drugs. They, they... And so this is, you know, first strike, second strike kind of approaches. Um, but they're not... They can't measure [laughs] their outcome. They can only measure their outcome in the long term by saying, "Well, we've cured this kid."

   13. PAPeter Attia1:10:42

       Right. They can't say which drug was more effective in that cocktail.

   14. RGRobert Gatenby1:10:46

       Right. And it... You'll probably never know. In, in, in, uh, i- there's this, there's this thing called the extinction vortex that they talk about in, in, in, uh, extinctions, where when the, when you've got a small population, there's a s- there's typically a sequence of perturbations. A- and, and, and they af- they, they, um, they, they tend to be self-synergizing. In other words, they, the further down the population you push, uh, the more sensitive it is to stochastic and, and, um, allee effects. And so now you, you can never really tease apart those dynamics. It just, it, it just all goes into extinction eventually. Um, and, and the goal then is not to try to really put these things together in a, in a really additive way except to say that all these guys together, um, will, will tend to push this to, you know, this, this population to extinction. Again, it's a different strategy, uh, than, you know, we, we... It's... And it's a little less, um, precise [laughs] than I guess, you know, we would like. But, but that, that is, you know, the nature, I think, of the, of the extinction process as we've learned it. I mean, we... It's interesting because whenever you say extinction, everybody thinks about the dinosaurs. Um, and, and I would argue even that some of our therapy, uh, is, is that, that kind of single event, single cause, you know, extinction, um, application of massive evolutionary force, uh, to, to the species, and you wipe it out. And of course, the problem is you also wipe out most of the land animals on Earth, so it's, it's indiscriminate. Whereas, uh, what we've learned from Anthropocene extinctions, from our own species eradicating other species, you know, as unfortunate as, as that is, we've been able to study those in detail and have learned that, in fact, most extinctions are multi-cause, multi-event, not, not, it's not the dinosaurs. They are the exception, not the rule. And so when we wanna think about an Anthropocene extinction of cancer cells, which is, which is arguably what therapy is, that we would probably, we should probably be m- thinking more about these multi-cause, you know, approaches rather than trying to find a magic bullet that Um, can, can, could, could cure the cancer by itself because you always have these side effects, um, and it, it's, it's so far we've not found a, a magic bullet.

   15. PAPeter Attia1:13:12

       Well, and to your point, it's, uh, the bigger issue with the dinosaur analogy is not even so much that it's the exception and not the rule, it's the collateral damage. When, when it, when it, when there's a single strike success-

   16. RGRobert Gatenby1:13:27

       Yeah

   17. PAPeter Attia1:13:27

       ... the collateral damage, you know, changes the planet. Um, if what killed the dinosaurs when it killed them came on our planet today, it would probably kill a lot of other things as well. Um-

   18. RGRobert Gatenby1:13:39

       Absolutely.

   19. PAPeter Attia1:13:41

       Let me ask you a question about-

   20. RGRobert Gatenby1:13:42

       Let me just-

   21. PAPeter Attia1:13:42

       Oh, go ahead.

   22. RGRobert Gatenby1:13:43

       No, I was just saying that sometime I, when I ta- tell people that, you know, I said that, you know, a tumor might ha- uh, a hundred grams of tumor, which is a, which is still a pretty-

   23. PAPeter Attia1:13:52

       Yeah, still pretty small

   24. RGRobert Gatenby1:13:53

       ... small tumor, is gonna have 100 billion cells, let's say, which is far more than the human population on Earth. You know, think about could you do one thing, could you apply one event that would kill all the people on earth and no- nothing else, you know? And, and, um, I, I think it would be... I mean, it's pro- probably something could be done, but I, I, I think that'd be very difficult and, and, and it's a kind of a gruesome analogy, but at least it, it kind of makes the point that it's, it's, it's... The idea of a magic bullet, I think is, um, m- may not be... It, it may not be an achievable result.

9. 1:14:30 – 1:25:56

   Using a sequence of therapies to make cancer cells more susceptible to targeted treatment

   1. PAPeter Attia1:14:30

      What role does time play in the sequencing of this? So let's go back to the example of pediatric oncology, where, um, you could sequence... You know, you go induction therapy, and then you go with a series of therapies to follow.

   2. RGRobert Gatenby1:14:43

      Yeah.

   3. PAPeter Attia1:14:43

      So single shots, right? So one, two, three, four, five, six-

   4. RGRobert Gatenby1:14:47

      Yeah, yeah

   5. PAPeter Attia1:14:48

      ... versus all six at once. Let's put aside the toxicity for a moment-

   6. RGRobert Gatenby1:14:52

      Yeah

   7. PAPeter Attia1:14:52

      ... because a big reason you wouldn't do that is the toxicity to the child, and a lot of these, you know, you have synergistic side effects that are intolerable. But just thinking about this from a theoretical standpoint, um, would there be an advantage or disadvantage to one of those approaches?

   8. RGRobert Gatenby1:15:08

      Yeah, so I think that, I mean, it would certainly be reasonable to say, well, if we've, if, if we've got these three different therapies, why don't we put them together and give them all at once? And, and oncologists have been doing this for a long time, and the results have been pretty much, uh, uniform in that what we find is that they do better than one... You know, is the, the, the results are, they, they... The tumor is controlled for a longer period of time, but the result is still that they die of the disease. The, the, the tumor comes back, and they die now. And, but, and you can add more, you know, four or five drugs, and what tends to happen is that you get this diminishing return so that you just start getting more toxicity-

   9. PAPeter Attia1:15:50

      Mm-hmm

   10. RGRobert Gatenby1:15:50

       ... and no real increased benefit. The, the, so one of the things to think about is suppose you have two drugs and you're applying it to a 10 billion population, you know, so what is the probability that, that there are gonna be cells present that are resistant to both?

   11. PAPeter Attia1:16:08

       Still high. Yeah.

   12. RGRobert Gatenby1:16:09

       You, you have a big denominator, you know.

   13. PAPeter Attia1:16:11

       Yeah.

   14. RGRobert Gatenby1:16:11

       So but now let's say you, you, you have a million. So let's say you, you have one drug, you get it, you, you know, you really do a great job. You, you're down to a million cells, or let's say 10 million cells. Now you add the second drug, and so now it's, what's, what is the probability that within this 10 million, uh, that you, you, you will have some resistance? Knock it down again, give a third drug. Now, what's the probability, let's say, of 100,000 cells? You, you, you see what I mean? So the, the model-

   15. PAPeter Attia1:16:40

       But is that, is that predicated on delivery? Because you would argue that if those are independent events, it shouldn't matter if they're done in sequence or all at once, right? What is it about sequencing those that would create a treatment advantage?

   16. RGRobert Gatenby1:16:54

       There, there's two things. One is you get, as you get smaller, the, there's gonna be, you're both killing the tumor cells that are sensitive, but remember that, that the ones that are resistant are also have to deploy mechanisms of resistance.

