1 00:00:00,160 --> 00:00:04,160 My name is Astha Simes and welcome to Live Longer World. 2 00:00:05,600 --> 00:00:07,560 I'm really excited for this conversation because I think you 3 00:00:07,560 --> 00:00:10,920 bring such a multifaceted approach to looking at cancer 4 00:00:10,920 --> 00:00:15,040 from mathematical modeling, game theory and also evolutionary 5 00:00:15,040 --> 00:00:18,440 lens. So just to jump in, I would love 6 00:00:18,440 --> 00:00:22,840 it if you could discuss the new framing of the hallmarks of 7 00:00:22,840 --> 00:00:27,480 cancer, not as a static process, but one which you see from an 8 00:00:27,480 --> 00:00:30,280 evolutionary lens. So you've discussed how the 9 00:00:30,280 --> 00:00:34,040 cancer gets tumor gets initiated, it changes this tumor 10 00:00:34,040 --> 00:00:36,920 microenvironment. And then you also start to see 11 00:00:36,920 --> 00:00:41,520 this emergent phenomena of cooperation among these tumor 12 00:00:41,520 --> 00:00:44,440 cells, something which Mike talks about a bit bit as well. 13 00:00:45,000 --> 00:00:48,760 How do you see this evolutionary progression of cancer? 14 00:00:50,080 --> 00:00:57,520 Well, from an evolutionary point of view, cancer is, is, is a, is 15 00:00:57,520 --> 00:01:00,200 a fundamental evolutionary event. 16 00:01:00,440 --> 00:01:03,280 And, and whenever you talk about evolutionary, you talk about 17 00:01:03,280 --> 00:01:08,760 what's the unit of selection and in for our body, for the cells 18 00:01:08,760 --> 00:01:11,400 in our body, the unit of selection is us. 19 00:01:12,640 --> 00:01:16,720 Our cells have the same fitness as the, the, the 20 00:01:16,720 --> 00:01:21,760 three-dimensional, the, the, the multitude organ us. 21 00:01:23,080 --> 00:01:27,200 And they share that with us. They, they contribute to our 22 00:01:27,200 --> 00:01:33,520 fitness and, and so they're controlled by the, the, the 23 00:01:34,640 --> 00:01:35,800 structures of our, of our tissue. 24 00:01:36,160 --> 00:01:40,200 You know, the, the local tissue instructions, their death, their 25 00:01:40,200 --> 00:01:43,000 proliferation, their movement, their phenotype, all that is 26 00:01:43,000 --> 00:01:47,000 controlled by the tissue, but by tissue signals. 27 00:01:47,040 --> 00:01:49,400 And as a result of that, they do not evolve. 28 00:01:51,400 --> 00:01:55,840 Whereas in cancer, it's the unit of selection as the individual 29 00:01:55,840 --> 00:01:58,560 cell. So that carcinogenesis means 30 00:01:58,960 --> 00:02:03,080 that you've, it is a fundamental transition of, of cells that are 31 00:02:03,080 --> 00:02:07,200 defined by the fitness of their Organism to cells that are 32 00:02:07,200 --> 00:02:10,919 individually subject to evolutionary selection. 33 00:02:11,640 --> 00:02:15,200 And, and that's a, that's a tremendously, I, I think 34 00:02:15,760 --> 00:02:20,040 important way to look at this. The the traditional view of 35 00:02:20,520 --> 00:02:23,480 carcinogenesis is that it's an accumulating mutations. 36 00:02:23,800 --> 00:02:26,560 Something about those mutations generate a cancer. 37 00:02:28,360 --> 00:02:32,200 In this setting, what we would say is that the the cancer cells 38 00:02:32,200 --> 00:02:35,720 have to become independent of the host tissue signals. 39 00:02:37,800 --> 00:02:41,880 One of the, one of the problems with the, the, the kind of 40 00:02:41,880 --> 00:02:47,440 sequential mutation model is observations that you could see 41 00:02:47,440 --> 00:02:50,120 the same mutations in the apparently normal tissue 42 00:02:50,600 --> 00:02:55,360 adjacent to the cancer, which seems to suggest that's not 43 00:02:55,640 --> 00:02:59,440 yeah, that it's, it's, it's a, it's a part of it, but it's not 44 00:02:59,440 --> 00:03:03,240 the necessarily the cause of it. And so in the evolution model, 45 00:03:04,480 --> 00:03:09,400 we admit that you may get these accumulating mutations which 46 00:03:09,400 --> 00:03:14,160 renders the, the cell, you know, blind and deaf to the tissue 47 00:03:14,160 --> 00:03:15,440 signals. So they become totally 48 00:03:15,440 --> 00:03:17,560 independent because they just can't receive them. 49 00:03:18,400 --> 00:03:22,320 On the other hand, an alternative is that the you can 50 00:03:22,320 --> 00:03:27,520 damage the normal tissue and that damage prevents it from 51 00:03:27,520 --> 00:03:31,920 controlling the local cell population, which now allows 52 00:03:31,920 --> 00:03:37,000 them to to evolve. And now the accumulated 53 00:03:37,000 --> 00:03:40,800 mutations that they've, that, that have occurred over a 54 00:03:40,800 --> 00:03:44,800 lifetime, which are similar to, you know, all around, but, but 55 00:03:45,120 --> 00:03:50,040 now these mutations can become part of the fitness function of 56 00:03:50,040 --> 00:03:53,840 an individual cell. So there's a, there's sort of a 57 00:03:53,840 --> 00:03:58,400 subtle difference in this. And, and, and, and so it's that 58 00:03:58,400 --> 00:04:01,800 transition to independence. That's the, that's the critical 59 00:04:02,080 --> 00:04:07,040 function. And what this suggests, I think 60 00:04:07,040 --> 00:04:11,040 is that is that cancer is not just a mutation. 61 00:04:11,040 --> 00:04:13,760 It's not just, it just isn't happening to the cells, it's 62 00:04:13,760 --> 00:04:17,880 happening to the tissue. So, you know, damages to the 63 00:04:17,880 --> 00:04:23,360 tissue, inflammation, injury or just old age, you know, where 64 00:04:23,720 --> 00:04:28,280 the tissues sort of lose control of the local cell population can 65 00:04:28,280 --> 00:04:30,360 then trigger this evolutionary process. 66 00:04:31,680 --> 00:04:35,800 And so when you think then about cancer as an evolutionary 67 00:04:36,400 --> 00:04:42,160 process, the, the, these the hallmarks of cancer then need to 68 00:04:42,160 --> 00:04:48,520 be framed in terms of how they add to the fitness of the, of 69 00:04:48,520 --> 00:04:52,720 the Organism. And so one of the things that 70 00:04:53,160 --> 00:04:56,720 organisms do is, is called niche construction. 71 00:04:57,880 --> 00:05:02,240 Beaver Dam being the, the most obvious one, but, but that's 72 00:05:02,480 --> 00:05:05,200 kind of been added to evolutionary theory over the 73 00:05:05,200 --> 00:05:12,440 last decade or so as, as part of the, of the inheritance process, 74 00:05:12,440 --> 00:05:16,080 because you can, the Beaver Dam is an example, again, you know, 75 00:05:16,080 --> 00:05:17,800 can last for several generations. 76 00:05:18,320 --> 00:05:21,240 And so it can persist as an ecological mechanism of 77 00:05:21,240 --> 00:05:24,480 inheritance. And so, you know, when, when you 78 00:05:24,480 --> 00:05:29,000 start to think in these terms, to me, a, a, a great example is 79 00:05:29,000 --> 00:05:31,720 the Warburg effect. And, and, and this has been 80 00:05:31,720 --> 00:05:36,520 known since Warburg, I was 100 something years ago that cancer 81 00:05:36,520 --> 00:05:41,280 cells, even in the presence of oxygen, prefer glycolytic 82 00:05:41,280 --> 00:05:45,000 metabolism, meaning that they, they don't use oxygen to 83 00:05:45,000 --> 00:05:47,080 metabolize glucose. They just metabolize it to 84 00:05:47,080 --> 00:05:50,920 lactic acid and the the problem with that is that it's very 85 00:05:50,920 --> 00:05:55,560 inefficient compared to aerobic glycolysis or aerobic 86 00:05:55,560 --> 00:05:58,920 metabolism. And so that's often called a 87 00:05:58,920 --> 00:06:01,560 dysregulation. You know, there's something 88 00:06:01,560 --> 00:06:04,040 wrong with the cancer that it's not doing what it should be 89 00:06:04,040 --> 00:06:07,120 doing. And you know, evolution doesn't 90 00:06:07,120 --> 00:06:10,640 do dysregulation. Evolution is, you know, at the 91 00:06:10,640 --> 00:06:13,800 greatest optimizing force in the universe. 92 00:06:14,440 --> 00:06:21,240 So if the, if you're seeing the, the cancer cells use glycoidic 93 00:06:21,240 --> 00:06:25,280 metabolism in the presence of oxygen, that means it's, it, it, 94 00:06:25,280 --> 00:06:27,320 it's conferring a fitness advantage. 95 00:06:28,920 --> 00:06:32,760 And my own hypothesis is it's the acid that it's produced 96 00:06:33,040 --> 00:06:36,120 that's the fitness advantage. It's, it's a niche construction 97 00:06:36,880 --> 00:06:42,520 so that the cancer cells now can adapt to a, a, a high level of 98 00:06:42,520 --> 00:06:45,000 acidity, which normal cells cannot. 99 00:06:46,240 --> 00:06:50,040 It promotes invasion and it tends to blunt the immune 100 00:06:50,040 --> 00:06:52,480 response. And so it serves a purpose. 101 00:06:54,120 --> 00:06:59,160 And, and I guess that's the kind of the, the theme here is that 102 00:07:00,680 --> 00:07:02,880 evolution is a scientific game of jeopardy. 103 00:07:02,960 --> 00:07:07,080 Evolution gives you the answer. Our job is to provide the 104 00:07:07,080 --> 00:07:11,840 question. Evolution tells you that that 105 00:07:12,080 --> 00:07:16,480 aerobic glycolysis is necessary. It's it increases fitness. 106 00:07:16,480 --> 00:07:21,520 Our job is then to find out why it is not to say that evolution 107 00:07:21,520 --> 00:07:24,800 is making an error that just will not happen. 108 00:07:26,000 --> 00:07:30,040 And so the idea that this that that this aerobic glycolysis is 109 00:07:30,040 --> 00:07:34,560 a dysregulation is, is an error in metabolism and somehow is at 110 00:07:34,560 --> 00:07:37,480 the root of cancer is really kind of missing the point. 111 00:07:38,560 --> 00:07:44,400 And it's interesting to, you know, talk to, to, to 112 00:07:44,440 --> 00:07:49,240 pathologists who who use stains to identify tumor cells, PSMA 113 00:07:49,240 --> 00:07:51,400 stain in, in prostate cancer, for example. 114 00:07:53,400 --> 00:07:57,240 You can then ask why is the PSMA overexpressed? 115 00:07:58,520 --> 00:08:01,240 And it's funny, 'cause it becomes a circular answer. 116 00:08:01,240 --> 00:08:04,840 It's, it's, well, it's because cancer, prostate cancer cells 117 00:08:05,160 --> 00:08:07,560 make it and, and you know, that's how we identify them. 118 00:08:08,280 --> 00:08:12,200 And, and I have to say that no, it's not there for you. 119 00:08:13,200 --> 00:08:17,640 It's there because it's, it's, it's increasing the fitness of 120 00:08:17,640 --> 00:08:20,680 the cancer cell. Your job is to understand then 121 00:08:20,680 --> 00:08:25,200 why PSMA is, is, is increasing the fitness. 