Therapy reshapes the landscape (punctuated equilibrium)

1:39:29tree of life and so there's a certain stress and then all of a sudden you get different types of species and cell lines and so forth. >> Basically almost not instantaneously in a literal sense. >> Yeah. But short time scale >> in a short time scale. >> Short time scale. And this actually shows that cancer is very much a punctuated equilibrium process. Right. The therapy actually sharpens the selection gradients. So certain certain fitness hills could become even more steep. Some some totally get >> Mhm. >> squashed and so on and so forth >> which tracks like conceptually like if you were to think about like why is cancer so hard to defeat like it moves so fast. It would make sense that this punctuated equilibrium is >> is what's happening and it's cool to see

1:40:10that you can actually measure >> get measurements that uh you know that point to that being the case. >> Exactly. And one thing that one can think about is like so why why would cancer cells do this where this you have this whole genome doubling sometimes where you know kind of like in a hollow all of your chromosomes have now four copies instead of two. Okay, why would you do this? Well, what this does is create a flat fitness landscape. And so you have something called survival of the flattest where imagine right before if there's a really thin peak >> your organisms will want to stay near that really thin peak because that thin

1:40:51peak is really really tall. >> But >> with cancer because you're throwing so much at them >> you kind of want to be in a flat hill >> rather than a thin peak. Because in a thin peak if you go off by a little bit it's like LCAP right in Yoseite you're just going to fall. >> But if you if you've got a sort of nice Kilamanjaro like hill then >> even if you stray a lot in your landscape you're still going to be able to be doing just fine in terms of fitness. And you can literally see that with this kind of trade-off, the tumor shifts from this sharp peak, high fitness, low tolerance to flat peaks,

1:41:32right? And the clinical relevance is if you've got instability and that instability pushes you past some kind of error threshold, >> then >> your population is going to collapse onto flatter peaks and not stay on that thinner peak. So then you're going to have a harder time maybe >> because at the flatter peak there's a lot of different stuff that cancer can explore and still be just fine. >> Mhm. The the the the point being you know you don't want to basically give an evolutionary advantage unnecessarily >> by how you're targeting your therapeutics and stuff like that. And so like if you can say like hey we know um if we sort of attack this in a

1:42:13particular way it's actually going to spread the evolutionary optionality that the cancer cells have across a wider surface area which is then going to actually make it subsequently more difficult to deal with. Uh which is like it's kind of like it's an interesting way to think about it is that like how you try to treat >> Yes. >> does have an impact on how it evolves and there's actually like right and wrong choices to minimize the uh surface area of risk. Yes. >> In how you treat. >> Exactly. And the other thing you can do is with that kind of rugged landscape, right? Suppose you've got a single peak and now there's a neighboring peak that's nearby. Traditional theory says that I can't get to the neighboring peak because I' I'd have to go through the

1:42:54valley. But now with this alpha K, we can actually it it's kind of like providing a navigational chart >> to steer and predict how it goes from one to to the next, how it could go from one peak to the other without going through the valley. >> Right. >> Right. Because it's this it's basically this map. >> Yeah. >> Right. And so we know all the routes between two different points on said map. >> And so we that's so good >> and it's it's really cool. I mean it just shows this very quantitative physics-based approach. Yes. to now I'm like going up on a fitness landscape. Yes, >> I can sequence, not sequence, but I can tell how much of a particular chromosome I have in certain cells and from that create this map of carotypes, right? And

1:43:35create okay >> how much of cell one do I need? It can depend on my past. It can depend on all the other contexts that I have because this model can build that in. >> It's it's very cool. And the computational cost is, you know, it's >> right now it's 22 dimensions. So, it is pretty expensive. >> Mhm. But it's better than doing the sister chromos the the sister cell treatment which is what we used to do where you take a little bit of the cancer cell and you see how it invol evolves in a test tube. I mean here you can just plug it into a computer. >> Right. Right. Right. Which which you know >> one while it may be expensive now it's the first formulation of the concept.

1:44:15You can in theory create uh other flavors that choose for different levels of dimensional precision >> as one key aspect. But two it's it's all simulation so you don't have the physical >> lab related costs associated with it. This is very very good stuff. >> Yeah I thought it was very cool and you know this one is doing it for any which is number of chromosomes but now you can think about creating you know you can think about creating landscapes for actual within a chromosome. How much of gene one do I have? How much of gene two do I have in a transcriptto? how much of mRNA for this particular gene do I have? >> You know,

1:44:55>> it's like really taking that fitness landscape and being like, no, we can actually just treat it as real, >> right? And then you can apply that to more than just the an employee for cancer. I mean, it's it's it can be applied in >> across the board, >> right? And I can now forecast >> what the cancer would do if I give it this treatment. >> This is very very good. I mean, you know, obviously cancer treatment, we've talked about a lot of different type of cancer related research stories and, you know, one of the there's so many challenges that are involved in it. Like there's it's like a >> multi- combinatorial mass of stuff. >> Yeah. >> Um but one of the things that's been so interesting is our tools to look, measure, andor understand what is

1:45:35literally happening >> have have been accelerating. Yeah. because we kind of right now have like more of a shotgun approach for therapeutics versus a sniper approach. Obviously, there's some cases that are getting more close to a sniper approach. Um, but like chemo is obviously very destructive to all the cell like all the cells which we actually discussed in a previous episode as why that's the case. >> Um, so stuff like this is really really impactful for oncology generally. >> Um, >> which is just fascinating. I mean my my mom works in clinical trials and they've you know historically they've looked at a whole variety of things. Obviously a lot of big pharmaceuticals are trying to go to big ticket things that have huge market value and obviously oncology is a

1:46:17huge one. >> Yeah. Huge one. >> Um >> and so really great stories today. Nice spectrum. >> Yeah. >> That we covered. Uh we started with uh botney uh one of our first plant stories about alkyoid biosynthesis. uh and that small factory we're now able to replicate in yeast >> in the new phytologist uh that was from uh York University of York in the UK. >> Uh we had a great rundown with a bunch of different uh variety of different pieces. The quantum entanglement story was fantastic that one out of the University of Basil and Sorb

1:46:58>> uh very very interesting. uh again measurement precision talking about my favorite the Heisenberg uncertainty principle we now can sort of not break the con we're not we're not we're not we're not doing anything it's not magic >> but it's clever creativity for how to work around those limitations >> and we ended with this alpha k local adaptive mapping which again I now have a way to gro this concept because we've talked about um concepts like gradient descent in the past like with a lot of the foundation and frontier models. That's how these things work. They're traversing. >> Y >> um you know these hide multi-dimensional spaces and so all very very good stuff.

1:47:39Uh I I just the only thing that I think we forgot this episode was what people should comment. >> Oh yeah, >> we didn't come up with a good one yet. Uh so we're going to do this on the fly. How about how about um alpha K alternative >> alternative alternative full forms of the acronym alpha K which is not alpha like the alpha particle or alpha Greek it's alfa K. >> Yes. Yes. Uh that's a good one. So >> yeah, let's let's see what people come up with cuz we do have some comedians. >> Uh we did see a lot of good responses to LBF from last episode. >> The freedom one was the best either. >> Uh Pound Force. >> Yeah. Uh, >> pound force is the correct one, but

1:48:19pounds per freedom, I think we're we're good. Yeah. >> And um, yes, the uh, the imperial system versus metric system is has >> its >> issues. Um, >> my name is Lester Nar joined as always by my co-host and our resident PhD and allound science genius Krishna Chowy. This is from first principles.