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so if anybody wants to chat at any point or download any of the primary papers the data sets the software everything is here at this website please feel free to contact me um I'm not a clinician I'm a basic
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scientist and I'm going to uh talk about some aspects of the cancer problem that I think are of fundamental interest but also I think we'll have implications for um for for for biomedicine of cancer and
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sometimes I give a talk that's focused on this question uh why is cancer not an issue for our various autonomous Robotics and and the various other kinds of things we make and uh this is a it sounds kind of
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silly but it's actually a deep a deep question and the answer is because mostly what we make in in our engineered constructs has a very flat architecture in other words the entire thing might have interesting
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complex behaviors it might have some some degree of intelligence and problem solving or whatever but the parts that it's made of are passive the parts do not have agendas of their own uh they there is no danger of them you know sort
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of going off on their own uh tangent that's um uh it doesn't it doesn't merge with with the goals of the rest of the of the structure now that is not the case in biology biology has a completely
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different architecture so all the way up from molecular networks through organelles and tissues and organs and whole organisms and even swarms biology is uh made of layers that are problem
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solving intelligent agents on their own they solve problems in various spaces this this might be not just the three-dimensional space of canonical Behavior but this might be the space of physiological States transcriptional
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space anatomical amorphous space metabolic space and so on and so we we are made of of a kind of nesting doll architecture not just structurally I mean that part's obvious that each thing is made of smaller things but in fact
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that each of these layers has their own problem-solving capacity uh in many cases various kinds of ability to learn from experience and and uh the the
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competencies of various kinds and this turns out to be very important and so a summary of everything I'm going to tell you today is basically this that all cells not just neurons communicate in electrical networks that process
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information and that we think that cancer can be detected it can be induced but it can also be normalized by uh computational models of the manipulation
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of the bioelectrical signaling that normally keeps cells operating towards large-scale anatomical goals and if we boil all that down to one sentence it's basically this that like the brain all
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of the tissues in your body form electrical networks that make decisions about anatomy and that we can now Target the system to change the uh the large-scale decision-making of these
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cellular collectives and that has huge implications for uh for all all kinds of aspects of medicine I'm going to show you some weird creatures today here's our here's our five-legged frog and I just point out at the beginning this is not Photoshop these are these are real
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um real living forms in our lab that serve as uh our attempts to test the various theories that we have so one really fundamental aspect of of the cancer problem is is how what what scale
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do you uh do you think about it at so um one particular uh kind of uh thing that people sometimes ask is uh you know there are there are numerous uh animals the planaria that I'll show you in a
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minute salamanders various other creatures that are really highly regenerative in other words they lose a limb and they regrow it things like that and people ask why do human bodies have reduced regenerative potential and a
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common answer to this that that people will advance is that it's to avoid cancer right so so if you're a long-lived organism that's going to be around for let's say up to 10 decades or so um you don't want to have access to
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highly plastic proliferative cells because the the chance of of developing cancer is going to be too high and so and so the idea is that something like a human will then not be regenerative because we don't have we we're really uh
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keep keeping those kind of plastic Pathways really uh uh suppressed and so a perspective that's focused on specific Pathways to TGF beta to cell cycle
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control all the things that we're used to thinking about for cancer and and Beyond at the Single Cell level predict that organisms with a high regenerative potential meaning they have easy access to proliferation Pathways they have lots
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of undifferentiated cells that those kind of animals should have a high cancer incidence and specifically that cancer and regeneration should go together that is if this this view predicts that if you are a highly regenerative type of creature that has
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lots of plasticity you should have a high oncogenic cost now you could turn that on on its head and make a make the opposite prediction and you might say actually organisms that exert robust patterning control
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over their cells meaning they have high regenerative ability um actually should have low cancer incidents because of this ability to control cell behaviors towards adaptive anatomical outcomes and so from that
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perspective regeneration in cancer should be at opposite ends of the spectrum and in fact augmenting regeneration May then be a promising approach to normalize cancer and so it turns out that actually the evidence um
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all of the evidence supports this view animals that are good at regenerating tend to be very cancer resistant and so that that turns out to be interesting and important and I want to show you um one one creature that in particular
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epitomizes this this is the planarian flatworm they have a true brain they are similar to our direct ancestor they have a centralized nervous system they have lots of internal organs and so on uh
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they have this amazing ability that you can cut them into pieces the record is something like 275 pieces so you can cut them into pieces every piece knows exactly what a correct planarian should look like and regenerate uh everything that's missing
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you get a perfect little worm in fact everything the remaining piece scales down so that everything ends up being the correct proportion and then eventually it will it will scale back up these guys not only are regenerative
