The Peter Attia Drive - July 15, 2019


#62 - Keith Flaherty, M.D.: Deep dive into cancer—History of oncology, novel approaches to treatment, and the exciting and hopeful future


Episode Stats

Length

2 hours and 57 minutes

Words per Minute

194.67958

Word Count

34,537

Sentence Count

2,080

Misogynist Sentences

22

Hate Speech Sentences

14


Summary

In this episode, Dr. Keith F. Flaherty, Director of Clinical Research at the Massachusetts General Hospital in Boston, joins me to talk about his work in immunotherapy and cancer research. Dr. F. Keith is a physician scientist at the Mass General Hospital and focuses on the understanding of targeted therapies in cancer.


Transcript

00:00:00.000 Hey everyone, welcome to the Peter Atiyah drive. I'm your host, Peter Atiyah. The drive
00:00:10.880 is a result of my hunger for optimizing performance, health, longevity, critical thinking, along
00:00:15.940 with a few other obsessions along the way. I've spent the last several years working
00:00:19.660 with some of the most successful top performing individuals in the world. And this podcast
00:00:23.620 is my attempt to synthesize what I've learned along the way to help you live a higher quality,
00:00:28.360 more fulfilling life. If you enjoy this podcast, you can find more information on today's episode
00:00:33.000 and other topics at peteratiyahmd.com. Hey everybody, welcome to this week's episode
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00:03:22.660 and also getting to hear these podcasts when they come out. Lastly, and this is something I'm really
00:03:28.000 excited about. I want my supporters to get the best deals possible on the products that I love.
00:03:32.800 And as I said, we're not taking ad dollars from anyone, but instead, what I'd like to do is work
00:03:37.360 with companies who make the products that I already love and would already talk about for free and have
00:03:43.220 them pass savings on to you. Again, the podcast will remain free to all, but my hope is that many of
00:03:51.000 you will find enough value in one, the podcast itself, and two, the additional content exclusive
00:03:57.880 for members to support us at a level that makes sense for you. I want to thank you for taking a moment
00:04:02.960 to listen to this. If you learn from and find value in the content I produce, please consider
00:04:08.480 supporting us directly by signing up for a monthly subscription. My guest this week is Dr. Keith
00:04:13.940 Flaherty. Keith is a physician scientist at Massachusetts General Hospital in Boston,
00:04:17.980 where he's the director of clinical research, as well as targeted therapies. His research focuses
00:04:23.000 on the understanding of targeted therapies in cancer. And if that term is a bit nebulous to you,
00:04:27.600 don't worry about it. We define it quite clearly. And he focuses on the development of responses and
00:04:32.460 predictive biomarkers to define the mechanisms of action and resistance of novel therapies.
00:04:37.060 He's researched a lot of stuff in immunotherapy. So this is really the first podcast that I discuss
00:04:43.220 immunotherapy in, which for me is super exciting because I've been looking forward to discussing this
00:04:47.740 topic for quite some time. And you'll see why when we get into it, because immunobased therapies
00:04:53.220 are basically the most exciting recent development in cancer therapy. And we talk quite a bit about
00:04:59.120 these checkpoint inhibitors for which actually the Nobel prize in medicine and physiology was awarded
00:05:04.020 last year. He's been a PI in a too numerous account first in human clinical trials using novel
00:05:09.580 therapies. What else can I say? He's a professor of medicine at Harvard medical school and serves as
00:05:14.560 editor in chief of the journal clinical cancer research. Overall, Keith is really a wealth of knowledge
00:05:19.880 in cancer. We talk about a bunch of stuff. Now, honestly, the first 20 minutes, we're just talking
00:05:25.960 general life medicine. We don't even touch on cancer. So if you're short on time and you really just want
00:05:33.500 to get into the stuff on cancer, definitely jump ahead to 20 minutes into this stuff. We talk quite a bit
00:05:40.460 about the history of chemotherapy, what its successes were, why they asymptoted, same with radiation
00:05:48.520 therapy, surgical therapy, and ultimately what took place and what didn't take place, maybe more to the
00:05:55.140 point in the period of time between when the war on cancer was declared in 1974 and the sequencing of
00:06:00.880 the entire human genome about 25 years later. And then we talk about what took place in the two
00:06:05.140 decades since that time. And you'll see that, well, at least even for me, I think you'll tell, I was
00:06:10.180 actually learning quite a lot here vis-a-vis how some of those changes took place. And again, for that
00:06:15.160 reason, this was a highly enjoyable experience. Even if not one person listens to this podcast, I got a ton
00:06:19.880 out of it. We basically got into this notion of what's a different approach to cancer. And again,
00:06:26.020 clinically, I found this very helpful because this is a problem I think a lot about. So I do think
00:06:30.480 people will enjoy this. We talk a little bit about liquid biopsies, even touch on roles of potentially
00:06:36.180 CRISPR and overhyped with respect to cancer therapies, potentially even at the end, talk about stem cell
00:06:43.360 therapy, vitamin D, melanoma, sun exposure, the list goes on. This is a pretty long episode. So
00:06:49.940 hopefully we talk slow enough that you can listen to it at a slightly higher speed. And the show notes,
00:06:55.100 as always, will contain a ton of information, not just links to the studies we talk about, but a lot
00:07:00.420 of the semantics. I wouldn't be discouraged if you find this topic and particularly this episode to be
00:07:06.820 somewhat challenging based on how technical it gets at times. I think we both do a pretty good job
00:07:12.140 of remembering that we're not just talking with each other. And I try to ask questions to bring
00:07:17.080 us back 30,000 feet and focus on the big stuff. But in many ways, I think this will be probably the
00:07:22.840 deepest podcast I've done to date on cancer, though certainly not the last. So without further delay,
00:07:27.980 please enjoy my conversation with Dr. Keith Flaherty.
00:07:33.740 Keith, thank you so much for letting me intrude in the middle of your living room on a rainy Monday
00:07:40.040 afternoon. My pleasure, Peter. Is this normal Boston April weather?
00:07:43.660 This is the wet season, mud season as they call it, but it's a welcome break from winter. Hasn't
00:07:49.240 been a particularly harsh one, but yeah, it's a good transition time. It was brown last week,
00:07:54.600 so everything's just finally waking up. Now you've pretty much spent your whole life
00:07:59.840 from basically Connecticut to, or actually Connecticut south of Boston, right? So
00:08:05.720 sort of basically Boston to Baltimore has been most of your life.
00:08:09.520 Yeah.
00:08:09.540 That's right. Born and raised in Baltimore, broke away to boarding school in Massachusetts for four
00:08:14.480 years, Connecticut for college, four years, then back to Baltimore, four years in medical school,
00:08:19.420 Boston for the first time, three years of residency, and then Philadelphia for nine years,
00:08:24.940 which was both medical oncology fellowship and my first faculty stint. And now 10 years ago,
00:08:30.840 moved back up to Boston to Mass General. So this fall will be 10 years, but as you say,
00:08:35.960 Northeast quarter through and through.
00:08:37.460 Yeah. Well, you get your seasons, right?
00:08:39.600 Yeah. That's always my defense of the Northeast to Californians is I need the seasons. And certainly
00:08:44.940 during my educational years, I always thought if I had San Francisco, LA, or God forbid, San Diego,
00:08:50.580 weather, I'm not sure I really would have been able to keep my nose to the grindstone. Seasons are good
00:08:55.140 to kind of force you inside and take your breaks when you need them.
00:08:59.020 Well, I think there's something else about it that I sort of lament. Both my wife grew up in
00:09:02.460 Baltimore. I grew up in Toronto. And there is an intestinal fortitude that comes from being in a
00:09:06.380 climate that is not particularly hospitable. You get a little tougher as a kid, I think,
00:09:11.740 when it's, you have to pay attention. Like if you forget your gloves, like you're hosed.
00:09:15.880 Yeah. You're going to pay for it.
00:09:16.720 Yeah.
00:09:16.980 I suppose that's true. I think resilience comes from a few parts of one's upbringing, but
00:09:21.480 climate is probably, you're right. It's at least a bias of mine that it's a good thing to have.
00:09:26.280 Even as the years keep passing and I think about, well, where would I want to spend the next 10
00:09:30.880 years, 20 years beyond? I love it up here. I mean, for me, it's really the, it gets just brutal
00:09:36.220 enough in the winter, but not Canadian brutal.
00:09:38.520 Although Boston is its own little, Boston and Toronto are not that different.
00:09:42.460 Oh, okay.
00:09:42.940 Yeah. Montreal might be worse.
00:09:44.460 Yeah. I've just had more figuring latitude drives harshness of winter. I have more respect for
00:09:49.220 Canadian winters, but maybe it isn't that different. I feel like, again, just gets harsh enough.
00:09:53.200 And then in the summertime, get the payoff for the flip side, which is just so pleasant,
00:09:57.300 but not like Baltimore burdensome in terms of the heat and humidity.
00:10:00.500 So you're kind of one of these guys who was exposed to medicine throughout, right? But I know
00:10:04.880 your father is a physician. Your mother was as well, right?
00:10:06.880 Yeah, that's right. My father was an academic cardiologist for 25 years and then almost an
00:10:12.040 equal stint in industry, pharma and biotech. And my mom was an academic psychiatrist, actually
00:10:16.920 really still is at the age of now 70, will be 76 end of this month. Very different career in
00:10:24.080 psychiatry versus cardiology, but an academic career nonetheless. So a bit of research, a lot of
00:10:29.740 teaching, mentoring, and that bit continues. She has incredible stamina for staying connected with
00:10:34.700 her field. She's retired from patient care a good long time ago, but couldn't give up the rest. And so
00:10:39.980 continues to haul herself off to conferences and oral examinations that are still required for,
00:10:45.380 for psychiatric boarding and so on. So kind of a inspiration in terms of longevity in the field.
00:10:51.280 You knew pretty early that you wanted to go into medicine or was that not even clear when you went
00:10:54.800 off to college? Yeah, no, it wasn't clear to me at all. I mean, I honestly would have to admit that I
00:11:00.260 didn't really understand how my parents' worlds turned. They were perfectly transparent and happy to
00:11:05.280 talk about their careers. I just didn't know to ask the questions. The two older brothers who then and
00:11:10.340 now had no interest in science or medicine. I guess all that I could say from a young age,
00:11:17.740 maybe by the time I was in boarding school and going to college, was that some way, somehow I
00:11:24.000 wanted to help people. This is a phrase that I recall saying, but I had no idea what that might mean
00:11:29.640 and what the different versions of it were. As years passed, I got more and more of the sense that
00:11:34.980 a lot of how the world turned was kind of transactional business transactions, I suppose,
00:11:40.680 people making careers on some version of transaction. I had this aversion, or developing
00:11:45.380 this aversion to that idea that I didn't want to be involved in what I broadly construed to be
00:11:50.820 business. Now, we'll come back to this later. I was about to say the irony, but okay.
00:11:54.860 Absolutely. I'm laying that right out there for you. There's so many ways in which I turned on that.
00:11:59.900 I mean, in a good way, I've turned on those initial principles. But yeah, in any case,
00:12:04.680 I thought this idea that I needed to find a path where I felt like I was very directly helping people
00:12:09.960 was going to be the most sort of satisfying career and something that would get me out of
00:12:13.980 bed in the morning without having to really try. That part, I'd say, really did work out.
00:12:18.540 So I think that's probably the one piece that I think I did get from my parents. So I didn't know
00:12:24.320 exactly what they did when they got to the hospital.
00:12:26.900 But you had some sense that it involved people and they were in probably a more direct way of
00:12:32.160 helping them. I mean, you could argue most people are helping people in some way, but you knew that
00:12:35.760 there was fewer degrees of separation. That's right. And then that final point that they were
00:12:40.320 super motivated by their careers, it was never a complaint. There was one thing about their marriage
00:12:44.860 they would talk about just inside baseball of division department, hospital level politics and
00:12:51.740 issues that were kind of headwind for them. And you hear them talk about their real mechanistic
00:12:59.360 elements of their careers. And it just was never a complaint about it. They were very kind of focused
00:13:04.480 on results and group dynamic and so on. But I guess my point is that you never had a notion that they
00:13:10.780 did not love what they did. And end of every vacation, end of every weekend, I mean, they were just
00:13:15.700 like hard charging back at work. My parents, because they were both building academic careers
00:13:20.220 when we were young, they were oftentimes alternating evening duty. One of them, even for a whole week
00:13:25.880 at a time, tied up either on service or something that was keeping them in the hospital. So watching
00:13:30.780 that conviction and how much they just loved doing that thing that I didn't understand, that was
00:13:37.020 probably the very nebulous notion that I kept with me. So that as I kept kind of crossing off like
00:13:43.640 vast segments of American economy had to offer in terms of careers, medicine's kind of the thing
00:13:48.940 that remained. Yeah. It's an interesting point you raise about the fine line for parents in terms of
00:13:54.680 the example setting versus the time there. I mean, both are really important, right? I mean, I know
00:13:59.080 this now. I have kids, met your daughter earlier. There's in some ways no substitute for this term
00:14:03.620 quality time sort of always struck me as a little bit of a hoity-toity term. I mean, there's time and
00:14:07.740 there's no time, right? But call it quality time. And there's no substitute for that, but there's
00:14:11.960 something to be said when a child sees their mom or dad feeling incredibly passionate about what
00:14:17.360 they're doing and how without saying a word about that, it sets an exam. Yeah. I hear my daughters
00:14:23.940 talk about this in relation to my wife. She's an internist at Mass General and she's part-time,
00:14:29.600 but because of Epic, the electronic medical record, she's full-time and then some because for every
00:14:34.600 minute she takes care of a patient directly, she's taking care of their medical record for three to
00:14:38.480 five minutes easily. That sounds like an excellent ratio. Yeah. And of course the kids see that side,
00:14:43.400 right? Because they're not with her in the hospital, but they see the constant overflow.
00:14:47.420 They know what she does in principle and internists, I guess, maps to a pediatrician. They have direct
00:14:53.420 experience with that, but they watch her pour herself into the indirect care of patients through the
00:15:00.000 electronic medical record and constantly reflect that she's the hardest working person they know.
00:15:04.220 And that example, like this, that kind of willingness to like give, give, give outside of
00:15:10.120 one's personal time, family time, it's related to what I was trying to put words to, but this very
00:15:16.520 nebulous notion of what it is that qualified as a satisfying career. I've spent my adult life,
00:15:22.300 particularly raising kids, making this comment that in my imagination, a number that I often comes back
00:15:29.340 to is like 95% of people don't like what they do. And they're just holding their breath, trying to get
00:15:33.760 to the weekend or vacations. And maybe I'm vastly off base, but I guess I'm partly using a high number
00:15:39.340 like that because I just feel incredibly fortunate to have been brought up in a household and educational
00:15:45.840 environment serially that my parents made available to me that allowed me to be in that, what I think is
00:15:51.040 a relatively small group where I just always loved what I did and just, and felt like I had absolute
00:15:57.140 choice and could engineer my schedule in every respect in a totally sort of suicidal, not respectful
00:16:06.120 of balance way. I mean, I just developed a career that was ridiculously off the rails in terms of
00:16:11.340 being overcommitted and trying to juggle way too many things in some respects. For me, I would defend
00:16:17.580 it also and say it was exactly the optimal amount of chaos that one needs to really feel like you're
00:16:24.300 kind of pushing on all fronts simultaneously. But, but how do you both find the, the outlet and
00:16:29.740 define the scope of a career that allows you to do that? Man, what a challenge and what a different
00:16:33.880 challenge I think that our children will have versus what it was like to try to build a career
00:16:38.700 in this case in medicine starting decades ago versus what they're looking at.
00:16:43.120 And medicine still may be one of the slightly easier places to do it because the path to quote
00:16:48.760 unquote academic success, non-academic clinical success, it's still relatively unperturbed from
00:16:54.800 so many other paths, right? Outside of medicine. Or is that not even true anymore?
00:16:58.200 I don't see it that way, but I'd be interested in your perspective as a surgeon, because I think
00:17:01.920 maybe we have a different angle on that being in medicine versus surgery, which obviously culturally
00:17:06.480 we've always had some real differences, not just culturally, sort of skill sets. So the thing that
00:17:11.860 I've been deliberating on, let's say this, I've had a 20 year oncology career, almost 20 years,
00:17:16.700 a few months away from that. And so I divide my career up into these two decades and I've watched
00:17:21.960 technology advance and the field-wide body of knowledge accelerate in a 2000 to 2010 interval
00:17:29.160 and then these past 10 years. And this is true in so many areas of technology advance, but in
00:17:34.180 biomedical research and in cancer, which is my only area of any expertise, I thought 2000, 2010 was
00:17:40.980 mind-blowing and I thought we were going to spend time catching up with the mind-blowing advances.
00:17:45.820 That was my talking point coming into the field in 2000, that I thought we've got this huge wave
00:17:51.180 of molecular insights, mostly genetic insights in terms of cancer that had built up, but hadn't
00:17:56.140 been transformed into medicine. That was my unbelievably naive, simple-minded pitch as I
00:18:00.140 was entering the field. And I said, I want to make myself useful in that translation of science
00:18:04.180 to medicine. Anyway, 2000, 2010, then you could say we're the first chapter of translating molecular
00:18:09.420 insights into medicine and oncology. Well, 2010 to 2020 makes that first decade look unbelievably
00:18:16.140 slow. And where it was every two years, there was maybe a monumental event, whereas now it's like six
00:18:23.160 at a time. So that's in terms of like crossing the finish line, but in terms of data generation,
00:18:28.400 ability to produce high-dimensional data, analyze it, try to make sense of it, raise hypotheses,
00:18:32.900 test hypotheses. Yeah, the cycle time is changing a lot. And the constituents that we now need to
00:18:37.840 interact with are totally different. The point I'm coming to, to answer your question, is I see
00:18:42.680 medicine now as this terrifying arena in which to try to assemble a multi-decade long career. Like,
00:18:49.120 how do you keep yourself relevant in a, let's say, 40-year arc? Here I am at 20 years and feel like I'm
00:18:55.800 an absolute dinosaur. Mentoring is the thing that I think I can still do with some relevance to the
00:19:01.640 younger generation. And in mentoring them, I tell them, look, you need to learn how to talk to a
00:19:07.120 bioinformatician, computational biologist. I couldn't have even imagined 10 years ago that I'd
00:19:13.600 be telling my mentees that, much less that I would have this notion that I need to understand
00:19:18.020 the world from that degree of mathematical modeling complexity. But it's having now mentees
00:19:24.460 who were in computational biology myself, I've come to realize that it's, I didn't have the skill set at
00:19:30.320 the dawn of my career. Is it possible for people, broadly speaking, to actually retrain themselves and
00:19:36.800 grow a new lobe of their brain? It's possible, but it's going to force a totally different
00:19:41.700 paradigm in terms of how one thinks about taking breaks, taking sabbaticals, gaining that knowledge
00:19:47.440 base. So I was actually thinking of something different, but what you're bringing up is more
00:19:50.760 interesting. So I want to double click on that before we jump into the meat of what we're going to
00:19:54.960 talk about. Based on the way you're describing it, Keith, I would say doctors coming out of training
00:19:59.620 are hosed because medical school, and I'm going to really make a lot of enemies by saying this,
00:20:04.240 but I guess it's my podcast I'm allowed to say this. I think medical school might be one of the
00:20:07.920 most anti-intellectual forms of higher education that exists. I mean, when you contrast it with even
00:20:14.220 the experience that many people have in college, where you really get to think creatively, you really
00:20:18.980 get to problem solve, you really get to explore the limits of what is known and what is not known and ask
00:20:24.180 questions, not having gone to law school, but my brother did. I got to see my brother do that in
00:20:29.080 law school, having more friends than I can count who did PhDs in everything from the humanities to
00:20:34.700 the sciences. They got to do that. Well, I went to a good medical school, but that's not the way my
00:20:38.560 education was. And I'm not sure it's that much more like it today. In other words, I'm not sure
00:20:42.360 medical school teaches you how to be a thinker or a problem solver, or even, and maybe again, I hope
00:20:48.600 I'm wrong. But if you don't learn how to learn and God forbid the people who go into medical school
00:20:54.920 as pre-meds. So then they've missed out on at least taking an engineering degree or taking a
00:20:59.520 humanities degree where you would have got some of that stuff. So, so yeah, then I think you're in
00:21:03.560 real trouble. I totally agree with you. And the word that you didn't use that I'll use is
00:21:07.920 investigation. That's not taught. And at best it's taught in a retrospective field-wide
00:21:15.280 introspective way. And by that, I mean like diagnostics. I mean, thinking about how to
00:21:19.280 diagnose illness in medical school is the beginnings of teaching that concept.
00:21:24.620 I actually tell people the one type of statistics that physicians get very well trained in without
00:21:29.860 explicitly being told what they're doing is Bayesian statistic, because that really is
00:21:34.120 clinical medicine. Clinical medicine is pure Bayesian statistics. It is learning how to update your
00:21:40.840 pre-test probability with new information over and over again. And the reality of it is that doctors get
00:21:44.660 very good at that. It's never codified and formalized such that they understand that that's
00:21:48.660 actually what's being taught. Yeah. Although contaminated by bias as in recency bias, right?
00:21:52.640 So this is, I mean, there's a huge issue in the practice of medicine that you're so clouded by the
00:21:57.240 last few outcomes. Your participability is not as accurate as it could be if you were able to
00:22:01.680 eliminate it. Going back to that point that medical school, it teaches information as fact. It teaches
00:22:08.080 the known, that known unknown divide is exactly, it's my pitch in academic medicine, at least talking to
00:22:14.340 people about cancer as a career. I tell them, look, it's so simple to find the boundary between what's
00:22:20.340 known and not known. There's so much out there we don't know. And in any area of trying to understand
00:22:24.680 physiology, pathophysiology in the mode of cancer, you will so quickly get to that frontier. And then
00:22:30.720 how do you operate in that frontier? Like once you're there, how do you help the patient in front
00:22:35.160 of you, the next wave of patients that are coming in the not too distant future, and then like a full
00:22:39.280 generation out, how do you help across that gradient? Well, investigation is the only way you can pose
00:22:45.280 yourself as being helpful. And that, I didn't get that in medical school, sadly, even though I was at a
00:22:50.680 fantastic environment for learning the archival version of medicine.
00:22:54.720 That's a great way to distinguish, right? I mean, you go to a place like Hopkins, you're going to get the
00:22:58.340 best archival education imaginable. You're walking through the halls where the actual profession came to
00:23:05.000 North America. And I actually, it was one of the things I cherished when I was there. And the few