   17. PAPeter Attia1:17:11

       Ah, bingo. We're right back to that discussion. And, and I guess to your point, they're gonna be more fragmented and therefore have less of the group network effect.

   18. RGRobert Gatenby1:17:20

       Right.

   19. PAPeter Attia1:17:20

       Yep.

   20. RGRobert Gatenby1:17:21

       And, and so now, you know, again, s- when you've got a small population, subtle changes in birth and death rates will be sufficient-

   21. PAPeter Attia1:17:29

       Yeah

   22. RGRobert Gatenby1:17:29

       ... to drive it to extinction.

   23. PAPeter Attia1:17:30

       That makes sense.

   24. RGRobert Gatenby1:17:31

       And so even, and, and, and as I talk to people about potentially designing this, even though there may be resistance, um, the, the, that you can still use the resistance to your, to your, uh, your benefit. And some people have talked about then adding things like, uh, uh, environmental changes. So let's take an angi- anti-angiogenic so that you're now you're delivering less blood, and you're creating a more difficult substrate and environment. Um, and some people have, you, you know, there's, there's people that have used, uh, antacids, people have used, you know, a number of different, uh, th... You know, these are more, these aren't typically, you know, common medical practice, but, but what individuals are doing based on their own exploration through Google and other, other websites is that, and they use various metabolic, um, things, and I, I think there, you know, is potentially advantage to that, a- again, in combination with this in a way that, that makes sense.

   25. PAPeter Attia1:18:30

       So, so far, most of what we've been speaking about is really more or less one class of drug with a slightly different take on another one, right? We've been talking about chemotherapy. Um, these are chemicals that are aimed at disproportionately killing cells that in theory are dividing, right? So let's go back to what you said earlier. The, the thing we learned in medical school that was incorrect was cancer cells divide more quickly than regular cells. Uh, those of us that pay attention today know that that's not actually true at all. The fundamental difference between a cancer cell and a non-cancer cell is the response to cell cycle signaling. It's that a normal cell It doesn't divide slower, it just when it's told to stop dividing, it stops dividing. The cancer cell doesn't. When it's told to stop dividing-

   26. RGRobert Gatenby1:19:17

       Yes

   27. PAPeter Attia1:19:17

       ... it says, "Piss off, I'm gonna keep dividing."

   28. RGRobert Gatenby1:19:19

       Yeah. That's a very good point. I mean, that, that really is. And, uh, e- evolutionarily what this, what this is, is that it has a self-defined fitness function. Its proliferation is dependent on its own properties, uh, as they interact with the environment, not on instructions from the tissue. Normal tissue cannot evolve because its birth and death is dependent on tissue controls. And so you're dealing with-

   29. PAPeter Attia1:19:44

       That's right. So knowing that, chemotherapy, which is the earliest form in the, uh, of, of drug in the modern arsenal against cancer, says, how can we kill a cell that is not responding to cell cycle signaling? And the, the first shot across the bow is, well, let's just kill anything that's dividing, because we know that normal cells are less likely to be dividing and cancer cells are more likely to be dividing, so let's target different cycles of the DNA proliferation phase. And that's why, of course, most people who are getting chemotherapy have side effects to the normal tissues that relate to that. So the mucosal ulcers, the hair loss, the, you know, skin damage, nail thinning, all of that stuff is because those are tissues, even though they're normal, that are dividing more rapidly and they're being, you know, smacked as part of the collateral damage. You mentioned another class of drugs, uh, courtesy of, you know, someone named Judah Folkman, who was really one of the first people to point out this idea that you've raised, which is, you know, cancer cells have another challenge that they face, which is they have to get the blood vessels to bring in the substrate, the glucose, um, that they need to replicate, make energy, and make building blocks to make more cells. And what if we target those things, these vascular endothelial growth factors? And those drugs haven't turned out to be very successful, by the way. So they're billion-dollar blockbuster drugs, you know, Avastin probably the first, if I recall. And they've extended median survival like a few months here and there, but they really haven't been blockbuster drugs. We haven't talked about immunotherapy, right? So we haven't talked about the, you know, Keytrudas of the world, how they fit into that. Um, but it seems to me... And, and then there's others of course, right? We, we can talk about, you know, the, the few cancers where a single gene mutation exists and you can target it with like a Gleevec or something like that. But it, it seems that you could use selective chemotherapies and target on top of that anti-VEGF, and the real question then becomes timing, right? How do you cycle those on and off to always be maximizing the gap in fitness? So how do you maximize that fitness ratio? By the way, did your model predict that there's something specific about the number seven? Because your, if I recall, you said your model thought you would end up between two and three. You actually ended up at seven. In retrospect, does the model now tell you seven is the tipping point?

   30. RGRobert Gatenby1:22:30

       It's somewhere around there. We've looked at that, at the transition as you go from, you know, w- zero to two to three to seven. It's, it's in that range. Um, I, I don't know exactly where it is, and it pr- it's certainly gonna vary from, uh, from, from, uh, tumor to tumor, but it's in that... It's certainly, I, I would guess at the five-ish range.
10. 1:25:56 – 1:31:25

    How immunotherapy fits into the cancer treatment toolkit

    1. RGRobert Gatenby1:25:56

       just didn't happen, so.

    2. PAPeter Attia1:25:57

       So where do you think immunotherapy fits into the, uh, the, the toolkit here, given that it's, it tends to be more binary than chemotherapy, right? So immunotherapy, y- I'm making this up because it varies by histology, but let, let's just say you take people in the best case scenario, so people that have checkpoint, checkpoint, uh, mutations, right? So someone that has a, a PD-1 mutation.

    3. RGRobert Gatenby1:26:23

       Mm-hmm.

    4. PAPeter Attia1:26:24

       Um, the, the response rate to those people for a, a, an anti-PD-1 drug like Keytruda is very high and very durable, I mean, far more than anything you see with chemotherapy.

    5. RGRobert Gatenby1:26:35

       Absolutely.

    6. PAPeter Attia1:26:36

       Conversely, if they don't have the PD-1 mutation, the, the drug is useless.

    7. RGRobert Gatenby1:26:41

       Mm-hmm.

    8. PAPeter Attia1:26:41

       Um, so what does that tell us about the opportunity to use, um, immune-based therapies? And by the way, we borrow the term adaptive therapy again here, right? So you have-

    9. RGRobert Gatenby1:26:51

       Yeah

    10. PAPeter Attia1:26:51

        ... adaptive therapies within-

    11. RGRobert Gatenby1:26:52

        Yeah

    12. PAPeter Attia1:26:52

        ... immunotherapy, which are not to be confused with-

    13. RGRobert Gatenby1:26:54

        Sure

    14. PAPeter Attia1:26:54

        ... what you're describing as adaptive therapy.