122 00:08:26,000 --> 00:08:29,920 It's nice to say that you can use that as a, as a diagnostic 123 00:08:29,920 --> 00:08:32,440 tool. You know, Gatta 3 increased 124 00:08:32,679 --> 00:08:37,320 expression in, you know, as a, as a marker for breast cancer. 125 00:08:37,840 --> 00:08:41,120 But but but it's also evolution telling you this is really 126 00:08:41,120 --> 00:08:45,800 important and that that that connection is often not not 127 00:08:45,800 --> 00:08:49,440 made, I think. Interesting. 128 00:08:49,440 --> 00:08:52,880 So instead of seeing the hallmarks of cancer as static, 129 00:08:52,880 --> 00:08:58,480 dysregulated traits, you instead see them as traits that evolve 130 00:08:58,600 --> 00:09:01,760 to enhance the fitness of the cancer cells in order to allow 131 00:09:01,760 --> 00:09:05,800 them to spread further. Yes, this is evolution's message 132 00:09:05,800 --> 00:09:09,320 to us. Evolution is telling us this is 133 00:09:09,320 --> 00:09:11,880 what's important for cancer. This is what's necessary to 134 00:09:11,880 --> 00:09:14,320 optimize its fitness, which means to optimize its 135 00:09:14,320 --> 00:09:16,960 proliferation. We should listen to evolution 136 00:09:17,280 --> 00:09:21,360 more than we do. And, and you know, we, we talk 137 00:09:21,360 --> 00:09:26,320 about mutations and, and, and clearly if you see mutations in 138 00:09:26,320 --> 00:09:30,080 a lot of the cancer cells, then that's that mutation is 139 00:09:30,080 --> 00:09:33,440 optimizing fitness. But the opposite is also true. 140 00:09:33,760 --> 00:09:37,120 If you don't see mutations in the cancer cell in certain 141 00:09:37,120 --> 00:09:40,800 genes, those genes are necessary for fitness. 142 00:09:41,160 --> 00:09:44,240 And although we always talk about drugging, you know, 143 00:09:44,960 --> 00:09:48,680 mutations, I think, and we have some math models that have 144 00:09:48,680 --> 00:09:52,600 looked at this, is that actually targeting the, the, the genes 145 00:09:52,600 --> 00:09:57,200 that are conserved is probably a more effective way to, to treat 146 00:09:58,240 --> 00:10:02,960 than, than the mutations cause those are unconditionally 147 00:10:02,960 --> 00:10:06,600 necessary for, for optimal cancer cell fitness. 148 00:10:08,040 --> 00:10:10,560 Why do you say that? What does it mean to treat the 149 00:10:10,560 --> 00:10:15,880 genes that are not affected? So what that tells you is that 150 00:10:15,920 --> 00:10:19,640 if, if you assume that all the, all the genes are undergoing 151 00:10:19,680 --> 00:10:25,480 random mutations, they then undergo what we've called 152 00:10:25,480 --> 00:10:29,840 evolutionary triage, meaning that this if, if they increase 153 00:10:29,840 --> 00:10:31,400 fitness, the cell will prophyrate. 154 00:10:32,320 --> 00:10:35,120 If they decrease fitness, the cell will not proliferate. 155 00:10:35,680 --> 00:10:39,640 So over time, what you'll see is that any mutation in that gene 156 00:10:40,040 --> 00:10:44,080 is, is selected out, meaning that evolution is telling you 157 00:10:44,400 --> 00:10:48,480 that that that a mutation in those in that gene decreases 158 00:10:48,480 --> 00:10:51,320 fitness. Evolution does not want that 159 00:10:51,320 --> 00:10:58,040 that gene has to work perfectly. And so attacking that gene is 160 00:10:58,040 --> 00:11:00,200 attacking something that's very important to the cancer. 161 00:11:04,360 --> 00:11:06,720 Right, I see. OK, this this maybe. 162 00:11:06,720 --> 00:11:09,760 Does this feed into some of the atavistic theory of cancer as 163 00:11:09,760 --> 00:11:12,680 well, in terms of attacking some of the weaknesses of cancer 164 00:11:12,680 --> 00:11:14,040 instead of the strengths of cancer? 165 00:11:15,760 --> 00:11:21,360 I, I think it does the, you know, the atavistic theory is 166 00:11:21,360 --> 00:11:27,600 that cancer sort of becomes more primitive and, and there's 167 00:11:27,600 --> 00:11:30,600 something that's slightly pejorative about that, you know, 168 00:11:30,600 --> 00:11:32,360 way of looking at it. Oh, they're primitive self. 169 00:11:33,240 --> 00:11:36,280 In fact, they've evolved to a very high state of fitness. 170 00:11:37,480 --> 00:11:41,640 So, so I sort of admire them. You know, I mean, as, as a, 171 00:11:41,920 --> 00:11:45,600 they're, they're deadly, but beautiful evolutionary 172 00:11:45,600 --> 00:11:48,720 processes. They, they, they can basically 173 00:11:48,720 --> 00:11:50,800 withstand almost anything we can throw at them. 174 00:11:52,240 --> 00:11:57,280 So Atavistics feels like, it's like it's we're, we're 175 00:11:57,440 --> 00:12:04,440 minimizing the, the, the complexity of cancers. 176 00:12:06,680 --> 00:12:10,640 Taking this fitness function forward, is it fair to view that 177 00:12:10,760 --> 00:12:15,080 saying normal cells, there's a degree of cooperation, right, 178 00:12:15,080 --> 00:12:19,160 for them to function? And then the cancer cell, it 179 00:12:19,160 --> 00:12:24,120 becomes this individual cell that starts off as an individual 180 00:12:24,120 --> 00:12:29,560 cell and then it become it. It adapts these functions to 181 00:12:29,560 --> 00:12:32,720 gain cooperation again, but it's a different level of cooperation 182 00:12:32,720 --> 00:12:36,240 now at this point. Yeah, I the the word cooperation 183 00:12:36,240 --> 00:12:41,520 is so is so anthropomorphic that it's it's it's I think you have 184 00:12:41,520 --> 00:12:46,960 to be careful about using that the the evolutionary biologists 185 00:12:46,960 --> 00:12:51,880 tend to use the word mutualism or something like herd effects. 186 00:12:51,880 --> 00:12:55,400 So for example, herd effects being I guess the most obvious 187 00:12:55,640 --> 00:13:00,080 one where you know these animals individually are the are the 188 00:13:00,080 --> 00:13:04,720 unit of selection. But groups of animals can act in 189 00:13:04,720 --> 00:13:12,320 a way that protects them all. And so groups of cancer cells 190 00:13:12,320 --> 00:13:15,880 need to have at least a loose affiliation to to work. 191 00:13:15,880 --> 00:13:20,560 So, for example, to be cancer cells need blood vessels, but 192 00:13:20,560 --> 00:13:24,960 it's probable that one cancer cell cannot produce enough 193 00:13:25,640 --> 00:13:29,680 angiogenic, you know, molecules to to to bring those in. 194 00:13:29,680 --> 00:13:31,880 So, so the whole group has to do it. 195 00:13:33,640 --> 00:13:35,480 Now then there's cheating that can occur. 196 00:13:35,480 --> 00:13:39,920 So you can that, you know, a someone in in this group can 197 00:13:40,040 --> 00:13:44,360 that's getting blood vessels in can decide not to have not to 198 00:13:44,360 --> 00:13:47,800 make GEDF, for example. And so now it's getting the 199 00:13:47,800 --> 00:13:51,160 benefit of the group, but not giving, you know, paying, not 200 00:13:51,160 --> 00:13:57,600 paying its, its due cost. And, and so these are, these can 201 00:13:57,600 --> 00:14:02,680 be very complicated dynamics, but, but the word cooperation, 202 00:14:03,240 --> 00:14:06,680 the, the word cooperation implies sentience, you know, 203 00:14:06,680 --> 00:14:08,880 that there's some thinking that's going on. 204 00:14:09,360 --> 00:14:13,040 And I think we should, I, I tend to like to avoid that. 205 00:14:14,240 --> 00:14:17,680 One of the things that, that I've noticed in working with 206 00:14:17,680 --> 00:14:21,480 oncologists is that there's almost a tendency to think 207 00:14:21,480 --> 00:14:25,240 magically about the cancer that somehow it can, it's, it's, 208 00:14:25,560 --> 00:14:28,000 these are plotting against you and they, and they, you know, 209 00:14:28,000 --> 00:14:31,320 has a remarkable capacity to overcome your therapy. 210 00:14:31,760 --> 00:14:34,280 And, and they said there must be some inherent evil in it. 211 00:14:34,480 --> 00:14:40,280 And, and I, I think it's, it's, it's more mundane than that, but 212 00:14:40,280 --> 00:14:43,000 it's not playing. They're not sitting down there, 213 00:14:43,000 --> 00:14:45,600 you know, like, Gee, what let's, how can I get around this? 214 00:14:46,440 --> 00:14:49,160 But they are extraordinarily powerful because they have the 215 00:14:49,160 --> 00:14:54,760 whole human genome to to bring to bear on whatever evolutionary 216 00:14:54,760 --> 00:14:59,680 problem they face. Mike, you often talk about 217 00:15:00,200 --> 00:15:05,440 cancer as dissociating from the collective behavior of cells or 218 00:15:05,440 --> 00:15:08,280 the tumor cells. So what are your thoughts here 219 00:15:08,280 --> 00:15:11,800 with the herd behavior and evolutionary processes? 220 00:15:12,600 --> 00:15:15,240 I have a couple of, a couple of things to to talk about. 221 00:15:15,640 --> 00:15:19,160 I think, I think one thing I'd love to dig into a little more 222 00:15:19,160 --> 00:15:22,960 is the, the notion of, of stress initiating these processes. 223 00:15:23,640 --> 00:15:28,720 And you know, there's a, there's a particular kind. 224 00:15:28,720 --> 00:15:30,280 And so you mentioned tissue level stress. 225 00:15:30,280 --> 00:15:33,000 And so it was one of my favorite examples from our developmental 226 00:15:33,000 --> 00:15:36,400 biology world is this old, old finding that when you take a, 227 00:15:36,400 --> 00:15:40,560 when you take a tail of a of a Newt and you graft it to the 228 00:15:40,560 --> 00:15:43,760 flank, to the side, the thing turns into a limb. 229 00:15:44,080 --> 00:15:47,160 And if you look at the cells at the very end of the tail, 230 00:15:47,600 --> 00:15:50,440 they're tail tip cells sitting at the end of a tail. 231 00:15:50,440 --> 00:15:52,520 There's nothing locally wrong. Nobody's poisoned, nobody's 232 00:15:52,520 --> 00:15:55,240 damaged. And yet they completely remodel 233 00:15:55,920 --> 00:15:57,560 this. You know, the, the issue isn't 234 00:15:57,560 --> 00:16:00,000 that the cell level, it's at a much, it's at a much higher 235 00:16:00,000 --> 00:16:02,960 level, but then filters down and makes the molecular biology 236 00:16:02,960 --> 00:16:05,880 dance to this, to this, to this higher level of error. 