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they're Immortal they literally have no lifespan limit uh they they do there's no such thing as an old planarian of of this kind um they are very cancer resistant and all of this in the context of a
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mixiploid genome if you look at their genomes the cells could have different numbers of chromosomes their genomes are a total mess and if we have time later at the end of the talk we can we can talk about why that is I think it's a
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deep thing but but what they're telling you is that it's possible to be a very long-lived creature uh despite having a really chaotic uh genome and also be
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cancer resistant so um I want to for for a little bit so the first part of the talk I wonder for a few minutes just kind of think about that that broader context what you know uh this this idea of multicellularity versus cancer and
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and what's going on here so so the first thing to realize is that um I I think that the right question isn't why is there cancer the right question is why is there anything but cancer ever
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because what we are made of are things like this so this is a free living organism but this is a single cell this is called the lacrum area and you can see that uh it's actually very competent in its environment it's got this local
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little uh very very tiny um sort of a light cone of the goals that it pursues and it's very competent in in control of its morphology of of its physiology metabolics and and so on and it has
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little tiny single cell agendas it's going to reproduce as much as it can it's going to go wherever life is good it's going to explore it's going to feed um and dump entropy into into the environment and this is the sort of
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thing that we are all made of and so so that raised this is an interesting question why do these these kind of creatures who have lots of uh lots of different competencies in their own single cell goals why do they come
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together during multicellularity to do this this is what happens um with us uh this is a cross-section through a human torso you can see the incredible uh complexity and order everything is uh
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most of the time in the right size and shape and position and relative sitting next to the right thing and so on but we all Start Life as a collection of embryonic blastomeres and so all of these cells have to reliably get to
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something like this and uh and and we need to ask the question first of all how do they do it but also where does this anatomical pattern come from how do they know what to build and the typical
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answer to this is people say well DNA you've got a human genome so you know what what else is is it going to build and uh actually this is this is very far from a satisfying answer because we can
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read genomes now and we know what's there what's there is the specification of proteins the tiniest uh pieces of Hardware that this is that the B cells have to deploy but there's actually nothing in the in the genome that talks
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about the size the shape the Symmetry type of of the organism so we need to understand how this Collective using the hardware that it's been given by its genome does all of the information
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processing needed to build what it's supposed to build to stop what it's when it's done um how could we of course as workers in regenerative medicine we ask um how could we uh re-ask these cells to
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rebuild a piece that's missing and in particular what happens when this amazing process breaks down and what happens is cancer and I just want to point out why this uh this this genetic information is is not sufficient because
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you might think well we've had we've had genomics and molecular biology for for many decades now I mean aren't we aren't we getting a handle all this and let's just do a thought experiment here's here's an axolotl larva and baby
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axolotls have little forearms this is a tadpole of the frog that we work with they at these stages do not have any limbs in our lab and this is we actually do this this is more than a thought experiment we make something called a frog level so from is a combination of
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of Axolotl cells and frog cells and they make a chimeric embryo now we've got the Axolotl genome it's been sequenced we've got the Frog genome that's been sequenced now I ask the question can anybody tell me if these frog lottels
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are going to have legs or not and you can't and you and despite the fact that we have the genomics and and we have some understanding of the molecular biology of these cells no one can make a prediction a priori of whether these frog levels are going to
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have legs and that's because while we understand the uh the molecular components inside of cells we really don't understand how groups of cells make large-scale decisions about what they're going to make
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um and this is something that uh actually in uh in in planaria is uh is is a very Stark problem because the species that we work with reproduce by fission and regen and narration so they
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rip themselves in half and then they regenerate that's how they reproduce and when you do that uh what happens is that every somatic mutation that doesn't get that doesn't kill the cell it ends up being Amplified into the Next Generation
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as regeneration happens so so so they have somatic inheritance so these body mutations propagate uh continuously this is why their genome is so incredibly uh chaotic because they just keep everything that happens to them they
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don't clean them the way that sexual reproducing organisms do and despite all of that uh with with despite all of this chaotic genome they have 100 regenerative Fidelity and uh they're
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very cancer resistant it's pretty scandalous when you compare that to you know what we learn in um basic biology that the animal with the craziest genome actually has the
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least susceptibility to cancer uh the best anatomical Fidelity and so on and so and so we're getting better at the mechanisms of biology but we really don't understand the algorithms yet so what we're interested in are these
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questions how are individual cell decisions harnessed towards large-scale anatomical goals and if we understood this it's not just about cancer we would have the answer to birth defects traumatic injury degenerative disease uh
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and then be able to make all kinds of synthetic living machines and so on so this is this is how I this is how we approach the uh the cancer problem and specifically uh we really think a lot about