    15. RGRobert Gatenby1:26:56

        Yeah, I think, you know, the, it's, it's gonna be a critical component of all this. And, uh, I, and as you say, sometimes immunotherapy can stand on its own. It's the closest thing to a magic bullet that I, I think we have. Um, I think i- what we tend to, to, to, to view, the, the, the group I work with tends to view immunotherapy, uh, with the exception of those, those unusually responsive tumors, a- as your closer, and this is our baseball analogy, that, um, when you get the population that's small, um, we think that allee effects are particularly important in immune response, in response to the immune system.

    16. PAPeter Attia1:27:37

        Meaning evasion from the immune system.

    17. RGRobert Gatenby1:27:39

        Evasion.

    18. PAPeter Attia1:27:39

        Yeah.

    19. RGRobert Gatenby1:27:39

        Right. And so, uh, bringing the immune system in when you've got the, the tumor on the mat, you know, it's, it's small, fragmented, uh, I think that will be the most effective closer that we have, uh, to, to essentially wipe it out. Um, I could be wrong, but that, in theory, uh, that's, that looks like a, a good, um, you know, you, you, this is the one you bring in to win the game.

    20. PAPeter Attia1:28:07

        And by the way, that could be going back to gen one immunotherapy, which is interleukin-2.

    21. RGRobert Gatenby1:28:12

        Mm-hmm. Mm-hmm.

    22. PAPeter Attia1:28:13

        Um, interleukin-2 had about a, maybe a 10 to 20%-

    23. RGRobert Gatenby1:28:17

        Yes

    24. PAPeter Attia1:28:17

        ... response rate in melanoma, a particularly immune sensitive cancer. Um, but, but that was treating patients with full-blown metastatic melanoma.

    25. RGRobert Gatenby1:28:27

        Sure.

    26. PAPeter Attia1:28:27

        Maybe it would look very different in patients who were-

    27. RGRobert Gatenby1:28:30

        Sure

    28. PAPeter Attia1:28:31

        ... NED or who are, you know, visibly without disease.

    29. RGRobert Gatenby1:28:34

        Mm. And, and there are some, I, I, I know that there have been some experiments that have suggested that cells that survive chemotherapy are more vulnerable to, uh, immunotherapy. Um, and ultimately, that would be the game that you'd wanna play here, is that you, what you want to do is apply a therapy and you know that the resistance strategy, uh, might be the following thing, you know, this is how it's going to evolve to become resistant, right? And then attack the Achilles' heel that's, that's, uh, that's exposed by this, uh, immune response. Um, we had a, uh, person here do a, as, this is, this is kind of the reverse of this now. Um, they did a P53 vaccine in, in lung cancer patients that were, had been treated it with multiple different things, and, and it didn't really get a, an effect. I mean, there was minimal, um, efficacy. One patient got a partial response. None of the others did, although they did generate, uh, immune cells to the, to the vaccine. Uh, they then went on and gave them chemotherapy, and the response rate to the chemotherapy was, uh, was 60 to 70%. Astonishing number for patients at that stage in their disease. It, it should've been less than 5%. And the patients that had the best response to the, i- i- the best immune response to the, um, to, to the vaccine were the ones that were most responsive to therapy, suggesting that those that responded, you know, they had, they, they developed adaptive strategies. Um, a- and those adaptive strategies then made them more vulnerable to toxicity. I mean, it, it's appealing to think that maybe they down-regulated P53 so that, you know, they didn't have, they were not expressing the target, and of course, P53 is important in, um, survival mechanisms and that sort of thing. So perhaps, um, that was a mechanism. I'm, I'm just speculating, of course, but that's the kind of thinking that, that I, um, I would, would like to apply here, uh, so that we're not isolating, uh, this, you know, you, you do this therapy, and then you do this therapy, and you do this therapy, all of them in isolation, but, but start to put strategic strings of therapy together where the adaptive strategies that you're, you're gonna select for with one become vulnerable to the, to two and three, and so that you're putting them together in a s- strategic, kind of thoughtful way, rather than just kind of putting them together, um, you know, in a, in a kind of haphazard or, or intuitive way. Um, and again, that's where math models can, I think can be very helpful.

    30. PAPeter Attia1:31:24

        No, that, that, that actually

11. 1:31:25 – 1:42:45

    Insights into why cancer spreads, where it metastasizes, and the source-sync trade off of cancer

    1. PAPeter Attia1:31:25

       makes a, a ton of sense. Um, I wanna talk about another, uh, feature of, of cancer, which is, um, what I call the source-sync trade off Uh, trade-off, right? So, uh, I'm sure you've thought a lot about this. Uh, I, I endlessly thought about this and, and really never came up with a great insight. Um, there are some cancers... So, so let's start from first principles. There aren't that many cancers that can kill you without spreading. Let's list the ones that can. Brain cancer can kill you without spreading, right? So glioblastoma multiforme can kill you, and it doesn't leave the brain. [lip smack] Uh, primary hepatic cancer can kill you without spreading. Hepatocellular carcinoma can kill you. Um, I suppose lung cancer can kill you without spreading, though it's less common. Am I missing an example? Is there some other cancer that can kill you shy of metastasizing?

    2. RGRobert Gatenby1:32:23

       Huh. I think you've, you've... F-for all, f-for all intents and purposes, yes.

    3. PAPeter Attia1:32:28

       Okay.

    4. RGRobert Gatenby1:32:28

       I think you're right.

    5. PAPeter Attia1:32:29

       Okay. So that's principle number one. Then let's go to observation number two, or observation number one, I suppose. There are certain cancers that always, uh, uh, leave, and they're ve- so there are certain cancers that are very deadly that leave tissues that other cancers never come to. So breast cancer, prostate cancer, pancreatic cancer, colon cancer, these are deadly cancers which come from an environment that are not especially hospitable to cancers. Because when a woman gets breast cancer, the first thing that cancer wants to do is get out and kill her by going to her bones, her brain, her lungs, her liver. Pancreatic cancer virtually always wants to go to the liver, and that's where it kills, right? You know, colon cancer wants to go to the lungs, wants to go to the liver, and wants to go to the brain sometimes, and that's where it kills. But rarely does a cancer go to the breast or go to the pancreas or go to the colon or go to the prostate. Prostate virtually always wants to kill you by going to the bones.

    6. RGRobert Gatenby1:33:43

       Mm-hmm.

    7. PAPeter Attia1:33:44

       So, so do you see where I'm going with this? Like you have this... And I could go on for hours with all of my observations, right? Like the brain is another one, right? It's an enormously attractive place for cancers to go to, but a primary cancer from the brain never seems to leave. Um, now, now theoretically, there's an exception to that, I suppose. There are some vascular tumors of the brain that can leave, but they're not really brain parenchymal tumors. Do you have an insight into what explains this? And more importantly, does, does the answer to that question or the, the inference of an answer to that question offer an insight into the environment in which tumors thrive and therefore what we might be able to do about it?