00:23:09.840 books I brought with me out of medical school, surrounding myself with books that are not
00:23:14.120 medicine as a general sport, were the history of medicine. I mean, Osler particularly, I thought was
00:23:19.680 absolutely an Aristotelian figure. So I thought those are the roots and we have to figure out how to
00:23:25.120 reimagine ourselves like those great builders of the medical discipline. So it was very retrospective.
00:23:30.720 And it wasn't really honoring the notion that everybody in the field, particularly these big
00:23:36.320 academic centers that are given tons of resources to investigate, can and should see themselves as
00:23:41.120 being absolutely on the frontier. It's a more dynamic frontier now than ever before, mostly because
00:23:45.940 the sensing technology, to be able to actually understand what's wrong in the system. And when
00:23:50.980 you perturb the system with a therapy, how the system responds, cancer is such a great example of this.
00:23:55.320 Our sensing technologies have just gone berserk in terms of the acceleration. So there's just so much
00:24:02.000 more that one can learn. But again, this is the concept that only, even in my oncology training,
00:24:07.180 I didn't get that. My oncology training was the same notion of learning about how we got here over
00:24:11.900 decades. Well, my talking point going on oncology was that I was right at this end of the conventional
00:24:17.720 chemotherapy era, as I was calling it, and the beginning of the so-called molecularly targeted therapy
00:24:23.040 era. But it hadn't happened yet. And so I wasn't interested in learning about the past.
00:24:27.260 So in other words, you could see that the futility of chemo, which basically had made minimal progress
00:24:31.680 over 40 years.
00:24:32.480 Would have reached an asymptote, right? So you basically, if you blindly develop drugs against
00:24:37.200 cancer cells to find out what's poisonous to them, and then you filter those in mice to see what kills
00:24:42.840 the mice at equal concentrations versus what doesn't quite kill them, and you call that your possible
00:24:48.360 therapeutic, what will you get out of that? This is one of my first lectures that I used to give to
00:24:52.540 medical students about cancer therapeutics as I was trying to outline a path forward,
00:24:57.300 is that basically what you get out of that is all these agents that tangled the DNA
00:25:00.000 and some microtubules stabilizing and destabilizing drugs. And the blind approach only gave those types
00:25:06.280 of therapies. Those types of therapies then thrown at cancer cure a good fraction of testicular cancer,
00:25:12.440 a respectable fraction of lymphomas and leukemias, and cure almost nothing else.
00:25:16.220 Let's pause there for a moment because we're going to just dive right into cancer. But in the spirit of
00:25:20.480 being true to the history, let's just reproduce what you said. So let's take a step back. Many
00:25:25.640 people listening to this certainly hear the terms chemotherapy, radiation therapy. It might be a bit
00:25:31.760 of a fog beyond that. So what you just described was chemotherapy, and what you just described was
00:25:37.360 an arbitrage that must be true. Chemotherapy, it's not hard to kill a cancer cell. It's actually very
00:25:43.260 easy to kill a cancer cell.
00:25:44.260 Yeah, bleach does a fantastic job.
00:25:45.400 Bleach, formaldehyde, go to Home Depot. Most things on the shelf kill cancer perfectly. Problem
00:25:50.080 is they kill everything perfectly. So the arbitrage you described eloquently is it has to kill cancer
00:25:56.800 and almost kill, but not kill, not cancer. So that's a narrow subset of things. And as you described it,
00:26:04.680 they're targeting DNA for the most part, which is why they're targeting things that grow, which is why
00:26:10.180 when most people think of a patient on chemotherapy, the first thing they think about is their hair
00:26:14.360 has fallen out. They've got sores in their mouth. Their nails are brittle. And if you look a little
00:26:19.320 deeper, you'll understand that their gut is really falling apart. What's common to all those things,
00:26:23.540 right?
00:26:23.760 And their bone marrow cells.
00:26:24.640 Yeah.
00:26:24.760 Yeah. Rapidly dividing bone marrow cells. That's exactly right. So the analogy I oftentimes use
00:26:29.080 with patients about talking about chemotherapy is it's bicycle going down the road slowly,
00:26:34.340 one bike going very quickly, one going very slowly. So the cyclist in this case being the
00:26:38.900 determinant of that. And you're standing between two cars with your broomstick and you come out to
00:26:45.120 throw your broomstick in the front wheel of those two bicycles. One of them goes ass over tea kettle
00:26:50.260 and the other one looks at you and says, what are you trying to do here, punk? And it's that fast
00:26:56.220 growing cell concept. It's that filtering system of what can kill a fast growing cell. That's what
00:27:02.800 generated those hits. We could have come up with other hits potentially. It's a chemical diversity
00:27:08.040 of probes that were used were broader. Maybe other hits could have been found.
00:27:11.540 For example, we didn't really look at metabolic distinction between them beyond DNA. That Warburg's
00:27:16.840 stuff left behind, we'll come back to it later, but you're right.
00:27:20.000 How to manipulate it particularly was completely lacking. This concept of you take cancer cells,
00:27:24.400 you establish this mind-blowing ability to grow them outside of a patient and create so-called
00:27:29.220 immortalized cancer cell lines. Henrietta lacks cervical cancer being a paradigm example out of Hopkins,
00:27:33.820 but eventually dozens to hundreds to now thousands and hundreds of thousands of these cell lines.
00:27:38.980 Which ones take in plastic versus which ones don't? Well, there's definitely a fast versus
00:27:42.940 slow cell growing just by cancer type. And then within the cancer cell population, which is always
00:27:47.640 heterogeneous, you've got faster and slower growing varieties there too. And the ones that take are
00:27:53.060 these hot rod cells. And if you then use that as your filtering mechanism to ask, well, what will kill
00:27:58.800 them? What you come up with are these toxins to rapidly dividing cells. That's exactly right. So
00:28:02.960 that caps. The term chemo, when I use it, is always to describe these things. Now, important piece of
00:28:09.860 nomenclature is that people will still always say that, well, a cancer therapeutic is a chemotherapy.
00:28:14.940 Right. But no, I favor the way you think about it. I like to think of chemo as that type of chemical.
00:28:20.680 Immunotherapy is used chemicals, but they're totally different, right? Metabolic therapies, PI3K inhibitor,
00:28:25.160 I'm not really considering that chemo, but I want to put a point on what you said, because it's sad,
00:28:29.860 but it's just the reality of it. So when Nixon declares a war on cancer, it's what? It's about 72,
00:28:35.460 74. 74. Okay. If you look at 10 years survival for metastatic solid organ tumors, so I'm going to
00:28:44.360 just take out leukemia and lymphoma. And as you pointed out, we have seen success in some of those,
00:28:50.020 and we'll come back to it. From a solid organ metastatic perspective, from 74 until 10 years
00:28:57.380 ago, isn't testicular the only success? Maybe, and GIST? Yeah. Yeah. GIST was an early targeted
00:29:03.120 therapy success. So testicular, basically seminobinous testicular tumor. That's right.
00:29:06.980 You could cure with doublet chemotherapy. You could cure the large majority, greater than 90% even.
00:29:11.800 But if a woman had metastatic breast cancer in 1974, and a woman had metastatic breast cancer
00:29:16.020 40 years later. Shockingly a little difference. I mean, we had median survival extensions of maybe
00:29:20.920 six months, 12 months. Yeah. Per new therapy that might come along at best. And then you could stack
00:29:25.420 a few of those in a disease like breast cancer. So what actually kills the population of cancer,
00:29:30.600 breast, colon, prostate, and lung, and then pick up some other notables that are still refractory to
00:29:35.300 this day, like pancreatic cancer and so on, in terms of number of deaths. But the common cancers,
00:29:39.800 they are perturbed at best a little bit by these agents. So some subpopulation of those cells will
00:29:46.360 slow down and die with conventional chemotherapy, but many of them are pre-wired. They were hardy to
00:29:51.720 begin with. They got there through a hard-earned evolution under selective pressure of the immune
00:29:56.620 system and adverse metabolic environment. And they used all the tricks up the sleeve of a cell,
00:30:01.280 of a normal cell, to reprogram themselves to be able to survive in these harsh environments.
00:30:06.340 You throw in another harsh environment reagent in the form of chemo. And not surprisingly that
00:30:12.280 these things were already basically hardwired to be able to survive yet another insult. But that's
00:30:17.820 chemo. That's an interesting way you explain that. I think that that's important, I think,
00:30:21.080 for a listener to understand is a cancer cell has to overcome a heck of a lot to get to be
00:30:25.640 clinically relevant. So how many, I used to remember all the numbers and the growth rates,
00:30:29.740 but a clinically relevant mass has how many billion cells in it approximately?
00:30:33.360 Yeah. Clinically relevant that you can find on a scan.
00:30:35.580 Something that you could see, like a one by one by one centimeter cancer.
00:30:38.280 No, you're in a billion cells already.
00:30:39.780 You're in a billion cells. So just to get a billion rogue actors, you have to evade T-cells. You have
00:30:45.760 to grow your own vascular supply. You have to overcome, as you said, adverse metabolic conditions.
00:30:52.080 These things are evolutionary warriors by this point.
00:30:56.100 Yeah. I mean, I usually start, you're absolutely right.
00:30:58.340 I mean, it starts much smaller.
00:30:59.640 The filters. Yeah, no, no, but I start with the analogy. There's a random spinning of the
00:31:03.840 combination lock where mutations are being acquired over time through a variety of insults or not even
00:31:09.440 necessarily insults, just bad replication technology, if you will, where the detection of errors and the
00:31:15.620 correction of errors is not perfect. Anyway, we accumulate mutations over time, some of which we
00:31:19.940 could limit and control, some of which we can't. Combination lock is just spinning, spinning.
00:31:24.080 The combination has to be dialed in the right sequence, just like when you're opening your gym locker
00:31:27.760 or you don't get cancer. You've got to get your tumor suppressor early and in the right order
00:31:32.300 before your activated oncogene comes along. You're randomly spinning the lock. You're picking up lots
00:31:36.740 of past true mutations, not just true drivers. So these incidental mutations that happen here and
00:31:41.760 there. So as that's happening, you finally click important components of the program. But along the
00:31:47.700 way, some of those are actually mutations that are seen as foreign by the immune system. And if they're
00:31:51.700 too visible, if they're too far out there, then they're gone. So it has to be the right kind of
00:31:57.480 genetic alteration that will give the cell what it needs to be able to proliferate abnormally,
00:32:02.060 to be able to sustain a lot of DNA damage as it accumulates and not commit suicide as a consequence,
00:32:07.700 and be able to handle all the other adverse features and filters of the tumor microenvironment
00:32:11.660 that you enumerated. It has to be able to do all that, but it has to be below the radar,
00:32:15.320 as in not detectable, as overly far into the immune system. That's a powerful insight that we only
00:32:19.900 really picked up in the field within the past five years. This notion that this is not just a cancer
00:32:24.940 cell co-opting its normal cells in the microenvironment in some kind of cocooned way.
00:32:30.920 There are a few cancers that do develop in so-called sanctuary sites that aren't subject
00:32:35.200 to immune surveillance, but the vast majority are. So that is a lot to have to overcome.
00:32:41.040 So there's a chance element on the combination lock spinning, but then there's these, you have
00:32:44.620 to survive the selective pressures that are being applied both within the cell and outside the cell.
00:32:49.920 The relevance of that thought process is highly relevant to how we think about developing therapies
00:32:54.040 right now. But it's also highly relevant to understanding this asymptotic limit of chemotherapy,
00:32:58.220 like how it is that you try to poison this DNA replication process and like just sort of shred
00:33:04.000 the DNA a bit more. Radiation, the same concept.
00:33:07.220 Yeah. I mean, radiation even more limited in that it's not systemic.
00:33:10.060 Yeah.
00:33:10.240 So basically radiation became a great tool to locally control cancer, but now you've basically reached
00:33:15.880 an asymptote at the two of the three pillars. And you could argue the third pillar being surgery,
00:33:21.860 also asymptotes at your alma mater. I mean, basically when you look at one of the most
00:33:26.680 complicated surgical procedures for cancer, which is removing the head of the pancreas,
00:33:30.680 that was an operation that used to carry a 50% 30 day mortality. Meaning the surgery was,
00:33:36.020 you had a 50% chance of living through the surgery and the post-operative course. Today that's 0.1%
00:33:42.320 mortality at 30 days, but long-term survival is still abysmal. So cutting tumors out matters a lot,
00:33:48.840 especially for colon cancer, I would say is the poster child for where cutting cancer out
00:33:53.820 really makes the biggest difference.
00:33:55.640 Even in metastatic disease.
00:33:56.880 Yeah. Yeah. It's a huge benefit. Other cancers, frankly, I'm still not even convinced,
00:34:01.320 not to say we shouldn't be cutting them out. We absolutely should, but it's not clear to me,
00:34:05.660 for example, when you talk about breast cancer, if the dye is cast long before the mastectomy is done
00:34:09.840 and that local control, I don't know anymore.
00:34:12.120 Yeah. We're learning so much more. Again, as our sensing technologies,
00:34:14.900 you can continue to elaborate because this issue of how many patients already have
00:34:18.440 metastatic disease at the time of their initial surgery.
00:34:20.740 And you take 10 women who all have one by one by one centimeter breast lesions that are all going
00:34:26.280 to be, let's assume, make them all the same stage. Some of them are going to make it,
00:34:30.060 some of them are not. And it's not clear to me how much of that we could have, or Monday might know
00:34:35.800 at the time of surgery and alter our course.
00:34:37.780 Not all hope is lost. I mean, remember the cure rate from all cancers, solid tumors that are
00:34:43.820 amenable to surgery is in my career has never been less than 40% and is probably more like 50%.
00:34:49.840 As we develop more diagnostic technology, it allows us to understand that there's circulating
00:34:54.340 cells in the blood. Those have a hard time surviving, right? People think about a circulating
00:34:58.320 cancer cell and assume that it's going to succeed. No, no, it's super hard to launch a cancer cell
00:35:03.280 into the bloodstream and actually have it find soil, get out of the bloodstream and find fertile
00:35:07.440 soil. That's a whole different problem. Lung cells aren't supposed to live in the liver.
00:35:11.400 It's not a happy environment for them. The growth factors there aren't. Their native ones,
00:35:15.080 super, super challenging bit of biology to overcome. But anyway, the point being that there
00:35:19.620 are a large number of patients who have curative outcomes from surgery who had seeding of distant
00:35:26.060 organs, even successful microscopic deposits, at least in animal model data, you'd say that that
00:35:31.960 can happen. And yet they still outlive the diagnosis, which is to say at least it lived decades
00:35:36.600 thereafter and never have a metastatic occurrence.
00:35:39.060 You alluded to this earlier. What do you think it is about the removing the mothership
00:35:43.420 that harms the satellite ships?
00:35:45.900 Well, I think they are fragile, the micrometastases. I don't know how much they're being fed. That's
00:35:50.480 not so much, say we have the evidence to support that, but they have a significant task ahead of
00:35:54.800 them to really take and survive in this so-called dormant state and then ultimately awake out of
00:36:00.900 that dormant state. So what I'm getting at is the idea that there's a larger fraction than we would
00:36:05.800 have thought decades ago when surgery was curing patients, but we just assume that they got it
00:36:11.040 early before it had ever traveled. More and more evidence suggests, no, you didn't get it that early,
00:36:16.620 but you got it early enough because those micrometastases that were established, micrometastases,
00:36:21.580 they didn't have all that it takes. In another wave, more evolution was going to be needed in the
00:36:27.140 primary tumor to be able to launch now micrometastases that had all the skills to be able
00:36:32.240 to both set up shop in the first place, live in a dormant state for not just months, but years and
00:36:37.860 even decades in some cases, and then make their way out again. So there's those additional challenges
00:36:42.740 that cancer cells have to overcome or tricks that they have to pick up that clearly just become
00:36:49.180 incrementally more likely the more time and evolution gets to happen in the primary tumor. So I think you
00:36:54.260 just stop the clock in terms of that evolution when you come along and either a patient in their bodies
00:37:00.140 tell them that they have a tumor or it's an only found or whatever the diagnostic trick is. So that's
00:37:05.560 the great hope in an area of cancer research that I watch very avidly, but being a therapeutics oriented
00:37:11.640 researcher, and that's where my mind always goes. So let's take stock of where the world was 25 years
00:37:18.580 after the war on cancer was declared. It's the late nineties. The scientific community is on the cusp
00:37:25.500 of fully sequencing the human genome. At this point, we know a number of things, right? I mean,
00:37:31.600 that's when I was in medical school. We certainly understood that cancers are initiated by genetic
00:37:37.340 mutations and everything you've alluded to with respect to genes that suppress tumors and genes that
00:37:43.480 promote tumors. The relationship there is pretty well understood. If you refresh my memory, I also
00:37:48.460 think people understood that virtually all of those mutations were somatic. Did anybody have a hope
00:37:52.740 that the human genome project was going to give us a whole bunch of germline mutations that cause
00:37:57.600 cancer? No, I don't think we believe that, right? No, that's right. You're right. The spinning of the
00:38:01.940 combination lock concept, the right sequence, Burt Vogelstein innovation in colorectal cancer
00:38:07.220 initially, that was in hand by the late nineties, that basic concept. Now, what was left to be
00:38:13.700 sorted through and a justification for doing whole genome sequencing in cancer was that we didn't know
00:38:20.420 what that sequence might look like across cancer. We didn't know what the spectrum of genetically simple
00:38:25.740 to genetically complex cancers was. And I mean that at the individual cell level, not talking
00:38:30.200 necessarily about across all cancer types. So what I'm getting at is, do you need three mutations to get
00:38:35.240 cancer? Is eight somehow better a number? By that, I guess, I mean, just look at a distribution of
00:38:39.940 quote unquote true drivers. So wait, because I sort of know the answer today, but I never actually
00:38:43.800 thought about this then. In 1999, did we know if the average breast cancer had three versus 30 versus
00:38:50.520 300 mutations? No. And most importantly, how many- How many were drivers? True drivers. I mean,
00:38:56.340 I'd say true drivers because that term driver is thrown around a bit. And true drivers, what are the
00:39:00.440 essential building blocks? And we'll come back to what essential ultimately means because I think that
00:39:05.740 has to do with therapeutic vulnerability. But any case, yeah, this idea of how many hits did you
00:39:10.580 really need? Remember that Knudsen described this, you know, the two-hit hypothesis, right? And it seems
00:39:15.440 reasonably clear that in very simple tumors, two hits actually might be enough. Now, probably then,
00:39:23.280 I think it's fair to hypothesize- Explain for the listener what two hits means in that situation,
00:39:27.940 because that's a great teaching example. Yeah. So two hits, I mean, as it was initially construed,
00:39:31.680 really was the combination of the inactivation of a tumor suppressor gene, tumor suppressor gene
00:39:36.520 being by definition, the gene, when its function is disabled, cancer becomes more likely. Nearly all
00:39:42.980 of the genetically inherited cancer types that people are familiar with come from having a inherited
00:39:49.500 alteration that partially or completely disables a tumor suppressor gene. We know very few of the
00:39:55.640 opposite, which is the activation of another gene. Oncogene could just mean cancer gene, but in the field,
00:40:01.080 most people think of oncogene as the thing that gets activated, that tumor suppressor gene is the
00:40:05.080 thing that gets inactivated. That's the simplistic version of the two-hit hypothesis.
00:40:08.320 So you're born with two copies of each gene, and one of them is not working, of a tumor suppressor
00:40:12.260 gene, and later on in life, just from a stochastic process, you only have to hit it once, not twice,
00:40:18.340 which is far less likely. And that's why these are patients that are getting cancer in childhood and
00:40:22.720 adolescence. And multiple of them over time, new unrelated cancers, sometimes in the same organ.
00:40:27.240 I mean, a patient with- Yeah, multiple colon cancers.
00:40:29.240 Exactly. They keep starting new cancers over and over again. Now, even in the most genetically
00:40:34.320 simple cases, I would just quickly assert that we have plenty of evidence now that suggests that
00:40:39.060 you get these genetic alterations that can dial the combination lock in the right way. But the
00:40:44.920 simplest genetic-defined cancers almost certainly have then a quote-unquote epigenetic, as in not
00:40:51.260 hardwired mutation alteration change as well. So a so-called state change, where they occupy a different
00:40:58.960 state of development, basically, compared to their normal cell counterparts. So if we're talking
00:41:04.040 about a pancreas cell, endocrine cell in the pancreas becoming a cancer, it moves away from
00:41:10.160 its differentiated, fully mature neighbors and does so in a way that's important in terms of its cancer
00:41:16.160 biology. It makes it more hardy. It makes it be able to survive insults. It makes it be able to adopt
00:41:20.640 programs that it's not supposed to have, like traveling, as in becoming metastatic.
00:41:24.660 More and more evidence suggests that, yes, a lot of that work is done by mutations, but then the
00:41:29.520 mutations, in some cases, actually make the cells more plastic, make them more able to read parts
00:41:37.000 of the genome and use parts of the genome that that cell type isn't normally supposed to have access to.
00:41:42.880 This is an insight that I think has only come...
00:41:45.740 Yeah, we didn't know that 20 years ago.
00:41:47.260 No, I didn't know in the late 90s. This is my argument, in retrospect, about what it is that the
00:41:53.220 Cancer Genome Atlas really uncovered for us. A criticism is that we just relearned a lot of the
00:41:58.240 same things we already knew. We already knew that RAS mutations occurred in 25% of all cancers,
00:42:02.420 and we knew then and pretty much know now that we can't drug them directly, so that's an inconvenient
00:42:07.560 reality. The point being that the catalog of activated oncogenes had actually been largely
00:42:12.720 resolved one by one by one from the mid-80s going up to the late 90s. This was the catalog I was
00:42:18.760 looking at when I was saying, I'm going to go into the field and try to figure out how to take this
00:42:23.120 information and turn it into some version of first therapy. I was a student at Hopkins when HIV was
00:42:29.380 absolutely uncountered with any therapies at all. I did a second sub-internship on the service where
00:42:36.660 the HIV patients were cared for as inpatients, usually...
00:42:39.340 That was on the Osler service, wasn't it?
00:42:41.040 Exactly, right. And AZT was in humans in clinical trials for the first time. It was talked about
00:42:45.780 actively on that service because it was definitely a research-minded service. So by the time I got
00:42:50.460 finally in through my medical training into oncology, a few more years have passed...
00:42:54.480 So wait, you nadered. I mean, the nadir, meaning the nadir of despair, the peak of hope,
00:42:58.720 would have been 96 when heart was introduced, right?
00:43:01.580 That's right.
00:43:01.900 And that's when you were starting medicine.
00:43:03.480 So I was graduating from medical school at that time.
00:43:06.040 Yeah, I mean, starting your medicine residency right as heart was introduced in 96.
00:43:09.400 And so my talking point was we need to find in cancer as many AZTs as we need as the initial