237 00:16:06,360 --> 00:16:10,480 So, so my question is, what typically do you think that 238 00:16:10,480 --> 00:16:14,320 cells are measuring that leads them to be unhappy enough to 239 00:16:14,320 --> 00:16:17,680 break the multicellularity contract and say, you know what, 240 00:16:17,680 --> 00:16:20,080 this isn't working out for me. I'm going on my own like, what's 241 00:16:20,080 --> 00:16:22,240 the, what is it? Is it metabolic? 242 00:16:22,240 --> 00:16:24,240 Is it like what, what usually triggers this stuff? 243 00:16:24,240 --> 00:16:27,200 And do we know? It's a great question because 244 00:16:27,800 --> 00:16:31,400 I'm not really sure. I mean, and, and we've, we've 245 00:16:31,400 --> 00:16:34,960 talked about this a little bit. I mean, the, the, there's this 246 00:16:34,960 --> 00:16:39,160 tendency to, to think about diffusing hormones and diffusing 247 00:16:39,160 --> 00:16:43,600 signaling molecules and, and receptors and things that seems 248 00:16:44,400 --> 00:16:49,440 to be nowhere near enough to, to, to, to, to get the level of 249 00:16:49,440 --> 00:16:51,840 complexity that you see in cells. 250 00:16:51,840 --> 00:16:54,840 I mean, they, they in tissue. I mean, it's not, it's their 251 00:16:54,840 --> 00:16:57,160 location, it's their phenotype. I mean, there's this 252 00:16:57,240 --> 00:17:01,240 extraordinary synchronization of all this. 253 00:17:03,240 --> 00:17:08,079 I, I tend to think that and, and Mike, we've, we've talked about 254 00:17:08,079 --> 00:17:12,640 this, that, that, that, that actually we're missing the a key 255 00:17:14,560 --> 00:17:17,160 information dynamic in, in cells. 256 00:17:17,160 --> 00:17:20,560 And that is the I, I, I guess you would probably call it 257 00:17:20,560 --> 00:17:23,720 electricity. I I would maybe say ions that 258 00:17:23,720 --> 00:17:30,040 there's communication that goes on that's not genetic that that 259 00:17:30,240 --> 00:17:34,320 is and that is fundamentally important. 260 00:17:34,320 --> 00:17:39,520 I, I think it was, I don't, no, if you remember this, this era, 261 00:17:39,520 --> 00:17:43,800 but when the human genome was, was being deciphered, there was 262 00:17:43,800 --> 00:17:50,000 a, a, a, a contest and there was a, this was a around the world. 263 00:17:50,400 --> 00:17:52,880 Scientists from over the world could put in. 264 00:17:53,840 --> 00:17:56,680 They would bet it was a, a pool. And in fact, I think it was 265 00:17:56,680 --> 00:18:01,560 called the gene pool. And they, they put in, each of 266 00:18:01,560 --> 00:18:05,440 them put in, I don't know, $20 and they bet what the number of 267 00:18:05,440 --> 00:18:09,200 human, how many genes would be in the human genome. 268 00:18:10,920 --> 00:18:17,480 And four or 500 scientists across the world took part in 269 00:18:17,480 --> 00:18:19,480 this. And basically none of them are 270 00:18:19,480 --> 00:18:22,640 right. The, the, the, they, they 271 00:18:22,640 --> 00:18:29,120 measure the, the mean estimate was about I think 6070 thousand 272 00:18:29,120 --> 00:18:31,640 genes. Upper ranges were in the 273 00:18:31,640 --> 00:18:36,280 300,000, the lowest was 27,000 and the number is it's under 274 00:18:36,280 --> 00:18:42,120 20,000. And so David Baltimore wrote in 275 00:18:42,640 --> 00:18:47,080 a, a, an editorial with with in that I think it was, I think it 276 00:18:47,080 --> 00:18:51,960 was published in Nature and said we need to understand this. 277 00:18:52,120 --> 00:18:55,200 You know, if we believe that we are the most complex of the 278 00:18:55,200 --> 00:18:59,480 organisms on earth, why is our genome smaller than that of a 279 00:18:59,480 --> 00:19:03,880 mouse? And, and I, I think the argument 280 00:19:04,200 --> 00:19:07,680 I would have is that it's because the genome only 281 00:19:07,680 --> 00:19:12,680 indirectly controls the information dynamics. 282 00:19:12,960 --> 00:19:18,960 It sets up the, the dynamics that are based on ion conduction 283 00:19:18,960 --> 00:19:25,280 and on electricity flow that really are at the, at the basis 284 00:19:25,280 --> 00:19:30,520 of complexity and of these interactions among cells. 285 00:19:30,720 --> 00:19:35,520 And you know, one of the, what to me is interesting is that 286 00:19:37,160 --> 00:19:41,520 that our cells have tremendous transmembrane ion gradients. 287 00:19:42,360 --> 00:19:47,760 They're they're enormous. And mammalian cells spend about 288 00:19:47,760 --> 00:19:51,440 a third of their energy budget maintaining these, which is 289 00:19:51,440 --> 00:19:53,800 about as much as they use maintaining the genome. 290 00:19:54,960 --> 00:19:58,680 Now you know, if you remember the Watergate thing, you know 291 00:19:58,680 --> 00:20:02,280 you follow the money. And I think in evolution, you 292 00:20:02,280 --> 00:20:06,320 follow the energy. What evolution is telling you is 293 00:20:06,320 --> 00:20:10,400 that this transmembrane ion gradient is really important. 294 00:20:10,760 --> 00:20:15,360 It's so important that it, it devotes A tremendous fraction of 295 00:20:15,360 --> 00:20:19,520 its annual of its energy budget. And yet we know no reason for 296 00:20:19,520 --> 00:20:21,560 that. I mean, there it, it, it serves 297 00:20:21,560 --> 00:20:25,720 no apparent purpose in the current sort of understanding of 298 00:20:25,720 --> 00:20:28,640 biology. And, and what I think is that 299 00:20:28,640 --> 00:20:36,080 that's a tremendous a gradient of information and, and cells 300 00:20:36,080 --> 00:20:40,640 interact with each other at opening ion pores, which allows 301 00:20:40,640 --> 00:20:47,080 flux of ions across the these gradients and those fluxes are 302 00:20:47,080 --> 00:20:52,880 information. And that another interesting, 303 00:20:52,880 --> 00:20:57,600 you know, factoid is that elements of the cytoskele are 304 00:20:57,600 --> 00:21:01,160 tremendous ion conductors. I mean, they're really, really 305 00:21:01,160 --> 00:21:02,240 good. I mean, they, they're, they're 306 00:21:02,240 --> 00:21:07,160 described as living wires. Why is that the case? 307 00:21:07,160 --> 00:21:10,360 And, and, and, and you know, again, there should be a purpose 308 00:21:10,360 --> 00:21:14,000 to that evolution doesn't do things with no purpose. 309 00:21:14,680 --> 00:21:19,720 And, and I think that that is, is sort of a kind of wiring that 310 00:21:19,800 --> 00:21:24,160 of that allows ion flows across the cell to communicate within 311 00:21:24,160 --> 00:21:27,800 the cell. And then I think Mike does a lot 312 00:21:27,800 --> 00:21:31,440 of work without cells communicate among themselves, 313 00:21:32,800 --> 00:21:38,520 all of which is through ions kind of connectivity and stuff. 314 00:21:38,920 --> 00:21:40,600 There's, there's no genetics in that. 315 00:21:40,600 --> 00:21:46,480 The, the, the genes set up, the, the dynamics that allows the, 316 00:21:46,520 --> 00:21:48,640 they, they make the pumps, they make the pores. 317 00:21:48,640 --> 00:21:55,400 And this, this is necessary for this other information dynamic, 318 00:21:55,400 --> 00:21:59,200 but I think it's an information dynamic that has been sort of 319 00:21:59,200 --> 00:22:03,600 missed over the, the years, or at least it's hinted at, but 320 00:22:03,600 --> 00:22:07,240 not, or, or let's say it's not, not necessarily in the 321 00:22:07,240 --> 00:22:12,480 mainstream of biology. And, and I, and so I, I think 322 00:22:12,480 --> 00:22:15,960 that to understand multicellularity and multicent 323 00:22:16,360 --> 00:22:20,080 and complexity, I think we need to invoke a different 324 00:22:20,400 --> 00:22:26,440 information dynamic, you know, going beyond the genome. 325 00:22:27,280 --> 00:22:29,880 Yeah, yeah, for sure. Do you want to talk a little bit 326 00:22:29,880 --> 00:22:34,320 about your, your recent paper on the, on the computations in the 327 00:22:35,320 --> 00:22:38,080 in the networks within cells, I thought was was incredibly 328 00:22:38,080 --> 00:22:39,520 interesting. Do you want to talk about that a 329 00:22:39,520 --> 00:22:42,160 little bit? Well, it really goes to that. 330 00:22:42,200 --> 00:22:48,360 That idea is that, and, and I, I don't know if it, it may be 331 00:22:48,600 --> 00:22:50,880 going off the deep end here, but there's something called 332 00:22:50,880 --> 00:22:54,720 Maxwell's demon. And if you're familiar with 333 00:22:54,720 --> 00:23:00,520 that, Maxwell proposed this Pedonkan immunity thought 334 00:23:00,520 --> 00:23:03,640 experiment. This was in the, the mid to late 335 00:23:03,840 --> 00:23:07,960 19th century and is when thermodynamics and both Swan 336 00:23:08,240 --> 00:23:11,080 kinetics were being discovered sort of simultaneously. 337 00:23:11,640 --> 00:23:15,360 And what he said was that suppose you, you have a, you 338 00:23:15,360 --> 00:23:18,960 have two boxes with gases at the same temperature and there's a, 339 00:23:19,040 --> 00:23:23,880 there's a hole between them with a gate and a demon sits there. 340 00:23:24,320 --> 00:23:27,560 And because the temperature that because in, in any given 341 00:23:27,560 --> 00:23:30,160 temperature, you have this Boltzmann distribution of 342 00:23:30,160 --> 00:23:34,080 velocities. And what he said the, the demon 343 00:23:34,080 --> 00:23:38,880 would open the, the gate if, if, if, if a high velocity molecule 344 00:23:38,880 --> 00:23:41,920 was, was coming toward it and close it otherwise. 345 00:23:42,160 --> 00:23:45,200 So essentially what he did was to shift all of the high 346 00:23:45,200 --> 00:23:49,040 velocity molecules to 1 box and the low velocity molecules to 347 00:23:49,040 --> 00:23:52,640 the to the other. And basically, so this one box 348 00:23:52,640 --> 00:23:55,760 would be hotter than the other. It would look like a spontaneous 349 00:23:55,760 --> 00:24:00,600 flow of heat in isothermal between two systems of the same 350 00:24:00,600 --> 00:24:02,680 temperature. It's also a spontaneous 351 00:24:02,680 --> 00:24:08,880 reduction in entropy. And he said this, he viewed this 352 00:24:08,880 --> 00:24:12,000 as a as a violation of the second law of thermodynamics. 