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um anatomical homeostasis the the the most amazing thing about regeneration is that it knows when to stop so here's here's an axolotl uh these guys uh regenerate their limbs their eyes their
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jaws uh portions of the brain the heart they regenerate their tail including spinal cord ovaries uh just amazing as adults and and what happens is you can amputate anywhere along along this uh
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this this the the axis of the limb and they will regrow exactly what's needed no more no less and then they stop when do they stop they stop when the correct salamander arm has been completed so so
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now it's clear that that this is a as a collective this structure actually has a really good idea of what the final steps are supposed to be and we know that because it stops the proliferation the morphogenesis everything stops when they
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get there by the way this isn't just for frogs and worms of course human livers are highly regenerative even the ancient Greeks knew that I have no idea how they knew that back in that in those days um uh human children regenerate their
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fingertips so a clean amputation uh at a at a fairly young age if you don't sew the skin over will eventually result in a normal um normal cosmetically uh acceptable finger and deer when they regenerate their
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antlers they grow up to a centimeter and a half of new bone per day okay so so here's a large adult mammal growing massive amounts of new bone vasculature innervation skin and so on so
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um what what we really would like to do is to move uh from the questions of of molecular biology and we'll work the community is quite good at getting this kind of information what genes and proteins interact with each other to
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really try to understand the large-scale decision-making of uh of of of complex organs and you you can think about the journey that computer science took so this is this is what programming looked like in the 1940s and 50s and what's it
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what's uh important about this is that you can see in order to program this computer what she's doing is she's physically rewiring it right the focus is on the hardware so so she's there plugging what you know wires back and forth
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and the idea is that in order to control this machine and make it do something else you have to physically interact with the hardware and this of course uh the reason we have this amazing Information Technology Revolution is that we've moved away from that I mean
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some people still still work on Hardware but the vast majority of us don't need to have a soldering iron when when we want to switch from Photoshop to to Microsoft Word on your laptop because
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we've learned to take advantage of the reprogrammability of the device and so I'm going to argue that biology is is is highly reprogrammable and that this is really what we need to do we need to
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move a biology and Medicine towards uh understanding that because all of the current excitement in the field is all about the hardware so crispr genomic editing um uh rewiring molecular Pathways
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protein engineering all of this stuff is focused on the hardware and the kind of the kind of software competencies I'm talking about are the sorts of things that you see for example here so this is something we discovered a few years ago
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uh tadpoles need to become frogs and in order to become a frog they have to rearrange their face so the eyes have to move the nostrils have to move the Jaws everything has to move and it was it used to be thought that this was a hardwired process that basically every
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organ just moves in the right direction the right amount and um there you go you have your you have your fraud well so we decided to to uh test that idea and to see if there was in fact more intelligence to this process how do you
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test for intelligence you perturb the system in a novel way and you see if it still has the ability to have its goals met despite uh starting in the new configuration this is William James's definition of intelligence basically it
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says same goal by different means right how competent is the system so what we did was we created what we call Picasso tadpoles so everything is in the wrong place the eyes on top of the head the Jaws are off to the side the thing's a complete mess and if all it was doing
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was moving each organ in the right direction the right amount the Frog would be equally messed up because you're starting in the incorrect configuration in fact what we find is that these animals make quite normal frogs because all of this stuff is going
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to move in novel paths in fact sometimes it goes too far and actually has to double back and come back but all of them will will move around and rearrange relative to each other until they get to a correct frog face so what evolution
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has given us here is not a hardwired system that makes certain movements it's given us an error minimization scheme that is able to continue to operate until a particular morphological goal
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has been met and so it has it has it has lots of different types of feedback and so this this is the kind of uh Paradigm that that we all learned it's based on uh it's based on genetics and emergence
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this idea that the the cells will uh the the gene regulatory networks will create proteins they interact with each other uh uh using local rules and then eventually there's emergence of complexity something something complex
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happens like this uh salamander uh and that's true this does happen but it's only a part of the story and I think not even the main part uh the main part is that this Hardware that that is produced
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has this amazing ability to uh Implement uh anatomical homeostasis when the system is deviated uh by injury by mutations by teratogens pathogens whatever when it's when it's deviated
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there are feedback loops that kick in both at the level of transcription and at the level of physics and this is the one we're going to talk about uh that try to get you back to where you need to be it's an error minimization process like the thermostat in your house it's a
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basic homeostatic Loop now the thing about homeostatic Loops is that uh they have to have a set point so this is a very unconventional I mean of course but biologists know all about feedback loops
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but typically these these feedback loops are scalar there's single numbers like pH or you know hunger level things like that um here the set point actually has to be a description of a fairly complex anatomical structure not to the