00:43:15.960 foot in the door. We know we're going to see resistance in this much more complex entity
00:43:20.080 that is a human cell that's gone rogue versus relatively simple virus. But it's when we poke
00:43:25.780 it with the AZT equivalents, we're going to learn about how it is that it tries to adapt. And that's
00:43:31.440 going to allow us to develop rational combination therapy exactly the way the HIV field does.
00:43:35.300 I still say that in 2019 and it still hasn't really happened.
00:43:39.860 I was about to say, when you were saying that a second ago, I was thinking that doesn't sound
00:43:43.460 that naive. Earlier you said you had this very naive point of view.
00:43:47.320 It was naive in the sense that with no single example, being able to drug an oncogene,
00:43:53.480 so an activated gene, nearly all of the drugs that people take are inhibitors of something
00:43:58.860 as opposed to activators. We have some activators in medicine, but not that many.
00:44:02.480 So if you think about cancer and its genetic assembly, then and now, we don't know how
00:44:07.560 to restore the function of something that's lost, particularly if it's wildly genetically
00:44:11.440 disabled, to the point of even missing from the DNA of a tumor cell in some cases. We don't
00:44:17.580 know how to replace that. This was the hope of gene therapy, the dawn of my career, that
00:44:20.980 we might be able to figure that problem out. We haven't figured it out by a long shot.
00:44:25.160 Inhibiting things that are activated, that has been where there has been success, A, in all
00:44:29.160 of medicine, and B, in oncology. So could we catalog activated events and target them with
00:44:34.520 drugs successfully and have these AZT moments? The headwind against that, and the reason why
00:44:38.960 people kind of smirked or smiled at my pitch, this is when I was applying for medical oncology
00:44:43.900 fellowships and saying these very, I think, truly simple-minded concepts, was, kid, do you
00:44:49.120 understand how complex cancer is? I mean, you poke it with a stick, it's not going to care
00:44:53.260 about blocking one thing. I mean, these things have an inordinate number of tricks up their
00:44:57.900 sleeve. Like, no way.
00:44:59.220 Right. To think that you're going to poke it once and everything will remain unperturbed
00:45:03.660 except that one thing, and then... The idea that that would actually help a patient and
00:45:07.960 that you could learn from it, both things, I think, were absolutely not accepted. You remember
00:45:12.560 the first targeted therapy success in cancer.
00:45:14.300 But the concept, the concept translationally makes sense. I think, I guess what people were
00:45:19.160 bristling against was the notion that, oh, and by the way, in the next three years, this
00:45:23.900 is what I'm going to do.
00:45:24.800 Yeah. Right. And doing this in humans, as opposed to the laboratory, wet lab, relying on reduced
00:45:29.760 model systems like immortalized cancer cell lines or some other newfangled approach of
00:45:34.760 a reduced system in the lab, that saying that doing this in humans was going to be the way
00:45:39.400 to make fastest progress, that job description hadn't been created yet. So saying that I wanted
00:45:45.480 to do it, A, and I wanted to do it in people, that's what made people for their brows, which
00:45:50.700 was fine. And that really didn't slow me down because I just, I kind of intuited that at
00:45:54.760 least this is going to be a thing to get out of bed in the morning to do.
00:45:57.680 So you did your residency at the Brigham and then your med-onc was at Penn.
00:46:02.220 At Penn.
00:46:03.000 Yeah.
00:46:03.220 Was Carl June there at the time?
00:46:04.360 He was.
00:46:04.720 So let's take a detour into immunotherapy for a moment because there's part of me that
00:46:08.020 is like wants to do this temporally because of how much we know today. And I don't want
00:46:13.060 to lose stuff that we now take for granted, but at the time was so important. So there
00:46:19.160 were a couple of cancers. Well, let's go even further than that. Based on everything
00:46:23.320 you said a moment ago, it's pretty clear that we need systemic therapy. We've reached
00:46:27.740 the limits of local therapy. So surgery and radiation work pretty darn well when they
00:46:33.260 work, but there ain't a lot of ways to make it better.
00:46:37.220 Yeah. You can minimize their adverse effects.
00:46:39.140 Exactly right. You can make them less harmful, but they're about as efficacious as they can
00:46:42.960 be. We take our first type of systemic treatment, which is chemical chemotherapy. And as we basically
00:46:48.840 saw from 25 years of 74 to 99, we basically cured one additional cancer. Somewhere along
00:46:55.080 the way, there's another idea for a systemic type of therapy. And you alluded to it earlier,
00:47:00.000 which is look, I mean, you didn't say it explicitly, but I'm just going to put words in your mouth.
00:47:04.020 Once the mutations happen to cancer, they cease to be purely self. They start to display a little
00:47:09.260 bit of non-self characteristic. And we have this branch of the immune system that is, I mean,
00:47:16.260 staggeringly effective at eradicating non-self things, namely viruses. So we don't have to go
00:47:22.340 back to Cooley's toxins, but basically if you just go into the nineties, you've got guys like
00:47:27.760 Allison who are working on things called checkpoint inhibitors, which we're going to come back to.
00:47:32.140 You've got Steve Rosenberg at the NIH, who's having limited success in melanoma and renal cell
00:47:37.360 carcinoma. You've got Carl at Penn and a number of people around the country that are starting to
00:47:43.740 show little cracks in the armor of cancer. And these results, well, I want to talk about the
00:47:48.600 durability of them, but just for a moment, explain what cancers were we seeing this in and what did
00:47:55.200 we know by the late nineties about immunotherapy? Yeah. So what you just described, one way of
00:48:00.400 rephrasing it is that you had people recognizing this idea that there's a, let me back up a step.
00:48:06.300 What had been recognized pathologically decades before was that there are some tumors that at
00:48:12.500 the time of surgery are evidently visible to the immune system because you can find a ton of immune
00:48:16.920 cells infiltrating into them. I mean, I like to go back to melanoma. Many instances is a good entry
00:48:22.620 in there because melanoma is the cancer type that I have focused on throughout my career. Fortuitous for
00:48:27.320 a couple of reasons, that choice, but in any case, it definitely useful for this discussion. So what's
00:48:31.860 useful about melanoma in this discussion? Let me just remind listeners that melanoma harbors just
00:48:37.420 about the largest number of mutations per cell of a tumor that makes it, if you will,
00:48:41.860 to succeed in becoming a cancer. It flies as high as possible beneath the radar. That's right.
00:48:47.340 There's a few other cancers out there, but it's a simple reality that they're picking up so many
00:48:50.860 mutations, these melanocytes, the precursors to melanoma from ultraviolet radiation, the vast majority
00:48:55.980 of which we think are useless to the formation of a cancer. What's the typical number of mutations
00:48:59.420 in a metastatic melanoma? It's high thousands. So you can have in the tens of thousands, but high
00:49:04.820 thousands. There's a distribution and a limit to that distribution. Aren't there only about 20,000
00:49:08.960 genes? Oh, I mean individual. Oh yeah. You'll find multiple mutations per gene in a melanoma. So
00:49:13.660 on mutations per megabase and then scale that out to the... And how many of those do we think are
00:49:17.680 playing a functional role? We don't know. Five, six is a rough estimate based on real functional
00:49:22.820 evidence now. So you have this huge onslaught of mutations, which are useless to the cancer's
00:49:29.080 purpose, probably adverse for the purpose of immune recognition. And so it's an outlier. It's
00:49:34.860 not a completely separate, but it's at the far end of the spectrum in terms of cancers that aren't
00:49:39.140 cleared and eliminated by the immune system and survive with all of this mutational abnormality
00:49:44.600 in them, a lot of non-self. So that's a cancer that at the time of initial diagnosis, a superficial
00:49:51.400 melanoma on the skin, you will find, not in all cases, but in the vast majority, a robust amount of
00:49:56.500 immune recognition. Infiltrating immune cells and T cells that are the variety that can clear a virally
00:50:01.040 infected cell and can kill a cancer cell. When they see that the internal contents being presented on
00:50:05.800 the cell surface by the so-called MHC complex have enough difference from self, then that's the cell
00:50:12.440 population that you will witness in those tumors. And then it had been described in the 60s that a
00:50:18.680 melanoma, notably other cancers by the 80s, you looked at a spectrum of melanomas. Those that had the
00:50:24.340 most robust immune cell infiltrate were going to be least likely to be life-threatening to the
00:50:28.780 patient after adjusting for other factors. In other words, was the experiment ever done
00:50:32.680 when you took a hundred patients who had a local resection, normalize them for depth, so they're all
00:50:38.940 Breslow 5, and you add up the TIL, tumor infiltrating lymphocytes, and you get a prediction of who's going
00:50:46.840 to be alive in 10 years? That's right. Powerful, very powerful, that prediction. And then that was just
00:50:51.600 replicated across the rest of cancer. That finding, colorectal cancer has its own distribution in
00:50:56.860 that regard, and some that are wildly mutated, immunogenic. Has anyone commercialized this today
00:51:02.340 as a diagnostic, at the time of therapy, diagnostic or predictive tool? To a degree. So immunoscore is a
00:51:10.200 commercial assay that's been developed that is about more complex version of immune recognition than
00:51:15.900 just these T cells. But we can unpack this more deeply now, cataloging the success, the huge
00:51:23.080 waterfall event in the immunotherapy development era when PD-1, PD-L1 interactions were discovered and
00:51:29.700 then leveraged as a therapeutic. That fraction of cancer patients who are one drug away from clearing
00:51:34.320 their tumor with a PD-1 antibody, which is the largest impact we've had with an immunotherapy of any
00:51:38.320 kind by a long shot in terms of numbers of patients helped. These are those patients. Yes, their cancer
00:51:43.900 succeeded, but they had the immune system nibbling at their heels at every step of the way. So yes,
00:51:48.440 they developed a true bona fide cancer. We just had to block this one checkpoint inhibitor. This
00:51:53.940 one break on the immune system where the foot was being expressed by the tumor cell and literally
00:51:58.460 reaching across the divide and repelling or making quiescent a T cell that had succeeded otherwise and
00:52:04.200 making it into the environment. That's a swath of cancer. Now it's interesting too when you go,
00:52:08.580 like I'm much more familiar with CTLA-4 because that was the work, what I was doing when I was doing my
00:52:12.860 time in the lab, both in medical school and later in residency. It was interesting the amount of
00:52:17.920 autoimmunity you saw as well, suggesting that boy, when you took the brakes off the immune system,
00:52:23.420 it didn't just want to kill cancer. It actually wanted to kill a bunch of things. Yeah. So this
00:52:28.040 reminds people these systems were not created purely to survey for cancer and eliminate it, right? So
00:52:33.540 the purpose of dampening effects on the immune system are that you don't just mount an immune
00:52:38.340 response and have it just take over your body, which is what a CTLA-4 blocking or transgenic
00:52:43.740 experiment will produce is lymph proliferative overdrive that kills the mouse. So the idea that
00:52:49.520 these brakes exist for a reason, I think is intuitive. If you think about the fact that basically we live
00:52:54.980 in a complex system, we're exposed to pathogens. We were talking about viruses, but we're being exposed
00:53:00.420 to microbial pathogens that are trying to infiltrate all the time. You wipe out someone's immune system
00:53:04.840 with chemotherapy or a bone marrow transplant and those bacteria that are living in the gut and,
00:53:09.860 you know. Seemingly harmless in symbiosis. Exactly. They will then infiltrate. They're
00:53:14.640 right at the margin to begin with. They'll infiltrate and they'll take over. This is a really active
00:53:18.740 border zone that's being policed all the time. You give a CTLA-4 antibody and where does the most
00:53:24.840 life-threatening chaos erupt? It's at the gut. You've unleashed this pre-existing force that's at work
00:53:31.380 all day every day in this very immunologically active environment and it starts attacking normal
00:53:37.440 colonic tissue and can perforate the colon from which patient then dies. So leading cause of death
00:53:43.180 from that therapy is rare as those events are, but it's a very powerful sign of how this sort of gas
00:53:48.960 pedal and brake component is at play. Playback the conversation to talking about chemotherapy and
00:53:54.120 this notion of therapeutic index. Well, here's the issue with unleashing the immune system systemically
00:53:59.180 with these types of therapies. Yeah. The early days of this in the 80s when Steve Rosenberg and
00:54:04.360 his colleagues were using mega doses of interleukin-2, you saw that flip side, right? Which
00:54:09.760 was the systemic inflammatory response syndrome was as life-threatening as the cancer. You were
00:54:16.280 teetering between the patient dies of what looks like sepsis versus the patient dies of cancer and you
00:54:23.100 have to thread that needle. Right. Sepsis in a bottle. You start dripping in interleukin-2 and the only
00:54:27.920 other time a human being sees that cytokine at levels like that is when the immune system says,
00:54:33.700 screw it, we've got to go all guns. We're going all nuclear. All guns blazing or else the host is
00:54:38.660 going down here. And there's a 50% chance we're going to kill ourselves in the process, but so be
00:54:42.580 it. But we, but this is our last shot and with interleukin-2, thank God you can turn it off and
00:54:46.720 within certainly hours, but even minutes in some cases like that whole storm settles down. But the
00:54:51.680 cytokine era, that was the first wave. So coming to your point about how do we get-
00:54:55.820 Yeah, there's a great proof of concept.
00:54:56.980 Yep. But narrow therapeutic index, as in the asymptote was reached awfully early. What were
00:55:02.120 the cancers that responded? Melanoma?
00:55:03.580 RCC and renal. Yeah, melanoma.
00:55:05.440 Melanoma that has the highest mutation burden. I didn't cover kidney cancer. Kidney cancer,
00:55:09.460 for reasons that we're still trying to unpack, is very immunogenic. It is highly visible to the
00:55:14.200 immune system. When you diagnose a kidney cancer at the time of surgery, the amount of infiltrating
00:55:17.480 immune cells, active immune cells, so-called cytolytic T-cells that are like churning out
00:55:22.520 the enzymes that will kill their neighboring cancer cells, that actually scores at the top.
00:55:26.600 I understand why we see it in melanoma. Why in RCC?
00:55:29.440 Not known because it's not mutation burden driven. If you look at mutation burden in relation to this
00:55:35.780 immune recognition, there's a very strong correlation across all of cancer with a couple of outliers.
00:55:41.060 And RCC is the renal cell carcinoma. It's an outlier on that curve.
00:55:44.820 Yeah, it's immunogenic without a high mutational burden.
00:55:47.360 Very precisely. And how much of this is epigenetic then, as opposed to genetic? That's the piece that
00:55:52.440 investigators are currently trying to uncover. Admittedly, renal cell carcinoma, because of
00:55:55.920 its relative rarity, doesn't draw that much attention, whereas so much more of this work
00:56:01.020 is being done in the more common cancers. But there's a story here across cancer that there's
00:56:05.420 this whole issue of what determines visibility of the immune system versus invisibility, right?
00:56:09.920 These successful cancers have to find cloaking mechanisms. They will not succeed otherwise.
00:56:14.000 One cloaking mechanism is just stop presenting antigens. Don't make MHC complexes that present
00:56:20.360 these mutated antigens. And if you go high enough up the mutation scale...
00:56:23.960 We'll go so far in this that I want people to be comfortable with the lingo. So what's MHC class
00:56:29.580 one to... What is antigen presentation? Maybe do... Pretend this is a group of first year college
00:56:35.340 kids and you've got a few minutes to explain how T cells work, basically.
00:56:39.060 So the major histocompatibility complex, MHC, is this machinery that exists. These are cell
00:56:45.600 surface proteins. Well, they become cell surface proteins. When they're first expressed endoplasmic
00:56:51.580 reticulum as all proteins, when they're initially translated into proteins, they have the opportunity
00:56:56.400 to sample internal contents, protein fragments, basically. So they're sampling all the time the
00:57:01.880 protein fragment repertoire. And MHC class one and class two, and we each have a portfolio of them.
00:57:09.560 We inherit the diversity of these ultimately from our parents, but we have a massive diversity of
00:57:15.060 them that we're born with. So class one and class two can hold different size protein fragments.
00:57:19.700 So they're fundamental difference. And there's a flexibility or a nimbleness in terms of class two,
00:57:25.220 which can hold longer peptides. It can see potentially bigger repertoire than class one.
00:57:30.060 So the analogy is your job is making sure a house is okay. There's a house party.
00:57:34.980 The internal house.
00:57:35.680 Yeah. The internal house is okay. And you're kind of the guy that got hired to help make sure the
00:57:39.820 house party doesn't get out of control. And you're roaming around the house looking to try to figure
00:57:45.320 out, do I need to take any of these guys outside to show the police?
00:57:48.300 That's right. So the immune cells that are not only activated, not only T cells,
00:57:52.460 other immune cells are interviewing normal cells constantly and effectively all organs.
00:57:58.520 So this surveillance process is happening. We think viral pathogens are what created the
00:58:02.800 evolutionary pressure to evolve this system. Cancer couldn't have been the excuse, right?
00:58:07.060 If cancer is distributed across ages 40, 60 to 80, it's not relevant because you've reproduced and
00:58:13.360 you've served your purpose. So we benefit from having this system that evolution handed to us from
00:58:18.700 viral selected pressures. But in any case, so the system was tuned for that, for picking up viral
00:58:23.460 pathogens inside of cells, being able to present them on the cell surface.
00:58:26.840 So we'll use an example, sorry, just that everyone will get. When you get a virus that
00:58:31.440 gives you a sore throat, for example, the pain you're feeling, the soreness of your throat
00:58:36.520 is the inflammation. It's the actual endothelial cells within your throat that are hurting because
00:58:42.220 a virus has gotten there. The virus has hijacked your DNA replication system. It's doing its nonsense
00:58:48.280 because that's what it does. It wants to survive. It can't make its own DNA. In the process,
00:58:52.800 new proteins are showing up inside a cell. And these little antigen presenters are saying,
00:58:58.140 I don't recognize this. I don't think this belongs in here. I'm going to take it to the surface
00:59:01.860 and let these guys that come by who are... We think the interviewing happens even with
00:59:05.960 normal proteins. So normal proteins will be shown as well as abnormal proteins, not only...
00:59:09.740 That's right. And then it's the cop who's coming by who has the ability to go,
00:59:12.900 that gun's okay, that one's okay, that one's okay. Whoa, that one, we actually need to go in the
00:59:16.300 house and rip it up. Exactly right. And it turns out that when MHC complexes are presenting antigen,
00:59:21.300 it turns out that differences even in a peptide fragment or protein fragment,
00:59:25.300 the position of the abnormality matters. And if it's in the middle, that's able to be seen
00:59:29.520 more efficiently. Some of these principles now have been reasonably well elucidated.
00:59:33.520 So it's really nuanced interview technology. So a ton of normal self that's being seen and excused.
00:59:39.220 And then there's the chance then that some of the abnormal proteins, viral pathogens,
00:59:43.480 and then mutated proteins as well can be presented and seen as non-self.
00:59:47.280 But I do want to just jump quickly to mention a point, which is that, well, if cancer is developing
00:59:53.820 all these mutations and quote, unquote, trying to become a cancer, what might be a trick that you
00:59:59.040 could use to try to evade the immune system? How about if you disable this machinery? How about
01:00:03.700 if you just don't allow MHC complexes to be made?
01:00:06.640 Right. So a cancer cell is, instead of a cell that gets infected with a virus, although notwithstanding,
01:00:11.420 that's how some cancers start. If now the cancer cell takes over the entire DNA replication system,
01:00:17.720 the smartest thing to do is say, of course, I'm going to make proteins that are foreign.
01:00:22.300 I'm just not going to get them presented on the MHC molecules outside. I'm not going to let anybody
01:00:27.600 outside of me know what's going on inside.
01:00:29.900 Right. So you might think a virus would have figured this out a long time ago to suit their
01:00:34.440 purposes. Maybe they would figure out how to wipe out MHC complex presentation. It turns out
01:00:39.000 natural killer cells don't like that very much. This is very primordial branch of the immune system
01:00:43.560 that we think about innate immunity, adaptive immunity as being primordial versus more modern,
01:00:48.380 quote unquote, higher organisms having them. Any case, these natural killer cells, which are part of
01:00:52.500 the more primordial immune surveillance machinery, if they see a cell not showing MHC complexes,
01:00:59.160 that targets that cell for destruction. So it's not okay in a fully civilized ecosystem of all cells
01:01:06.340 playing their role and being willing to be interviewed. It's not okay not to make MHC
01:01:11.120 complexes. So it's thought to be intolerable, if you will, at least in the face of natural killer
01:01:15.680 cells to do that. Otherwise, all cancers would have figured that trick out long ago.
01:01:21.220 There's this really fascinating story that's emerged in trying to understand the features of
01:01:25.620 cells that will survive the onslaught of an activated immune system after checkpoint therapy,
01:01:30.060 PD-1 or CTLA-4 therapy. Some patients will clear their tumor and they're cured. There are those who
01:01:34.500 don't clear their tumor and they're not cured. And under selective pressure of a-
01:01:38.080 Meaning they undergo a complete response, but then they relapse or they only undergo a PR
01:01:43.160 and never CR.
01:01:44.280 Yeah. Amazingly, if you look at the data with the PD-1 antibodies, which are, again,
01:01:48.620 that's the thing that's really helped humanity in terms of large numbers, I usually summarize that
01:01:53.160 to say that there's 10% of cancer patients currently are getting a heroic benefit from that therapy.
01:01:58.280 There's a higher percentage who get some benefit, like actually double the number, 20%,
01:02:02.360 who do respond. Enough tumor cells are killed by the activated immune system that the tumors will
01:02:07.180 shrink. Under that selective pressure of now heightened immunity, remember there was already
01:02:12.080 baseline immunity to a degree, variably, yes, across cancer, all cancer types, but still now this
01:02:18.500 activated immune system has just been raging. Those that survive, what do they do? Well, it turns out
01:02:24.560 they start to dial down their MHC complex expression through genetic and epigenetic means.
01:02:30.240 Just enough to satisfy the NK cell, but no more.
01:02:33.700 Precisely. Exactly. So they find this new homeostatic set point, and this is true in
01:02:37.220 metabolism and other programs in cancer, that they find new set points under selective pressure
01:02:42.620 of the onslaught, in this case of activated immune systems, but it could be other oncogene
01:02:46.480 targeted therapy does a similar thing. Actually, more and more convergence as opposed to divergence
01:02:51.300 has been emerging in the cancer therapy resistance world, where even melanoma, for example,
01:02:56.600 where we have effective oncogene targeted therapy and we have effective immunotherapy,
01:03:00.800 there's more and more evidence that actually what survives both is the same sort of phenotype,
01:03:06.080 if you will. Cancer is adopting similar programs to be able to try to survive the onslaught,
01:03:11.180 even from those two very different modalities.
01:03:13.000 Do you think it's safe to say that the lethality of cancer is directly proportional to that evasion?
01:03:18.420 For example, why is it that when you take the ratio of people diagnosed with pancreatic
01:03:24.620 adenocarcinoma to people who die of it, contrasting that with something like prostate cancer? Now,
01:03:31.100 prostate's a tricky one because it's sort of immune protected, but maybe we can pick an example