353 00:24:12,360 --> 00:24:16,720 And it's been controversial ever since, but what it gave rise to 354 00:24:16,720 --> 00:24:19,960 in the wake in the early 20th century is information theory, 355 00:24:20,200 --> 00:24:22,600 because what they said is the demon has information. 356 00:24:23,480 --> 00:24:26,000 And so that's become sort of a, a, a link. 357 00:24:28,800 --> 00:24:33,840 And there's what, So the, the, the ion gradient across the cell 358 00:24:33,840 --> 00:24:38,160 membrane is similar to what the, what the, what the demon does, 359 00:24:38,160 --> 00:24:44,800 but in with, with velocities. And what, what was really never 360 00:24:44,800 --> 00:24:48,040 appreciated is the fact that you, once the demon has set up 361 00:24:48,040 --> 00:24:54,000 this gradient, you can have, you know, Maxwell's angels that can 362 00:24:54,000 --> 00:24:57,440 sit on the, on the looking out for information coming from the, 363 00:24:59,240 --> 00:25:02,640 the environment. And they can open a gate And now 364 00:25:03,040 --> 00:25:07,680 ions can flow down the this gate look according to the gradient 365 00:25:07,680 --> 00:25:09,240 and that is a flux of information. 366 00:25:10,560 --> 00:25:17,400 And so I, I think that's an important part of the, of, of 367 00:25:17,400 --> 00:25:19,560 how cells interrogate their environment. 368 00:25:20,360 --> 00:25:26,800 And now the, the, the, the gross part of this at a, so there's 369 00:25:26,800 --> 00:25:31,120 this molecular level difference. These are the ion gradients, but 370 00:25:31,440 --> 00:25:37,320 they, they converge to make a transmembrane potential. 371 00:25:38,360 --> 00:25:45,120 And, and this is this is at the border of ions. 372 00:25:45,720 --> 00:25:51,880 And so you have this molecular level dynamic and you have this 373 00:25:51,960 --> 00:25:56,360 bigger scale dynamic. And for, for, for Maxwell's 374 00:25:56,840 --> 00:26:01,440 demon, it was really the gas molecules and the as, as 375 00:26:01,600 --> 00:26:06,320 changing the Boltzmann kinetics of each of the chambers, but 376 00:26:06,320 --> 00:26:09,920 manifesting as a thermodynamic change. 377 00:26:10,160 --> 00:26:16,760 That, that I think that that intersection of, of, of 378 00:26:16,760 --> 00:26:21,160 microstates and macrostates is kind of where information works. 379 00:26:22,440 --> 00:26:26,560 In this case, the, the information from the, from the 380 00:26:26,560 --> 00:26:30,560 genome pumps the ions against the gradient using it, using 381 00:26:30,560 --> 00:26:33,880 energy. You know, again, there's got to 382 00:26:33,880 --> 00:26:36,160 be a reason for that. And I, I think what you can 383 00:26:36,400 --> 00:26:40,600 calculate the amount of information within that by 384 00:26:40,600 --> 00:26:46,600 Shannon information criteria and it's enormous. 385 00:26:47,560 --> 00:26:50,720 It's it's orders of magnitude greater than the information 386 00:26:50,720 --> 00:26:57,160 content of the genome. Yeah, yeah. 387 00:26:58,600 --> 00:27:01,680 You know, another, another interesting thing that you were 388 00:27:01,680 --> 00:27:06,160 mentioning before about aging and we, we have this, we have 389 00:27:06,160 --> 00:27:08,600 this new. So, so I think it might be, it 390 00:27:08,600 --> 00:27:12,840 might be relevant to this, this, this new, new work where, you 391 00:27:12,840 --> 00:27:15,520 know, we, we, we look at, at morphogenesis as a kind of 392 00:27:17,240 --> 00:27:21,080 homeostatic process which tries to minimize error from a, from a 393 00:27:21,080 --> 00:27:25,400 certain setpoint. And we did this simulation where 394 00:27:26,200 --> 00:27:31,080 we looked at what happens to to this goal seeking system in the 395 00:27:31,080 --> 00:27:34,160 cybernetic sense, right? What happens to that system 396 00:27:34,160 --> 00:27:37,560 after it has completed its goal? What was it due after that? 397 00:27:37,920 --> 00:27:42,800 And what we found is that in the absence of any additional noise, 398 00:27:42,880 --> 00:27:47,840 thermodynamic, you know, the damage, no entropic stuff at 399 00:27:47,840 --> 00:27:50,560 all. Even without all of that stuff, 400 00:27:51,000 --> 00:27:54,400 what the morphogenetic system does is it, it, it reaches its 401 00:27:54,400 --> 00:27:56,040 goal and it builds a nice pattern. 402 00:27:56,040 --> 00:27:58,560 So there's your embryo and then it hangs out for a while. 403 00:27:59,200 --> 00:28:02,800 And then, and then the cells start to, it starts to disband. 404 00:28:03,120 --> 00:28:05,760 The cells start to go off and do different things because that, 405 00:28:05,760 --> 00:28:09,480 that, that pressure to keep to, to a like to upkeep a specific 406 00:28:09,480 --> 00:28:11,840 morphology is no longer there. They've sort of done it. 407 00:28:11,840 --> 00:28:15,000 And now what? And mission accomplished. 408 00:28:15,000 --> 00:28:18,360 And, and that, and, and, and it, you know, this, it's, it's sort 409 00:28:18,360 --> 00:28:22,440 of my of, of, of a scheme that I've, that I've been developing 410 00:28:22,440 --> 00:28:24,760 on this idea that these, the goals are what keep collective 411 00:28:24,760 --> 00:28:27,520 intelligences together. And that after that goal is no 412 00:28:27,520 --> 00:28:31,760 longer active, it they just, they just start to, to go off 413 00:28:31,760 --> 00:28:34,680 and, and do theirs, their, they go their separate ways in the 414 00:28:34,680 --> 00:28:37,400 absence of any external damage. You know, it's a, it's a 415 00:28:37,560 --> 00:28:39,080 fundamentally A cognitive problem. 416 00:28:39,080 --> 00:28:41,680 It's not a, it's not a, you know, a, a thermodynamic 417 00:28:41,680 --> 00:28:43,760 problem. And even that's even there. 418 00:28:44,080 --> 00:28:47,120 And, and then you start thinking, well, what happens to 419 00:28:47,120 --> 00:28:50,880 what, how, how do, how do immortal animals deal with this? 420 00:28:50,880 --> 00:28:54,880 Well, Planaria, who are both extremely cancer resistant and, 421 00:28:55,080 --> 00:28:57,320 and ageless and highly regenerative. 422 00:28:57,680 --> 00:29:00,920 They tear themselves in half every two weeks and they sort of 423 00:29:00,920 --> 00:29:03,880 refresh this, this thing, you know, they don't have a chance 424 00:29:03,880 --> 00:29:06,880 to sort of settle down and, and wonder what to do next because 425 00:29:07,080 --> 00:29:10,280 they, they have this right, like radical damage event every that 426 00:29:10,280 --> 00:29:12,320 they caused themselves every every couple of weeks. 427 00:29:12,760 --> 00:29:15,880 And that seems to be enough to keep them rolling. 428 00:29:15,880 --> 00:29:18,480 And so I just wonder, you know, this in the connection between 429 00:29:19,200 --> 00:29:22,200 aging and cancer and everything that's like, you know, what, 430 00:29:22,200 --> 00:29:25,720 what do you think as part of the part like a stressor can be? 431 00:29:25,720 --> 00:29:30,600 And we, we all know people who they, they, they retire and they 432 00:29:30,600 --> 00:29:33,160 don't know what to do. And then the things things go 433 00:29:33,160 --> 00:29:35,720 poorly after that, right? So it seems like that's a whole 434 00:29:35,720 --> 00:29:37,840 other new kind of stress. It's not like there's anything 435 00:29:37,840 --> 00:29:41,760 happening to you. It's that the goal setting is 436 00:29:41,760 --> 00:29:46,080 kind of gone, you know? Maybe that's where exercise is 437 00:29:46,320 --> 00:29:50,440 creating these sort of micro stresses, keeps us alert, keeps 438 00:29:50,480 --> 00:29:52,880 your body, keeps your cells in the game. 439 00:29:54,520 --> 00:29:59,440 But one of the interesting things that I've been sort of 440 00:29:59,440 --> 00:30:05,320 thinking about is that the, the information in a, in a gene is 441 00:30:05,320 --> 00:30:09,640 translated into a, a string of amino acids that can do 442 00:30:09,640 --> 00:30:12,720 precisely nothing until it folds. 443 00:30:13,360 --> 00:30:18,920 But that folding process is non it, it is, there's a, there's a, 444 00:30:19,680 --> 00:30:21,560 it's almost a, a probability matrix. 445 00:30:21,560 --> 00:30:23,600 There is, it can fold into a number of different 446 00:30:23,600 --> 00:30:28,280 configurations. And because of that, there's 447 00:30:28,280 --> 00:30:31,520 actually information gain in the folding process. 448 00:30:31,520 --> 00:30:35,200 And I, I don't, I'm not sure we've sort of understood that. 449 00:30:35,200 --> 00:30:41,000 But what's interesting then is that proteins for proteins that 450 00:30:41,000 --> 00:30:46,960 form enzymes, for example, are, are fine graining because they 451 00:30:46,960 --> 00:30:51,000 act at a quantum level. But they, they, they're what 452 00:30:51,000 --> 00:30:54,480 they do is they, the substrate, half the, the quantum 453 00:30:54,480 --> 00:30:57,640 interactions of the substrate need to be optimized to make 454 00:30:57,640 --> 00:31:04,120 this, this the enzyme work and which and and so, and fine 455 00:31:04,120 --> 00:31:08,920 graining requires information. And it, it, it's occurred to me 456 00:31:08,920 --> 00:31:16,400 that this, that the, the, the, the way life does this is that 457 00:31:16,400 --> 00:31:18,960 is the protein folding that, that going from one dimension to 458 00:31:18,960 --> 00:31:24,480 3 dimensions in a sort of predictable way provides an, an 459 00:31:24,480 --> 00:31:28,960 information gain. And I wonder if some of multi 460 00:31:28,960 --> 00:31:33,880 cellular organisms have that same kind of process where the 461 00:31:33,880 --> 00:31:36,600 cells you you have essentially a point source in in in the sense 462 00:31:36,600 --> 00:31:39,440 of the the cell is a point source as it proliferates. 463 00:31:39,880 --> 00:31:43,000 The interactions among the different cells are sufficiently 464 00:31:43,000 --> 00:31:48,280 predictable somehow in this in this in this fertilized egg. 465 00:31:49,360 --> 00:31:53,400 The information content is then sort of magnified, is increased 466 00:31:53,400 --> 00:31:57,600 by these interactions, these non random distributions of the 467 00:31:57,600 --> 00:32:02,040 cells so that the the the collective information of a 468 00:32:02,040 --> 00:32:05,360 multi Organism, which is vastly greater than that of a single 469 00:32:05,360 --> 00:32:11,840 cell is gained by these these dimensionality changes. 