Why elephants get deadly cancers less often than humans
Rob Wiblin: Another fascinating thing in the book: elephants have way more cells than humans — and no surprise there; I think it’s 100 times as much or something — and yet they get deadly cancers less often than we do. That’s super counterintuitive on its face, because you’d think that the probability of you developing a seriously dangerous cancerous tumour would be roughly proportional to the total number of cells you have, because each one of them has an opportunity to itself become cancerous. Why is it that elephants don’t get cancer much more than humans?
Athena Aktipis: That’s a great question. And again, we have to think about definitions here, because a lot of elephants actually have growths, have tumours — they are just not metastatic and cancerous, and they don’t threaten their lives so much.
But to get back to your main question about why an elephant is less likely to die of cancer than we are, or than a mouse is? That’s a big contrast. And to think about those big-picture issues, we have to consider that there’s different selection pressures on organisms that are long-lived and large versus short-lived and small.
Long-lived large organisms have to invest a lot more in what we call “somatic maintenance,” which is just a fancy way of saying fixing your body and making sure that the body maintains itself well. In order to have a chance at reproduction, a large, long-lived organism needs to be doing a lot more cellular things to take care of the body — including DNA repair, monitoring for cellular cheating, and all of that. Organisms that are larger and longer-lived have more robust cancer suppression mechanisms than organisms that are smaller and shorter-lived. And this ties in with an idea in evolutionary biology called life history theory.
Rob Wiblin: I like to picture life history strategy by imagining the evolution kind of embodied in these engineers or something, who are standing around chatting about the animals they’re going to design. And one of them’s like, “I’ve got this great idea. It’s going to be called an ‘elephant.’ It’s going to be massive. It’s going to be this huge organism. It’s going to have no predators because nothing’s going to be able to eat it or beat it and it’s going to be able to reach up really high in the trees to get all this energy.”
I imagine another engineer being like, “That’s never going to work. It’s going to have way too many cells. It’s going to have cancers all the time. What are you thinking? You’re an idiot.”
The other engineer says, “No, I’ve thought about this. What we’re going to do is we’re going to invest a tonne, OK? It’s got all these benefits and we’re going to invest a tonne of energy and molecules in making sure it doesn’t get cancer. We’re going to have real tripwires everywhere. Any cell that seems to be acting out, we’re going to shut it down right away. And OK, this is going to slow down the growth; it’s going to have an overhead. But at the end of the day, we’re going to have this massive elephant. It’s going to live for ages. It’ll be able to have lots of babies because it will live long enough.”
Then you could do the opposite with a mouse, basically, where you’re like, “OK, forget it. We’re not going to worry about the body. It’s just going to replicate like crazy.”
Is this basically the idea?
Athena Aktipis: I love this, and you’re just being the adaptationist engineer right now. You’re like, “All right, how are we going to design this thing for this function or that function?” And yeah, I think it’s a great cognitive tool to use to just wrap our minds around how things are going to evolve given constraints, and what kinds of adaptations we would expect, given that you want an organism to be able to do this thing or that thing.
A subtler approach for managing cancer
Rob Wiblin: One thing you talk about in the book is the possibility of not trying to kill a tumour, but instead taking a more subtle, soft approach, where we just try to manage its behaviour. Can you explain that whole approach?
Athena Aktipis: Yeah. The approach I think you’re referring to is adaptive therapy, which is really proposed and brought to the fore by Bob Gatenby from the Moffitt Cancer Center in Florida. The main idea of this is that if you try to treat a cancer with a high-dose therapy, with the approach of trying to eradicate it, you can inadvertently select for the cells that are most resistant to the therapy. So this is akin to what happens with the evolution of resistance to pest control.
Rob Wiblin: And antibiotics.
Athena Aktipis: Yeah. So with high doses for a long time, you’re actually applying the strongest possible selection pressure to favour the cells that are resistant.
Rob Wiblin: Because all of the other cells will be dead.
Athena Aktipis: Exactly. The only cells that survive are the ones that can survive in the presence of the drug that you’re trying to use to get rid of the tumour.