01:03:34.760 that's less...
01:03:35.700 Glioblastoma is right there with pancreas.
01:03:37.760 Although for a totally different reason, right? It doesn't really metastasize. I mean,
01:03:40.420 it's causing most of its local destruction.
01:03:42.420 And it's in a bad spot.
01:03:43.160 Yeah, yeah. It's in a space-restricted...
01:03:44.420 You're right. But it is fair to say, though, that both pancreatic cancer and glioblastoma
01:03:48.760 are really not immunogenic on the spectrum. Prostate, as you say, is out also in that end
01:03:54.520 of the spectrum. So if you just look at this baseline at the time of diagnosis, how much
01:03:58.320 immune recognition is there? How much does that relate to how long someone lives and how likely
01:04:03.040 they are actually to respond even to conventional chemotherapy? You can splay cancer out, all cancer
01:04:08.980 types, and there's heterogeneity within cancer types as well. So not all lung cancers are the same.
01:04:13.540 And you can come up with some of these that are, as you say, they are aggressive tumors.
01:04:18.340 They're not being seen adequately. So not being slowed or being nibbled at by an immune system in
01:04:23.820 their evolution. And then at the time that we diagnose them to the time of death, basically
01:04:27.840 almost nothing happening there either.
01:04:29.520 Do you teleologically have a rationale for it? I mean, we didn't come up with a good explanation
01:04:33.160 on why RCC, renal cell carcinoma, would be so immunogenic despite the relative positive
01:04:38.600 mutations. At the other end of that spectrum, what is it about a pancreatic endocrine cell
01:04:45.560 that would allow it or have it be so protected?
01:04:50.560 Yeah. This is a black box at the moment. What you're asking is the fundamental comparative
01:04:56.040 biology question in cancer. That's this decade.
01:04:59.340 Yeah, I leapfrogged us past 2010.
01:05:00.960 We are now wrestling with this opportunity to do comparative biology, not just experiments,
01:05:07.420 but analyses. I mean, what are the building blocks, genetic, epigenetic, the metabolic features?
01:05:12.700 How did each of these tumors assemble themselves to be able to accomplish the various behaviors
01:05:17.440 of cancer that make them lethal? I would say this is where we have more black boxes in diseases
01:05:23.440 like pancreatic cancer and glioblastoma anyway. The hormonally driven cancers are a unique entity,
01:05:29.100 right? So prostate cancer is almost all hormonally driven, at least at its outset. It can evolve away
01:05:33.960 from hormonal drive slash dependence during its subsequent evolution. And then a significant
01:05:39.620 portion of breast cancer, but not all, is hormonally driven. Those cancers need to be considered a little
01:05:45.020 bit separately because they're still using this lineage-dependent tissue of origin-dependent
01:05:50.980 program of using the feeder, the hormone, to help achieve its purpose, if you will, always going
01:05:57.160 back to anthropomorphic concepts in cancer. It's just how I've always thought about it.
01:06:00.580 Cancer and immunology are so geared towards that way of thinking.
01:06:03.680 Yeah, that's right. Yeah, it's immune cells, exactly. You readily put yourself in the driver's
01:06:07.300 seat, if you will, in terms of various immune cell types. Everybody likes to be a CD8-positive
01:06:11.140 T-cell, I think.
01:06:11.980 I'd rather be CT4.
01:06:13.200 A helper.
01:06:14.020 A CD4, yeah.
01:06:14.660 A helper, yeah.
01:06:15.020 I'm more of a helper cell.
01:06:15.800 Right. Any case, now to answer your question, if we had better insights into this, we would have
01:06:20.180 more hypotheses moving towards therapeutics in these cancer types. But the have and have
01:06:25.960 not spectrum in cancer is only getting wider. The advances that have been made in certain
01:06:31.400 areas where we very clearly fingerprinted the top of the pyramid vulnerability, it's not
01:06:37.100 just about mutations. I mean, it really is about other cancer programs that are at the
01:06:41.300 forefront of that cancer slash cancer type. The AZT equivalent has been worked out to dismantle
01:06:47.120 that one program. It doesn't cure everybody, but it helps patients directly, perturbs the
01:06:52.360 hell out of that cell. And I still maintain the hope and, I guess, belief even, if I'm
01:06:57.660 allowed to use that word in a scientific discussion, that secondary vulnerabilities are going to
01:07:02.540 come from being able to have enough AZT-like primary interventions or points of vulnerability.
01:07:07.920 But you said something earlier that I want to repeat because you've alluded to it twice,
01:07:11.580 I believe. It's a bit of a scary concept, right? Which is some of these mutations may have
01:07:16.380 no obvious, immediate, targetable quality, but they enable epigenetic change that itself
01:07:27.120 is the problem and much more difficult to target. Is that a fair assessment?
01:07:31.300 That's right. I dropped that thread from before. I meant to finish a thought previously that the
01:07:35.340 Cancer Genome Atlas Project, like whole genome sequencing of large numbers of cancers, what did
01:07:40.960 it teach us? Well, it retaught us what we already knew in terms of the common tumor suppressor
01:07:45.100 genes and activated oncogenes. The big discovery was how commonly you will find across cancer
01:07:51.500 driver genetic events, so like causative genetic alterations in genes whose protein product
01:07:58.700 regulates chromosomal well-being. So epigenetic regulators, as they're oftentimes thought of.
01:08:04.880 So chromosomes are complicated. They're dynamic in normal cells, and they're definitely dynamic
01:08:10.420 in cancer cells. Think of it as a folding and unfolding of the blueprints. Basically,
01:08:14.980 certain cells in the body only need to read one segment of the blueprint to be able to do their
01:08:19.220 job. Cancers, generally speaking, like to open up the blueprints. That's a fair generalization,
01:08:24.560 and you can reflect that even at just the entire chromosome level. Literally, chromatin is open and
01:08:30.060 being read more actively. It's the only way that a lung cell can figure out how to travel like a white
01:08:35.400 blood cell, ultimately, is you have to open up the blueprint and see that part of it. It's these
01:08:39.760 epigenetic regulators that are being, that now were really discovered by the Cancer Genome Atlas
01:08:44.540 Project. So going back now, I guess 10 years ago is when it really kind of these insights first began
01:08:49.200 about five years ago. That era taught us how widespread these types of genetic alterations were.
01:08:56.140 That was not known before that campaign was launched. So yes, you have these activated events,
01:09:02.100 these tumor suppressor genes that are eliminated. Many of them have to do with DNA repair mechanisms
01:09:06.740 and talk about other common tumor suppressor genes. But anyway, in the middle are these epigenetic
01:09:12.280 regulators that themselves are activated or inhibited through genetic alteration. That was just a big
01:09:18.600 aha moment in the field because it showed how essential, well, A, how cancers do it, that they
01:09:22.980 create this so-called plasticity, this ability to basically go from being a differentiated lung cell into
01:09:28.400 a less differentiated lung cell that's not now able to do things that it's normal lung cells
01:09:32.080 It gives up some of its lung superpowers in exchange for greater pliability. And yeah, it's
01:09:38.180 just, it's like a reality TV show you couldn't make up.
01:09:42.640 Yeah, it's diabolical, but it's using the whole playbook, right? I mean, I use that blueprint
01:09:46.620 analogy, but it really is, you know, every cell in the body has the entire chromosomal content in it.
01:09:53.900 It just doesn't use it. Like that discussion in neuroscience about how much your brain do you use
01:09:58.140 at any given time? Well, the normal cell isn't using so much of the blueprint to do its job.
01:10:03.140 If it's going to become a cancer, which is a cell doing many jobs all at once and to the detriment
01:10:08.840 of the host, ultimately, it really has to open up and maintain this open blueprint, not just wildly
01:10:14.400 open, but very, you know, kind of strategically and purposely. So that happens. Again, relatively recent
01:10:19.540 insight. We are just at the beginning of actually developing tools as in like chemical tools to actually
01:10:25.800 alter the function of these proteins to see, well, then what would happen? Can you actually
01:10:29.620 restrict the blueprint reading? So go back to melanoma one more time. Melanocytes derive from
01:10:35.760 the so-called neural crest. So the brain tissue and these pigment producing cells, like super weird
01:10:41.060 developmental fact, come from the same tissue type. So, and melanocytes is people probably well know
01:10:46.680 distribute generally just throughout the sun exposed skin, although there's a few stragglers here and
01:10:51.780 there, which can form melanomas. Any case, these guys are sparsely distributed in the skin, creating
01:10:56.700 a little bit of a shield of sorts, but not a very effective one. Any case, they derive from the
01:11:01.720 neural crest. That's where they come from. So what happens when you blast the hell out of a melanoma
01:11:06.980 with BRAF targeted therapy and a PD-1 antibody and you're shrinking tumors down, but not eradicating
01:11:11.960 the cells and things come back out? What do they start to look like? They look like neural crest
01:11:16.740 cells. So they take a step back in the evolutionary developmental path and in doing so, find hardiness
01:11:24.780 mechanisms that allow them to survive an activated T-cell repertoire, allow them to have their dominant
01:11:30.440 driver activated oncogene, largely disabled, and be able to manage, not only survive, but ultimately
01:11:36.820 then begin again growing and becoming life-threatening. This is a theme across cancers. I mean, this has been
01:11:42.360 seen now lung cancer and breast cancer and other tumor types where there's been substantial advance
01:11:46.900 in terms of therapies and real outcomes being achieved for patients. So these leapfrog moments
01:11:52.160 that have been happening, common, common principle is this so-called epigenetic state change thing.
01:11:57.660 And the genetic determinants of it, as I said, are really, it's within this past 10 years that we've
01:12:01.680 gotten any insights into it. When we talk about targeted therapy, it's a bit of a buzzword now. And I
01:12:06.960 think for someone like you, it's worth maybe clarifying, how do you define targeted therapy?
01:12:13.440 And what do you think is really our first great example of it?
01:12:17.200 Just to get right through the jargon and be able to keep chemo to one side and targeted therapy to
01:12:22.620 the other. What I've always said is targeted therapy is simply that we knew what we were doing
01:12:27.560 from the beginning. So we knew what we wanted. We knew what the specs were.
01:12:33.440 It's Babe Ruth actually pointing at the wall. Everybody can hit a home run.
01:12:38.880 Not just closing your eyes.
01:12:39.620 That's right. But if you can actually point to where the ball is going to go before you hit it.
01:12:43.520 So it's basically none of the conventional chemotherapy drugs were known to be DNA binding
01:12:48.660 and designed and engineered to be them. But the target product profile, if you will,
01:12:52.820 was specced out for everything that we call targeted therapy. Now, some people might take exception
01:12:57.560 with that, including the first monumental success. So we actually had two versions of targeted
01:13:02.740 therapy at work in the 90s, somewhat quietly. Epidermal growth factor receptor and HER2,
01:13:08.300 which is related in the same family, close-knit family, actually, of epidermal growth factor
01:13:12.540 receptors, plural. These two surface growth factor receptors had been kind of discovered and cataloged
01:13:19.320 in terms of their biologic function in many cancers in the 80s. And then antibody that could reach
01:13:24.400 the cell surface component of these receptors were engineered and were being investigated in clinical
01:13:29.320 trials. They weren't causing heroic effects, as had been hoped. But those were definitely targeted
01:13:34.600 therapies. They did end up moving the needle and largely in combination with conventional
01:13:39.380 chemotherapy, notably in the case of HER2-targeted therapies in breast cancer and EGFR antibodies,
01:13:44.720 at least in colorectal cancer.
01:13:46.200 And before we leave HER2-new, what's the success rate? So if a woman... HER2-new is used pretty commonly
01:13:51.520 as an adjuvant now, right?
01:13:52.560 Yeah. But the naked antibodies produced a 10% to 20% response rate. So tumor shrinkage by the
01:13:58.420 criteria that we use in clinical trials.
01:13:59.760 Yeah. So more than a 50% reduction.
01:14:01.940 Yeah. So notable benefit in a pretty small fraction of patients when given as monotherapy.
01:14:06.580 And given in patients who still had disease.
01:14:08.860 That's right. Initially, patients with overt metastatic disease, overt versus covert metastatic
01:14:13.240 disease. So that's right. So is that really an AZT-like moment to see that type of tumor shrinkage
01:14:19.800 depth slash reliability or unreliability of tumor shrinkage in that low range. So to be debated
01:14:25.980 with conventional chemotherapy, which itself had a 30, 40% likelihood of causing the same
01:14:31.140 amount of regression. And then you are now in business because you're producing 60 plus
01:14:35.320 percent response rates.
01:14:36.280 Now, these are mostly PRs, not CRs?
01:14:38.360 Correct.
01:14:38.760 PR is partial response. CR, complete response.
01:14:41.240 And in every cancer type, it's true in leukemias or hematologic blinkancies, as is true in solid
01:14:46.220 tumors. The more you can beat down the tumor, the more likely that's going to last for a
01:14:50.600 while. So putting people, quote unquote, into remission, which is a leukemia term, actually
01:14:54.980 has its solid tumor equivalent. So complete responses are the most durable. Surprise,
01:14:59.460 surprise. And amazingly, even our kind of stupid CAT scan technology, as much as we think, oh,
01:15:04.560 I can only pick up a smaller than billion, but many, many millions of cells needed to be
01:15:08.820 visible on a CAT scan. It turns out that actually that threshold, like clearing below that threshold,
01:15:12.720 a so-called complete response, actually does mean something very powerful in terms of patient's
01:15:18.100 longish term outcome, maybe not cure, but still longish term outcome, even with certain monotherapies.
01:15:23.220 So HER2 was an example where, yeah, it moved the needle to a degree in a subpopulation.
01:15:27.220 With conventional, stupid chemotherapy, it seemed to actually collaborate reasonably well and improve
01:15:33.020 survival in big phase three trials when HER2 antibody was given with chemotherapy versus
01:15:38.160 chemotherapy alone. That was a slow motion aha moment. What was the fast motion one was the,
01:15:45.040 to me, kind of validating moment, which was in BCR-able translocated chronic myelogenous leukemia.
01:15:52.520 And then the same drug amazingly worked in gastrointestinal stromal tumor. But any case,
01:15:56.400 that came a couple of years later.
01:15:57.540 So what, explain what's the tyrosine kinase? What is that whole thing that you just said? And
01:16:01.380 why does that matter?
01:16:02.240 Right. So the chronic myelogenous leukemia.
01:16:04.660 So there's four leukemias, broadly speaking, right? Acute and chronic, myeloid and lymphoid
01:16:09.320 leukemias.
01:16:09.780 The kids are more typically getting the acute ones, both lymphocytic and myeloblastic, correct?
01:16:15.260 Yeah. Turn that around. Pediatric cancers are rare, generally speaking, but it turns out-
01:16:20.240 Sorry, when a kid gets one, it's more likely-
01:16:22.260 Yeah, right, right. Bone marrow drive cancers are a common problem for kids. We think that actually
01:16:26.560 relates to the number of hits, by the way. Like if you're a kid, you can't accumulate that many hits.
01:16:30.440 And so cancers that can form with few hits are the ones reflected in the pediatric population.
01:16:35.880 So exactly as you say, those things, they're built on few hits. They're rapidly, acute leukemias,
01:16:40.540 rapidly dividing cells, and you can cure them. Kids, greater than 90% with multi-agent chemotherapy
01:16:45.440 cocktails. Yes, that make them sick, but you can cure them. And then there can be long-term
01:16:48.860 consequences. So I'm not trivializing the room for improvement there. But anyway, chemo definitely
01:16:53.660 in pediatric acute leukemia is a big deal. Chronic leukemias happen very uncommonly in kids,
01:16:59.560 but can happen. Adults more commonly get chronic leukemias, but can also get acute leukemias that
01:17:05.580 are more genetically complex than the kids' versions, notably, and therefore harder to cure with the
01:17:10.140 same exact chemotherapy regimens. So one form of chronic leukemia, so-called chronic myelogous
01:17:15.640 leukemia, so in the quadrants as you were depicting them, this is one. People could live with it for
01:17:20.020 five to seven years. If you replace their bone marrow, so-called bone marrow transplant, it could cure
01:17:23.700 a minority population. On a good day, maybe 40% of CML patients can be cured with bone marrow transplant.
01:17:29.560 But a molecular insight came in the 1970s that basically there was a very common
01:17:34.200 kind of macroscopic, if you will, chromosomal change, where one part of a chromosome would
01:17:39.460 very stereotypically, 95% likelihood, that a CML patient would have the repositioning of one
01:17:45.760 portion of a chromosome to another. Which is kind of hard to imagine when you think of how big that
01:17:51.580 is. Yeah. Right? It's a big migration.
01:17:53.700 Everything we've been talking about is this base pair. Maybe it's worth it. I think most listeners
01:17:59.520 know this, but it never hurts to be reminded. Can you walk from the scale of base pair to gene
01:18:06.380 to chromosome? Just give people a sense of, you're on a little spaceship, you get shrunk down, you are
01:18:11.640 entering the nucleus of a cell. What do you start to see as the plane's landing?
01:18:16.940 Right. So we talk about 23 pairs of chromosomes, and that really is a biologic reality. Decades and
01:18:22.340 go the practice of being able to kind of spread out the chromosomes and fix them in a way that you
01:18:26.460 could stare at them outside of intact cell is the picture that people have been shown in elementary
01:18:32.060 school. In cells, they really are. They do exist as coherent, separated entities, but much more
01:18:37.780 nebulous than how they're splayed out as 23 pairs. 23 chromosome pairs, we get one of each from each of
01:18:44.120 our parents, and they range in size. So you got one to 22 looks sort of the way they do, and then XX
01:18:49.160 or XY, round out the... Exactly. And so their size difference relates then to the amount of genetic
01:18:54.560 content in each of them. It's an important point. I usually go straight to genes, but we can come
01:18:59.140 back to base pairs. So there's 30,000 genes. That's the current number that people... I've got to update
01:19:03.960 my estimate. I've been saying 2025. Yeah, so this is... Coding versus non-coding. Coding versus non-coding.
01:19:09.160 So, and that's still, even if you include non-coding, true genes, you still have a lot of in-between
01:19:14.880 material. A ton, a ton. The vast majority of base pairs are function not determined, essentially.
01:19:21.180 Are they important scaffolds? Probably, at a minimum. They're at least scaffolds. This whole
01:19:25.540 notion about opening the blueprint, closing the blueprint, they probably play an important role.
01:19:29.140 Much of the genome probably plays some role in that opening-closing process, normal and
01:19:33.500 pathophysiological. Any case, so you think about the number of total genes that exist and the size of
01:19:39.680 them and the amount of genetic code that's in them versus the dark, quote-unquote, dark matter. At least
01:19:44.200 scaffold, maybe smarter scaffold than we give it credit for. There's relatively small portions of
01:19:50.460 it that we actually understand. Really, coding genes are what we at best understand.
01:19:54.560 Which is why when somebody does a 23andMe sequence where for $100, I mean, you can pretty much... I mean,
01:20:00.940 you're not going to get a complete sequence, but you can get a complete sequence anywhere on the street
01:20:04.320 today. Right. And so usually those tests will hone in on the component of the genetic sequence that we
01:20:09.140 know something about. So you can at least present fingerprint to someone in terms of
01:20:14.080 their inherent or their ancestry and then maybe something about disease, but not a lot of insight
01:20:19.400 there. The genes, of course, vary, individual genes amongst the tens of thousands, vary enormously in
01:20:25.180 their size and therefore the amount of genetic code in them. And the mutation opportunity, of course,
01:20:30.340 we think is to a degree equal opportunity. I mean, you can develop a mutation either because of a
01:20:35.180 replication error or because of an insult.
01:20:36.760 So the larger the gene, in theory, the greater the probability it can acquire a mutation.
01:20:41.840 Sure. And P53, the most famous tumor suppressor gene of them all.
01:20:45.120 How many base pairs?
01:20:46.400 P53, I don't know off the top of my head. I should Google that someday.
01:20:50.100 We'll do it for you. It'll be in the show notes.
01:20:51.880 Yeah. Right. So let's go with ballpark it at a couple hundred thousand base pairs. Big gene,
01:20:59.040 multiple exons that are separated by introns that are stitched together when the gene is
01:21:03.160 transcribed into RNA. And then...
01:21:05.540 And extrons and introns for folks is coding. I mean, it's part that actually gets turned into
01:21:10.460 RNA versus that that doesn't.
01:21:11.980 Exactly. But they still play an important regulating role. And again, at least scaffolding,
01:21:15.980 kind of stitching together.
01:21:17.020 And that's something that, again, 20 years ago, people thought those introns don't matter.
01:21:21.040 Yeah, they're dead. Right. Exactly. But that's where all the...
01:21:23.140 Junk DNA.
01:21:23.600 That's where all the regulating elements really largely reside. So it's a huge... In the past 20 years,
01:21:28.480 it's been a parallel track, big area of innovation. So in any case,
01:21:32.920 so then you have a big gene like P53. So 50% of cancers have genetic aberration P53. Well,
01:21:38.700 partly it's just a really large gene, but so you can pick up mutations in it seemingly relatively
01:21:43.700 easily. But it's a master regulator.
01:21:46.180 What percentage of cancers do not have a P53 mutation?
01:21:49.600 50%. And the other 50 do.
01:21:50.960 Oh, so it's 50-50.
01:21:51.900 Yeah, yeah, yeah.
01:21:52.220 I would have guessed that fewer people with cancer do not have a P53 mutation.
01:21:56.880 Do not.
01:21:57.360 Yeah, I would have thought it was almost essential.
01:21:58.420 Okay. So P53 is such a complex central node in a very complex network. So there's tons
01:22:04.780 of translated proteins that interact with the protein product P53. And then P53 has a lot
01:22:09.860 of outputs, like literally networks of outputs. It's in cancer, in any case, I would say it
01:22:14.140 is the most magnificent and thus far well mapped out of these networks. What is the function
01:22:19.360 of P53? Very simply put, it's basically a sensing apparatus. It's trying to understand
01:22:23.400 how bad things are in a cell. And usually people would say, well, first, if there was a singular
01:22:28.440 function, it's how poorly is the genetic code doing? Which is to say the chromosomal architecture,
01:22:34.760 how intact versus not intact is it? How many mistakes, mutations or mistakes, so insults versus
01:22:40.920 mistakes, how many of those exist and are being repaired at any one time? Like, so that machinery
01:22:44.940 is at work, the DNA repair machinery that feeds then into P53, which basically is just sensing
01:22:50.120 overall, how well are we doing in terms of kind of... And P53 possesses the power to command
01:22:57.300 apoptosis directly. Yeah. So it senses damage in a normal cell, that's its function, in a cell that's
01:23:02.380 becoming abnormal, continues to keep its finger on that pulse. And if there's catastrophic damage,
01:23:07.220 then it's P53 that says, let's not try to repair this anymore. Let's fold up shop and undergo a civilized
01:23:12.660 cell death and let our neighboring, let's say, liver cell just take over and do our job if we're a liver
01:23:18.560 cell. So P53 is the master regulator in all cells in the body. I love doing these podcasts because I
01:23:23.100 still, even if it's on a topic like this where I know a little bit, like I'm amazed at how much I
01:23:27.100 keep learning. So 50% of people who get cancer have a perfectly intact P53. Yeah, that's right.
01:23:33.140 Yeah. But the point about describing the network is the likelihood that they will have a genetic
01:23:37.600 aberration in one of the inputs or one of the outputs of P53 is enormously high. Got it. So we say
01:23:43.080 the gene P53 only 50% of the time is mutated, but the pathway is virtually always hosed.
01:23:48.800 So retinoblastoma gene, you're familiar with that one. That's another very famous,
01:23:52.140 long ago described tumor suppressor gene. What was not known decades ago, but is known now is that