470 00:32:12,880 --> 00:32:17,680 It's kind of hard to explain that, I guess, but it, it does 471 00:32:17,800 --> 00:32:23,800 it, it feels like biological information is not as simple, I 472 00:32:23,800 --> 00:32:28,120 think as we well, I mean, everybody's the biological 473 00:32:28,120 --> 00:32:31,080 information is in the genome of of so great. 474 00:32:31,720 --> 00:32:35,440 How do you go from genetic information to the thermodynamic 475 00:32:35,440 --> 00:32:39,120 state of the cell, which is a, which is a highly, you know, 476 00:32:39,160 --> 00:32:43,960 highly ordered low entropy, but far from thermodynamic 477 00:32:44,000 --> 00:32:45,680 equilibrium state? It's extraordinary. 478 00:32:45,680 --> 00:32:48,040 There's nothing in the universe like that. 479 00:32:49,520 --> 00:32:52,600 Intuitively, it seems clear the genetic information does that, 480 00:32:53,200 --> 00:32:57,600 but to me it's not clear how you go from genetic information 481 00:32:57,880 --> 00:33:02,120 quantified incidentally by bits. So there's no physical unit in 482 00:33:02,120 --> 00:33:06,480 that to thermodynamics, which is of course quantified by the the 483 00:33:06,480 --> 00:33:08,560 typical units of thermodynamics. You don't. 484 00:33:08,560 --> 00:33:10,720 You don't have unit matching in this. 485 00:33:12,960 --> 00:33:15,200 Yeah. I mean they do you know they 486 00:33:15,280 --> 00:33:20,120 there there is there is some some theory around that what 487 00:33:20,120 --> 00:33:22,520 bits like the minimal cost of a bit, right. 488 00:33:22,520 --> 00:33:24,720 The the Bennett stuff and and all the land hour and all that. 489 00:33:25,160 --> 00:33:28,280 But I think, you know, the bigger I, I think the bigger 490 00:33:28,280 --> 00:33:31,880 issue with, with the genome is that it's information about the 491 00:33:31,880 --> 00:33:34,200 hardware. And as you pointed out, it's, 492 00:33:34,200 --> 00:33:37,000 it's some very cool reprogrammable hardware that it 493 00:33:37,000 --> 00:33:38,920 encodes. And after that, you know, 494 00:33:38,920 --> 00:33:41,240 there's only so much you can, you know, you can blame on the 495 00:33:41,240 --> 00:33:42,840 hardware itself. There's a lot of the 496 00:33:43,080 --> 00:33:45,440 physiological dynamics afterwards that that are the 497 00:33:45,440 --> 00:33:48,440 main show I think. It's, it's, it's magnificent. 498 00:33:48,680 --> 00:33:52,960 It's an extraordinary thing. And as I said, I think there's 499 00:33:52,960 --> 00:33:57,520 a, there's, there's the, the I'm, I've become interested in 500 00:33:57,520 --> 00:34:01,480 the idea of dimensionality, you know, the, the linear, the 501 00:34:01,480 --> 00:34:04,800 linear string of the DNA folding into a three-dimensional 502 00:34:05,080 --> 00:34:09,920 configuration, a a single sort of point source of as a 503 00:34:11,480 --> 00:34:15,920 fertilized egg turning into a, you know, large 3 dimensional, 504 00:34:16,560 --> 00:34:22,000 you know, structure. There's, there's, there's those 505 00:34:22,000 --> 00:34:27,159 rules may be similar. I I think and the changing 506 00:34:27,159 --> 00:34:35,719 dimensionality may have it may it may be a it where how life 507 00:34:35,719 --> 00:34:40,280 exploits the limited information that comes from the genome to, 508 00:34:40,280 --> 00:34:44,120 to generate these, you know, highly large and complex, you 509 00:34:44,120 --> 00:34:48,239 know, organisms. Yeah, and that and that's just 510 00:34:48,239 --> 00:34:51,760 in 3D like in 3D space, right you so you so you also get 511 00:34:51,920 --> 00:34:55,360 structures in, in physiological state space and transcriptional 512 00:34:55,360 --> 00:34:58,040 state space got only your metabolic like who knows like 513 00:34:58,040 --> 00:34:59,800 there are all these different spaces, right that it's 514 00:34:59,800 --> 00:35:04,480 unfolding into. And then I mean to, to get like 515 00:35:04,560 --> 00:35:08,280 really wild, you could say, well, what is the, what's the 516 00:35:08,280 --> 00:35:12,680 human mind, which is, which is also sort of unique in nature. 517 00:35:14,400 --> 00:35:18,320 You could argue, I think that what evolution is going to 518 00:35:18,320 --> 00:35:22,960 select for things that allow you to live longer or to survive or 519 00:35:22,960 --> 00:35:25,880 to proliferate. There's no evolutionary 520 00:35:25,880 --> 00:35:30,600 selection, you know, to figure out the stars or to, you know, 521 00:35:31,480 --> 00:35:36,120 engage in quantum mechanics. There's no it it, it exceeds 522 00:35:36,120 --> 00:35:38,680 what evolution would have selected. 523 00:35:39,360 --> 00:35:43,480 And you know, my kind of armchair and speculation, which 524 00:35:43,480 --> 00:35:49,040 I'll deny ever, ever saying, including saying that this, this 525 00:35:49,040 --> 00:35:56,640 whole broadcast was a hoax, is that is that we have a we, we 526 00:35:57,040 --> 00:36:02,040 recognize an additional dimension time, that our ability 527 00:36:02,040 --> 00:36:07,680 to work in the dimension of time adds A dimensionality change 528 00:36:08,000 --> 00:36:12,800 which allows us to access information that would not 529 00:36:12,800 --> 00:36:18,000 ordinarily be present in strictly 3 dimensional 530 00:36:18,000 --> 00:36:20,440 structures. Again, you can. 531 00:36:20,880 --> 00:36:29,600 I'll deny I ever said that. Going back to information 532 00:36:29,600 --> 00:36:32,480 dynamics, I guess, how do you think about information dynamics 533 00:36:32,480 --> 00:36:36,320 for a cancer cell then compared to healthy cell? 534 00:36:38,000 --> 00:36:41,320 Well, I think there's two components to to this. 535 00:36:42,680 --> 00:36:47,760 The healthy cells, you know, are really tuned into their 536 00:36:47,760 --> 00:36:50,120 environment and to the other cells in the environment. 537 00:36:50,120 --> 00:36:52,800 They're they're, they're tuned into this collective. 538 00:36:52,880 --> 00:36:56,880 I I think might use the term cancer cells have to be 539 00:36:56,880 --> 00:37:01,080 independent of these of these control mechanisms. 540 00:37:01,600 --> 00:37:08,040 At the same time, cancer cells have to be able to forage, they 541 00:37:08,040 --> 00:37:13,200 have to be able to detect sources of of substrate and they 542 00:37:13,200 --> 00:37:16,120 also have to detect bad environments. 543 00:37:16,200 --> 00:37:20,720 And probably ideally they have to detect predators like like 544 00:37:20,720 --> 00:37:23,960 the immune system. So the information dynamics 545 00:37:23,960 --> 00:37:30,000 change and and that's where, you know, I think that calling them 546 00:37:30,000 --> 00:37:32,560 atavistic is, is is sort of insulting to them. 547 00:37:33,080 --> 00:37:39,640 You know, they've they they are extremely fine-tuned to optimize 548 00:37:39,640 --> 00:37:41,920 their proliferation in the middle of your body. 549 00:37:42,880 --> 00:37:48,040 And and that's often not a very, you know, good, good place to 550 00:37:48,040 --> 00:37:50,840 be. I mean, some, some of them, they 551 00:37:50,840 --> 00:37:53,160 grow in the lymph nodes where the it's, it's that's like 552 00:37:53,360 --> 00:37:56,360 robbing from a police station. They the, you know, the whole 553 00:37:56,360 --> 00:37:58,960 immune system is around them and yet they continue to grow. 554 00:37:59,520 --> 00:38:03,720 So they need sophisticated information next. 555 00:38:03,720 --> 00:38:08,680 But these are different from what I think normal mammalian 556 00:38:08,680 --> 00:38:12,720 cells have. But they what, what's I think is 557 00:38:12,720 --> 00:38:16,800 really important to cancer is that the, you know, normal 558 00:38:16,960 --> 00:38:20,040 mammalian cells a, a lot of the genome is, is blocked. 559 00:38:20,520 --> 00:38:23,560 You know, they, they don't have access to a lot of the gene 560 00:38:23,840 --> 00:38:27,280 cancer seems to be able to access the whole human genome. 561 00:38:27,280 --> 00:38:30,880 So they, they find things that were the genes that were being 562 00:38:30,880 --> 00:38:37,000 expressed in, in the fetus that, you know, just weren't expressed 563 00:38:37,000 --> 00:38:39,120 in adults, but now, but they can use that. 564 00:38:39,120 --> 00:38:47,520 So they, they, they find ways to, to, to evolve and to 565 00:38:47,720 --> 00:38:52,240 optimize their fitness using parts of the genome that 566 00:38:52,280 --> 00:38:55,440 ordinarily are not accessible. And, and I, I think it's 567 00:38:55,440 --> 00:39:02,080 remarkably clever and, and really scary because they're 568 00:39:02,080 --> 00:39:06,960 really good at it. But I suppose from an 569 00:39:06,960 --> 00:39:11,520 evolutionary perspective, I mean, evolution would obviously 570 00:39:11,520 --> 00:39:15,320 want us to reproduce and live as long and pass on our genes. 571 00:39:15,760 --> 00:39:19,320 So the information that it would pass to us would be the ones 572 00:39:19,320 --> 00:39:23,800 that normal healthy cells have. Where do you think cancer cells 573 00:39:23,800 --> 00:39:26,680 are acquiring this information per SE? 574 00:39:26,680 --> 00:39:30,680 Or, or do you say maybe it's it's the fact that evolution has 575 00:39:30,680 --> 00:39:34,680 just programmed us for fitness and cancer cells just have this 576 00:39:34,680 --> 00:39:37,960 ability to figure out whatever is needed in order to 577 00:39:37,960 --> 00:39:42,560 proliferate? Well, I, I think, you know, 578 00:39:42,560 --> 00:39:45,280 after you've reproduced, and I'm sorry, I know you have a, a new 579 00:39:45,280 --> 00:39:49,160 baby at home, but after you've reproduced, nature would rather 580 00:39:49,160 --> 00:39:52,360 you were dead. I mean, and, and of course 581 00:39:52,360 --> 00:39:55,360 there's, I mean, there's the, the, the whole grandmother 582 00:39:55,360 --> 00:40:01,560 hypothesis and various things that are, are, are, you know, 583 00:40:01,560 --> 00:40:05,840 that, that produce the offs that increase fitness of offspring. 