    8. RGRobert Gatenby1:34:27

       Um, the, the short answer is I don't know. [chuckles] Um, the, um, w- let, let me tell you what I, what I- I'm certain of, and that is this is not a planned event. The, it, uh, we tend to give, uh, cancer cells this sort of anthropos, uh, you know, anthropomorphic kind of, you know... They are... First, they go out and prepare a metastatic site, and then they send their cells out to it. That doesn't happen. Um, the, a, a, an evolving population can never adapt to conditions it has not seen before. It, it, it, it, it, you, you, it cannot plan to make metastases. It c- i- and, and it certainly can't plan to feather its nest, you know, in some distant site before sending out its scouts. Um, that's not happening. Um, but we know in nature that, that, uh, we see introductions all the time, and we know from nature that, uh, these intro, species introductions are sometimes, uh, successful and sometimes not, and it has to do with the way their phenotype interacts with the local adaptive landscape and can they adjust or not. And, and we know that sometimes it takes several introductions before one occurs. Sometimes it never happens. Sometimes they can expand and then, and then die out. Um, uh, so I think that those are, uh, th- th- that this is, again, this is, th- they're just basic rules that they have to, um, you know, live by. So for example, uh, the, you can see, uh, uh, species being c- coming out of the, the Amazon. They, they're, they, they get onto y- you know, just the Amazon collects, um, uh, trees and, and things that are floating down. The animals are on it, and so they go out. And then anything that's in front of the Amazon is going to be receiving more of these and, um, so more, are more likely to see a metastatic y- you know, monkey or s- or something like that from the middle of the Amazon. Uh, but a- and so the, the, the pancreas, uh, spills into the portal vein, which then goes into the liver, and so it's delivering a lot of its cells to the liver. So it makes sense then that it tends to metastasize there, if only because it's just sending a lot of cells there. Um, with others, uh, you know, I'm not-

    9. PAPeter Attia1:36:58

       Right. The pancreas makes sense, but how do you, how do we make sense of-

    10. RGRobert Gatenby1:37:01

        The other stuff doesn't.

    11. PAPeter Attia1:37:01

        Yeah. How do we make sense of the breast? How do we make sense of the prostate-

    12. RGRobert Gatenby1:37:04

        Yeah

    13. PAPeter Attia1:37:04

        ... going to the bone disproportionately?

    14. RGRobert Gatenby1:37:07

        Yeah. And so I think that there's, um, I mean, w- there's, y- I, I think we just suggest general principles. That, that there's something about, uh, you know, some of the breast cancer cells seem to be able to set up shop in bones, some of them in the lung and some of... And, and for reasons that are, are, are not yet clear. Um, but y- you mentioned actually something that's, that's, I think important. It's source-sync. Uh, and I think that's a dynamic And that's something that we've been talking about recently, source habitats, sink habitats. The idea that you've got habitats that are, uh, have, have very good blood supply, that they produce a lot of cells, but they ... And then now they're producing too many cells for the spatial environment, and those cells have to go out.

    15. PAPeter Attia1:37:53

        Mm-hmm.

    16. RGRobert Gatenby1:37:53

        And, um, one can think of those within a cell, so that you've got areas with poor blood flow and, uh, areas of good blood flow next to one another, and you can imagine cells migrating between them. Um, and this can set up dynamics that are very interesting. Uh, but you could also think about a, you know, breast cancer cell that's got ... Let's say it's near a blood vessel because ... And as it, as you might expect, it ... So now it's getting big. It, there's too many cells. They crowd into the blood vessels. It sends them out, and so now you've got perhaps sink habitats somewhere else, and there may be some coupling that goes on in ways that, uh, honestly I don't understand. Uh, but, but I think that we can sort of make up rules for that. But, but for sure ... I mean, I think what, what, what we know is that the limiting factor in this is the dynamics at the s- metastatic site, that, that if you inject cancer cells into mice, the, that nearly all of them die at the metastatic sites. Only there's a very small percentage of them that will form even a few cells, and a smaller percentage of those that ultimately form more cells, uh, that form a, a, a population. But I think this is again, is that small population dynamics that we've, we've talked about. There's stochastic effects, allee effects. You know, there's a, there's a lot of, uh, statistical, uh, problems with, with going from a single cell to, uh, to, to a cancer that's, that's sig- significant. We are very lucky for that because we know that human cancers are, are frequently dumping millions of cells into the blood a- and yet metastatic sites, metast- metastases are, are, are relatively rare, um, when you think that. You know, people with early stage lung cancer, you know, you can find cancer cells in their bone marrow, and yet they don't get bone marrow metastasis. Breast cancer's the same kind of thing. You, you, you, um, you could do bone marrow biopsies on women getting mastectomies for apparently localized disease, and maybe 30 to 40% of them will have breast cancer cells in their bone marrow. And yet all of them do not develop, um, you, you know, metastatic disease in the bones, thank, thank goodness because, uh, it seems like, uh, for a variety of reasons-

    17. PAPeter Attia1:40:06

        And, and how much of that do you attribute to the allee effects and the stochastic variability that says, "Look, they're just not gonna be fit enough to take up residence there," um, versus some other inherent principle of like the genetic robustness of the tumor itself? Because a lot of those women may go on to get adjuvant therapy, and then it becomes a question of how successful was the adjuvant therapy?

    18. RGRobert Gatenby1:40:31

        Exactly. Yes. Exactly. And I think that's where, you know, if you look at breast cancer for example, what we know is that adjuvant therapy will reduce the probability of metastatic disease, but not eliminate it. It's, it's at best a, a, a small effect. A- and we need to do better with that. Um, and, and I, I, the, it's, it's, it's a great point because, um, w- well how do we treat, you know, adjuvant ... How do we treat breast cancer with adjuvant therapy? Well, we give them platinum or some, you know, some drug for some period of time, and that's it. Uh, w- well, why don't we give, you know, a sequence of drugs? Why don't we take advantage of ... Because we know for sure we're dealing with small populations, and we know for sure that we can, we can cause them to go extinct at least some of the time. So why don't we optimize how we do this in- in- instead of simply pick up a drug from the shelf and, and, and administer it continuously, you know, for six months? I, that does ... You know, this is w- a, a, you know, another good example of where I think we've, we've, we've not thought through the eco-evolutionary dynamics of what we're trying to treat. It seems to me-

    19. PAPeter Attia1:41:39

        Yeah, it's, it's basically a paint by numbers approach, right?

    20. RGRobert Gatenby1:41:41

        Yeah.