01:23:57.420 they actually relate to each other and you will find cancers that if they don't have a P53 mutation,
01:24:02.080 they will have an RB retinoblastoma gene mutation. It's another big tumor suppressor gene that actually
01:24:07.280 is quote unquote downstream or regulated by P53 and its alteration will do much of what a P53
01:24:13.560 mutation will do. So there's these kinds of functional substitutes in that axis. On the
01:24:18.460 activated side, that's where I spent most of my career. So KRAS. Exactly. Talk to me about KRAS.
01:24:24.280 What is this clown doing? So I was just going to say that growth factor receptors, which I touched
01:24:27.400 on before because epidermal growth factor receptor and HER2 were these kind of early discovery slash
01:24:32.720 therapeutic translation exercises. Well, that was the beginning of a theme that to this day we think
01:24:38.820 is kind of the biggest unit in terms of where the activating events happen and where we have drugs
01:24:44.820 now is in the growth factor receptor RAS and RAS pathway system. So growth factor receptors,
01:24:52.420 literally their normal function is to receive growth factors. So in a cancer cell, if you can figure out
01:24:56.940 how to grow in a growth factor independent way, then you've accomplished a good trick because now
01:25:01.880 you'll be able to survive very harsh environments. You'll be able to replicate kind of an autonomous,
01:25:06.140 not governed by not just environment in terms of nutrient availability, but even like what your
01:25:10.360 neighbors are telling you, you should and shouldn't do. You can ignore that.
01:25:13.060 One of the explanations for why we see more aggressive prostate cancers in men with lower
01:25:18.180 testosterone levels than higher testosterone levels. If your prostate cancer can grow without
01:25:22.700 testosterone, beware. It's a bad problem. And then same with breast cancer, with hormone receptor,
01:25:27.220 positive breast cancer, quote unquote, versus negative, the prognosis and treatment response.
01:25:31.140 Yeah, the negatives are wildly different.
01:25:32.520 Much more different.
01:25:33.000 A different disease, basically. So that's exactly right. So cancers fundamentally need to accomplish
01:25:38.420 this task. So growth factor receptor genetic alterations, HER2 is genetically amplified,
01:25:44.780 then like massively increasing the number of surface receptors and allowing them to actually complex
01:25:49.400 together and signal in the absence of needing the growth factor itself. That was the seminal discovery
01:25:54.640 going back even into the 80s, but certainly picked up a lot of steam in the 90s. And then was a validated
01:25:59.760 target, ultimately, as I said, in a relatively slow motion way compared to BCRA-able, which we're
01:26:04.360 going to come back to. So anyway, these growth factor receptors feed RAS, R-A-S, and that comes
01:26:10.900 in three forms, KRAS, HRAS, and NRAS. And 25% of all cancers have a RAS mutation. Right downstream of
01:26:18.360 these growth factor receptors is where RAS sits just on the inside of the cell surface. We can't drug it
01:26:23.120 directly, certainly with an antibody. Small molecule inhibitors have been hard. That's its own discussion
01:26:27.100 terms of what's assailable and what's not assailable in terms of cancer drug targets, but let's park
01:26:31.520 that one and say that RAS is a big deal. And then RAS has its so-called effector pathways. And the
01:26:37.560 numbers, to a degree, I think, how many people agree on the number of cancer-relevant RAS effector
01:26:43.200 pathways? I can't find a lot of consensus there, but six is a reasonable number of described cancer-related
01:26:49.260 RAS effector pathways. So downstream of RAS, RAS will activate other cascades. The two most famous are
01:26:55.080 the MAP kinase pathway, where I've focused my career, PI3 kinase pathway. Arguably, there's
01:26:59.540 more mutations that activate the PI3 kinase pathway than the MAP kinase pathway. But
01:27:02.580 Lou and I have been trying to sit down for, we cohabitate parts of New York that are 10 feet away
01:27:07.460 from each other. So at some point, Lou and I are going to sit down and have a lengthy discussion on
01:27:11.140 PI3K. Yeah. This is where I wanted to take a little deep dive into Lou and Craig Thompson's-
01:27:16.520 By all means. Travels in the PI3 kinase pathway. Here's a pathway in this growth factor
01:27:20.980 receptor signaling apparatus. Metabolic regulation comes, we think, largely, but not completely,
01:27:27.900 through the PI3 kinase pathway. If you link up all the discoveries of Lou and others regarding the
01:27:33.300 importance of PI3 kinase in cancer, the fact that 20% of cancers have PI3 kinase, intrinsic mutations
01:27:39.060 in one of the isoforms of PI3 kinase, most commonly alpha, it's a nasty little trick. I mean,
01:27:44.680 it's co-opting this kind of metabolic regulation pathway. It largely explains growth factor independence
01:27:50.380 of cancers that have those mutations. But these are metabolic pathways that are fundamental to
01:27:54.840 normal cells as well. And so where's the therapeutic index in terms of leveraging that
01:27:58.660 observation? This has been a major challenge and not yet really adequately tackled. But one positive
01:28:04.400 result, at least in PI3 kinase mutant breast cancer that finally came across in slow motion,
01:28:09.320 phase three result. When it takes a phase three clinical trial to be the aha moment, that's a slow
01:28:13.240 motion result versus 20 patients get treated and you know you're in different territory, which is
01:28:17.440 the BRAF example in melanoma and then other cancers thereafter. So the MAP kinase pathway is this
01:28:23.560 proliferative pathway as it's canonically described, but it does other things, at least in cancer when
01:28:27.880 it's co-opted by mutation. Common theme, by the way, when you activate an oncogene in cancer,
01:28:33.820 very commonly you will see that the downstream wiring diagram changes and that pathway is now able to do
01:28:40.720 more things than we would have given it credit for or said that it had those same abilities in a
01:28:46.180 normal cell. It's what we mean by oncogene addiction. If you turn it around in terms of
01:28:50.300 building blocks, oncogene addiction means that cancer really needs that activated oncogene to
01:28:56.800 be able to do not just one thing like dry proliferation, but actually to alter other essential
01:29:01.620 programs for cancer. The flip side is that normal cells in the body, they have other ways. They can
01:29:07.340 break up the work between proliferation and metabolism between, for example, the MAP kinase pathway and the
01:29:11.860 PI3 kinase pathway. But in melanoma, for example, where we see, we call it kind of this paradigmatic
01:29:17.280 MAP kinase pathway activated tumor. Yeah, it cares about the PI3 kinase pathway, but in quite a secondary
01:29:22.620 way. Breast cancer, flip that around. So this idea that we could actually come up with an understanding
01:29:28.920 of these normal cell processes that are co-opted by cancer, drug them, and do more harm to the cancer
01:29:34.180 cell than the normal cell, it wasn't intuitive to people. I mean, this goes back to this watershed era of
01:29:39.980 the early 2000s when the concept of targeted therapy finally kind of had its aha moment.
01:29:45.360 It really relied on this concept. And term oncogene addiction, when did I first hear that? I suppose it
01:29:52.040 was in the early 2000s. This idea that by a cancer co-opting this one molecule, it's actually now
01:29:58.760 essentially using it to drive kind of more components of cancer biology than you would have thought in
01:30:05.060 terms of the normal physiologic role of that molecule and where there's compensatory mechanisms
01:30:09.520 and parallel processing that can happen in normal cells that make it not so dependent on the function
01:30:14.240 of that one molecule. So anyway, RAS, 25% of cancers have a RAS mutation. 20% of cancers have a PI3
01:30:19.820 kinase mutation. There's a little bit of overlap there. 8% of cancers have a BRAF mutation, which is
01:30:24.600 intrinsic in the MAP kinase pathway. It's the most popular point of mutation in that pathway.
01:30:29.300 What percentage of melanomas have a BRAF mutation?
01:30:31.400 About 50%. And it was that simple alignment of facts. I was finishing my fellowship in 2002,
01:30:38.640 June of 2002, becoming faculty at Penn in July of 2002. And June of 2002 in Nature was described the
01:30:46.220 research project that the Sanger Center in the UK, one of the sequencing powerhouses then and now,
01:30:53.160 they had launched this campaign specifically to sequence the RAF genes, not RAS, R-A-S, the one that's
01:30:58.340 undruggable, unfortunately, still to this day, but rather the RAF genes. Why did they do this?
01:31:03.100 Because the MAP kinase pathway had been implicated as being relevant in cancer for a couple decades.
01:31:07.680 And no one knew other than RAS mutations that can activate it. Outside of that, no one understood
01:31:12.840 how and why the pathway could be co-opted by cancer cells. So a logical thing to do would be just go one
01:31:18.780 bucket down in the bucket brigade from RAS to the molecule that RAS regulates, which is RAF,
01:31:23.720 three isoforms of RAF, C-RAF, B-RAF, and A-RAF, understood lesser and lesser degree across that
01:31:30.020 sequence. So C-RAF was the first discovered, called RAF1 at the time. Then it was renamed C-RAF
01:31:34.640 later. People had studied C-RAF to a large degree. B-RAF, not so much. There were only really a couple
01:31:40.440 slash few B-RAF mavens in the world, and still to this day, not very many A-RAF mavens.
01:31:45.280 The hypothesis was that these RAF genes are probably going to have some mutations,
01:31:49.800 and C-RAF would be the one most likely because it'd been the best studied up to that date.
01:31:54.720 So the big headline from that nature paper was rarely ever do you see a C-RAF.
01:31:59.860 B-RAF was the big discovery. 8% of all cancer was the estimate when they sequenced 484 tumors.
01:32:05.880 A-RAF rarely, if ever, mutated. So B-RAF was the one. The why of that is its own fascinating little
01:32:11.900 bit of kind of molecular evolutionary history. B-RAF and C-RAF are different molecules.
01:32:16.240 Does RAS actually play a causal role in the mutation, or is it more a function of
01:32:21.840 the things that bug RAS bug B-RAF? Yeah, that's true. They're related. They talk to each other.
01:32:29.000 But let me answer it this way. In a cancer that has a RAS mutation, you will not find a B-RAF
01:32:34.800 mutation and vice versa. They are mutually exclusive. So you don't need to skin that cat twice. You do it
01:32:40.220 one way. RAS is sufficient or B-RAF is sufficient to get activation of the pathway. Melanomas,
01:32:46.320 for example, 50% of them have B-RAF mutation. Very similar to the P53 problem.
01:32:50.100 Yeah, that's right. These tumors, anyway, need it. And many cancers need this pathway on.
01:32:54.980 How they accomplish it varies. And we don't understand all the determinants of why certain
01:33:00.300 cell types are more prone to picking up certain mutations as their, if you will, their means of
01:33:05.620 activating certain pathways. But there's certainly a teleology argument there. Any case, so B-RAF
01:33:11.060 mutations discovered an 8% of all cancers. I had decided melanoma was a cancer of terrible unmet need.
01:33:16.740 Interesting biochemistry insights coming from the previous couple decades. Very strong lab-based
01:33:21.720 science in melanoma at Penn, where I was choosing to put myself on the clinical frontier, clinical
01:33:27.000 research frontier. This aha moment in this paper was that 8% of cancers had B-RAF mutations,
01:33:32.060 but the cancer type that most commonly had them in that paper, later paper described that there's
01:33:37.620 one rare cancer that more commonly has B-RAF mutations, was melanoma at 50%. And the vast,
01:33:44.080 vast majority of those mutations affected a single point in the gene.
01:33:47.900 So let me pause now to go back to the question so that people understand scale. A point in a gene,
01:33:53.500 right? So you have 23 chromosomes, call it 30,000 genes. Let's make the math easy. You could have
01:33:57.660 about 1,000 genes wrapping around each chromosome, order of magnitude. Okay. So one chromosome's got
01:34:03.500 about 1,000 genes wrapped around it. You got 23 pairs of those. And now each gene could be anywhere
01:34:10.540 from a few hundred to a few hundred thousand base pairs. And what you're talking about is one of those
01:34:17.760 could be mutated. You could get one letter wrong out of 100,000 and you change the function of a gene.
01:34:24.020 Exactly. You asked before about kinases and this is going to-
01:34:26.960 All of this is in service of CML.
01:34:28.880 Right. Exactly. We're going to link those two concepts. So basically we have, I use that phrase
01:34:34.160 bucket brigades. We have these pathways where one molecule alters another, alters another. We
01:34:39.640 too commonly think of these as linear, one augmenting another followed by another and not
01:34:44.180 as systems that where there's side inputs into these pathways, which has been well described,
01:34:49.480 including in the MAP kinase pathway. In any case, follow me here that basically
01:34:53.260 RAS activates RAF. When RAS itself is activated, it pushes RAF into a pair of molecules, so-called
01:34:59.580 dimers, and will facilitate their phosphorylation or activate a molecular feature change that allows
01:35:05.700 them to be active. So kinases are a form of enzyme whose job is to add a phosphate group,
01:35:13.320 a single fairly small molecular entity to specific amino acid residues on its target. And usually it's
01:35:20.900 more than one target, but the point is that there is a fidelity in terms of that relationship where
01:35:25.120 you've got a kinase and its substrates, plural. So RAS will activate RAF, RAF will activate MEK,
01:35:31.180 MEK will activate ERK, all through phosphorylation events. So they glom onto each other and find the
01:35:35.800 right domain and stick a phosphate group on there. People are used to hearing me say that I get
01:35:39.760 phosphorylated and I think they understand exactly what you're-
01:35:43.220 I can sometimes- my five-year-old can get me more phosphorylated than any tyrosine kinase in the
01:35:49.980 history of our known universe. So phosphate residue additions are- they're not the most important,
01:35:56.200 but they're a key facet of how the molecular machinery works inside of cells in terms of how
01:36:01.080 to activate or inactivate these networks. And here we're talking about growth factor receptor
01:36:05.540 related networks. So right in the middle of the so-called kinase domain, the part of BRAF
01:36:11.460 that actually is basically responsible for latching a phosphate residue on MEK, its downstream
01:36:16.620 substrate, right in the middle of that domain, I mean literally right in the middle, is where
01:36:20.560 these mutations happen in the vast, vast majority of cases. That discovery alone was just shocking,
01:36:26.480 right? Because by chance alone, you're not going to find- stumble upon these mutations piling up in
01:36:30.840 8% of cancer. And there's one point right in the middle of the kinase domain.
01:36:34.780 That wasn't also in the same paper, was it?
01:36:36.760 No, that point was.
01:36:37.960 It was.
01:36:38.420 Oh yeah. The distribution, if you will, of them being V600 position mutations, a valine at the
01:36:43.660 600 position in the amino acid sequence, right in the heart of exon 15, which is in the middle of
01:36:47.920 the kinase domain, that was in the paper. The additional killer experiment that they did was to
01:36:52.700 basically transfect that into a fibroblast, so a normal cell, and show that that could transform
01:36:56.980 them and make them proliferate to a degree. And that was it, kind of end of paper. So the phenomenology
01:37:02.260 that these mutations exist, this wild distribution, or if you will, non-distribution, this like piling up
01:37:07.840 at this one position, it was just this huge aha moment. And when you link that in melanoma with
01:37:13.680 this couple decades worth of insights that the map kinase pathway really seemed to be important in
01:37:18.280 this tumor, and now you find these mutations sitting here right in the middle of the pathway,
01:37:21.380 like that was just like the most drop-dead, obviously important thing in my view, and a
01:37:26.260 couple other people's view, but shockingly few other people at the time decided to take a complete
01:37:30.600 left or right turn and focus on it. But that was the dawn of my career. So this is a problem with
01:37:35.160 biomedical research, is that every time a discovery is made. It impacts the people who are in search
01:37:40.380 of substrate. Precisely. Who've said, I want to get to the frontier of known and not known,
01:37:44.060 and I want to investigate. Everybody else is busy. They're already doing their thing. And if they're
01:37:47.920 grant-funded, then forget about it. Like they're already mining away. I think of the lab I was in,
01:37:51.860 in 02, 03, 04, it was all immunotherapy. Like we never talked about, I mean, maybe that paper came up
01:37:59.060 at Journal Club, as like one of 50 papers discussed that year, is interesting. But I mean, it was
01:38:05.480 anti-CTLA-4. It was TIL. It was, because everybody there was super seasoned, super senior, and they
01:38:11.240 were already on this path. That's a great point. I never really thought of that bias that can exist
01:38:16.180 temporally through a person's career.
01:38:18.580 Yeah. And melanoma, for all the reasons we discussed before, had been dominated by cancer
01:38:22.140 immunologists, because they recognized that there was this robust evidence of tumor-immune
01:38:26.080 interaction. You had this huge opportunity.
01:38:27.980 Yeah. And so the idea that you could just make one more maneuver, be it a cell therapy or a
01:38:32.980 checkpoint antibody or a cytokine, and tip the balance and clear the tumor, the field was very
01:38:37.740 focused on that. And if you were interested in the general notion of cancer immunity, well,
01:38:41.840 melanoma seemed like a very natural home for that work. And that really was the subtext. I came walking
01:38:47.200 in with this very different idea.
01:38:49.100 The last thing you wanted to do was do what everybody else was already doing.
01:38:52.040 Exactly. I'll just finish this point by saying that this is the whole coaching point to the
01:38:57.460 petrified or even paralyzed young trainee who's thinking, well, how am I going to find my entry
01:39:03.320 point? Where am I going to find something to work on? What I say is, okay, you're not waiting
01:39:07.440 for something top secret that someone comes and whispers in your ear. What you're waiting
01:39:11.000 for is the next Nature Science and Cell paper to be published that describes something that's
01:39:15.000 very important in an area that you've said you've just, for some intuitive reason, that you have
01:39:18.640 an interest in. And trust me, the field is not going to drop everything that they're doing
01:39:22.720 to go pursue that. But if you're at the dawn of your career, you're in the perfect moment
01:39:26.600 to now actually build the knowledge base, meet the people who are the relevant players, assemble
01:39:31.720 the knowledge, pull together the tools to actually start testing this hypothesis, whether it's
01:39:35.240 you're a wet lab investigator or a clinical investigator, the same. And I've never witnessed
01:39:39.220 a case where someone's been basically crowded out or hasn't been able to make a career
01:39:43.360 in investigation by using that approach. I'm trying to come back to the watershed moment
01:39:47.360 of BCRA, but I'm going to do it this way. So BRAF mutations were discovered in 2002.
01:39:52.300 People ignored it, not only because they thought tumor-immune interactions were a cooler thing
01:39:57.340 in melanoma, but remember, melanoma is jacked up with mutations. It's got an inordinate number
01:40:02.700 of them. So you find this one. So what? If there's a cancer on Earth where we're poking
01:40:09.340 that beast with a single drug approach, just antagonizing BRAF, is going to do nothing.
01:40:14.960 This is the example. That was the headwind argument.
01:40:17.940 Absolutely. In fact, I would say that that should be the null, second, and third, fourth
01:40:23.880 alternative hypothesis. That is a capital so what?
01:40:27.760 Yeah, exactly. Maybe we'll circle back later.
01:40:30.820 Maybe that's why it wasn't even mentioned in journal club.
01:40:33.120 And then when the first putative RAF inhibitor didn't work, this was the other big, ah, we
01:40:37.700 told you so moment, which let's table that for a moment. So chronic myelitis leukemia
01:40:42.860 is fundamentally different. I mean, this was known even in the seventies, that if you look
01:40:46.400 at the splay of chromosomes and you see this one migration of one segment.
01:40:50.140 Right. And the listener now understands why I got phosphorylated when you said that so
01:40:53.700 they could understand it. These chromosomes are huge. Like one piece of one of them could
01:41:00.300 literally, it's like picking up a building in a cell and moving it and attaching it to
01:41:05.640 a condo somewhere else.
01:41:07.400 So this was observed by Peter Knoll decades ago. And as a characteristic event in CML, that
01:41:13.400 you would see this in at least 95% of cases, this massive chromosomal shift, but not others.
01:41:17.660 In other words, it wasn't like the DNA was shredded at the chromosomal level. It was this
01:41:21.620 one migratory move and it was like characteristic pathognomonic of the disease. That was striking,
01:41:28.100 right? Just that fact.
01:41:29.540 Striking. It's also important for the listener to understand. You could see it under a microscope.
01:41:33.440 Like there's nothing genetically, like all this stuff you and I are talking about right
01:41:38.760 now, you don't look at your microscope and see that.
01:41:41.200 No, you got to sequence individual base pairs and large numbers of them.
01:41:43.760 This might be the only genetic mutation in cancer that is visible under a microscope.
01:41:48.980 Well, we'll come back to that.
01:41:50.280 There's another example?
01:41:51.180 Yeah. Well, fusions in general.
01:41:52.480 Okay. Yeah, yeah, yeah. No, that's a fair point.
01:41:53.840 So the term translocation was the term that was used then. Now we use the term fusion.
01:41:58.400 Yeah. My point being anything outside of a piece of a chromosome moving.
01:42:01.640 So fusions as a theme in cancer have their own kind of substrate of discovery, but this was the
01:42:06.940 first one. So basically you had what appeared to be at the chromosomal level, genetically simple
01:42:11.540 cancer, where nearly always one big fragment migrated to join another big fragment. What was
01:42:17.020 at that juncture? Like why were those two coming together? So fascinating. So this is a white blood
01:42:23.120 cell cancer, right? The myeloid cells are white blood cells, a branch of them anyway. And so to get
01:42:27.800 chronic myelitis leukemia, you needed this genetic migration thing to happen. On one side of it is
01:42:34.100 the BCR gene. And that gene is basically responsible for immunoglobulin kind of reshuffling in white
01:42:41.980 blood cells. It's a very dynamic, very active gene in white blood cells. If they're going to be able
01:42:46.840 to do their immunologic job and create the relevant kind of repertoire of foreign recognition,
01:42:52.200 then the BCR gene needs to be active to facilitate that program. Let me put it that way.
01:42:57.500 So any case, the BCR gene is on one end of this migration event. It's not a doer in and of itself.
01:43:04.860 It's just a very active gene locus that's just on, on, on in white blood cells. On the other end
01:43:11.980 is the abel kinase. So abel kinase is a signaling molecule. It's inside of cells. It's not important in
01:43:18.940 all cell types. It's important to a degree in white blood cells. That's, I think, a fair
01:43:23.940 summary statement now, looking back 20 years in retrospect with a lot more information.
01:43:28.380 But this is a signaling molecule that does a lot of work inside of cells. It's a kinase,
01:43:31.660 so it phosphorylates substrates. And when BCR-ABLE, this very active regulating domain,
01:43:38.080 is stitched onto the abel kinase.
01:43:39.940 BCR is stitched to abel.
01:43:41.180 Yes, correct. So it creates the BCR-ABLE translocation or fusion. So you now have a new
01:43:44.940 gene product of these two genetic components being stitched together that otherwise
01:43:48.160 wouldn't have been. They're quite far apart from each other on chromosome 9 and 22.
01:43:52.100 So in any case, when they come together, you crank up the expression of abel kinase. So abel kinase
01:43:57.240 is normal abel kinase. It's not mutated.
01:44:00.100 Yeah. It's just all of a sudden, instead of firing once every minute, it fires 40 times a minute.
01:44:05.540 It's jacked up. It's an expression to preposterous degrees. You have an enormous amount of abel kinase
01:44:09.680 being made in these white blood cells because the BCR-ABLE locus is just being driven all the time in
01:44:14.580 normal white blood cells. So now you've got ABLE on the other end of that.
01:44:18.380 Which is really aptly named.
01:44:20.040 Abelson was the discoverer of it.
01:44:22.360 But in this context, it's aptly named. It's very ABLE. It's an ABLE kinase that has become much
01:44:26.540 more ABLE.
01:44:27.280 Right. But unlike BRAF, which has this activating mutation sitting right in the middle of it,