584 00:40:06,360 --> 00:40:11,120 But basically, if you're a man at my age, you know, evolution 585 00:40:11,160 --> 00:40:16,600 would rather I just drop dead because in fact, that's why I 586 00:40:16,600 --> 00:40:19,160 exercise, because I'm trying to convince my body that I'm still 587 00:40:19,160 --> 00:40:25,520 part of the hunt. And it'll let me live but but I, 588 00:40:25,600 --> 00:40:27,240 but I think that's a really important point. 589 00:40:27,240 --> 00:40:32,360 There's, there's no evolutionary selection for anti cancer 590 00:40:33,680 --> 00:40:37,800 mechanisms beyond the sort of reproductive age. 591 00:40:38,080 --> 00:40:43,960 And we live far longer than our reproductive age, unlike I think 592 00:40:44,440 --> 00:40:48,640 most animals. And so I, I, there's, there's 593 00:40:48,640 --> 00:40:53,280 unfortunately no selection for people that get cancer in their 594 00:40:53,280 --> 00:40:56,200 60s and 70s. It's, it's just because we've 595 00:40:56,200 --> 00:41:01,400 reproduced. So evolution is pretty harsh. 596 00:41:03,920 --> 00:41:06,200 But if you think about it from an information standpoint, 597 00:41:06,200 --> 00:41:09,960 because cancer cells also have some information embedded in 598 00:41:09,960 --> 00:41:12,320 them in terms of just how they want to behave. 599 00:41:12,760 --> 00:41:17,320 So do you think after we've reproduced the information 600 00:41:17,960 --> 00:41:21,240 dynamics change in the sense that the information that the 601 00:41:22,640 --> 00:41:26,800 evolution programmed us for being healthy just shifts or it 602 00:41:26,800 --> 00:41:30,480 just no longer cares about that? And I I guess what I'm trying to 603 00:41:30,480 --> 00:41:33,000 understand is how cancer cells acquire this different set of 604 00:41:33,000 --> 00:41:36,000 information dynamics. Yeah, I, well, I think that the 605 00:41:37,240 --> 00:41:41,360 James De Gregory is, you know, a great scientist in, in Colorado 606 00:41:41,360 --> 00:41:46,320 who, who looks at aging and one of the things that happens with 607 00:41:46,320 --> 00:41:51,040 aging is that there seems to be a loosening of the, of the 608 00:41:51,160 --> 00:41:54,960 tissue controls over the individual cells. 609 00:41:55,560 --> 00:42:00,680 And so probably that contributes to the fact that it's a, you 610 00:42:00,680 --> 00:42:04,280 know, process that occurs over generally in older adults. 611 00:42:07,040 --> 00:42:15,800 And, and I, you know, I, I think the, it's the information. 612 00:42:16,600 --> 00:42:20,640 I, I, I don't think the information cancer uses was not 613 00:42:20,640 --> 00:42:23,600 necessarily information that was there for the cancer's benefit. 614 00:42:24,040 --> 00:42:26,800 It was there because it benefited fetal cells or 615 00:42:26,800 --> 00:42:31,720 there's, there's some, some part of it that's that the cancer 616 00:42:31,720 --> 00:42:36,600 that a cell can then adapt. And, and, and of course it, you 617 00:42:36,600 --> 00:42:38,960 know, it's also, it's not just the, the gene itself, but 618 00:42:38,960 --> 00:42:42,000 there's the spliceosome, there's the, you know, there's a number 619 00:42:42,000 --> 00:42:47,120 of things that the, that the cancer cell can change not, not 620 00:42:47,120 --> 00:42:51,160 to mention the role of the environment of, of, of, you 621 00:42:51,160 --> 00:42:52,920 know, acidos and things, things like that. 622 00:42:52,920 --> 00:42:55,720 It can change the environment in ways that are, that are 623 00:42:55,720 --> 00:43:00,920 beneficial. So but but I will not pretend to 624 00:43:00,920 --> 00:43:04,000 know all of the all of the details of this. 625 00:43:08,560 --> 00:43:11,320 Do do you have any? I mean, you must, you must get 626 00:43:11,320 --> 00:43:13,160 this way way more than than I do even. 627 00:43:13,160 --> 00:43:16,120 But but I get, you know, we, we, we published some things on 628 00:43:16,120 --> 00:43:19,040 cancer and we have a lot of a lot of patients writing to us, 629 00:43:19,040 --> 00:43:23,360 you know, saying what to do. So, so do, do, do you have any? 630 00:43:23,360 --> 00:43:24,480 And if if you don't, that's fine. 631 00:43:25,000 --> 00:43:28,440 Aside from sort of follow whatever the your best 632 00:43:28,440 --> 00:43:31,160 oncologist is telling you, do you have any other favorite 633 00:43:31,160 --> 00:43:33,760 thoughts for people to look into whether that'd be like 634 00:43:33,760 --> 00:43:37,560 Seyfried's, you know, metabolic stuff or anything else at all? 635 00:43:37,560 --> 00:43:39,280 Do you have anything that that you tell people? 636 00:43:40,880 --> 00:43:43,920 As a cancer prevention agency agent, is that well? 637 00:43:43,920 --> 00:43:45,840 I think we're be, I mean the be be on that. 638 00:43:45,920 --> 00:43:49,120 So once somebody's already been diagnosed, any, anything, any 639 00:43:49,120 --> 00:43:51,960 suggestions there? Well, you know, cancer is an 640 00:43:51,960 --> 00:43:56,720 evolutionary process. It's it cancers, like all living 641 00:43:56,720 --> 00:44:00,000 systems, have to obey the laws of evolution. 642 00:44:01,240 --> 00:44:06,200 And so cancer is not magic. You know, it's, it's not an evil 643 00:44:06,200 --> 00:44:08,560 entity, it's just an evolving population. 644 00:44:09,320 --> 00:44:11,840 Now we know evolution. I mean, we know the rules of 645 00:44:11,840 --> 00:44:17,640 evolution and we can use those to optimize cancer therapy. 646 00:44:19,000 --> 00:44:25,000 So for example, the standard practice in oncology, which has 647 00:44:25,000 --> 00:44:29,880 been the case for five decades, is that any therapy is given at 648 00:44:29,880 --> 00:44:33,400 maximum tolerated dose continuously until progression. 649 00:44:33,400 --> 00:44:38,280 It's almost the the mantra that they have evolutionarily, you 650 00:44:38,280 --> 00:44:42,400 could hardly do it worse because what you're doing is that you're 651 00:44:43,720 --> 00:44:48,200 placing strong selection pressure for resistance on a, on 652 00:44:48,200 --> 00:44:51,880 a large and diverse population. And you're also removing their 653 00:44:51,880 --> 00:44:53,320 competitors. You know, you're killing the 654 00:44:53,320 --> 00:44:57,320 cells that are sensitive. You're selecting the ones that 655 00:44:57,320 --> 00:45:02,040 are resistant and you're, you're, you're these resistant 656 00:45:02,040 --> 00:45:06,840 cells are now open to, to they, they have no competitors. 657 00:45:08,200 --> 00:45:11,080 And so it's, it's open for them to proliferate. 658 00:45:12,160 --> 00:45:14,440 And this is well known. This is actually a phenomenon 659 00:45:14,960 --> 00:45:18,720 in, in that's observed in, in evolution that's called 660 00:45:18,720 --> 00:45:24,600 competitive release. And you know, this, this is not 661 00:45:24,600 --> 00:45:29,360 a, this is a strategy that's, that optimizes the proliferation 662 00:45:29,360 --> 00:45:32,840 resistance cells. So, so one of the things that 663 00:45:32,840 --> 00:45:39,600 we've tried to do is to bring evolutionary dynamics into 664 00:45:39,600 --> 00:45:45,280 cancer therapy. So for example, we've used 665 00:45:45,320 --> 00:45:47,640 something, something that's called adaptive therapy. 666 00:45:48,240 --> 00:45:51,960 And here what you do is instead of giving maximum tolerated dose 667 00:45:51,960 --> 00:45:55,120 continuously, what you give is, is cancer dose. 668 00:45:55,200 --> 00:46:00,680 I mean, you give a, a drug dose a little bit in, in prostate 669 00:46:00,680 --> 00:46:03,880 cancer, for example, we use the serum, the biomarker, which is 670 00:46:03,880 --> 00:46:09,200 PSA and just drop it 50%. And then you stop there, you 671 00:46:09,200 --> 00:46:13,160 withdraw it, the tumor comes back, but the tumor's not 672 00:46:13,160 --> 00:46:17,440 proliferating with no selection for resistance. 673 00:46:18,200 --> 00:46:23,000 And because in general, in the absence of therapy, the, the 674 00:46:23,000 --> 00:46:27,280 resistant guys have some molecular machinery that allows 675 00:46:27,280 --> 00:46:31,840 them to be resistant, which is really good when you've got, it 676 00:46:31,840 --> 00:46:34,880 gives them a fitness advantage when therapy's present. 677 00:46:35,480 --> 00:46:38,880 But in the absence of therapy, it's, it's, it's a, it's a cost 678 00:46:38,920 --> 00:46:42,560 with no benefit. And so in general, the fitter, 679 00:46:42,560 --> 00:46:46,720 the, the, the sensitive cells are fitter than the, the 680 00:46:46,720 --> 00:46:48,680 resistant cells in the absence of treatment. 681 00:46:49,280 --> 00:46:54,280 So the tumor comes back and you, and it recapitulates the 682 00:46:54,280 --> 00:46:57,840 distribution of fit of, of sensitive and resistant cells 683 00:46:57,840 --> 00:46:59,960 that was there at the beginning. And you just treat it again, You 684 00:46:59,960 --> 00:47:02,560 just just just keep pushing it down. 685 00:47:04,000 --> 00:47:08,320 Now this is in metastatic cancers that are fatal. 686 00:47:08,560 --> 00:47:13,680 This is a where the, the goal is to maintain life with as high 687 00:47:13,680 --> 00:47:15,920 quality as possible for as long as you can. 688 00:47:16,960 --> 00:47:20,520 So what we've, what we've learned is that we can this in 689 00:47:20,520 --> 00:47:23,160 this kind of mechanism, we, we're only giving about half the 690 00:47:23,160 --> 00:47:25,200 drug that you would ordinarily get. 691 00:47:25,280 --> 00:47:29,080 And so the side effects and the cost of the drugs are much less, 692 00:47:29,760 --> 00:47:32,920 but we can prolong life considerably with that kind of 693 00:47:32,920 --> 00:47:36,680 approach. It doesn't have this sort of 694 00:47:36,680 --> 00:47:38,600 sexiness of trying to kill all the Kingstons. 695 00:47:38,920 --> 00:47:42,760 I mean, that intuitively is what we would like to do. 696 00:47:42,960 --> 00:47:45,160 I mean that that's, that just feels very appealing. 697 00:47:45,920 --> 00:47:48,240 And that would be the, the right thing to do if you could. 