So then the question becomes, “Well, what’s the alternative then?” I’m not going to say for all tumours, because there’s some where, yes you can get rid of them with standard chemotherapy. But if you accept that for certain classes of tumours, at least — especially if they’re advanced and are likely genetically diverse, they probably already have resistance mutations — the sort of logical approach is to look at it and say, “It’s unlikely that this could be eradicated with high-dose therapy. So we have to take as given that this tumour is going to stick around. So what kind of tumour do we want to cultivate?”
Well, what you want is a tumour that’s going to respond when you treat it. That’s going to be controllable. That’s going to not become invasive and metastatic. One that’s not going to disrupt the life of the person who harbours it as much. So you can then approach it from this perspective of, “Given that it’s going to stick around, what are the priorities?”
So the approach of adaptive therapy is really that you start by giving a dose of the drug, to get the tumour to a smaller size so that it’s a little bit more manageable. And then you only treat it when it’s growing, and when it’s not growing, you let it be. The idea here is that there’s usually a cost to resistance to drugs, because it takes energy for cells to pump out drugs from the cell or do other things that can confer resistance. So that means that when you’re not applying the drug, the cells that are sensitive to the treatment are going to more likely have an advantage over the cells that are resistant. So you kind of manage the tumour by treating it when it’s growing too much and then you back off, so you can get more of the sensitive cells there.
And patients are able to live for much longer than expected with these kinds of treatments. There’s ongoing work, there’s a lot more work to be done, but the clinical trials that have been done are really promising, even with late-stage cancer.
Cell suicide and single points of failure
Rob Wiblin: One really mind-blowing thing in the book is — I remember I was on the Tube and I was listening to this, and I thought I knew the answer to it and then I was completely wrong — so, basically you set up in the book that we have this gene and this set of processes that we’ll call TP53 gene. It collects a lot of information about what’s going on in the cell and in the local environment in order to decide whether the cell should commit suicide. So it’s trying to look for funny business and see, “If A is wrong and B is triggered and there’s also X, then OK, we’re going to shut down the cell. We’ve got to shut this down because it’s too high risk that I’ve become cancerous now.”
Now, the interesting thing is that because so much work is being done by this one TP53 gene, protein and general system, that creates a single point of failure — where if you have a really destructive mutation in the TP53 gene such that it cannot function anymore, then your chances of that cell becoming cancerous go way up. So you might think, why wouldn’t you have a more robust system? Where, rather than put so many of your eggs in one basket, why not have lots of different processes going on at the same time, all independently deciding whether something has gone wrong and the cell should commit suicide/apoptose. Why do you think it is that the cell puts so many eggs in one basket? I want to know what’s the answer.
Athena Aktipis: So, two things. One thing is there are many different processes that are all going on. It’s not just TP53, but it is the case that, like you said, all of this information is kind of flowing through TP53. And that’s a case for many of these other systems, where there is one point where if you break that point, then the whole system can get messed up.
So then the question is: why have everything flowing into one spot and then flowing out? One potential explanation for why this is the case is that in order for a cell to really figure out if there’s a problem or not with a cellular behaviour, it needs to integrate information from many, many different sources. For example, earlier we were talking about wound healing. So it would be important to know if the reason that the cell is proliferating and moving has to do with being in an environment where that’s actually what is beneficial for the organism. Is this a wound healing situation or is it not?
In order to be able to integrate information from all of those different sources, at some point it all has to come together. So you can potentially have these points of vulnerability, because you need to integrate information across a lot of different domains, I guess you could say, in order to actually make a “smart decision.” Because it has a very different meaning, you could say, for a cell to be proliferating and moving if it’s in a wound-healing environment versus if it’s in a normal tissue environment. The downstream consequence of what should happen is going to be different in those two cases.
Cheating within cells
Rob Wiblin: Yeah. Speaking of cells, we’ve mostly been talking about cheating and defection between cells. But we should talk for a minute about ways that you can get cheating within cells, which sounds a little bit crazy because already a single cell is such a small scale. How can you have sub-components of a cell fighting against one another? But it turns out that you totally can.