01:44:31.660 nucleotide substitution resulting in an amino acid substitution that alters its kinase function,
01:44:35.520 this is just normal ABLE.
01:44:36.780 Yeah. It's just more on.
01:44:38.040 Yeah. And HER2, amplification and breast cancer, also just there's more of it. And then they
01:44:42.560 complex together and signal more. So when we talk about mutation and genetic alteration,
01:44:47.280 just understand that there's amplification, there's point mutation, and there's translocation
01:44:51.420 or fusion. These are the three canonical ways that you can have it.
01:44:54.520 And do most of the fusions have this phenotype?
01:44:57.780 So this is other fusion cancers outside of-
01:44:59.960 Yeah. Meaning do they have this phenotype of normal protein just doing more?
01:45:05.520 Precisely. Yeah. And kinases are the ones that have been discovered, described, and now drugged
01:45:10.120 multiple times. So what's fascinating about now, this is a 2019-ish insight, or at least the past few
01:45:16.820 years, is these fusion or translocation, quote unquote, driven cancers, they tend to be genetically
01:45:22.860 simple. Not all of them. Point mutations happen in the sea of genetic complexity, melanoma being an
01:45:30.360 example, but all BRAF mutations distribute across cancer types that are actually quite genetically
01:45:34.820 complex. There's a lot of other genetic aberrations turning on and turning off other things.
01:45:39.380 These fusion-driven cancers, they seem to get a lot of juice out of that one genetic alteration.
01:45:45.960 So BCR-ABLE was the initial example. But remember, it's chronic myelogenous leukemia. It would kill
01:45:50.280 patients over five to seven years. And it was super genetically simple, at least at the level that
01:45:55.160 one could make such comments in the 90s, which is when therapeutically attention started to be
01:46:00.180 turned to this able kinase phenomenon. So it turned out that Siva-Gyge ultimately subsumed into Novartis
01:46:06.860 over serial acquisitions, had a kinase inhibitor program broadly for cardiovascular disease. I knew
01:46:13.080 Siva-Gyge from my father's academic cardiology pursuits. So they had these kinase inhibitors. They
01:46:18.620 were pretty crude instruments. But in the mix, my understanding initially was all endothelial
01:46:23.620 proliferative cardiovascular disease. It was the kind of phenotypic screening, if you will, that was
01:46:28.740 being done with the kinase inhibitor library at the time. Again, this predates the cancer
01:46:32.880 investigations. So they created this library, not massive, of kinase inhibitors. It's a small
01:46:38.000 molecule tool compounds. So there's this guy, Brian Druker, at Dana-Farber in Boston at the time,
01:46:43.080 who uncovers that now Novartis has this kinase inhibitor library. And in it is a apparent
01:46:49.560 able kinase inhibitor. Not perfectly selective for able kinase. Kinases exist in the hundreds.
01:46:55.340 So about 600 or so kinases have been described in the family tree. They're highly related,
01:47:00.880 but then there's some that are more distant cousins than others. And if you try to inhibit
01:47:05.520 a kinase, it's pretty easy to pick up inhibitory activity against another kinase because of their
01:47:11.220 relatedness, their structural relatedness. So it turns out imatinib, the first able kinase inhibitor,
01:47:15.980 it was not just an able kinase inhibitor. Fortuitously, it was also a C-kit inhibitor,
01:47:20.940 which we'll come back to because that's the gastrointestinal stromal tumor, dual purpose of
01:47:24.440 that molecule. But in any case, he wanted an able kinase inhibitor. The more perfect he could have
01:47:28.820 had, the better, more selective and only targeting able. But back in these days, certainly in the 90s,
01:47:35.500 it was a difficult sport to actually profile how promiscuous or selective a kinase inhibitor was.
01:47:41.680 So it wasn't really known what its full selectivity spectrum was. But able kinase is what it was
01:47:46.640 labeled as an inhibitor of. So it's been cataloged in many papers, but just briefly put that basically
01:47:52.940 Brian started this campaign to try to get Novartis to liberate this molecule that had been to a degree
01:48:00.600 investigated in cardiovascular disease models, but to like kind of get it out of the company and have
01:48:06.960 it actually made available experimentally initially in model systems, not even in humans yet.
01:48:12.040 Any case, fast forward now. So the drug enters phase one clinical trials in cancer patients with
01:48:18.640 knowledge that there's this cancer out there.
01:48:20.840 And this is like mid 90s?
01:48:22.660 No, no, no. This is now late 90s. And I'm about to show up in fellowship in July of 2000.
01:48:27.380 And it's 2000-2001 that the ongoing phase one trial cleared the first few dose levels where
01:48:34.640 somewhat homeopathic doses were given. Didn't have to go on for very long as a phase one study.
01:48:39.660 Recruiting these patients, these patients who didn't need to be molecularly tested because you
01:48:43.860 just knew by their diagnosis that they were at least 95% likely to have this alteration in those
01:48:48.420 cells. And so it was in the midst of my first year of fellowship.
01:48:52.340 Yeah, this is the phase one trial where there's efficacy.
01:48:54.420 Yeah. First time ever that basically consecutive patients were responding
01:48:58.980 to therapy in a phase one trial as the dose was still being escalated.
01:49:03.100 So talk about aha moment. I mean, you needed three patients, six patients,
01:49:07.180 not a big phase three trial to know that there was a transformational event happening.
01:49:11.680 So that happened in the first year of my fellowship. And my naive talking points, I was saying,
01:49:17.540 this is the future of cancer. This is what we're going to do.
01:49:19.920 This is it. This is our first ACT moment. Drugs working extremely reliably, killing lots of cancer
01:49:26.220 cells, admittedly not eradicating all of them in most patients. But still, there were cures even
01:49:31.020 in the early days, or at least durable, complete responses. So anyway, the point being that this was
01:49:36.400 the big moment. The objection to that big moment relates to the comment I made a little while ago,
01:49:41.500 which is, this is chronic myelitis leukemia. This is a genetically simple thing. This is barely cancer
01:49:48.180 compared to pancreatic cancer. This is barely cancer compared to non-small cell lung cancer.
01:49:52.660 Okay, fine. It worked here. But why on earth would you think this is going to work in real cancers?
01:49:58.380 And again, let's make sure people understand why you're saying CML is barely cancer. You have a
01:50:03.220 translocation fusion that does not even mutate the kinase involved. So is it safe to say that
01:50:11.420 someone with CML doesn't actually contain true genetic mutation?
01:50:16.920 That's fair. Stable phase CML, as it's called, which is this long period of time where people will
01:50:23.020 have large numbers of these abnormal white blood cells circulating, but not impairing their health in
01:50:28.080 any significant way. Stable phase CML is this genetically simple thing. Given enough time to
01:50:34.740 evolve, just like we talked about with the small solid tumor, give it enough time to evolve, it will
01:50:39.600 pick up more alterations. And the rate at which alterations are picked up accelerates also. So
01:50:44.440 evolution begins to happen in a more substantial way, leading to accelerated phase and then blast crisis
01:50:50.300 and patients die of an acute leukemia-like death. So CML isn't quote-unquote real cancer in this
01:50:57.780 objection rendering frame here for a good long time, but it certainly becomes real cancer
01:51:03.320 ultimately. So the New England Journal of Medicine publishes the back-to-back papers in 2001 now of the
01:51:10.180 phase one clinical trial describing these heroic and quite reliably observed responses to single
01:51:15.220 agent abel kinase inhibition with a non-perfect abel kinase inhibitor in the form of imatinib.
01:51:20.600 So this felt certainly like a big deal. The next paper in this back-to-back, same authors,
01:51:26.140 were reporting on the activity of imatinib, the anti-tumor effects of imatinib in patients with
01:51:31.160 accelerated phase and blast crisis CML. So same disease, now allowed to genetically evolve and
01:51:37.020 become more complex and certainly to pick up additional mutations beyond this foundational
01:51:41.080 translocation event. What happened in those patients? It wasn't even discussed. People for
01:51:46.360 years were celebrating this CML, stable phase CML result, and never would you see a talk describing,
01:51:53.060 well, what happened with the same drug now in a more genetically complex environment where the same
01:51:57.340 truncal as an original alteration existed, but now surrounded by these other partners that were
01:52:02.520 clearly important because now you're transforming into a truly aggressive life-threatening disease.
01:52:07.580 You got responses.
01:52:09.060 They weren't durable.
01:52:09.700 They were transient. They lasted for months at best, weeks in some cases. So yeah, you could poke it with
01:52:15.100 a stick, but it would just laugh its way right around within a very short time and patients would still
01:52:19.740 come to their disease. So this is where the debate was. Okay. So you have CML in its stable phase where
01:52:26.040 you get these kind of heroic, deep and durable responses. Okay. Map that out for me and the rest
01:52:30.940 of cancer.
01:52:31.660 Right. So you realize that CML is the exception. It's not the rule.
01:52:34.860 Well, this is the argument, right? This was the argument that never again are we going to find such
01:52:39.240 genetically simple cancers where you can get deep and durable responses from a single agent targeted
01:52:43.020 therapy. Now, again, I didn't feel so defeated by that argument in the sense that I,
01:52:46.760 my talking point, even before we had the cancer equivalent of AZT was, well, this isn't going to
01:52:51.840 be about one drug. This is cocktails. Look, look, it took cocktails to wrestle HIV down. And that's a
01:52:57.060 laughably simple organism compared to a human cell that's now been co-opted by the blueprint being
01:53:03.460 widely opened. So of course it's going to take combinations. How high order a combination do we
01:53:08.160 need? Well, that goes back to the building block argument. We still don't know any case, but we still
01:53:13.200 need to find our individual AZT moments and hope that they would actually do something for an
01:53:17.080 individual patient and not just serve as a biologic building block. So this was the subtext. Fast
01:53:22.760 forward and just connect one dot, which is that one thing that we have learned is that even in
01:53:28.640 so-called solid tumors, so leaving aside the leukemias like chronic myelitis leukemia,
01:53:33.880 even in solid tumors, you will find subsets of them that are driven by these translocation
01:53:39.700 fusion events. And they tend to be genetically simple. And now time and time again, that has
01:53:44.940 proven to be a population sparsely distributed, if you will, across cancer types where you get deep
01:53:51.440 and durable responses. That was the next big aha moment. So time matters, meaning? Evolution.
01:53:57.260 Well, yes, but also like if you catch CML and treat it early enough, in theory, you're going to have a
01:54:04.260 better response than waiting until the tail starts coming out of the dragon.
01:54:08.900 That's right. So the compensation that a cancer cell will be able to leverage by having now these
01:54:14.620 built-in accelerants or more disabled tumor suppressors, like the ability to adapt and work
01:54:19.800 their way around with de novo resistance or rapidly acquired resistance is absolutely a huge risk the
01:54:26.220 longer you wait. That CML example, well, we've begun to map it out in quote-unquote common solid tumors.
01:54:32.400 So in breast cancer, if you look at HER2, I was beating up HER2 for its not aha moment efficacy.
01:54:39.480 This is trastuzumab, the first naked antibody. But modified forms of HER2-targeted therapies have
01:54:43.920 come along since. These more armed antibodies, if you will, that definitely have greater effect.
01:54:48.760 But even just take trastuzumab, the naked antibody, its ability to help a metastatic breast
01:54:54.740 cancer patient live longer for a period of time, well-cataloged, but measured in months,
01:54:58.960 several months, let's say. Now you take that into the so-called adjuvant setting. So this is covert
01:55:05.920 metastatic disease. So for those who have heard enough jargon and had family members deal with
01:55:10.620 cancer, they know of two situations where the surgeon says they got it all, but the medical
01:55:16.060 oncologist is telling them, we're still worried there's still some cancer cells around. We're too
01:55:20.020 stupid to know if they're there or not. CAT scans can't tell us because they're too low resolution.
01:55:24.280 We're not there yet in terms of actually measuring circulating tumor cells or circulating tumor
01:55:28.320 DNA in a diagnostic and high-resolution way. But we're just worried because we know that looking
01:55:34.100 back a decade, if we had 1,000 cancer patients like you, we know that half of them are going to show
01:55:40.280 up with overt metastatic disease over the first few to several years of follow-up. So you know a time
01:55:46.920 that someone had microscopic metastatic disease after their surgery with curative intent.
01:55:51.740 So what I'm getting at is now that's the adjuvant setting. So the possibility but not certainty that
01:55:57.040 microscopic metastatic disease exists, you give therapy in that situation, systemic therapy,
01:56:01.800 to seek and destroy microscopic deposits. That's so-called adjuvant therapy. So with that jargon
01:56:06.360 stated, adjuvant use of HER2 antibody, this was the first example of this is why I'm giving it its due
01:56:12.380 credit, cures patients. Cures patients. You don't cure patients in the overt metastatic setting with
01:56:17.300 HER2 antibody therapy. Like that's unheard of. So that was the first
01:56:21.100 paralog in a common cancer that kills lots of women that this CML evolution concept.
01:56:26.840 And remind me what the numbers were because we sort of take it for granted today.
01:56:30.020 You take two groups of women that have HER2 new positive tumors that are NED, meaning surgically
01:56:36.820 resected down to having no evidence of disease as you described. Half of them get a placebo. Half of
01:56:41.880 them get the antibody in 10 years. What percentage are alive in each group?
01:56:46.640 Usually the way we think about it is like how many patients are saved, if you will,
01:56:50.080 because it all depends on the level of risk of recurrence to start with.
01:56:54.140 Yeah. So what's the AR and RR?
01:56:55.600 Yeah, right, right. So whatever you start with, so it's depending on the trial,
01:56:59.120 a third to a half of the recurrences that would have occurred don't happen by the addition. This is,
01:57:05.380 you're right to mention placebo, but by historical fact, in this case, everybody got chemo.
01:57:08.740 Everybody gets the same. Yeah, yeah.
01:57:10.140 Chemo plus minus, if you will. So the addition of the HER2 antibody or not. And this is how many
01:57:14.300 subsequent studies and other cancer types have been done to try to show the same kind of benefit of
01:57:18.940 treating only microscopic or digital disease as opposed to overt metastatic disease. So a third
01:57:23.640 to a half reduction in risk of relapse over long periods of time now, and stably so in the case of
01:57:29.400 HER2, we have lots of data.
01:57:30.240 Do women take anti-HER2 new for life now in adjuvant or how many, it's five years?
01:57:33.820 No, no, no. The hormonal therapy is the long duration therapy in the adjuvant setting. So
01:57:38.460 hormonally driven breast cancers, you're now complicating this, my attempt to make adjuvant
01:57:43.080 therapy, disease eradication sounds simple. Hormonally driven cancers like breast cancer
01:57:48.020 and prostate cancer in the so-called adjuvant setting, it is clear that the original data was
01:57:55.080 a year of therapy, then three years of therapy, five years of therapy. It's clear even that 10 years
01:57:58.600 of therapy is better than five years of therapy in a population. And hormonal therapy
01:58:03.260 prevents relapse at least to a third to half standard analogous to HER2. But when you see
01:58:10.340 an effect like that in series of clinical trials where longer durations of therapy to treat covert
01:58:15.960 metastatic disease, longer is better than shorter, it tells you you're not eradicating in everybody,
01:58:21.380 you're suppressing in some people. And that's the story over and over again. And gastrointestinal
01:58:26.000 stromal tumor, which was the first solid tumor big targeted therapy success where imatinib was being
01:58:30.940 repurposed for the fact that it's a C-kit inhibitor and C-kit is mutated in two-thirds of gastrointestinal
01:58:35.760 tremor tumors. That drug first showed benefit in metastatic patients, overt metastatic patients.
01:58:40.080 Then in a series of adjuvant trials, one year, three years now ongoing therapy beyond that,
01:58:46.920 incrementally better. Is there a reason to believe that some patients are being cured? Absolutely.
01:58:51.100 But there's some patients where disease is just being suppressed and maintained in a
01:58:55.720 micro-metastatic state from which they will not die, at least in the foreseeable future.
01:59:00.300 But this just goes to my point about, okay, is single agent targeted therapy a tumor clearing
01:59:06.860 treatment for very many cancer patients? Even when we use optimal next generation early detection
01:59:12.340 methodology, that is going to be realized in a real fraction of cancer patients. But we're still
01:59:18.400 going to need combination regimens to dismantle tumors in their fully complex way. The BRAF example
01:59:23.120 has already now played out. So melanoma, BRAF inhibitor monotherapy, improved survival to the
01:59:29.680 tune of a nine-month improvement in overall survival, which in melanoma, which is median survival used to
01:59:34.920 be six to nine months. So on average, six to nine months. So like getting a bump like that.
01:59:38.500 You're basically doubling the survival of patients with metastatic melanoma, but not curing.
01:59:42.620 Right. That was a big deal. Interestingly, BRAF inhibitor monotherapy was tried in an adjuvant
01:59:47.560 trial. Didn't meet its endpoint. So it apparently numerically reduced risk of recurrence, but
01:59:52.960 marginally so, and not enough to achieve statistical significance. So that trial was called negative.
01:59:58.120 In parallel, I and others had been pushing hard in the metastatic setting to go from AZT to doublet,
02:00:04.940 what was the first doublet HIV regimen? I'm blanking now, but in any case, a proteasome inhibitor.
02:00:10.460 And so in any case, in melanoma, we were treating with BRAF inhibitor monotherapy. We're seeing
02:00:14.100 responses. Those responses would last on average six months. It's an aggressive disease. Again,
02:00:18.640 patients would typically die within six months in the untreated state. So patients would respond,
02:00:23.420 and their response would be maintained for a huge range of times, but the average was six months.
02:00:30.000 We saw that basically the tumors were working their way right around the drug in the MAP kinase
02:00:34.060 pathway. They were bypassing BRAF through CRAF, most commonly. That was the easiest trick for them
02:00:39.500 to use. They didn't need to develop mutations that resisted the drug itself.
02:00:44.100 Which is a theme in PCR-able CML and other oncogene-driven tumors that are treated effectively
02:00:49.340 with targeted therapy, and fusion-driven cancers in particular. Remember those genetically simple
02:00:53.600 tumors? A very, very common theme is they need to mutate the actual gene that's being targeted
02:00:59.140 because they need that thing back on. They don't have very many tools in the toolkit. They need that
02:01:03.700 guy back on, and the only way they can evolve resistance is to basically repel the drug in the
02:01:09.380 first place. Those are so-called gatekeeper mutations. So in BRAF, mutant cancer,
02:01:13.600 BRAF mutant melanoma, you don't see those mutations emerge because it's too easy for
02:01:18.860 these cells to rewire their way past BRAF through CRAF. So we saw this happening in humans. So yes,
02:01:26.000 in parallel and laboratory systems, but more importantly, we were seeing it in humans within
02:01:29.940 the same year that we first documented responses in those patients because we were biopsying them
02:01:35.280 serially for research purposes, which was then thought to be a crazy concept, but now it's not so crazy.
02:01:41.120 In any case, we saw this bypass happening. We knew that there were available inhibitors of
02:01:45.840 downstream MEK, M-E-K, the guy that BRAF turns on. Those drugs already existed. They weren't shown to
02:01:51.420 be useful on their own yet anywhere in cancer. There were signs of life here and there in clinical
02:01:57.780 trials. But MEK is right below BRAF and C-RAF. And we said, let's just put these two together,
02:02:03.460 try to intercept this bypass. That worked. Like we went very quickly from BRAF inhibitor monotherapy to
02:02:08.440 BRAF-MEK combination therapy, including overall survival improvements that were as big as the
02:02:13.200 overall survival improvement. BRAF inhibitor monotherapy. I'm fast forwarding through my
02:02:16.640 entire career here. In any case, BRAF-MEK combination in the adjuvant setting prevents
02:02:21.600 relapse by 50% and patients receive a urotherapy, stop treatment. And there's a persistent gap there
02:02:28.040 in terms of cured patients. This is melanoma we're talking about. Melanoma that will work its way
02:02:32.780 around BRAF inhibitor monotherapy and on average six months. You can wipe it out in the covert
02:02:38.300 metastatic state, microscopic residual disease, aka adjuvant therapy, with that same regimen. So the
02:02:43.700 point is there is some real kind of early detection, early treatment theme that is absolutely yet to be
02:02:49.820 fully leveraged and realized because we're still working on the early detection technology, blood-based
02:02:55.500 mostly. But it's coming. And then adjacent to that, even in some cases, when we find cancers very early,
02:03:02.700 they are already genetically complex. We have to have a toolkit that allows us to dismantle
02:03:07.220 at more than one point. And that's its own long conversation. But the issue of adjacent to AZT,
02:03:14.020 what does that armamentarium look like in terms of the next agents that we're discussing?
02:03:17.820 Right. Because with HIV, we think of it by class of drug. You basically have a toolkit
02:03:22.760 of drug classes. And it seems to me that you've done a very eloquent job explaining this.
02:03:29.480 There are basically some fundamental pillars in growth and some fundamental pillars in protection.
02:03:37.340 And when the day comes that we have a toolkit that knows, okay, I've got these three things that can hit
02:03:42.760 this pillar, three things that can hit that pillar, four things that hit this pillar, six things that hit
02:03:47.460 this pillar, nothing that hits this pillar, and two things that hits it. I mean, you're in the golden
02:03:52.080 zone when you can start stacking, because that's what HART, highly active antiretroviral therapy
02:03:56.360 did. It basically put whatever, three or four pillars together. And at that point, HIV was not
02:04:02.280 cured, but it was chronic. You didn't have to die. You didn't have to get AIDS.
02:04:06.320 We can't keep hitting the same pillar and expect that we're going to cure cancer. So we got away with
02:04:11.860 it in melanoma because we kept hitting the same pathway, got away with it by hitting it twice and
02:04:16.780 improving outcomes and actually improving side effects, which is its own weird story, but really cool
02:04:21.560 story biochemically. The bigger point, just hitting some of the talking points that we touched on
02:04:26.420 before, is we need the activators of the immune system. We need the inhibitors of the activated
02:04:31.400 oncogenes. We need the drugs that target these epigenetic regulators. We need the metabolic switch
02:04:37.080 regulators, which are emerging, I would say, just as we speak, very early days. Epigenetics and metabolism
02:04:42.860 generally are what I point to to say that these are the pillars where the tools are coming,
02:04:47.680 but it's early. And I generally make the point that if we just flesh out those toolboxes and we're
02:04:55.720 lacking still, um, some famous gaps would be like understanding how to wrestle down telomerase.
02:05:01.600 This kind of like is a clock that exists in cells that allows them to basically measure their age.
02:05:08.820 Did you see the science paper last week? It was the science paper about the,
02:05:11.920 the astronaut Kelly's time in space, the year in space. I read a lay article summary of it,
02:05:17.320 but yeah, go ahead. You know, it's interesting. So twin brother, right? So one,
02:05:21.000 the, I only bring this up because you mentioned, uh, telomerase. So the, I could be having this
02:05:25.280 backwards. I think the telomeres of the astronaut that was in space elongated significantly during his
02:05:31.960 year in space, but within three days back on earth, completely reverted to normal, which of course
02:05:36.620 just made me question the importance of telomere length. It's an interesting point. So your pillars