698 00:47:49,600 --> 00:47:53,480 But given the fact that we don't have magic bullets, we, we don't 699 00:47:53,480 --> 00:47:57,240 have treatments that will kill all the cancer cells and 700 00:47:57,240 --> 00:48:02,200 standard good example is antigen deprivation therapy for 701 00:48:02,280 --> 00:48:04,840 metastatic prostate cancer. It's really effective. 702 00:48:05,440 --> 00:48:10,200 You know, 9095% of the time it reduces the PSA to normal or 703 00:48:10,200 --> 00:48:15,360 even unmeasurable. But it's also never curative. 704 00:48:15,480 --> 00:48:19,200 I mean, we know that just historically it just is never 705 00:48:19,200 --> 00:48:25,360 curative. So, you know, that's, that's the 706 00:48:25,360 --> 00:48:29,800 dynamic, yeah. And the, the goal is then, you 707 00:48:29,800 --> 00:48:33,920 know, to to reduce the amount of ADT that you give antigen 708 00:48:33,920 --> 00:48:36,720 deprivation therapy, which meant hate, by the way. 709 00:48:37,000 --> 00:48:41,360 And it's, and it's, it's got a lot of toxicity, significantly 710 00:48:41,360 --> 00:48:46,400 decreases quality of life and typically gives you maybe three 711 00:48:46,400 --> 00:48:49,840 years. But if, if we can do much better 712 00:48:49,840 --> 00:48:52,840 than that with so that they, they have a normal testosterone 713 00:48:52,840 --> 00:48:57,560 level about half the time. We've both reduced the cost and 714 00:48:57,600 --> 00:49:01,400 we've reduced the, the toxicity while also increasing, you know, 715 00:49:01,400 --> 00:49:04,400 lifespan. So that's kind of the approach 716 00:49:04,400 --> 00:49:09,560 that we've tried to take. And so we, and, and you know, 717 00:49:09,560 --> 00:49:13,320 that's, that's, that's worked quite well, but it's, it's so 718 00:49:13,320 --> 00:49:18,720 different from the standard cancer therapy that it's, it's 719 00:49:18,720 --> 00:49:23,760 really kind of intuitively unappealing to, to oncologists. 720 00:49:24,040 --> 00:49:27,400 And sometimes the patients, you know, 'cause they, you, you, you 721 00:49:27,720 --> 00:49:32,000 drop the PSA to 50% of its original prefigurement value. 722 00:49:32,000 --> 00:49:35,120 And there's some, there's something that says, let's just 723 00:49:35,120 --> 00:49:37,520 keep hitting it. You know, that that's the, the 724 00:49:37,520 --> 00:49:42,040 right thing to do. So it takes a sort of, you have 725 00:49:42,040 --> 00:49:47,120 to like think through that and, and overcome that kind of the, 726 00:49:47,160 --> 00:49:50,440 the intuitive sense that that you're, you're, you're not doing 727 00:49:50,440 --> 00:49:53,360 it right. And and is that sort of thing 728 00:49:53,360 --> 00:49:56,920 just in terms of availability it's so you guys are doing it at 729 00:49:56,920 --> 00:50:01,680 Moffett, is that it or are are is this accessible to people or 730 00:50:01,720 --> 00:50:05,800 like how is this? It's, it's, there are trial, 731 00:50:05,800 --> 00:50:10,080 there's there's large trials going on in in Europe and 732 00:50:10,080 --> 00:50:13,640 Australia. There's one using this approach 733 00:50:13,640 --> 00:50:17,120 in ovarian cancer that's going on in a multi institutional 734 00:50:17,120 --> 00:50:21,400 study in the UK. There are some physicians, 735 00:50:22,000 --> 00:50:26,680 oncologists who are not willing to, to do this, but it would, it 736 00:50:26,680 --> 00:50:29,920 would still be considered, I think non standard practice. 737 00:50:31,200 --> 00:50:37,880 And so is it it it it? It will take a a long time to, I 738 00:50:37,880 --> 00:50:46,160 think, change ideas about this. If you were to hypothesize, 739 00:50:46,160 --> 00:50:50,080 where do you think adaptive therapy might not work the best? 740 00:50:52,160 --> 00:50:57,360 We, we don't know. We, we, I don't think we 741 00:50:57,360 --> 00:51:00,000 understand immunotherapy sufficiently well. 742 00:51:01,040 --> 00:51:02,760 The, the, the basic rules should be the same. 743 00:51:02,760 --> 00:51:08,640 I mean, evolution is evolution, but what we don't know are we 744 00:51:08,640 --> 00:51:13,200 have like to, we have the, the cancer cell population which can 745 00:51:13,200 --> 00:51:17,280 evolve and we have the immune response, which can change. 746 00:51:17,560 --> 00:51:20,600 And, and those are very complex dynamics. 747 00:51:21,760 --> 00:51:24,680 And we're just beginning to, to sort of look at those dynamics 748 00:51:24,680 --> 00:51:29,480 as they're very complicated. And there's so many things that 749 00:51:29,480 --> 00:51:33,000 are going on it it's, it's difficult to put all that 750 00:51:33,000 --> 00:51:34,640 together. It's much easier to work with 751 00:51:35,440 --> 00:51:37,200 hormonal therapy and chemotherapy. 752 00:51:38,200 --> 00:51:43,720 Targeted therapy seems to be perhaps slightly different, but 753 00:51:43,720 --> 00:51:47,400 but I will, you know, continue to argue that the fundamentally 754 00:51:47,480 --> 00:51:53,040 evolution are first principles. We we evolutionary dynamics will 755 00:51:53,040 --> 00:51:55,640 hold all it's these principles will occur. 756 00:51:55,840 --> 00:51:59,040 They simply, we don't know how they play out in, in some of 757 00:51:59,040 --> 00:52:01,960 these treatments. But I, but I think you can 758 00:52:01,960 --> 00:52:07,280 argue, I mean, when I first was working at a Cancer Center, 759 00:52:07,280 --> 00:52:11,720 which is a long time ago, there just weren't effective therapies 760 00:52:11,720 --> 00:52:14,760 for a lot of cancers, lung cancer, renal cancer, Melanoma, 761 00:52:14,880 --> 00:52:20,600 I mean, there's just nothing. And what we have now is really 762 00:52:21,160 --> 00:52:24,760 pretty good therapies for almost every cancer. 763 00:52:25,960 --> 00:52:31,240 And yet metastatic lung cancer is, is fatal now as it was then. 764 00:52:31,480 --> 00:52:37,920 And the reason is evolution that that the cancer cells evolve 765 00:52:37,920 --> 00:52:40,800 resistance to an initially effective therapy. 766 00:52:42,400 --> 00:52:47,560 And so I, I think increasingly you could argue that evolution 767 00:52:47,560 --> 00:52:51,680 is the proximate cause of death in, in cancer, cancer patients. 768 00:52:52,360 --> 00:52:57,400 And I think unless we acknowledge that, and unless we 769 00:52:57,680 --> 00:52:59,720 start to really actively integrate evolutionary 770 00:52:59,720 --> 00:53:03,680 principles into our therapy, we're we're, we're not going to 771 00:53:03,680 --> 00:53:09,640 necessarily make progress unless we find a magic bullet which may 772 00:53:09,640 --> 00:53:13,920 or may not exist. Yeah. 773 00:53:13,920 --> 00:53:16,760 I'm curious, what are some of the open questions you're 774 00:53:16,760 --> 00:53:19,960 tackling now by integrating more of the evolutionary dynamics 775 00:53:20,000 --> 00:53:25,240 into cancer? One of the things that we we 776 00:53:25,240 --> 00:53:28,800 need desperately are biomarkers to understand intratremal 777 00:53:28,800 --> 00:53:33,040 evolution over time. We don't have a good way to 778 00:53:33,040 --> 00:53:39,480 estimate that recently. And, and sometimes you just need 779 00:53:39,480 --> 00:53:42,000 more data, you know, just need to acquire more data. 780 00:53:42,000 --> 00:53:45,440 A lot of our trials have been done on shoestring budgets. 781 00:53:45,440 --> 00:53:49,200 So we, we didn't necessarily have the ability to take, do 782 00:53:49,200 --> 00:53:50,640 some of the tests that we would like to do. 783 00:53:51,000 --> 00:53:54,160 But something as simple, what we found recently is, is if you 784 00:53:54,160 --> 00:53:58,240 take the testosterone level and the PSA level simultaneously, 785 00:53:59,160 --> 00:54:03,000 the ratio of that can tell you a lot about the subpopulations. 786 00:54:04,160 --> 00:54:07,200 So it doesn't have to be esoteric, you know, circulating 787 00:54:07,200 --> 00:54:12,960 DNA, you know, we can use kind of standard tests by by 788 00:54:12,960 --> 00:54:14,760 understanding the connection between them. 789 00:54:15,560 --> 00:54:21,280 So what we find is if the, the, the, the, the PSA should reflect 790 00:54:21,280 --> 00:54:23,280 the testosterone level in general. 791 00:54:25,080 --> 00:54:30,240 But if you start to see the, the PSA for each, for a, for any, 792 00:54:30,280 --> 00:54:33,200 yeah, for the testosterone level, if the PSA starts to be 793 00:54:33,400 --> 00:54:37,520 increasing over over time for that individual, that means 794 00:54:37,520 --> 00:54:43,160 there are cells present that are able to, to use much lower 795 00:54:43,160 --> 00:54:45,240 amounts of testosterone. That's over the concentration of 796 00:54:45,240 --> 00:54:49,360 testosterone to proliferate. And so you're, they're making 797 00:54:49,360 --> 00:54:53,320 the PSA, but the testosterone level is, is low. 798 00:54:53,520 --> 00:54:58,080 So something like that then allows us to understand that the 799 00:54:58,120 --> 00:55:02,600 that there's an this population of resistant cells is increasing 800 00:55:03,040 --> 00:55:04,600 and we need to do something about that. 801 00:55:10,800 --> 00:55:14,760 I know you've also discussed this idea of habitat imaging and 802 00:55:14,760 --> 00:55:18,880 looking at the tumor microenvironment itself and then 803 00:55:18,880 --> 00:55:22,840 personalizing protocols based on that one. 804 00:55:22,840 --> 00:55:26,760 I'm curious how, how, how that personalization gets done. 805 00:55:26,760 --> 00:55:30,400 And then two, I guess, why is this something that's not being 806 00:55:30,400 --> 00:55:36,480 done right now? The, the I don't, if you've ever 807 00:55:36,480 --> 00:55:40,480 seen habitat maps, I'm sorry, species maps. 808 00:55:40,840 --> 00:55:43,960 So if you look Florida, for example, and say, what's the 809 00:55:43,960 --> 00:55:45,400 distribution of ground squirrels? 810 00:55:45,400 --> 00:55:48,000 They'll be, you know that they'll show you maps of what 811 00:55:48,000 --> 00:55:50,280 are these? The Gray squirrel is dominant 812 00:55:50,280 --> 00:55:51,720 where the fox squirrel is dominant. 