    21. PAPeter Attia1:41:41

        Which is paint by numbers is we're just gonna do it this way and, and-

    22. RGRobert Gatenby1:41:45

        Yeah

    23. PAPeter Attia1:41:45

        ... versus I'm gonna think through this strategically. Um, y- we, we, we, we have a pretty good sense that the more cancer cells a person has in their body, the more mutations they have, right? So the difference between a billion cells, i.e. one cc of cancer, versus a trillion cells, right, which is like an almost fatal load of cancer, is an enormous number of mutations. And therefore it's not only bad from the mass effect, but also from now the fitness of it, right? You have so ... You just have such a genetically, um, a bad genetically diverse population. So you have enormous heterogeneity within the genetic, um, you know, badness for lack of a smarter word. Um-

    24. RGRobert Gatenby1:42:36

        Can I add that you, you also have diversity of their, uh, ecosystem. Uh-

    25. PAPeter Attia1:42:42

        Well, I, I, I wanted to now get into the eco-

    26. RGRobert Gatenby1:42:44

        Okay. All right. Okay, sorry.

    27. PAPeter Attia1:42:44

        Yeah,

12. 1:42:45 – 1:55:24

    Defining Eco- and Evo-indices and how they can be used to make better clinical decisions

    1. PAPeter Attia1:42:45

       yeah, yeah. No, no, no. But, but-

    2. RGRobert Gatenby1:42:46

       Go ahead

    3. PAPeter Attia1:42:46

       ... let, let's, let's do that. Yeah, so let's talk about these two indices of, of eco and evo indices, which you've written about in, in, in a very recent paper. So explain for folks what these mean, 'cause these are, these are ... They're not the easiest concepts to get your head around sometimes.

    4. RGRobert Gatenby1:43:01

       Yeah, so s- so when you talk to a cancer biologist about evolution, they say it's mutation selection. You know, you get a random mutation and that the cancer cells, you know, accumulate these mutations. Occasionally they provide a benefit, and that's what causes the tumor to expand. Uh, the, the, the problem with that approach is that, um, it assumes that the environment is stable. It's, they're all dealing with the same environment. Now, um, the alternative is to say that, a- and I think the more evolutionary appropriate thing to say is that, um, there's tremendous variation in blood flow And, and other factors within the tumor. And, um, as the tumor goes into these areas of, say, low blood flow, the environment is entirely different. And so the en- the environment is applying selection forces that are totally different from, let's say, down the road, where the, it's, it's, you know, the blood vessels are really good. And the edge of the tumor, the- these cells are competing with the normal cells. Internally, they're competing with other tumor cells. So, so again, entirely different environments. And so the, the, the ... a more evolutionary model, in my opinion, is to say that the different environments within the tumor are the ones that give rise to different phenotypes, which in, in turn give rise to different genotypes. So that the, in, in this case, the genes aren't causing the evolution. The genes are the consequences of evolution. Um, one of the, uh, ways to think about this is to, is to think about whether a modern day Darwin sitting on the Beagle, y- you know, in the, in the, in the ship, um, with his microarray machine. He's got all these, these fancy molecular biology equipment, and sailors just brought random samples of finches t- to this modern Darwin. They ground them up, put them through the machine, got, you know, billions and billions and billions of, of data points. Could they have written Origin of the Species from that, from that data? Um, and, and I think the answer is no. And I think that the reason is that what Darwin saw was that the s- the beak of the bird and the seed matched. There's a morphologic, uh, matching that makes common sense. This is not, this isn't magic. It's just that beak's gotta be bigger to p- you know, pick up that seed. A- and-

    5. PAPeter Attia1:45:26

       He paired phenotype to environment.

    6. RGRobert Gatenby1:45:29

       To environment.

    7. PAPeter Attia1:45:29

       Yeah.

    8. RGRobert Gatenby1:45:29

       To environmental selection. Right. That is, that's the logical way that evolution occurs. The, the genes are kind of downstream of that. The, you know, multiple gene ... You know, the beak, uh, you know, could be under the, uh, the control of, you know, a few genes and ... But how would you, how would you distinguish the, these genetic changes, um, and, and say, "Well, there's the beak there, and oh, there must be ... That means there must be a big seed there." And-

    9. PAPeter Attia1:45:57

       Well, isn't it safe to say we might not even know? Like, isn't it safe to say that if you took the two closest finches, right, the, the one that went from the beak like this to the beak like this, and you sequenced them both, you might not be able to extract which genetic differences between those accounted for the beak. In fact, I'd be surprised if you could.

    10. RGRobert Gatenby1:46:18

        Yeah, I agree. I mean, put a, a human in a chimpanzee ... I, I don't, actually, I don't know that, so I, I don't wanna go there. But, um, no, no, I completely agree. And I, I think that when we talk about cancer as a disease of the genes, um, what the, the, it's more complicated than that. And I think that the intense effort, uh, to characterize the genetics of tumors, you know, has had some benefit, but it also has some disadvantages because you lose that morphologic, uh, matching of, of, uh, of, of the, of the environment and, and the, and the morphology of the, of the cell, h- which i- is more common sense and I think in the long term helps us understand it better. I mean, one of the questions one of my colleagues likes to ask is, uh, who's an evolution biologist, you know, "How many niches do you think are present in a cancer, and how many species are present?" Um, and, and, you know, you can ... The answers are all over. You know, it could be ... Some, some people say it ... I mean, certainly not one.

    11. PAPeter Attia1:47:22

        Right.

    12. RGRobert Gatenby1:47:23

        Uh, 'cause we, we, I mean, virtually never is it gonna be one. But is it nine? Is it 100? Is it a million? Um, and, and so we t- when we think about, you know, tumor as a clade, it's a starting from a single cell or small number, but it's speciating all over the place, you know, as it, as it gets in dif- different environments. But the speciation isn't magic, and it's not just due to a random mutation. It's because there are environmental variations, and trying to understand that I think would help us a lot, uh, in, in, in terms of really getting a handle on, you know, what the cancer is, is, is doing. And the, the reverse of that is the ... I mean, so, so take cancer cells out of a patient, put them in a dish, a- and now you start to grow them in culture. Well, no th- they're no longer, uh, being attacked by the immune system. They no longer have to worry about angiogenesis. They, they, they ... I mean, it's an entirely different-

    13. PAPeter Attia1:48:18

        Right. They don't have the edge effects that you described earlier where some of them have a selective advantage vis-a-vis access to substrate, whereas others are more competing with the tumors at the inside.

    14. RGRobert Gatenby1:48:29

        Sure. So they, they may be ... They're subjected to entirely different environmental selection forces. Um, now we say we take those tumors out, we do molecular biology studies, and we say, "Oh, well, this came from a lung cancer. That means lung cancer must interact with this to do this," when in fact we're dealing with cells that have evolved far past. You know, they're, they're, they're far different from the cancer cells that were present. Um, those, you know, th- that, that makes up a enormous amount of the cancer literature right now. A- and I don't know that that's useful. Um, I don't know that y- you can, um, extrapolate from those results to anything that goes on in vivo. And it's also I think has led to very confusing literature, at least in, in my opinion. You take s- you know, genes that are commonly, that, that are, that, that, that have been extensively evaluated, a- and it's like they could do anything. Accor- uh, you know, according to the literature, they have any function you can name, um, because it's, we, they, they get found everywhere. So I think it's ... That's becoming, um, non-useful. It, it, it ... I mean, if, if, if you don't re- if you can't really sort of pin down what its role is, um, in, in, in vivo in a, in a patient Um, you've got a lot of literature, but I don't know that you have a lot of knowledge.