02:05:41.480 then, cause I want to share with you my framework, which is purely a clinical framework. It's not a
02:05:46.060 research framework. It's a, you're on the front lines, you're a primary care doctor, you're a
02:05:51.140 patient. How do you think about cancer? Because while I think most patients, when you talk about
02:05:57.280 the big diseases, most people are afraid of Alzheimer's disease above all else because of
02:06:02.240 the phenotype. But when you think about probabilistically, most people are afraid of cancer
02:06:07.760 because the likelihood of getting it is somewhere between a third and a half, depending on your
02:06:12.100 gender. So you said epigenetics, metabolism, immune, would those be your three fundamental
02:06:17.360 pillars of cancer? Yeah. I mean, growth factor receptors, which again,
02:06:20.560 that was the original pillar because those are the first discoveries made, frankly, in cancer
02:06:25.180 biology and cell signaling. But these others are clearly the other major pillars of normal cell
02:06:32.080 programs that have to be co-opted by cancer for cancer.
02:06:34.160 Yeah. So the epigenetic modulation, the immune stuff, the metabolic stuff, and of course the
02:06:39.500 growth factors. So I usually tell patients, I think cancer is really hard. Like atherosclerosis
02:06:45.860 is inevitable, but we also know so much about it. Not everything, but we know enough about it. And we
02:06:51.440 have enough tools that look, if you really want to be aggressive, you can delay it so that you're not
02:06:57.320 going to have your first heart attack till you're a hundred. That's doable. That's totally doable.
02:07:01.040 If you start early enough, I'll save my soliloquy on Alzheimer's disease. But I say, look, cancer is
02:07:07.560 the hardest one. And it's the one that I think most about in the sense of it's the one that I am
02:07:14.140 least confident at our ability to reduce risk in. So I say, look, here's my take on it. Step one,
02:07:19.720 try not to get cancer. Sounds like a dumb thing to say, but we know a handful of things that are
02:07:24.240 increasing our risk for cancer. So let's keep those to a minimum. Luckily, most people have figured on
02:07:29.000 that smoking is not a good idea, but right behind it is insulin resistance and obesity. And so there's
02:07:33.980 something about that probably down. So if smoking was probably acting more on the mass genetic level,
02:07:39.800 something about insulin resistance was acting on this growth sort of pathway. Okay. So we could talk
02:07:44.640 about all the things we can do to not get cancer. Step two, which again, creates a lot of enemies,
02:07:50.780 especially depending on which side of the Twitter sphere you live on, is let's look for cancer early.
02:07:56.000 If burden of disease matters, you can take the approach of women should never have a mammogram.
02:08:03.140 Just if a lump shows up in your breast, go see your doctor, but otherwise don't do anything as
02:08:07.540 one end of the spectrum. And then you've got coconuts like me on the other end of the spectrum
02:08:11.340 that say, no, I understand why you might come to that conclusion if you're trying to do it at a cost
02:08:17.060 basis. And if you're only limiting yourself to mammography, which has such horrible sensitivity and
02:08:22.300 specificity, but if at least theoretically you could say, well, in a world where costs become
02:08:28.000 less ridiculous, i.e. not in the United States, if you took it out of the equation and you were willing
02:08:33.920 to layer mammography, which will always be important to catch a calcified lesion with diffusion-weighted
02:08:39.880 imaging, MRI, as an even superior technology to ultrasound, coupled with molecular screening,
02:08:46.780 well, you can make the case that no woman should ever present with breast cancer. And in that
02:08:53.900 situation, can we do better? And then you talk about looking at therapies that would go after
02:09:01.140 multiple pillars simultaneously, not in serial, not waiting for one to fail and the other to go on.
02:09:07.140 So that's my sort of Neanderthal approach to cancer. How would you make that more robust?
02:09:11.380 Okay. So what we're missing is still components of the toolbox to be able to actually knock out
02:09:16.720 pillars. So that's, I often say we still need to diversify our toolbox. Then it's the issue of
02:09:22.020 marrying diagnostics or therapeutics. So understanding the assembly process of cancer in a patient-specific
02:09:28.280 way and being able to deploy those therapies. That is an emerging hard task. I spend a lot of my
02:09:34.580 academic time railing against the impediments that keep us from pushing drugs together in
02:09:40.440 supervised settings, both experimentally and clinically in clinical trials. So this idea of
02:09:45.180 getting to following the HIV example, we are chronically facing headwind in terms of getting
02:09:50.500 there.
02:09:51.020 Is that because HIV killed patients so much quicker and there was more desperation that clinicians,
02:09:57.500 IRBs were more willing to move quickly to stacked therapies?
02:10:01.800 Yeah. We have all the same regulations. The HIV advocates created-
02:10:06.120 It was the advocacy.
02:10:07.100 Yeah. They've created regulations to cover life-threatening disease and cancer is captured
02:10:11.240 right in that. We have an amazing forward-thinking regulatory environment in the United States and
02:10:16.620 increasingly in Europe. Because of the lead blocking that was done by the HIV advocacy community,
02:10:21.940 we have the same benefits.
02:10:22.960 So the heavy lifting on that front was done in the 80s and early 90s.
02:10:26.000 Absolutely. And I've spent tons of time exploring whether there are remaining impediments there,
02:10:31.860 talking with FDA leadership in particular. And I usually quickly sum up to say they are on our
02:10:37.600 side. They are our friends. They have self-organized in a way that actually will be the accelerator,
02:10:42.080 not decelerator progress. The problem, if I were to put a finger on it, is the way in which companies
02:10:48.480 that decided they could see a business model in HIV and basically decided they were going to pursue it,
02:10:52.240 could create the toolbox within their one company. Had it not been for that, we would not have seen
02:10:58.260 doublet and triplet therapy.
02:10:59.560 And is that purely a simplicity of therapy and therefore an economic issue?
02:11:04.400 Precisely. And simplicity of the organism that you're-
02:11:06.260 That's what I mean. Yes. It's simplicity of the opponent.
02:11:08.460 That's right. The number of enzymes that the thing has in its genome, you could then
02:11:11.540 postulate as potential targets, massively smaller. And so within one umbrella of one company,
02:11:16.340 you could see combination therapies-
02:11:18.240 Right. So even though Merck or Pfizer could have a program under each pillar,
02:11:22.840 that's typically not the way it goes, is it?
02:11:24.940 Here's how I generally draw up the math. So 60% of drugs coming in the cancer pipeline now come from
02:11:31.340 small biotech companies. It used to be that Big Pharma was the driver. And the phrase I often use is
02:11:37.520 that Big Pharma outsourced its R&D to risk-taking, venture-backed, highly specialized small biotech companies,
02:11:44.120 not just in cancer, but here I'm sticking with cancer.
02:11:46.380 So you've got this distribution of where drugs are coming from that is a huge swath of different
02:11:51.780 firms, many of which have a single asset in the small biotech space. And at most,
02:11:56.040 they get to have two or three.
02:11:57.200 What's the sweet spot for Big Pharma? Is between phase two and phase three or between
02:12:01.040 phase one and phase two? If you exclude the big aha moments.
02:12:03.900 Yeah. Okay. So if it's an aha moment, then it's phase two. That's the acquisition moment. And if it's
02:12:07.940 not, then it's randomized phase two slash phase three. Optimal moment, as you said, kind of where's
02:12:12.380 enough risk been taken off the table and where now you've got a commercialization opportunity,
02:12:16.740 which is what Big Pharma is for us in oncology, at least. Yes, there's still innovation and incubation
02:12:22.180 new therapies coming out of Big Pharma. But as I said, it's shrunk down to a small component. The basic
02:12:27.160 science, as you well know, across all of public private domain is in the public sector, right?
02:12:33.040 The basic science, the stuff where you can't guarantee any kind of return in terms of when you're
02:12:37.380 going to get an insight that you could turn into a potential therapy. So you've got this fantastic
02:12:41.380 chaos of publicly funded biomedical research, the world's greatest bio. I was just about to say,
02:12:45.620 by scale, when you look at the public domain, everything from most of it, of course, being NIH,
02:12:51.440 but also Howard Hughes and others, what percentage of the world's pure exploratory science is funded
02:12:58.700 in the United States? 90%. It's that much of an advantage. Yeah. It's narrowing in Europe a bit.
02:13:04.020 With now central investment in cancer research in Europe, that number is dropping percent by
02:13:08.600 percent. Truthfully, if you said 50, I would have still thought that was impressive. If half the
02:13:12.840 world's basic exploratory research was happening. It's where the money is. The public investment
02:13:17.540 in research and then add the private. Well, I'm adding the philanthropic on top of that, but yes.
02:13:21.460 Yeah. Well, we live in a philanthropic environment that's not known in much of the world. So that is a
02:13:25.640 meaningful additional layer. So no, huge, huge, huge engine here is the public domain. Those
02:13:31.940 discoveries then are out-licensed to small firms over large firms by a huge margin. Of course,
02:13:37.600 I here live in one of the, well, not one of, the world's biggest biomedical research engine vis-a-vis
02:13:43.760 taking those discoveries into small firms and the Bay Area for sure and New York and San Diego are the
02:13:50.040 kind of other major pillars of that. But so you have these hubs of activity of taking new discoveries,
02:13:54.640 some of which come from outside the United States even, but then are incubated into companies.
02:13:58.140 What I'm describing here is this very dynamic, very exciting, very purpose-driven, expertise-heavy
02:14:05.480 biotech sector, which is great for so many reasons. But I'm bringing it up as a complaint,
02:14:11.520 even though I personally have benefited from the ability to step into entrepreneurial roles and
02:14:16.540 co-found companies and so on and so forth. That's been enormously gratifying for so many reasons.
02:14:20.940 I registered as a complaint because it's distributed our toolbox so widely. And we live in a world right now
02:14:27.860 where 0.37 of rational combinations of two cancer therapeutics that are still in investigational
02:14:33.780 territory are finding each other in clinical trials. I published a paper on this topic a
02:14:37.420 year and a half ago. It is a terrible sampling mingling rate, terrible. So we make new discoveries
02:14:44.060 all the time in the academic domain that would suggest a new combination. You've got patients dying
02:14:47.960 every day of that addressable cancer by molecular subtype or whatever. The likelihood that you're going to be
02:14:54.360 able to launch a clinical trial to marry those two drugs when they exist in two firms is that small.
02:14:59.660 That is a terrible problem. HIV didn't have that problem. But because of the complexity of human cells
02:15:05.440 and therefore human cancer cells, the toolbox is being chaotically distributed. We need a way to change
02:15:11.700 that. And we need a way for drugs to be able to be married in life-threatening cancer in a rapid,
02:15:16.360 rapid fashion. So it's not an inertia problem in the culture. It's not doctors. It's not patients.
02:15:21.700 It's not academic medical centers. It's not the regulatory environment. It's not.
02:15:25.400 And it's a shame because some of those are a heck of a lot easier to solve.
02:15:28.140 You'd think. This is the least rocket science thing that I've put my shoulder into the past
02:15:32.360 number of years now. Novel, novel cancer therapeutic investigation. But it's the hardest to change.
02:15:37.780 And to me, there's an obviousness in terms of focusing on this problem. But the obviousness in the
02:15:44.140 entire ecosystem in terms of actually getting alignment and incentives aligned to allow this
02:15:50.280 dabbling to happen, it is a major, major impediment. And I've been making the point that I think we need
02:15:56.140 quadruplet therapy to dismantle most complex cancers if early detection is only going to get
02:16:01.420 us so far. And ideally across four pillars. Yes, exactly. And different ones, right? So going back
02:16:06.760 to the PCP3. Yeah, you have a huge combination. Right. You might want to always be targeting tumor
02:16:10.640 suppressors. Yeah, sure. But that's not one drug. That's right. That's up and down the chain.
02:16:13.940 Right. And unique to certain patients' tumors. Now on the tumor suppressor side,
02:16:17.820 does CRISPR offer any role? Because if you fix a tumor suppressor gene, that seems more beneficial
02:16:24.040 than just fixing an oncogene. This is gene therapy. You need to be able to deliver that to every last
02:16:29.740 cancer cell. And how in the world do we do that? Is there a virus that can do this? No, no, not
02:16:34.280 currently. And I, in the beginning of my career, because if I've communicated nothing in talking with
02:16:39.400 you, I am an optimist. The beginning of my career, I absolutely thought like this is, on one hand,
02:16:44.280 we have these things that we need to inhibit. And on the other hand, thank God, we're going to have
02:16:47.800 gene therapy. 20 years later, we still don't have gene therapy. We have gene therapy that can correct
02:16:52.560 if you need only a little bit. We're a little at Penn when Jesse-
02:16:55.460 I got there right after. Okay. Yeah.
02:16:57.080 Yeah. So I was still to Brigham at the time when I was postulating that gene therapy was going to help
02:17:01.740 us on the tumor suppressor side. And yet friends of mine who were in the lab doing work on genetic
02:17:07.300 delivery methods were saying, no, no, we're not. We're not there. These adenoviruses are getting wiped
02:17:11.680 out. You can't get persistent expression. Hemophilia then to a degree now was kind of
02:17:16.080 paradigm case where people were saying, well, we just need to get these clotting factors expressed
02:17:19.700 to a little degree in a small fraction of cells and we'll be okay. As people were trying to just
02:17:24.440 climb that hill, I was like, well, that's not the cancer hill. The cancer hill is every single cell
02:17:28.820 widely distributed. And some of these cells are dormant. These micromats, they've lodged in distant
02:17:33.760 sites and they are truly quiescent dormant cells. How are you going to get integration into that cell?
02:17:38.420 So it's a major, major problem. So I don't see that trick coming in the foreseeable future. So I
02:17:43.780 don't focus on it. I do think we can understand the pillars up and down, as you said, and knock them
02:17:49.500 out in ways that potentially at least turn off what's turned on as a consequence. I mean, this is
02:17:55.100 a thing about tumor suppressor genes that are eliminated is that you can always find a downstream
02:17:59.680 thing that's turned on as a consequence. So the issue is, can you find that point of
02:18:03.480 drug ability intervention to counter that? So that's at least until I retire, I think that's
02:18:08.740 going to be the relevant approach. You've alluded to it already, but are you pretty bullish on liquid
02:18:12.440 biopsies? For sure. There's several reasons why. The early detection piece, I think we've touched
02:18:17.100 a little bit on. Let's tell folks what they are. I use the term from time to time. Right. So tumor
02:18:21.780 cells, a primary tumor with no, let's go with the notion that we can have knowledge that there is no
02:18:27.360 microscopic metastatic disease. It's just a primary tumor. Right. You have a tumor in your
02:18:32.320 colon. You have an adenocarcinoma in your colon, and we know that it's nowhere else.
02:18:36.600 And that thing will shed its genetic contents. DNA and RNA, which mutated genes will have their
02:18:43.560 mutated RNA versions. You have mutated DNA and RNA kind of detection opportunities, if you will.
02:18:49.320 So DNA is shed, we think, from lots of cell types, but definitely cancer cells seem to
02:18:54.720 disproportionately shed their DNA, which is chewed up a bit as it circulates in the blood,
02:18:59.300 but you can find it. And with higher and higher resolution technologies, if you find a single
02:19:04.160 copy even and can amplify that up and detect it as a signal, since we know what the genetic map is
02:19:09.780 of all cancer, we can have those probes reasonably well in hand. And a lot of acceleration has happened
02:19:15.540 in this space the past just few years now. I'll come back to my complaint on the impediment side
02:19:20.680 when it comes to reimbursement of diagnostic tests, because that's the problem I think we face there.
02:19:24.480 In reality. But from a public good perspective and from a science perspective.
02:19:27.380 Yeah, just, I mean, I'm just curious right now from a purely, like I'm thinking about this through the
02:19:32.140 lens of cancer screening at the population level. And again, I'm always trying to make the problem
02:19:37.400 simpler by taking away one constraint, which is cost. Because in the short term, I think you have to
02:19:42.020 start, if you try to solve this problem at a quality adjusted life year perspective, one, you're
02:19:47.960 inserting your morality into the discussion. And two, I don't know what the number is, and it's too hard.
02:19:52.140 So let's make the problem simpler. All we're doing is trying to reduce the risk of physical
02:19:56.600 harm to a patient and psychological harm through false positives. If you could layer liquid biopsy
02:20:02.660 on top of diffusion-weighted imaging, MRI, the best colonoscopy, the best mammography,
02:20:08.860 boop, boop, boop, boop, boop, boop, boop. I mean, you can theoretically construct a point
02:20:12.080 where you can catch every cancer prior to its clinical presentation.
02:20:17.480 Yeah. Let's just go with breast, colon, prostate, and lung, since that's 80% of
02:20:20.940 solid tumor cancer deaths. So that would be a good goal just to go after those.
02:20:25.940 So the challenges are, so again, the DNA is shed.
02:20:28.480 Do we have a sense of how big a tumor needs to be to even start shedding?
02:20:32.780 That has not been well mapped out, but certainly less than a centimeter. And this,
02:20:36.080 you mentioned centimeter before, is it radiographically findable and so on, nodule.
02:20:39.800 So if you go map out cure rates with surgery alone across common cancers, breast, colon,
02:20:45.620 prostate, and lung, at centimeter...
02:20:47.660 Right. At centimeter below, the exceptions are few. I mean, pancreatic would still be one of the
02:20:53.000 few where even sub-centimeter, your odds of survival are less than 50-50.
02:20:56.760 Melanoma happens to be measured in literally one millimeter increments, so huge metastatic
02:21:00.560 potential. But in any case, we have other strategies for that superficial tumor to find
02:21:04.580 it early. But in any case, so coming back to your point...
02:21:07.320 I see your point, which is, if you could decide no one ever shows up with a tumor bigger than
02:21:11.680 one centimeter, it's potentially doubled cancer survival, right?
02:21:16.000 So those guys are definitely shedding, so it should be detectable. If we need to use
02:21:20.700 microvesicles or exosomes, which have RNA and some DNA in them as a way of being able to find
02:21:25.800 scarce entities, these mutated gene products that are now, in this case, in the case of exosomes,
02:21:31.560 why they're being transmitted around the body, we don't know, but it happens.
02:21:34.660 Not just tumors, of course. Normal cells do this too. So circulating tumor DNA, exosome or
02:21:39.860 microvesicle packages of nucleotides, these opportunities for detection, as well as circulating
02:21:45.820 tumor cells, but circulating tumor cells are based on available technologies. They're the
02:21:49.300 hardest to find in a patient who has a one centimeter tumor nodule, using that as a threshold.
02:21:54.440 So already it's in sight that we're going to have high resolution methods for shed DNA and probably
02:22:00.060 same for exosomes and circulating tumor cells, I think could get there. The issue, to come back
02:22:05.280 to your framing here of like false positives and anxiety provoking and so on, remember P53 mutations,
02:22:12.200 50% of cancer. Finding a P53 mutation in blood, what does that tell you? A, you might have cancer,
02:22:17.780 you may not have cancer. And where is it? What part of the body is it coming from? Well, P53,
02:22:21.960 50% of cancer, it could be virtually.
02:22:23.960 Yeah. So how much of the effort in the liquid biopsy is going to be histology specific?
02:22:28.540 Exactly. This is where circulating tumor cells would be the favored approach.
02:22:32.080 The DNA will not offer tissue specificity.
02:22:34.540 You can get the whole fingerprint out of a circulating tumor cell and know exactly what
02:22:37.820 the entity is that you're hunting for now in terms of organ type. And so you just survey that
02:22:42.400 one organ with every imaging methodology yet to come. So there's reason to be hopeful there going
02:22:47.600 from CTCs forward. What's really cool in the circulating tumor DNA and exosomal RNA field
02:22:55.260 is lineage mapping. So it turns out basically that the genetic blueprint, when it's folded up
02:23:00.420 in a colorectal villus cell of the colon, the epigenetic alterations that occur in that cell
02:23:07.820 are characteristic. So you can fingerprint cell of origin by looking at epigenetic marks. This is a
02:23:13.040 realization that's now being ported into the blood detection world so that you can actually map
02:23:18.640 where did that fragment of DNA or RNA come from. So this is work in progress as we speak. There's
02:23:25.260 an ongoing collaboration between our group and the Broad Institute at MIT on this topic, but I know of
02:23:30.180 other groups who are in this space. So there's a convergence of sort of cell of origin fingerprinting
02:23:35.260 with genetic detection methodology that you could readily see how we could get there
02:23:40.060 in the foreseeable future. This idea of being able to say, okay, our imaging, it still isn't picking
02:23:44.760 it up, but we know that you've got a breast cancer brewing. And now-
02:23:47.940 And in some cancers, for example, if you took a woman that was high risk to begin with,
02:23:52.520 and now you had DNA proof that she had cancer, I suspect there are some women who would actually
02:23:57.480 just say without additional imaging, I might be willing to just undergo a mastectomy. Or a guy would
02:24:01.960 say, look, I'm willing to undergo a prostatectomy or whatever. Now it gets harder with lung cancer.
02:24:06.100 You can't have just bilateral lobectomies all day long or pancreatic even, but that's a step in
02:24:11.220 the right direction. Because as you said, maybe at that point we could justify, even at the societal
02:24:15.860 level, because certainly at the individual level, you'll do anything. But at the societal level,
02:24:19.340 we'd say, look, once you have that DNA test that points to that tissue, we're going all out on
02:24:24.340 scrutinizing the tissue.
02:24:25.220 And your first instinct is to think down a potential upcoming surgical path. If not, if you can't see it
02:24:30.580 now, you don't know where to cut, but eventually you will. But I'm actually, as a medical oncologist,
02:24:34.420 just leaping to the systemic therapy concept, can we motivate an immune response against that thing
02:24:39.140 when we know enough about its genetic fingerprint or an oncogene-targeted therapy and monitor the
02:24:44.420 response using the same method, right? So when you were talking about blood biopsy, a huge near-term
02:24:49.620 opportunity is to use it as a therapeutic monitoring tool to understand, can you actually
02:24:53.480 get people down to a minimal residual disease, no detectable evidence anymore by this blood method?
02:24:59.680 So yes, it's an early detection tool, but it's also a therapeutic monitoring tool. So you can
02:25:04.000 take a patient, you don't know where their breast cancer is, but you don't wait for it to emerge.
02:25:08.240 You attack it when it's still genetically simple and monitor that effect in blood. So you know when
02:25:12.820 to stop treatment or you know when treatment's not proving effective and switch gears to something
02:25:17.380 else because you've got a toolbox with different regimens in it.
02:25:21.120 I want to switch gears for a minute. There's so many just sort of cancer questions that I get asked all
02:25:26.300 the time that I don't know the answer to. So I have at least two patients who, I guess,
02:25:32.820 somewhat against my recommendation are adamant that stem cells, intravenous stem cell therapy has
02:25:39.100 played an enormous role in the improvement of their health. One patient in particular, there's no
02:25:45.160 denying that his symptoms improved dramatically with IV stem cell therapy. And I don't want to
02:25:50.000 represent that I have the hubris to suggest that it's not working. I just don't know. My bigger concern