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individual cell level of detail but but you know a a some level of anatomical description and and in general uh we're not encouraged in biology to think about goals or final States or anything like that we're encouraged to think about
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molecular mechanisms and and how what the emergent qualities are of of that complex dynamical system but here this this cybernetic view really forces you to think about uh uh is it possible that the system literally
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stores a set point of what it's supposed to build and uh and and what it's doing is like any homeostatic system it tries to reduce the error to that standpoint so this is what we've been doing for years now we've taken this very strong
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and counter-intuitive prediction if this thing literally knows what shape it's supposed to grow and uh the prediction is that we should be able to find that encoding we should be able to decode it right so whatever biophysical
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um medium holds it we should be able to decode it and then we should be able to rewrite it and if we rewrite it something amazing should happen which is that in in typical uh uh approach to this to this problem if you if you believe only in emergence that means
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that all your interventions have to be down here you have to make changes here maybe with crispr maybe something else you make changes down here and and eventually they percolate up but the limiting factor there is for complex you
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know beyond single Gene diseases the question is how do you know which genes to manipulate for a complex outcome you generally don't because this whole process is not reversible it's a it's a really terrible inverse problem however
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if if there is in fact a stored pattern that the the cells are working towards then you've got a different uh approach you might be able to change the pattern the way you do in your thermostat when you change the set point you don't need to know how the rest of the system works
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you just need to know how to change the set point and and rely on it to do what it does best which is to to to to try to get to that set time so so here's how we think about this that basically uh what
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evolution has done is scale up using a particular kind of interaction I'll tell you about shortly scale up uh competence single cell systems into something like this where the goals get much bigger
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instead of single cell level goals of metabolism and proliferation the goal here is to maintain this kind of thing and if you deviate from that goal the system will very commonly go back and try to try to build it but there's a
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breakdown of that cooperation and that's and that's scale up and that breakdown is cancer so this is this is human glioblastoma cells crawling around and I'm going to make the argument that what happened what what this this kind of process
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really is is a breakdown of this uh coordination system that is scaling up from from Tiny goals of single cells to anatomical goal States in an anatomical morphe space and and that process breaks
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down and you get cancer so that suggests that we ought to be able to uh uh you know this way of thinking about it which sort of weaves together embryogenesis regeneration and cancer as a uh uh a problem of information control in
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particular of scaling of goals uh in biology uh suggests this that that if we really understood this we should be able to develop strategies that don't just kill the cancer cells which are of course problematic because you get a
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compensatory proliferation and to tumor resistance and all that uh instead of trying to kill them um could we try to reconnect them more strongly to this the signals that normally keep them working together
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towards making nice organs uh and that requires us to know what are these signals how do cells remember what the whole thing is supposed to be because no individual cell knows how many fingers a salamander limb is supposed to have but
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the collective certainly does so the question is how does that scaling happens how do you go from single cell information to uh large-scale anatomical goals and this is where we get into bioelectricity now um my electricity is
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just one layer of a complex morphogenetic field of information that all cells have access to I am I'm going to spend the next half an hour talking about bioelectricity not because I think bioelectricity is the only thing that
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matters all of these things are important chemical signals extracellular Matrix biophysical pressures and tensions and so on all those things matter but this is a particularly interesting and important layer and that's the one that that I'm going to
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talk about in this morphogenetic field is is there uh guiding the large-scale system throughout lifespan from from basic embryonic development all the way through maintenance resistance to aging and all of that so so what are
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bioelectrical signals well um every membrane every cell not just neurons but every cell in your body has these ion channels and in fact also Gap Junctions in them
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and these ion channels let charged molecules in and out and as a result you get a voltage gradient across the membrane so every cell has a voltage gradient across that memory now uh it just so happens that if you take different kinds of cells and this is
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just a small sample of the data and you put them a lot you you sort of throw them on a scale from from depolarized to hyper polarized you get a very interesting relationship so so your mature quiescent cell types tend to be
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up here strongly polarized your proliferative cells such as embryonic stem cells uh and and other embryonic types of cells tend to be down here as do cancer cells now this is as
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interesting as this is I I always hesitate to show the slide because people people really like this and it takes away attention from the fact that I don't think any of this is really a single cell level uh problem I don't
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think cancer is a single cell disease um but this this kind of it focuses your attention on the on the individual voltage of a single cell but it's actually much more interesting than that it is true that this voltage um controls all kinds of cell properties
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that are important for cancer it controls differentiation apoptosis um cell migration uh cell shape and so on but but the story is actually much more interesting than than the Single Cell Behavior because
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as we start to think about how is it that collections of cells can store uh memories of what to do the the most obvious example of that is the nervous system and the brain so each of us