    15. PAPeter Attia1:49:53

        So how does this fit into the Evo Index? How do you ... Which basically looks at the diversity versus genetic change over time. How do you then use that to clinically make a decision?

    16. RGRobert Gatenby1:50:06

        Um, I, I, I don't know. [laughs] I mean, uh, I- i- i- is ... f- in dealing with a very, uh, heterogeneous population, and I think this is your question, it does ... As you increase the heterogeneity, does that increase the, let's say, its resistance to therapy or the likelihood that ... And I think that's probably true. Um, but I, I, I, I don't know how that can be taken into account right now in a clinical setting. I, um, and I'm sure that someone smarter than me is gonna figure this out, but, but right now, I, I don't have a good, uh, f- feeling about this. And-

    17. PAPeter Attia1:50:44

        So in other words, we can't do something as simple as biopsy patients to get a sense of drug resistance versus non-resistance because it immediately takes them out of the environment in which it matters, and we get back to this problem-

    18. RGRobert Gatenby1:50:59

        Yeah

    19. PAPeter Attia1:51:00

        ... of well, we can't-

    20. RGRobert Gatenby1:51:00

        Yeah

    21. PAPeter Attia1:51:00

        ... really do this in vitro.

    22. RGRobert Gatenby1:51:03

        Right.

    23. PAPeter Attia1:51:04

        So it all-

    24. RGRobert Gatenby1:51:04

        That's right. I mean-

    25. PAPeter Attia1:51:04

        Yeah

    26. RGRobert Gatenby1:51:05

        ... uh, uh, I mean, you, you know, does w- the, the, the, the, the nice thing ... I mean, you get, you get information about the s- the, the, the, the tumor, but those cells are dead.

    27. PAPeter Attia1:51:15

        Yeah.

    28. RGRobert Gatenby1:51:15

        You know? What's in the tumor is now gonna rapidly diverge from there because the minute you touch it with therapy or, or, you know, some other perturbation, it's evolving and changing very rapidly. Um, so, so that ... A- again, it's like the hurricane going on further and further, you know? That, that, whatever the data you got on day one, uh, you know, is, is important for day two, but becomes less important f- on day three and day four and day five, and f- ultimately, then having nothing to do, uh, with, you know, having no predictive capacity at all, um, for the hurricane. So, so I think o- o- one, one of the things that I think we have to be careful, careful about is how we use data. I mean, there's a lot of interest in circulating DNA and circulating tumor cells and, and that sort of thing, but there's very little information about where they come from exactly. Are those ... So are, are those ... Uh, is the DNA coming from cells that have died because they're less fit? And, and so those are the losers in the, the, in the evolution game. So they ... You know, we may not care about those.

    29. PAPeter Attia1:52:17

        Yeah.

    30. RGRobert Gatenby1:52:17

        Um, or are they the winners, you know? In its, in that case, we do care about them. Um, and how do they, how are they representative of, of all the different range of cells? Is this, is it a, um, is the distribution of DNA representative of the distribution of populations or ... I, I, I think that's highly unlikely. A- and so I think that we do have to be thinking about using imaging as a way to look at the intertumoral evolution over time. It's a non-destructive way to do it. Um, but we have to be able to take the macroscopic scale images that we can get from radiologic studies and bridge the scale to a microscopic, uh, level that can tell us about what's going on at, at, at the cellular and m- molecular level.
13. 1:55:24 – 1:58:36

    Advantages of early screening for cancer

    1. PAPeter Attia1:55:25

       What inference do you draw from your work with respect to the importance or lack thereof of early, early screening? In other words, um, d- do you now have a point of view one way or the other from the mainstream view, which truthfully is that screening is kind of important, but probably not that important, right? I mean, there's only five cancers for which, you know, the American College of, uh, or, or sorry, the, um, um ... Is it, would it be Probably the American Cancer Society would even offer, um, or certainly the US, uh, Task Force on Preventative Services would even offer a point of view on screening. Uh, prostate, we've basically thrown our hands up and said, "Eh, talk to your doctor," you know. So we have a point of view on lung cancer in smokers, mammography, cervical cancer, um, and colon cancer. Um, but, but given that we now have many more tools to go looking for cancer early, whether it be liquid biopsies and cell-free DNA or far, far better imaging studies, um, does, does your work point you one way or the other towards having a better shot at, at treating cancer by getting it early?

    2. RGRobert Gatenby1:56:36

       I, you know, I, I think it would make sense that, again, the smaller the population, the more likely you could, uh, cause extinction. Um, but that said, I'm, I'm not, I don't think really qualified to, you know, comment on the, the screening, uh, program. I, I, I'm very supportive of screening. It just intuitively makes sense. But, but that's just from a personal point of view. I, I, I'm not, not based on any work that I've done.

    3. PAPeter Attia1:57:01

       Be- because when I hear... So, so, so when I hear what you are saying, it, it, it makes me think you should be doubling down on screening, right? It makes me think that notwithstanding the challenges of screening, which are both economic and the psychological toll of false positives which invariably happen the earlier and earlier you look for a cancer, the trade-off is, is th- those effects that we've described, which is you are going after a colony. If, uh, you, you were going after, you know, a, a, a group of hunter-gatherer colonies rather than the United States of America, right? You-

    4. RGRobert Gatenby1:57:37

       Yeah

    5. PAPeter Attia1:57:37

       ... you have a much easier chance, and, and they've had far less time to accumulate mut- mutations. Um, and they are far less interconnected.

    6. RGRobert Gatenby1:57:45

       Far more vulnerable.

    7. PAPeter Attia1:57:46

       Yeah, exactly. Um, why, why did you select prostate cancer for your trial? Was it simply because you had a great biomarker in PSA, or was there anything else about the biology of prostate cancer that attracted you?

    8. RGRobert Gatenby1:57:57

       Um, the, the, the [laughs] two things was that, um, it had a great biomarker and, and it had a very brave oncologist willing to do it.

    9. PAPeter Attia1:58:05

       Mm.

    10. RGRobert Gatenby1:58:05

        You should not minimize the courage of the latter, uh, because it does go against the, the grain and does take, um... Y- y- y- you know, the, it's, it's, the, the oncologists have to, um, swim against the, the, you know, the stream, you know, to do this and, and many of them are, are really not willing to do it. So, uh, uh, it's just, uh, you know, I, I salute, uh, Jinsong Zhang, who was the very brave oncologist that, that, uh, ran the trial

14. 1:58:36 – 2:09:22

    Bob’s goals for follow-ups after the success of his prostate cancer trial

    1. RGRobert Gatenby1:58:36

       and did it very well.