813 00:55:53,200 --> 00:55:56,720 People don't walk around, you know, every square meter of 814 00:55:56,720 --> 00:56:02,600 Florida measuring squirrels and the way it's done is, is, is is 815 00:56:02,600 --> 00:56:07,640 what's called landscape ecology. And, and this was developed for 816 00:56:07,640 --> 00:56:10,880 satellite images and, and basically large space of scale 817 00:56:10,880 --> 00:56:17,920 images by identifying habitats, you can then you can bite, but 818 00:56:17,920 --> 00:56:21,400 and then investigating a habitat and counting the squirrels in 819 00:56:21,400 --> 00:56:23,840 that one habitat, you can then do a distribution. 820 00:56:24,360 --> 00:56:31,440 So for example, grey squirrels are very good at at at 4G and, 821 00:56:31,440 --> 00:56:35,240 and so they can out compete the the red squirrels and the and 822 00:56:35,240 --> 00:56:39,200 the fox squirrels for competing. So if you see a college campus, 823 00:56:39,840 --> 00:56:43,080 you will basically always see grey squirrels there. 824 00:56:44,440 --> 00:56:49,200 What fox squirrels and, and, and red squirrels are, are good at 825 00:56:49,200 --> 00:56:53,280 is, is dealing with predators. They'll go up a tree and attack 826 00:56:53,280 --> 00:56:54,800 an owl and, and that sort of thing. 827 00:56:54,800 --> 00:57:03,200 So in forests and in, you know, in, in wildlife areas, the red 828 00:57:03,200 --> 00:57:04,960 squirrel will Dom, the fox squirrel will dominate. 829 00:57:05,520 --> 00:57:07,040 You won't see grey squirrels as much. 830 00:57:08,960 --> 00:57:11,440 Now on the other hand, if you see grey squirrels on a college 831 00:57:11,440 --> 00:57:17,000 campus, that means either there's coyotes there or there's 832 00:57:17,000 --> 00:57:21,520 feral cats. So again, evolution tells you 833 00:57:22,080 --> 00:57:25,200 the truth and our job is to understand. 834 00:57:25,360 --> 00:57:30,080 So in this case, when we do imaging with radiologic studies, 835 00:57:30,080 --> 00:57:36,160 so these are large scale, the kind of the equivalent of of of 836 00:57:38,720 --> 00:57:42,960 satellite images. If we can identify certain 837 00:57:42,960 --> 00:57:47,960 habitats that we know will in which there will be typically 838 00:57:48,480 --> 00:57:51,080 certain kinds of tumor cells. So for example, if it's if it's 839 00:57:51,080 --> 00:57:53,960 an area that's very poorly perfused, we would expect cells 840 00:57:53,960 --> 00:57:56,960 that are, you know, hypoxic, that acidic, they have those 841 00:57:57,200 --> 00:58:03,240 kinds of capacities. So by by understanding how the 842 00:58:03,480 --> 00:58:08,640 large scale environment selects for the small scale population, 843 00:58:09,240 --> 00:58:14,560 you can then estimate the subpopulations of the, of the 844 00:58:14,560 --> 00:58:18,920 cancer. The the, the problem is that is 845 00:58:18,920 --> 00:58:20,200 that it's really hard to do that. 846 00:58:21,880 --> 00:58:26,640 You know, what we did was take MRI scan. 847 00:58:26,640 --> 00:58:31,160 So MRI scans are the the same tissue was repeatedly 848 00:58:31,160 --> 00:58:35,400 interrogated with different sequences that are that are 849 00:58:35,400 --> 00:58:37,520 sensitive to different components of the tissue. 850 00:58:38,320 --> 00:58:43,360 Putting those together, we can generate a habitat the, the, 851 00:58:43,880 --> 00:58:46,840 the, the, the, but this is technically very difficult 852 00:58:46,840 --> 00:58:49,760 because the, the sequences are never precisely the same. 853 00:58:51,240 --> 00:58:54,600 They, the, the, the, the spatial scales are often slightly 854 00:58:54,600 --> 00:58:57,120 different. For example, there can be a 3mm 855 00:58:57,120 --> 00:59:00,800 slice thickness versus 5mm, even 7mm. 856 00:59:01,200 --> 00:59:03,880 And so technically there's a lot of things to overcome. 857 00:59:03,880 --> 00:59:09,000 What we have pleaded with the imaging companies to do is to, 858 00:59:09,000 --> 00:59:14,640 is to develop a, a sequence that allows you to interrogate the 859 00:59:14,640 --> 00:59:17,920 same tissue with multiple sequences simultaneously, which 860 00:59:17,920 --> 00:59:20,960 in theory is possible, but, but that's been very slow to 861 00:59:20,960 --> 00:59:23,840 develop. So it's been a a frustrating 862 00:59:26,320 --> 00:59:31,560 path and it's, it's and these are this, this is sufficiently 863 00:59:31,560 --> 00:59:35,120 extent expensive that we need grants for that and they have 864 00:59:35,120 --> 00:59:44,240 not been forthcoming. Mike, any other questions? 865 00:59:45,000 --> 00:59:46,800 No, no, a lot, a lot to think about it. 866 00:59:46,800 --> 00:59:52,320 You know, I think this really this, this, this conciliants of, 867 00:59:52,360 --> 00:59:55,880 of evolutionary kinds of considerations over the, over 868 00:59:55,880 --> 01:00:01,080 the population and the sort of software aspects in the, the 869 01:00:01,080 --> 01:00:03,320 decision making of the collective and this, this 870 01:00:03,320 --> 01:00:07,760 physiological circuits. I think this is this is where in 871 01:00:07,760 --> 01:00:10,520 the end the the the solutions are going to come from. 872 01:00:10,880 --> 01:00:13,000 I think we really, we really need to understand both sides of 873 01:00:13,000 --> 01:00:15,400 it. It's funny if you go back to the 874 01:00:16,520 --> 01:00:20,720 era when the human genome was being deciphered and was if you 875 01:00:20,720 --> 01:00:24,840 read the literature, it sort of implies that this is pretty much 876 01:00:24,840 --> 01:00:27,520 it. We this is the end of the 877 01:00:27,520 --> 01:00:29,080 disease. I mean, I think that that term 878 01:00:29,160 --> 01:00:34,480 was even used. And, and it's funny because 879 01:00:34,480 --> 01:00:38,920 they, we still live in a, the very genetic era where, you 880 01:00:38,920 --> 01:00:44,200 know, everything that's done is, is, you know, it's based on, you 881 01:00:44,200 --> 01:00:49,640 know, genetic measurements. And, and I think that, you know, 882 01:00:49,640 --> 01:00:52,640 it's, it's a whole generation, I think has been almost lost 883 01:00:53,080 --> 01:00:57,080 because there's been so much focus on that, that we've, we've 884 01:00:57,880 --> 01:01:00,360 given up on many of the other things which are actually being 885 01:01:00,360 --> 01:01:04,120 developed in the 50s and 60s, but then just kind of got passed 886 01:01:04,120 --> 01:01:06,400 over by the, by the genetic revolution. 887 01:01:06,400 --> 01:01:10,560 It's just so easy to put your sample in a molecular biology 888 01:01:10,560 --> 01:01:15,400 machine and, and generate data. And I think there's a false 889 01:01:15,400 --> 01:01:18,400 sense that, you know, this, all this data is going to tell us 890 01:01:18,400 --> 01:01:20,840 something, you know, really great. 891 01:01:21,840 --> 01:01:27,560 An interesting analogy is to say, suppose you were a modern 892 01:01:27,560 --> 01:01:34,880 Darwin and and you were on the Beagle with with just $1,000,000 893 01:01:34,880 --> 01:01:37,560 worth of, of molecular biology machinery. 894 01:01:38,520 --> 01:01:44,200 And suppose the sailors tramped through the the Galapagos 895 01:01:44,200 --> 01:01:47,400 Islands and they brought you back pinch samples and you 896 01:01:47,400 --> 01:01:50,560 ground them up and put put them into the your molecular biology 897 01:01:50,560 --> 01:01:53,720 machines and generated, you know, terabytes of data. 898 01:01:54,760 --> 01:01:59,800 Could that modern Darwin have written on the origin of 899 01:01:59,800 --> 01:02:04,840 species? And I think the answer is no, 900 01:02:05,840 --> 01:02:09,040 although I, I've posed this to molecular biologists who always 901 01:02:09,040 --> 01:02:11,720 say, well, I think they've done it. 902 01:02:11,720 --> 01:02:14,440 But the, but the problem is that there's, there's not a clear 903 01:02:15,560 --> 01:02:17,440 mapping from genotype to phenotype. 904 01:02:19,120 --> 01:02:23,800 So you would have to know from the gene that, that the, there's 905 01:02:23,800 --> 01:02:27,120 something about the beak. But you laugh like what you, 906 01:02:27,120 --> 01:02:30,920 what you cannot see is the selection force, the, the 907 01:02:30,920 --> 01:02:33,600 morphology of the beak. I mean, what, what Darwin saw 908 01:02:33,600 --> 01:02:36,920 was something very straightforward and logical. 909 01:02:36,920 --> 01:02:40,560 The morphology, the beacon, the morphology of the seed matched. 910 01:02:42,080 --> 01:02:47,560 And we, we, I don't, I, I think for all the data we generate 911 01:02:47,800 --> 01:02:53,720 from the, from the molecular data, I don't know if we've 912 01:02:55,040 --> 01:03:00,200 gotten a, a true sense of the, of the, of what's, what's really 913 01:03:00,200 --> 01:03:01,840 going on. I mean, I think we've sort of 914 01:03:03,880 --> 01:03:08,160 missed the, the, the way we, we've missed the seeds, you 915 01:03:08,160 --> 01:03:12,360 know, and, and in cancer at least we've not done the 916 01:03:12,360 --> 01:03:16,960 phenotype, the beak versus seed kind of understanding. 917 01:03:17,560 --> 01:03:20,720 And so we've got lots of genetic information, but, but it's not 918 01:03:20,720 --> 01:03:24,680 being built on a solid framework of of sort of evolutionary first 919 01:03:24,680 --> 01:03:29,800 principles. Yeah, I think you're framing off 920 01:03:29,800 --> 01:03:33,560 where is evolution spending energy and how 1/3 of it is, say 921 01:03:33,560 --> 01:03:35,680 even just iron channel transport. 922 01:03:36,080 --> 01:03:39,200 It just tells you a lot where perhaps we should be focusing 923 01:03:39,200 --> 01:03:40,680 our efforts and other things as well. 924 01:03:41,240 --> 01:03:47,800 Yeah, follow the money. Yeah, I think, I think evolution 925 01:03:48,240 --> 01:03:52,680 is trying to tell us something and we've not been listening 926 01:03:52,680 --> 01:03:55,880 very well up until now. Hi everyone, if you wish to be 927 01:03:55,880 --> 01:04:00,200 notified of future podcast episodes and my writing on 928 01:04:00,200 --> 01:04:04,880 longevity and the frontiers of biology, please subscribe at 929 01:04:04,880 --> 01:04:09,440 liblongworld.com. And if you're enjoying the show, 930 01:04:09,640 --> 01:04:13,400 please leave a rating on Apple, Spotify, or elsewhere. 931 01:04:14,120 --> 01:04:16,560 Thank you for listening and I will see you next time.