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exists as a uh as a coherent individual over and above the many uh neurons that are in our brains because bioelectric because of bioelectrical signaling in in your brain that serves an important
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function it works as a kind of cognitive glue and what it does is it allows information processing and networks so while individual cells have these voltage Dynamics and so on what they do
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is they propagate uh those electrical States through through various kinds of synapses such as these Gap Junctions to their neighbors and it's the movement of these electrical signals through the network that binds them together towards
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computations that can underlie cognition of a and the appearance of an individual that is more than the sum of their parts so so this Hardware allows a kind of interesting software
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this is uh this group made this amazing video of a a zebrafish a living zebrafish brain and everything that's that's going on as this animal thinks about whatever it is that fish think about and you can see you can track all the electrical activity and there's this
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goal of neural it's called neural decoding this idea of being able to read out this electrophysiology over time and decode it so that you know what the animal is thinking you should be able to I mean that's the commitment of Neuroscience is that from this pattern
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you should be able to recover the memories the goals the preferences the behavioral competencies of this animal they're all encoded in this electrical activity but it turns out that um actually every part of your body has
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these ion channels most cells have these electrical synapses with their neighbors and so so we wondered um could we extend Neuroscience Beyond neurons and ask the same neural decoding
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kind of question uh except outside of the nervous system let's say in an embryonic tissue or in a nascent tumor uh could we read out the conversations that these cells are having and try to
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understand what the collective is going to do right by tracking the individual voltage States of each cell and so so this is this is not a model this is this is actual data of a voltage sensitive fluorescent dye this was a
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technique first developed by my colleague Danny Adams who made this um video of an early frog embryo developing and the idea is to be able to decode what the collective is going to build and so I'm going to show you here this
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is this is grayscale but it's the same idea it's a voltage reporting die and you see here this this is a time lapse of a frog and reel putting its face together and there's all kinds of interesting things happening this is one frame from that video
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what you see in that frame is that long before the genes come on to pattern the face and long before the anatomy of the face is established you can read out the pattern that it's going to make in the future here's where the eye is going to
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be here's where the mouth is going to be here are the placards we call this the electric face it is literally the uh the pre-pattern or the tissue memory of what a correct face is supposed to look like if you perturb this pattern at all you
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change the gene expression and then you change the anatomy this is instructive it is required for the normal face to take shape uh this this is a pathological uh pattern which we'll talk more about this momentarily which is
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when we inject human oncogenes and they make a tumor and eventually it starts to metastasize uh you can detect the the this process long before it actually happens by tracking the voltage of the cells and
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you can see here that B cells have already electrically decoupled from their neighbors and when they do that they're basically uh reverting to a single cell a unicellular ancient past as far as they're concerned then the
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rest of the animal is just environment to them all they're going to do is is the unicellular goals they're going to proliferate they're going to migrate to we're metabolically favorable and so on and so and so you can you can detect this breakdown of of multicellularity so
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what we've been doing is developing tools um first to uh to track uh and characterize these by electrical gradients lots of computational modeling to link them to the ion channels and pumps that are there
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um and the most important thing of course is the uh the functional uh tools to to rewrite the pattern it's one thing to read it and be able to see what the what the um uh the electrical states in
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the collective are but but critically you have to uh you have to manipulate them and try to write in the in the language of Neuroscience you're trying to incept false memories into the tissues or change the the electrical
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pre-patterns that guide their activities so the way you do that we don't use any kinds of Applied Fields there are no uh electrodes there are no magnets there are no electromagnetic waves or radiation nothing like that what we're
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using is we're exploiting the native interface that cells exposed to each other this is how the cells program each other natively in the body they're they're using this interface of these ion channels and these Gap Junctions and
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we can use them too we can use pharmacological molecular genetic or in fact Optical with optogenetics we can we can control the Gap Junctions and we can turn the channels on and off in spatial
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patterns and thus we can imprint new bioelectrical memories into tissues now look now now the next question is well what happens when you do that right what's the what's the evidence that these patterns are actually instructive for anything uh couldn't they just be a
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um a a a readout of housekeeping physiology you know an Epi phenomena how do we know they matter well we know they matter because because now that we have these tools uh we can start to rewrite the pattern I'm going to show you what happens when you rewrite the pattern so
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um one thing you can do I showed you the electric face which has a particular kind of pattern that says that determines where the eye is going to be built well we can recapitulate that pattern somewhere else we can put it anywhere on the embryo that we want when
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you do that uh so you inject in this case we inject an RNA for a specific potassium channel that that sets that that little voltage pattern and wherever those those cells get that information they will build an eye for example they
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might have been gut cells before but if you tell them to build an eye they will build an eye now that those eyes will have all the right lens retina optic nerve all the all the right stuff that um that belongs there um no note the incredible modularity