    2. PAPeter Attia1:58:36

       Well, given the success of that trial now, has that increased the appetite of, of, of others to consider doing this, uh, either in a larger scale with randomization for prostate cancer and/or for other histologies?

    3. RGRobert Gatenby1:58:49

       Um, minimally. Uh, the, there was a, um, a, a philanthropic, um, fund in Europe that will... that wants to, uh, fund a, a phase three trial a- and, uh, in, in prostate cancer. So, so that's really good, and I think that's really important. But, but I would say that at the same time, uh, I, uh, the... if, if anything, I, I get the feeling there's more resistance. I think just everybody's got their back up. Um, it's interesting that, that the article that I mentioned about, um, showing how you can, you can eliminate the resistant cells. Um, uh, I, I, I just got, I got this morning actually got the 10th rejection, um, for, for, for that article. I mean, it just, um, people just don't want to hear it. So it's been, um, uh, I, I don't get the sense that there's any, uh, greater interest in, in that sense.

    4. PAPeter Attia1:59:50

       If, if funding were available, what, what cl- a- and, and more importantly than funding or at least equally important would be, um, oncologist collaboration. What, what other experiments would you want to do?

    5. RGRobert Gatenby2:00:04

       Well, I think there's some low-hanging fruit. I think ovarian cancer is one that, um, could be treated using this technique and, uh, very successfully. Again, they have a, a nice serum marker. Um, there is a, uh... I think that small cell lung cancer, uh, almost universally fatal disease, but one that is responsive extremely well to initial therapy. So, you know, any tumor that responds well to initial therapy to the point that you, you, you know, you virtually cannot see any tumor is one that, um, in theory could be, um, I think we could eradicate. And then, um, initial prostate cancer, uh, therapy. So men that present-

    6. PAPeter Attia2:00:45

       Pre- pre-metastatic.

    7. RGRobert Gatenby2:00:46

       No, no metastatic.

    8. PAPeter Attia2:00:47

       Oh, metastatic. Okay.

    9. RGRobert Gatenby2:00:48

       So men that, men that present with metastatic prostate cancer, they get... They're treated with, uh, androgen deprivation therapy, and the PSA becomes normal or undetectable in 90-plus percent of the, of these, of these men. And of course, what do we do? We just keep treating with androgen deprivation therapy. I think we're gonna go to zero-

    10. PAPeter Attia2:01:07

        Which by the way says nothing about the metabolic damage and the total metabolic derangement it, it brings on those men. So if they don't die-

    11. RGRobert Gatenby2:01:16

        Oh, I know

    12. PAPeter Attia2:01:16

        ... from prostate cancer, they're gonna die from diabetes and-

    13. RGRobert Gatenby2:01:19

        Yeah

    14. PAPeter Attia2:01:20

        ... the complications of fatty liver disease.

    15. RGRobert Gatenby2:01:22

        Yeah. I mean, they hate this dis- that, that, the, the therapy. Um, so I think, um, we should, uh, when... as soon as it, as it normalizes, we should, you know, use additional therapies. Hit it again. You know, this is the-

    16. PAPeter Attia2:01:36

        Sure

    17. RGRobert Gatenby2:01:36

        ... the knife fight again. Um, and, and that's a very common disease and a very common scenario. And it's interesting that, um, I cannot get, um, anyone, any, any oncologist, uh, to be interested in doing that. Um, to me, that's very low-hanging fruit that, um, we should certainly try. Um, what... Or we could try the, this, the cycling, but with the idea that we drive the, the resistant cells to extinction also Probably fairly easy to do, um, perhaps even easier to do. Um, but with the idea that we, we, we get to the point where these men don't have to keep taking this, the androgen deprivation therapy. I mean, it, it's funny because, uh, you're, you're, you're exactly right. I mean, I, I think there tends to be the sense of, oh, it's not really cancer therapy, and it's certainly not like chemotherapy. I've talked to men-

    18. PAPeter Attia2:02:34

        I, I find it to be worse, truthfully, for the patients.

    19. RGRobert Gatenby2:02:36

        Men, men are miserable.

    20. PAPeter Attia2:02:37

        Yeah.

    21. RGRobert Gatenby2:02:37

        Um, and yes, uh, I mean, it's, it's... Y- y- we should not minimize the effect of this, which is very significant, and it's a pretty common problem. Um, so, so I think that we, there, there are some opportunities. I, I don't think, uh, uh, [laughs] to be honest, I don't think this will be, uh, something that I'll see in my lifetime. But, um, but I do hope that, that, you know, the next generation of oncologists and cancer biologists will, um, try to, uh, at least bring this, uh, another step forward.

    22. PAPeter Attia2:03:11

        Is there a cancer that you would stay away from at the early stage? In other words, you, you obviously want to start with the ones where you think you have the highest likelihood of success. Where, what would you put at the other end of that spectrum where you think, "You know, that's, that's gonna be a really tough problem to solve"?

    23. RGRobert Gatenby2:03:26

        I think the toughest problem I can think of is glio- is glioblastoma, one that you mentioned before.

    24. PAPeter Attia2:03:30

        Yeah, GBM.

    25. RGRobert Gatenby2:03:30

        I, I, I just don't understand how... I mean, every other tumor virtually is, the problem is not local control.

    26. PAPeter Attia2:03:39

        Yeah.

    27. RGRobert Gatenby2:03:39

        If, if you, if you control it locally, you, you, you cure it. It's metastasis. GBM is, is, you can't control it. I, I, I... It, it bothers me that this, this... There, there's something we're, we're missing in this that, that, um, that, that I don't understand, but, but it d- it feels like... First of all, it's, it's a, it's an intimidating cancer, and I would never try to get involved with it if, if, if I, uh... I mean, I would... I, I, I mean, I'd love to be, to be able to make an impact to help people with the disease, but it's such a difficult problem that I would be loathe to do that unless someone came up with a really good idea. Um, you know-

    28. PAPeter Attia2:04:20

        I mean, I think part of the problem is the, there's the m- there's the, quote-unquote, "The simple mass effect problem," right? Which is you're just, you know, anything in the brain is problematic due to the inability of the organ to absorb growth. I think a second problem with GBM is the ubiquity of radiation that is understandably used to treat it, but it introduces mutagenesis probably at an even greater rate. So now you have two layers. It, it basically puts, I, the, the... I think it puts a bit of an accelerator on its ability to outcompete its environment. It just introduces a new, uh, genetic heterogeneity. Um, I don't know if that's right. I mean, that's just a theoretical argument. I don't know that that's been documented.