Can you explain how it is that you can get genes cheating against other genes that are on the same strand of DNA, that are on the same chromosome?
Athena Aktipis: So very, very early on in the evolution of life, there wasn’t anything like a genome, like a bunch of DNA that is teaming up to replicate itself together with all the machinery to replicate and all of that. You had probably something that was much more RNA-like, so you had basically just these molecules that were able to replicate themselves in one way or another. Once you start having situations where these entities that are replicating can do so more effectively in a cluster, then they will stick together and then maybe machinery evolves that allows them to replicate together.
Now, you can imagine though, early on in the evolution of that, if you had a cheater that was actually replicating itself more than the others, that that cheater could then be overrepresented in the next generation. This is very, very likely what was going on in the evolution of proto-life, I guess we could call it — or maybe it’s life, if you think self-replicating entities are life.
So the very design of how our DNA works, how it replicates, there’s actually all of these cheater-suppression mechanisms already built in. And that’s the only reason that it works, is because there is a suppression of all of these sort of gene-level cheaters. So when we see fragments of DNA that over-replicate or jump into new chromosomes and replicate themselves in there, rather than seeing something weird and really unusual, we’re just seeing the uncovering of the fundamental [tensions that were already there].
That were sort of overcome in what’s called the major transitions in evolution — these times when previously independent entities came together to form higher-level entities, which then allowed for more complexity and then yet higher-level entities. So, a bit of coming together, regulating genes into a genome, having some cheater-detection-suppression response mechanisms at that level really is one of the steps in getting complex multicellular life, at least on this planet.
Rob Wiblin: So, a stylised illustration of what might have been going on is: you’ve got lots and lots of different strands of DNA, lots of different genes in this kind of soupy mixture, and they’re like, “We could do better if we all stick together. If we all get on one big, one very long strand of DNA so that we’re all there and we’re always available to use these genes if that’s going to be useful for replicating ourselves.” But every time the organism wants to replicate, each of the genes is like, “No, copy me a little bit more. Why not make more copies of me?”
Athena Aktipis: Yeah, something like that.
Rob Wiblin: “I would rather become a larger faction of the genome.” At least until the point where that causes the thing to become completely nonfunctional and then the cell is dying completely. That would set some limits pretty quickly.
Athena Aktipis: Right, yeah. And that’s where we get into multilevel selection again too, because you had presumably little clusters all over the place doing this over long periods of time. And those that were best at forming together, at replicating together, at suppressing cheating, were the ones that were more likely to create copies of themselves at that higher level. So yeah, multilevel selection is absolutely key for understanding these major transitions in cooperation — where you go from these lower-level entities that are competing or just facultatively cooperating in the right circumstances, to being locked in that they can only replicate as a unit together.
Cooperation in human societies
Athena Aktipis: We have this project called the Human Generosity Project, where we’ve looked at almost a dozen small-scale societies around the world now and how people within those societies help each other in times of need.
We have found that if you look at the risk management strategies that people are using, that in pretty much every society we see need-based transfers. It’s like, “Hey, if I’m in need, I will only ask for help if I’m genuinely in need.” And then if you receive a request, you will help if you’re able to without going below what you need. The one society where they don’t use it as much is this society I was telling you about in Mongolia, where they have these winters that are just horrible. They have to help each other ahead of time. They have to manage the risk proactively, because they can’t go to each other’s houses when there’s six feet of snow outside.
Rob Wiblin: Oh, wow. So what do they do?
Athena Aktipis: They will help each other build shelters and make sure that everybody has the resources that they need.
Rob Wiblin: For winter?
Athena Aktipis: Yeah. It’s basically sheltering in place for the winter. They’re helping each other be able to do that for their families and their livestock.
Rob Wiblin: I would emigrate. That sounds awful.
Athena Aktipis: Yeah. But the bottom line here is that people around the world in small-scale societies do this, and also in rural societies here in the US. We’ve studied ranchers in the Southwest, here in Arizona and New Mexico near the border with Mexico. They have a system they call neighbouring, which is largely a need-based transfer system where they help each other in times of need and they don’t expect to get paid back for those things that arise unpredictably.