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this is uh that we we didn't provide enough information of how you build an eye we didn't try to control gene expression levels or all the different stem cells that need to happen or all the different morphogenetic movements we
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didn't say any of that we provided a very simple bioelectrical pattern that serves as a subroutine call all it does is it it it encodes for the rest of the cells it encodes the information build an eye right here and in fact so this is
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a a cross-section through a lens created this way what happens is the blue cells are marked with beta galactosidase they're the ones we actually injected if there's not enough of them to build an eye they will actually recruit their neighbors all this other stuff out here
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that's making this nice lens was never manipulated by us in any way it's only the blue cells that we targeted so so you see one of the competencies here not only is is there is there a subroutine you can call to make a complex organ but
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actually if you don't hit enough cells they will have a conversation with their neighbors and recruit them the way that another collective intelligence for example ants will also recruit their buddies if they come across something that's too big of a job for for the few
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of them it scales to the task at hand automatically we didn't have to do anything for that the body already does it we tell these cells to make an eye and they tell their neighbors that you guys need to participate so that we can all make a properly shaped lens so if
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you do that you can make you can make a topic for brains here this is what a normal frog brain looks like you can make extra limbs lots of extra limbs you can make ectopic beating Hearts you can make ode
00:32:17
assists which are uh inner ear sort of balance organs and you can even make fins now that's interesting because tadpoles aren't supposed to have fins that's more of a more of a fish thing but we'll we'll talk about that and um and you can also you can also use this
00:32:30
technique to repair birth defects so just just kind of very very briefly this is the pattern that indicates what a frog brain should look like and the size and shape of it and um it's got a very particular voltage characteristic if you
00:32:43
sort of scan along this line it kind of looks like this bell curve and what we figured out is that uh there are many teratogens for example nicotine alcohol think fetal alcohol syndrome things like that but what they do is they ruin this
00:32:54
nice uh nice pattern so they'll flatten it out either here or here and in either case you get severe brain defects and so we made a computational model of this process as in what happens to the bioelectrics under various perturbations
00:33:07
and we asked the model if the bioelectric pattern is wrong how would we fix it in other words what channel would we open or close to get the pre-pattern back to the right place so so keep in mind this isn't uh at this
00:33:21
point what we're doing here this is this is rational repair we're not uh taking random shots in the dark we're not um trying to to ruin an existing pattern we're actually trying to use our
00:33:32
computational simulator of bioelectric uh gradients to ask how to repair a complex organ when it's been uh when it's been damaged and and this model uh proposed one specific thing which is
00:33:44
this which is this a very interesting Channel called hcm2 and when you activate these hcn2 channels sure enough uh an embryo that's been that's that here's here's what a normal brain looks like forebrain midbrain hindbrain
00:33:58
um uh this is this is a an embryo actually now now this is this is much worse than being hit with a teratogen this is a a mutation in a gene called Notch Notch is a really important neurogen Genesis Gene if you mutate
00:34:10
notch there is no forebrain the midbrain and hindbrain or a big bubble these animals have no Behavior they just lay there doing nothing uh on top of this mutation if you impose the right bioelectrical pattern and this was done
00:34:22
by opening the hcn2 channel which in turn was suggested by the computational model you rescue brain shape you rescue brain gene expression and you even rescue their IQ so their learning rates and we we check their IQs by by learning
00:34:35
in the training them in various assays they get their IQs back so now this is this is quite amazing and you can do this molecularly molecular genetically meaning meaning yeah put in new hcn2
00:34:47
channels which would be gene therapy or you can do it with drugs that open existing hcn2 channels so these happen to be too anti-epileptics that open the hcn2 channel and you can do this rescue I'm not claiming that that you that this
00:35:00
will work for everything but the amazing thing about this example is that there's a hardware problem they literally have a mutant Notch signaling pathway in which case things go terribly wrong but that Hardware problem is fixable in software
00:35:12
by going back in and telling these cells what the correct pattern is and so and and I think that's very powerful and so so this so that's an example of repairing birth defects here's an example of um some of our regenerative
00:35:24
um some regenerative work because frogs by themselves do not regenerate uh their legs after they lose them but we've we've come up with a cocktail that actually induces a pro-regenerative
00:35:36
blastema with msx1 and then eventually by 45 days instead of nothing you start to get toes and a toenail and eventually a pretty respectable leg that's touch sensitive and motile this whole this
00:35:48
whole interaction with our with our uh um ionophore cocktail took 24 hours and then the leg can grow for a year and a half without us touching it it's not about micromanaging where the stem cells go or what the pattern is it's about uh
00:36:02
communicating to the cell Collective very early on you're going to take the path through morphe space that goes towards leg building not the path that goes to scarring and um and and a stump so we are now and I have to do a
00:36:15
disclosure here because uh Dave Kaplan and I are co-founders of this company called morpheuticals where we're trying to apply that same strategy to uh to mammals and hopefully eventually to to human patients um of course we're quite quite far from
00:36:28
that still but okay so so the summary of of everything that I've said so far is that like in the brain the mechanism that binds cells towards large-scale common purpose meaning to upkeep to
00:36:41
create and upkeep uh against aging against cancer complex organs are specifically bioelectrical networks modifying the information processed by these electrical networks offers some
00:36:53
really uh high level meaning creating new organs fixing complex organ shapes and so on control over growth and patterning without genomic editing without bottom-up trying to engineer all of the pathways that are that are
00:37:06
involved in this the where we're harnessing the the competencies of the system like recruiting other cells like size control shape control and all that and so now and so now here we get um finally to um uh and you can you can you
00:37:18
can read about um all the all the details here but we're finally getting now to uh the part that's directly uh directly about cancer so um if if these bioelectrical signals are important for cancer then then four
00:37:30
things should be true first of all there should be some implication by molecular data of ION channel pumps and proteins in cancer uh bioelectric signatures should be a viable diagnostic tool for