    29. RGRobert Gatenby2:05:04

        Yeah. It, it's, it's interesting. But of course, the, the brain is, is inaccessible, and so it's hard to see what goes on. Um, but, but just, uh, uh, you know, even w- what, what we know is that, you know, you hammer this tumor with... I mean, you, you, you take, take it out, you bulk it-

    30. PAPeter Attia2:05:23

        Yeah
15. 2:09:22 – 2:18:30

    Treatment options for cancer patients who have been told they have “failed therapy”

    1. PAPeter Attia2:09:22

       I mean, there's no doubt, Bob, that there are gonna be people listening to this who either themselves or their loved ones are, um, progressing through therapy and basically looking down the barrel of no options. Um, and where... Le-let's, so let's say someone's in that boat, and they hear this, and they say, "Well, look, I'm basically being told by i- by my oncologist I've progressed through all my therapy," or, uh, the term that oncologists use, uh, some, that some oncologists use that I don't particularly find, uh, fond, is you've failed therapy, which to me-

    2. RGRobert Gatenby2:09:55

       I, I-

    3. PAPeter Attia2:09:55

       ... is a bit incorrect.

    4. RGRobert Gatenby2:09:56

       I ha- I hate that expression.

    5. PAPeter Attia2:09:58

       Yeah. Um, and th- and, and let's say they're listening to this, and they say, "I want to find a doctor who can help me try this therapy." What, what would, what would their options be?

    6. RGRobert Gatenby2:10:08

       Well, you know, you have to find an oncologist willing to do this, and, um, uh, there are some, uh, you know, who, who w-will, will work with them. Um, uh, but there's a lot that will not. Um, and it's a very difficult problem, and I, I can't help because, I mean, I'm not an oncologist. I don't, I, I... and I'm not qualified to be, um, you know, prescribing anything for, for people. Um, really always w- you know, when people call me, I say, "I'm happy to work with your oncologist. If your oncologist is willing to, to, to try something different, I'm happy to at least give them my best sense for what the underlying eco-evolutionary dynamics are."

    7. PAPeter Attia2:10:52

       Yeah.

    8. RGRobert Gatenby2:10:52

       Um, understanding, of course, that a lot of times we don't really know for sure, but, but this, again, in desperate situations, um, th- if they want to try this, that's between them and their doctor. Um, but most, you know, phys- a-and as you know this, physicians are very aware of medical-legal, uh, issues, um, are very afraid of doing anything that's non-standard because it does open them up to, um, to lawsuits and, and that sort of thing. So it, it's, um, and I understand that, and I, I'm, I'm not... That's not a criticism. It's just a statement. Um, so unfortunately, it's, it's a, it's a very difficult problem, and it's a lot easier to deal with patients that are just presenting with cancer than the ones who have been through many therapies, unfortunately. And I've... You know, my father died of esophageal cancer, and I, I remember this, uh, you know, vividly, uh, the desperation and, and the despair and the, and the, and, and, and everything that comes along with people at the end stages of the disease. Um, and, and, you know, I, I would love to help. I mean, I, I really wish I could, but, um, unfortunately, most of the time, it's, there's just nothing left to, to do.

    9. PAPeter Attia2:12:09

       Well, Bob, I, I, I have found your, your story really interesting and really provocative, and, um, I think the frustrating thing about what you say is that there is, in my opinion, very little downside to trying it. It would be very easy to conduct clinical trials-

    10. RGRobert Gatenby2:12:28

        Mm

    11. PAPeter Attia2:12:28

        ... that would have a crossover arm where, you know, you could take this adaptive approach, pit it against a standard approach, and if the patients on the adaptive approach were progressing, you could cross them over. And by the way, vice versa. When the patients-

    12. RGRobert Gatenby2:12:43

        Sure

    13. PAPeter Attia2:12:43

        ... who are progressing on the standard therapy, uh, too quickly, you would cross them over. In other words, um, y-you know, when you think about some of the risks that we talk about in medicine, this actually strikes me as a relatively low-risk proposition. The greatest risk is to our egos and to the dogma as opposed to the patients.

    14. RGRobert Gatenby2:13:03

        Yeah.

    15. PAPeter Attia2:13:03

        And that's, to me-

    16. RGRobert Gatenby2:13:04

        Yeah

    17. PAPeter Attia2:13:04

        ... a bit of the unfortunate part of medicine is, um, is when we... And we're all guilty of it. I'm, I, I-

    18. RGRobert Gatenby2:13:11

        No, I, I-

    19. PAPeter Attia2:13:11

        ... can probably count 100 examples of where my ego-

    20. RGRobert Gatenby2:13:14

        Myself

    21. PAPeter Attia2:13:14

        ... gets in the way, but, but this is a particularly, um-

    22. RGRobert Gatenby2:13:17

        Yeah

    23. PAPeter Attia2:13:17

        ... sad example of it when there is, um, a disease that we've really had very limited success treating, right? You referenced Nixon earlier, right? The war on cancer is now in its 50th year, um, and we don't have a whole heck of a lot to show for it, certainly not given the time and the resources that have gone into it. I don't, I don't think anybody in that era, in the early 1970s, if they had a crystal ball and showed them what we have today, would say, "That's success."

    24. RGRobert Gatenby2:13:52

        Yeah, I mean, we, we've certainly made some progress, but we have not made a, a lot of progress in the metastatic, you know, cancer population, which is still more or less as fatal as it was, um, uh, 50 years ago and, and of course well before then. Um, and you know, I, I, I, I think We, we do, I think it's important to try to rethink some of the, the things we do that just, just keep doing the, doing the same thing over and over again and just keep, you know, looking for new drugs, um, is, is certainly ha- you know, w- new drugs no doubt is, is important, but, um, but I think we could do better with the old drugs, and I don't think that we've been, um, r- really that, um, incentivized. I don't, I'm not sure we've really taken a lot of time to, to think this. And again, this is perhaps a bit of the, what we, we started with that, you know, in- intu- intuitively it would seem like killing as many cancer cells as possible is the best approach to, for the patient, right? And, um, in fact, in a nonlinear system, intuition is often not wrong, but it's, but nevertheless, it seems like it, it's, it's right. I mean, we just... You feel absolutely certain you're correct, um, even when, uh, y- you know, your own eyes tell you that it's different. Um, and that, that's hard. I mean, that's, it's hard for all of us.

    25. PAPeter Attia2:15:11

        Yeah. I, I mean, I think, look, I think that statement, um, is a great place to end this, which is in nonlinear systems, your intuition can be very misleading, and that's, that's true in life, of which biology, especially this corner of biology, happens to be exceedingly nonlinear. Um, and with that, Bob, I wanna, I wanna thank you for, for your generosity and time, and more, much more importantly, of course, the work you've done, which, um, I, I think is helping a lot of people. And you're right. I mean, it might not put a dent in the world of cancer, um, in the next decade. Um, but I, as, as we alluded to earlier, sometimes some of the most interesting, um, uh, things in, in medicine take decades, plural, uh, to, to take hold. So, um, hopefully there are a number of people who are going to be able to pick up this baton and run with you and eventually even be able to carry it.

    26. RGRobert Gatenby2:16:07

        Thank you. Thank you. It's been a pleasure.

    27. PAPeter Attia2:16:10

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Episode duration: 2:18:34