These are things that already exist, and they’re really good at handling the kinds of things that typically we want insurance for — those things that we can’t predict and can’t control. And if you take it to the extreme, there’s certain things that market-based insurance actually cannot insure against.
Rob Wiblin: Because everyone gets hit at once?
Athena Aktipis: That’s one possibility. Everyone gets hit at once. But another is just that it hasn’t happened yet and there’s no way to really calculate what the probability is of the event or how severe it would be. In the absence of any of that information, you can’t calculate what an insurance premium could be. It’s an actuarial problem: you need the data in order to price the insurance.
But with these need-based transfer networks, you can at least have them in place for any kinds of needs that arise unpredictably. Now, whether the system will be able to effectively handle those is another question, but you at least are able to set up systems that can deal with things that have never happened before — that we can’t even understand what the risks are like.
How to thrive in the apocalypse
Athena Aktipis: I think no matter where you live, having 72 hours of supplies is wise. And you can actually do this in a way that makes sense for having a very busy lifestyle, which is something that I love.
Rob Wiblin: Apocalypse prep — on the go!
Athena Aktipis: Exactly! Apocalypse-casual lifestyle. How do you do this well? For example, if you like couscous, couscous is a great food to have around. Not only can you prepare it very quickly on a weeknight if you need something to eat, but it stores well and you actually don’t even need hot water to prepare it. You can just add water to it and let it sit for a half an hour, and then you could eat it.
So if couscous is something that you’re fine with, then you can just make sure to buy enough couscous at the store that you could at least have it be part of what you would be eating for those 72 hours. Whenever you buy a new one, you put it at the back and you just have some extras. And then it also makes it easier when you’re super busy and you don’t have time to go to the store. You’re like, “Oh, I’ve got my 72 hours of prep.” Obviously, next time you go to the store you want to re-up.
Rob Wiblin: Yeah. You got to get extra.
Athena Aktipis: But sort of thinking about being prepared, not as like, “Oh, I have to go and figure out how to buy really long shelf life food on Amazon. Who’s a reliable source for this?” No, you just look at the kinds of things that you like to eat that are shelf stable, and just have more of those on hand. Because that will make your day-to-day life easier, and also will put you in a better position if something totally unexpected happens and you have to shelter in place.
Rob Wiblin: The UK has a pretty precarious food situation actually, because it relies on a constant stream of imports. It doesn’t produce anywhere near enough food for the population that it has. I would suggest having enough food for weeks, conceivably months, would be not outrageous, if you were able to do that here. I guess there are storage issues. I did at one point store a whole bunch of rice, but I didn’t store it well enough and mice got into it, and that was very embarrassing. I was a very amateurish prepper. But yes, now we have some rice and pasta in a thick Tupperware. The mice can’t get to it.
Athena Aktipis: Excellent. Excellent. I think that another thing is just not feeling intimidated by, “I have to do all of these things.” No, just start with having enough water around and having some extra dry food that is stuff that you eat anyway, and then you can work from there. It’s not like you have to do all of the things all at once or anticipate every possibility, because you just can’t.
Having conversations with people about what they’re doing: Do they have their preps? It can be fun. If you get into a little social competition about it, it could be playful fun. I have this idea for a new kind of dinner party. I haven’t tried it yet, but I absolutely want to: you roll the dice to figure out whose house you’re going to go to, and then you show up at that house, and you have to figure out how to make a really nice dinner with just the shelf-stable prep food that’s there. Then you practice making fun meals and surviving in your mini-apocalypse dinner party. Stuff like that. I think we could make it fun.
Then it just kind of puts our attention on how maybe we should just be ready for the unexpected, so that at least we have some more time to plan. That’s the thing. You might not be able to have enough food around to actually manage the risk of something catastrophic that would happen, but you can have enough food around so that you have a few days to figure out what your next steps are if something really catastrophic happens.