00:37:42
detecting tumors early we should be able to induce cancer like phenotypes by disrupting proper vmem gradients and best of all uh in cancer like phenotype
00:37:55
should be suppressible by the modulation of the mem gradient so these are all these are all predictions of this view that bioelectrics is the mechanism that binds individual cells towards organogenesis and away from the kind of
00:38:07
single cell behavior that we see uh among among cancer cells so these these data now are actually are actually quite quite quite old and I should update this but even and by 2016 it was already seen
00:38:19
there's this there's this kind of uh a very rapid rise of the number of of papers implicating various ion channels in cancer and there are lots of uh bona fide oncogenes implicated in both in
00:38:31
human patients and and in Mouse models and of course in in frog and zebrafish and so on um that uh that are pointing to a direct functional role of various ion channels so this is this is the kind of molecular
00:38:44
biology data you can you can scan databases so so here is uh here's from a from a a a a a Geo database that that looks at the expression of certain channels
00:38:57
during and so you can see here here's a particular ION channel and here it is in normal cells and benign by and then boom by the time you get to malignant uh uh malignant cells it's it tends to be tends to be shut off
00:39:08
so so yes there's evidence implicating ION channel genes and so on in the process of cancer but the genes aren't keen and this is really important we cannot just think about oncogenes the way we think about transcription factors and and growth uh regulators and cell
00:39:22
cycle checkpoints and so on it's the physiological state that matters here and so what I mean by that is I've shown you that that we can we can induce we can take different kinds of Wonka genes uh human oncogenes throw them in a frog
00:39:35
embryo and they and they will create tumors you can detect them early by using this voltage dye and we've we we're of course working on this as a Diagnostics modality because uh you can
00:39:46
see immediately that that the first thing these oncogenes do is they shut down the electrical connectivity between cells and their neighbors as soon as the that that connectivity is shut down these cells are out of the network that
00:39:59
processes large-scale information like hey you should be part of a nice liver or skin or whatever and they're back to a local tiny uh um a set of goals that that their
00:40:11
unicellular ancestors have and so these contrary to a lot of models in in of cancer and Game Theory and so on these cells are not more selfish it's not that they're more selfish it's that their self is tinier it's much smaller it's
00:40:23
now down to their their computational boundaries now down to the size of a single cell whereas before when they were electrically connected into this network they were part of uh something that uh that was working on much bigger projects you know these anatomical
00:40:35
constructions and so you could imagine and this is this is an artist rendering but this is one of the things that we're working on this is kind of like um augmented reality device where you can imagine during surgery the doctors wearing these goggles and they can the
00:40:48
surgeon can see the the area of course but overlaid onto the anatomy is an AI processed probability uh landscape that shows based on the electrical signaling so there's a voltage sensitive dye in
00:41:00
there um and these are these are not you know generally very well well tolerated these days and so you should you should be able to look down and see okay here is here's where the major the major tumors but actually these cells up here are
00:41:12
leaving the the collective as well and and you better you better get them so okay so so that's that's our story of uh of of the diagnostic potential of this uh now here's the second thing I promised which is um can you actually
00:41:25
induce a cancer phenotype uh by disrupting the bioelectric so this is a normal tadpole head these little black cells are mohanocytes and here's what normal the normal complement of melanocytes looks like and what we did
00:41:38
was we disrupted the electrical communication between uh a a very specific cell type we call them instructor cells for obvious reasons you'll see in a minute uh in these melanocytes there are there are no
00:41:51
oncogenes here there are no carcinogens there's no mutation no DNA damage there is nothing wrong with the hardware of these of these animals they haven't been exposed to any any carcinogens is there's nothing wrong with them except
00:42:03
that we've uh temporarily uh perturbed the community the communication between between these these pigment cells and this other cell population when you do that the pigment cells go completely wild they over proliferate you can see
00:42:17
here they've taken over like this normal periocular space that's normally quite clear they've taken over there everywhere in fact these animals turn pitch black there's melanocytes everywhere if you take a section through them this is the neural tube here and
00:42:28
you can see one two three four these small numbers normally a normal embryos small numbers of these nice round little melanocytes well when the bioelectric signals aren't there to tell them what to do they go crazy they revert back to
00:42:41
their original kinds of behaviors they they change shape drastically they acquire these long projections they're exploring their environment they're digging into the neural tube to the um to the nerve tissue itself to the Lumen
00:42:54
inside the space they they just invade all the organs here you can see the blood vessels so normally quite clear these blood vessels here we go the melanocytes are are hitting the the vasculature and propagating through it
00:43:06
this is basically a full-on metastatic melanoma in these guys um there's nothing there's nothing there's there are no genetic defects there are no if you were to sequence the The genome you would not see any any
00:43:19
mutations nothing like that although by these by by this stage you will see things like um uh markers of uh of epithelial and mesenchymal transition and things like that um now uh the the and and so this works
00:43:33
also in human melanocytes exactly the same way they will go completely crazy if you if you uh disrupt their their biological State now now here's the most interesting thing to keep in mind um here's again the cross section and here are these crazy melanocytes that
00:43:46
are digging in and taking over the brain and so on um these are not the cells that we manipulated these blue cells out here are the ones that we manipulated this is not a cell autonomous event meaning that
00:43:58
the thing that goes crazy is not this the the the cell whose voltage has been perturbed it's other cells in the environment it's the importance and of course I'm not the first person to talk about the importance of the micro environment but in particular the
00:44:10
bioelectrical properties of the micro environment are the switch that leads from normal melanocytes into this crazy uh converted melanoma-like Behavior and and the way it works and I won't have to I won't have time to go through
00:44:22
all this but it's actually a certain urgic signal that normally goes from these instructor cells to the melanocytes and if you perturb the bioelectrics of this instructor cell that if serotonergic process goes awry
00:44:36
and and these these melanocytes are left on their own and they do what they do they over they what they do whatever amoeba does they over proliferate they crawl whether they feel like they take over the the environment and and we've studied um in great detail on this this
00:44:49
whole serotonergic pathway and the downstream gene expression and then the the gene regulatory Network and so on but but but the uh the importance of this part of the talk is is this um
00:45:00
this uh one way to get cancer I'm not saying it's the only way but but one significant way to to have a carcinogenic transformation is to uh have cells that are isolated uh from the
00:45:14
electrical information that normally keeps them orchestrated towards uh towards proper functionality and more for Genesis and so on and um in oncogenes trigger this but there are other ways uh there are other ways to trigger this okay so so the final thing
00:45:27
I want to show you is and the thing that we actually want we don't want uh to create more more cancer obviously we want to we want a treatment modality so so here so so here it is so so one of the things we can do is we can inject these oncogenes even nasty KRS
00:45:40
mutations and so on um the oncogene is labeled with fluorescent red protein in this case tomato so you can see it uh here it is and what we know is that if we co-inject a particular ION channel
00:45:51
RNA that we've chosen to resist to to basically fight so so what this oncogene is going to do is it's going to try to tell the cells to uh depolarize and disconnect from their neighbors the this ION channel is going to dominate that
00:46:04
and it's going to say fine you have the oncogene uh but but you're not going to be able to depolarize we're going to keep you connected to all of the neighbors so so here this is the same animal so so here's the bolus of of
00:46:15
where the onco protein was expressed in fact it's all over the place you know there's design there's a few sequence this and you say wow this thing is full of um this this oncogen definitely going to make a tumor and there is no tumor because what drives the outcome is is
00:46:29
not the the genetic State it's the physiological State and if you manage now I've already shown you an example of this I've shown you um in the in the Frog brain right you could have a notch mutation and if you sequence it the prediction would be why you're going to
00:46:41
have terrible defects but that's not actually what drives what drives is the bioelectric state and so so you can override this this Hardware defect with a particular physiological State and then and then these same cells they're
00:46:52
not dead they're not they don't die they they just continue participating in normal morphogenesis now you can do this with light here's an example of optogenetics so so we just use optogenetic technology that we that we
00:47:04
took from from neuroscientists and you can you can knock down the incidence of of these tumors significantly by using light to trigger the right kind of channel in fact um here is here's a normal tackle and
00:47:17
here's the tail whether you get a tumor and and this the you know these kind of metastatic events whether you get a tumor or whether you get an ectopic eye is determined by the amount of sodium in the medium because in this case we were
00:47:29
using a sodium uh ION channel to do this and the sodium ion channel it's not like a transcription factor that always has the same effect it's a it's a physiological um uh it's it's an element of physiology
00:47:42
that that in part its activity is depends on how much sodium there is so whether you get a tumor or an eye is actually determined by a physiological parameter namely how much sodium is in the medium not at the level of DNA
00:47:54
damage or anything like that and so putting putting all this together our um uh kind of our our framework for for addressing all this is is uh this this idea of electroceuticals of using
00:48:06
existing ION channel drugs with our computational models that tell us what's going to happen when you open and close certain channels you know which channels there are because of course human tissues are extensively profiled so that
00:48:19
feeds into the model the one thing that is largely missing today is the physiomics of what are the correct bioelectrical States for all the organs we actually have no idea for for humans um and we only know this for certain
00:48:30
animal model systems so so this is where a lot of the work has to happen is actually to understand what the correct bioelectrical state is but then we have a simulator that can tell you how to get from the wrong state to the correct State and that helps you pick from from
00:48:43
existing from a huge Library something like 20 of all drugs or ION channel drugs it's a potentially a huge library of electrocuticals and so you can you can play with this a little bit this is uh this is online uh kind of our the
00:48:56
beginnings of this of this platform it's it's uh you know freely accessible you can pick different types of uh tissues you can you can pick um you know either cancers are normal it will tell you what channels there are if you uh pick
00:49:08
specific channels it'll tell you what drugs because because you can search of drug bank and so on uh it'll tell you what uh what what drugs you might want to use and so we've begun this process so now moving this from from frog and
00:49:19
and so on this is this is our first um uh uh paper on on the human glioblastoma it's in vitro and what we're using is some of these drugs that uh that that were picked by this process that I just
00:49:31
told you on uh glioblastoma cells and and there are all kinds of interesting um effects in terms of uh uh preventing proliferation in terms of partial uh reprogramming to so so differentiation
00:49:43
possibly normalization so stay tuned this is very much work in progress and of course we need we need in Vivo experiments but we're slowly moving now into uh into a mammalian uh context so
00:49:55
so so here's the here's the summary of the whole thing uh cancers are fundamentally a disorder of the scaling of cellular competencies uh individual cells can get certain goals met for
00:50:08
example overgrowth and migration but in normal bodies they are they are kept harnessed towards much larger sort of grandiose anatomical goals but this process can break down and that process is mediated by bioelectrical signaling
00:50:21
which is why by electrics can be used to detect induce and reprogram uh cancer cell behavior um just like in the nervous system we can instruct cell Behavior without
00:50:34
having to change the genome this is also true in in learning and and all the amazing things that nervous systems do they don't you don't need to change your genome to learn new things or to acquire new goals and so on and we are now
00:50:45
developing pharmacological and Optical strategies uh towards discovery of electroceuticals for normalizing cancer and and there's a huge role for machine learning and Ai and so on but also for
00:50:57
getting this physiomic data that basically um has has been neglected in uh in favor of uh transcriptomics and proteomics and so on so so the future directions what what we and our partners are working on
00:51:10
is to refine that physiological signature so Optical non-invasive diagnostics for pre-cancer and also tumor margins and surgery to refine control methods for voltage in in
00:51:21
mammalian systems and uh specifically the bigger picture here is to crack the bioelectric code to induce normalization towards normal tissues and organs using iron Channel drugs that are already in human use meaning they're already
00:51:34
approved so I will stop here I want to thank the students and postdocs that did all the work uh our many collaborators um our technicians our our funders I
00:51:46
have to do two disclosures so morpheuticals is the limb regeneration company astonishing Labs is a company that we're doing all the cancer Diagnostics with um and uh most of all uh thank the animal model systems because they do all
00:52:00
the heavy lifting so thank you and I will take questions
End of transcript