02:25:54.860 because putting the cost aside and the immediate risk like infections and sort of risks of the
02:26:02.560 therapy, which are non-trivial, of course, the risk on the other side, which is it's too successful
02:26:07.400 in a sense, and those stem cells acquire a life of their own. So is this something you spent much
02:26:11.440 time thinking about? I've thought about it. I just think that if they're wild type stem cells,
02:26:16.580 I think they'll follow the rules. So this whole discussion has been about cells that basically,
02:26:21.660 not through anthropomorphic spiritual means, but by random genetic alteration basically are able to
02:26:29.400 not follow the rules. I mean, this is this revolution that happens inside of our bodies
02:26:33.160 that is cancer. It's actually, I usually use the term evolution. This is individual cells following
02:26:38.560 the preservation and success, organismal success instincts that allowed us to crawl out of the
02:26:44.520 swamp in the first place and become the complex organisms that we are. This drive to continue
02:26:49.040 evolving for selfish purpose. So using that mindset to come back to your question,
02:26:55.060 I think a truly wild type stem cell will find its home and find its niche and its proper influences
02:27:00.700 and behave accordingly is my assumption. Unless it were to become non-wild type through external
02:27:06.800 manipulation outside the body when it's potentially fragile and capable of picking up aberrations that
02:27:11.700 aren't corrected. But stem cells are notably hardy cells that can survive insults remarkably well and
02:27:19.520 correct. So a cell that survives a genetic insult, a stem cell is particularly capable of detecting the
02:27:27.000 damage, repairing the damage, taking its sweet time in doing so, and not spawning daughter cells until
02:27:31.960 it's got its house back in order. So its P53 detection program and DNA repair machinery is particularly
02:27:38.780 robust. So this is why when people talk about cancer stem cells, notably, which no one would want
02:27:43.700 those, cancer stem cells are thought to be kind of the worst of the worst. They're these primordial
02:27:48.800 cells in the cancer cell population within a given tumor that have found their way back in development
02:27:54.620 towards a stem cell and in doing so have adopted these really hardy skills, survival skills. No,
02:28:02.700 they can't proliferate and divide very quickly, so they don't have that, but they can survive almost
02:28:07.100 anything. Whereas the avant-garde, highly proliferative, very dynamic population that will
02:28:12.100 multiply and actually be the life-threatening leading edge of a cancer, those things are more
02:28:16.520 vulnerable. So actually, if you look at what chemotherapy has done for us, it's fairly conventional
02:28:22.200 chemotherapy. It's fairly clear that actually what it can do is it can prune this highly proliferative
02:28:27.880 avant-garde population, leaving behind this more quote-unquote stem cell-like pool. And there's a whole
02:28:33.560 field, it's a contentious field to a degree in cancer biology slash therapeutics of how much true
02:28:39.700 stem cell biology really exists there. But you brought it up more from the perspective of whether
02:28:43.540 stem cells themselves could go rogue. And I would say, unless they're perturbed in some significant
02:28:49.060 and ultimately genetic way, I don't see how. Now, let's talk about another fundamental cancer
02:28:52.940 question that serves no real purpose other than unless there's some clinical application of
02:28:57.660 prevention, I suppose. It's impossible to deny the age-related association between age and cancer.
02:29:05.760 Certainly, kids can get cancer, but for the most part, cancer rates rise monotonically until the
02:29:11.840 ninth decade or so. I mean, there's a bimodal distribution because you've got the childhood
02:29:15.040 cancers. If you're 50 versus 60 versus 70, you leapfrog up in risk, right?
02:29:20.920 Almost exponentially, or at least quadratically. It's not just linear.
02:29:23.960 Consider two hypotheses. One is, as we get older, our genome is more susceptible to injury. Consider
02:29:31.200 three. Two, as we get older and we've accumulated more of these, the probability that they can start
02:29:38.880 to layer and stack and you get the phenotype that's not advantaged. Three, the immune system
02:29:46.220 loses some of its steam and therefore the radar window in which you can detect cancer
02:29:53.540 narrows, basically. Or the ability to detect all of the above, one of the above.
02:29:59.720 All of the above. You've just described very nicely what I call the inevitability of cancer. We've got
02:30:05.620 too many stochastic events accumulating and surveillance systems that are breaking down. DNA
02:30:11.020 damage repair and immunologic. Those are the two fundamental, most important components. And if
02:30:17.620 you're allowed to go one log shift in mutation burden per cell and the immune system not see it
02:30:24.500 and not clear it, that's it. I mean, there's no human that...
02:30:27.220 There's no immune system that's going to...
02:30:28.620 That's going to overcome that. So when I say inevitability, you connect the dots in terms of
02:30:33.340 the per decade acceleration and appearance of cancers across the population. And I oftentimes say,
02:30:39.220 if we all lived to 130, we'd all have a cancer, quote unquote, real cancer. Let's not get hung up
02:30:43.620 on benign growths that aren't cancerous. The definition of cancer for a totally lay person
02:30:48.840 who doesn't think about cancer much is ability to travel and actually wreak havoc and kill. Yes,
02:30:53.840 glioblastoma kills in its local site. But benign tumors, which are almost cancers, yes,
02:30:59.340 those happen broadly across the population. There's autopsy studies that show at least 50% of people die
02:31:03.640 with at least a benign tumor. So almost getting there, sure, that happens already. But I'm talking
02:31:09.400 about fully getting there, a full-blown and will be eventually life-threatening cancer.
02:31:15.280 It's interesting. Actuarially, by your 10th decade, your risk of cancer starts to go down. Although,
02:31:21.320 and I discuss this with my patients a lot, my explanation for that is that atherosclerosis
02:31:26.200 ratchets up faster than cancer. And it's not that cancer is going down, it's that heart disease
02:31:31.540 is dominating. And that's my, I say the same thing to patients that you do, which is whenever I get
02:31:36.520 asked these questions that frankly kind of annoy me, which is like, aren't we just going to figure
02:31:41.980 out a way to all live to be 200 one day? And I'm sort of like, no, what are you talking about?
02:31:46.980 You have to figure out a way to prevent age-related disease. And yes, there's lots of cool ideas. And
02:31:53.780 oh, what if you could just maintain telomere length is like one I love hearing. And it's like,
02:31:58.340 that's totally irrelevant because even if there were some benefit that came from that,
02:32:03.900 you have to thwart atherosclerosis and cancer.
02:32:07.280 Yeah. You don't want a proto-cancer cell to be getting more telomere length.
02:32:10.840 Yeah, yeah, yeah. Not even withstanding.
02:32:12.160 Going back to your stem cell comment, that's not a fix-all by any stretch. No, you're right. These
02:32:16.040 are intersecting risk issues. So you're right that this competing risk issue makes it look as though
02:32:21.660 if you make it long enough and you don't have cancer, then you're just not cancer prone.
02:32:25.800 It's a bad problem to have when your risk of atherosclerosis is so dominant over your cancer
02:32:30.800 risk. Now, one last thing I want to talk about is melanoma. And again, I don't actually know,
02:32:36.120 I haven't written anything you've read on the topic we're about to discuss. So feel free to
02:32:39.580 just dismiss it out of hand and say, I don't pay attention to that literature at all. But
02:32:42.700 have you been following any of the vitamin D melanoma sun exposure discussion lately?
02:32:48.140 Yeah, sure.
02:32:48.740 Okay, so I'll do my best to give a relatively brief synopsis and then feel free to just correct it
02:32:55.620 because I'm pretty sure I'm bastardizing it. There's not a huge body of descent to the notion
02:33:01.240 that sun exposure increases the risk of melanoma. We know that...
02:33:04.800 Not linear, but there's no question that there's an association there.
02:33:07.960 Okay, so we won't call it, it's not an axiomatic statement, but it's the evidence that sun exposure
02:33:13.060 and melanoma are associated in a causal way from sun to melanoma is strong. Okay. We also know that
02:33:20.080 sun exposure increases the de novo synthesis of vitamin D in the human body. We know that from
02:33:27.480 an association perspective, higher levels of vitamin D port with good things happening and low levels of
02:33:34.600 vitamin D port with bad things happening. This has led people to suggest that we should be supplementing
02:33:39.900 with vitamin D because yes, you can get it by being out in the sun, but the risk of melanoma is going
02:33:46.260 up, but we can just take it. It's a fat soluble vitamin. It's easy to administer. You can clearly
02:33:51.600 achieve levels in the plasma that mirror that of the sun. That should solve the problems. So many
02:33:57.100 doctors, myself included, have historically normalized patients' vitamin D levels. Now, again,
02:34:02.460 there's a whole spectrum in there. There's a bunch of weirdos that think you have to have super
02:34:05.900 normal levels, but most of us walk around thinking, God, if somebody shows up in their vitamin
02:34:09.900 D level is 20, we want it to be 40 or 50 or 60. The problem is these clinical trials, these pesky
02:34:15.880 little things keep showing up demonstrating that supplemental vitamin D doesn't really seem to help
02:34:21.100 that much. And I've scrutinized many of these trials and I can poke holes in all of them, but
02:34:27.080 the body of evidence is becoming hard to ignore. So any one of these trials, I can say, look, they didn't
02:34:33.660 use enough vitamin D or they didn't look long enough or they didn't have the right patient
02:34:39.660 population or, but when you have, I don't know what X is, but when you have X studies that are
02:34:44.780 basically all saying the same thing, which is give everybody vitamin D, it doesn't seem to matter.
02:34:48.000 Now there's exceptions. You know, JAMA had a paper a week ago about supplemental vitamin D in patients
02:34:52.720 with colon cancer, and there actually seemed to be a legitimate benefit. I'd love to hear your thoughts
02:34:55.940 on that. Where did this leave us all? This left us all, I don't know, for many of us, about six
02:34:59.920 months ago, there was a huge blitzkriek of just nonstop information being put out about this that
02:35:06.400 came to the suggestion as follows. The vitamin D that you take supplementally ain't fixing the problem.
02:35:12.360 The vitamin D that's getting fixed in the sun is a proxy for things that are happening good in the sun.
02:35:17.600 So it's sort of like saying gray hair is a proxy of aging, dyeing your hair black or blonde,
02:35:25.160 isn't fixing your aging. So get out in the sun. And oh, by the way, yes, your risk of melanoma will
02:35:33.280 go up slightly. We're not denying that, but it goes up at one eighth, I believe is the number,
02:35:38.760 your rate of decline of all of these other cardiometabolic diseases. So should we, or should
02:35:46.000 we not take vitamin D question one, or more importantly, I think for you question two, given
02:35:50.520 that you're one of the world's experts on melanoma, would you advocate we spend more
02:35:55.100 time in the sun as a way to get our vitamin D? No, I don't go that far. I'm recognizing all of
02:36:00.100 the cross currents in data. I thought where you were going to finish up, which is what you just said
02:36:05.000 to say, exercise, exercise, and yet again, exercise. Okay. Are there people currently who exercise a ton
02:36:13.640 get a lot of cardiovascular benefit from that and do all that indoors? Yeah, that exists. So shouldn't
02:36:20.100 we be able to pick that up in the data? No, I don't think this is a classic example of a confounder.
02:36:24.080 I don't think that's extricated from the data. What I'm hearing you say is you think that the
02:36:28.820 huge confounder is all these people outside are exercising. That's what's been giving them the
02:36:33.420 benefit. It's not the sun per se or the vitamin D per se. I'm going with the vitamin D being
02:36:37.900 beneficial. I'm going to come back to a reinforcing element of that argument, at least as I see it in
02:36:43.600 scientific evidence. What I'm getting at is that the most powerful benefit, you said good things are
02:36:47.920 happening in the sun, or I think I'm paraphrasing what you said. And what I'm saying is that good thing
02:36:52.040 that's happening is exercise. I face this with my patients, melanoma survivors, all the time.
02:36:56.980 I love to- Ride my bike.
02:36:59.040 Yeah. I'm a swimmer. I'm a runner. This is what I love to do. Is that okay? I've had a melanoma
02:37:04.540 diagnosis. I have a 10% lifelong risk of developing a new primary melanoma. So you, Dr. Flaherty,
02:37:09.580 have told me, I want to minimize that, but this is how I get my exercise. This is the conversation we
02:37:14.760 have. I say, I get it. If I can talk you into a more sun-safe version of exercise, as in early
02:37:20.980 morning slash evening running, swimming, tennis, I'm going to try to talk you into that. Stay out
02:37:26.120 of the sun in the middle of the day. When now you're pursuing the cardiovascular benefit of
02:37:29.840 exercise, you're taking on more vitamin D than you need, and you're taking on an inordinate risk in
02:37:34.260 terms of skin cancer risk. Obviously, other skin cancers are more common than melanoma, but not as
02:37:38.140 life-threatening. So we usually frame this discussion around global skin cancer risk, where it's more
02:37:42.700 linear with squamous cell and basal cell, the relationship between sun exposure. In melanoma,
02:37:46.920 it's not as linear, but it's clearly causally related. So I synthesize all of the available
02:37:51.300 evidence to say there's confounders in the behaviors that relate to sun exposure. Vitamin D is still,
02:37:57.460 I think, there's enough strength to say vitamin D. There's obviously strong associations, which is
02:38:01.920 where you were starting with. I mean, the epidemiology regarding vitamin D levels and risk,
02:38:05.740 colorectal cancer was one of the first to come, but then other cancers undeniably related to low
02:38:11.060 vitamin D levels. So I think there is a causal relationship. I think you want to serve higher
02:38:15.400 up on the vitamin D curve. The issue is how you get there. My synthesis is you exercise. And if
02:38:20.720 your exercise means that you get a low enough UV exposure that you need supplementation, then
02:38:26.300 supplement. And until proven otherwise, it's those two factors that are why pure vitamin D supplementation
02:38:33.220 alone is never going to do it in a population where you're not controlling for their exercise.
02:38:39.000 Now you're dealing with a highly motivated population, I think, in general. So where
02:38:42.920 they're inclined to be doing positive health behaviors. So they're probably already tackling
02:38:47.000 the exercise piece. When you look at these studies, you're looking at a different population of people,
02:38:51.860 in my view. So let me just throw one little bit of science at you. It's a nature paper published by
02:38:56.880 my very close colleague at Mass General, David Fisher, who's one of the preeminent melanoma biologists
02:39:01.560 in the field. So he came across this link in terms of the addiction potential of sun exposure.
02:39:09.000 And it comes from the fact that melanocortin, which is the, if you will, the growth factor for
02:39:13.960 melanocytes in terms of their daily function as well as their development, comes from propiomelanocortin
02:39:20.500 produced in the anterior pituitary. And that basically a component of that gene product or this
02:39:26.800 hormone as the pro-hormone is cleaved into its hormones is endorphin. Endorphin is produced and
02:39:32.060 released in addition to melanocortin at equal stoichiometric quantities.
02:39:36.020 So it was that simple bit of endocrinology that led him to wonder, is there something about sun
02:39:42.280 seeking behavior that's wired into us to try to get us to go out and get vitamin D exposure?
02:39:48.360 You have to go back to evolutionary pressure times. Like, was there a reason why human beings
02:39:52.240 would rather have not gone out and expose themselves to the sun because predatory risk,
02:39:57.520 presumably? So that's a cute argument, but the wiring is very clear. You can show that mice will
02:40:04.000 basically prefer sun exposure. We'll go through narcotic-like withdrawal when you deprive them
02:40:09.820 of their sun exposure. So it's meeting the criteria of addiction the way we would see it with cocaine,
02:40:16.460 for example, in a mouse. Exactly. So it's of lower grade to a degree, but it's anyway,
02:40:21.300 this fascinating initial paper in Nature and a couple follow-on papers since then that kind of
02:40:25.820 reinforces this kind of circuit. This idea that basically this is even in a lower species like
02:40:31.100 mice, you can even detect this sun-seeking behavior that humans presumably have as well
02:40:36.380 toward the end of getting vitamin D. So here's an argument to say, well, we're engineered to get
02:40:40.760 out in the sun and there must be benefits from it. And the issue I think that you posed is how much of
02:40:46.140 the benefit is vitamin D? Then the shakiness of that argument is that, well, you supplement vitamin D,
02:40:51.120 you don't seem to get all of the benefit one would think. Anyway, what I'm getting at is that,
02:40:55.240 no, no, I think this is a behavior that is maladapted for those who are going to live to be 60,
02:41:01.420 70, 80, a hundred years old. Not maladaptive for people who are going to live to be 30 and
02:41:06.040 die from predatory death or whatever the issue back in evolutionary times.
02:41:10.260 Yeah, evolution would have placed absolutely zero pressure on preventing you from getting melanoma.
02:41:15.460 That's right.
02:41:15.800 So from a thought experiment perspective, if you could exercise indoors, never see the sunlight except
02:41:24.040 through your window and supplement vitamin D, do you think you are doing as well health-wise
02:41:30.180 as someone who does not supplement vitamin D, exercises outdoors, and attains the same vitamin
02:41:36.340 D level?
02:41:37.160 That's my hypothesis.
02:41:37.880 That's your hypothesis. Those are the same.
02:41:39.100 Yeah. I look at all available evidence in each study as it comes out and I take that,
02:41:43.340 I have that long-standing hypothesis, put that filter on and I say-
02:41:46.320 Does this study contradict that hypothesis?
02:41:48.560 So the idea that there's some other magical component of UV exposure, presumably UV being that
02:41:54.920 basically that there's some other magical property, I'd say we lack the evidence to support that.
02:41:59.320 So I guess last thing I want to ask you about, because in many ways this interview, Keith,
02:42:03.860 has been great because I think there are tons of scientists, scientists in training that I know
02:42:08.840 enjoy this podcast and I think you've offered incredible advice to people across different
02:42:12.800 levels of that spectrum. In particular, those people reaching out who are in MDA, PhD programs
02:42:17.780 and they're trying to straddle how do I balance research and clinical work? And though you are an MD,
02:42:24.300 PhD, not an MD, PhD, you're from a functional standpoint, you are an MD, PhD. You are a
02:42:28.320 clinician who predominantly does research. I want to ask you another question along that thread is
02:42:33.160 you also do something that a lot of people haven't figured out how to do. And I'm curious as to what
02:42:38.320 you've learned along the way, which is you have a very rigorous academic, completely standalone
02:42:46.200 credentialed existence. And at the same time, you really understand industry. You've been a huge part
02:42:52.500 of industry and you seem to run these two parallel tracks that virtually, I don't want to say nobody,
02:42:59.120 but most people really struggle to live on both sides of that. They usually tend to be very good
02:43:05.300 at one and kind of mediocre at the other. I would add to that. I think people are cautious to believe
02:43:12.380 that it would be a good idea to do it, that there'd be synergy in trying to live on both sides.
02:43:18.080 That's been the lesson I've learned over the past, let's say six years anyway, in earnest,
02:43:22.960 which is the dates back to when I co-founded my first company of a series now of five and this
02:43:28.540 year working on a couple more. Is that because of what you said at the outset, which is you were
02:43:33.840 immediately focused on translational stuff. And if you were focused on basic science, for example,
02:43:38.960 that synergy is a lot harder. Is it because of where the intersection you sit?
02:43:42.600 I mean, I should back up at step and say that you can't do the work that I do and not interact
02:43:46.520 with industry. So my entire career, the drugs come from industry. We do not live in a world yet
02:43:51.320 where academic entities or the National Institutes of Health produce investigational agents, take them
02:43:56.820 through their measures and then make them widely available. That could happen. Actually, there's a
02:44:01.560 part of me that has pushed and advocated for that day to come because I think it would help bend the
02:44:05.640 cost curve in a major way. But park that one for a moment. That hasn't been the world I've operated in.
02:44:09.780 I depend on pharma, which means big companies and biotechs to be aligned partners, at least for much
02:44:16.740 of the time that we work together. The misalignment totally comes. And when it comes, we shake hands and
02:44:22.560 part company. But my world has revolved around the fact that therapies come from companies,
02:44:28.580 proto therapies, and then true therapies. Diagnostics kind of come from us and diagnostics are 50% of the
02:44:34.820 equation. They're woefully undervalued. Yet a lot of our research and NIH funded research is about
02:44:40.460 quote unquote biomarkers that are in their best form going to become diagnostics.
02:44:44.340 I mean, this is the world's worst industry.
02:44:46.460 I get that.
02:44:46.760 But that's the point.
02:44:47.280 But you can't direct a patient to therapy and use the phrase precision medicine.
02:44:51.520 Without pairing it with the best diagnostic.
02:44:53.400 So this isn't about diagnosing colon cancer. This is about diagnosing the molecular type and what
02:44:57.900 its therapeutic vulnerabilities are going to be. And that could be ex vivo functional diagnostics,
02:45:02.320 not just static diagnostics.
02:45:03.380 Shouldn't that just be absorbed into the therapeutic world?
02:45:05.760 Right. Not just the cost borne by the therapeutic world, but also the development and deployment
02:45:10.320 as well. And that's where it works. Companion diagnostics, quote unquote, are the success examples.
02:45:15.580 It will still be the case that that therapy developing company marketed diagnostic and therapeutic
02:45:20.580 world will make 10 cents off the diagnostic, a billion dollars off the therapeutic. But if that's
02:45:24.720 what it took to get there, then they will do it. They will also give the test away rather than
02:45:29.820 bothering with the 10 cents. They will say, well, we readily recognize that we can't protect this
02:45:34.320 diagnostic space. Yes, we have IP in this very specific diagnostic method, but we're going to
02:45:38.820 get undercut by 10 to 100 others who are just going to come in and compete us. That's fine because we
02:45:44.120 still own the therapy. And especially in a regulated environment, if certain companion diagnostics
02:45:49.260 only link to that therapy, then the therapy developer still benefits.
02:45:52.760 The problem that I faced in my career, this is now taking a little bit of a detour from your first
02:45:58.000 question, but I'm going to come back to it. The problem that I faced as an academic is the issue
02:46:02.220 of alignment slash misalignment around diagnostic therapy pairs. If you get to market in a broad
02:46:08.080 population that is not biomarker selected, and you can get there, you know you're treating some
02:46:12.320 patients who aren't getting benefit from therapy. You've seen it in phase one slash two. You're still
02:46:16.340 seeing it in phase three, but you're having enough of an effect in enough of a subpopulation that
02:46:20.580 you're able to drive a result in an unselected population. If you can do that, that remains in
02:46:25.920 the current environment, the best version of success there is. It decreases the degree of
02:46:30.220 difficulty in terms of having two moving parts in your development plan, both a diagnostic and a
02:46:34.400 therapeutic, and you get the broadest population. Admittedly, patients who aren't getting benefit from
02:46:38.680 therapy aren't going to make a lot of money for you because in a cancer context, they're going to get
02:46:42.300 two months of treatment and stop. But still, broad population, broad use. A clinician doesn't have to
02:46:47.920 think about doing more testing than they've already done. They just give this colon cancer patient the
02:46:52.800 EGFR antibody, go back to the mid-2000s when that was the reality. A light bulb went off over hundreds
02:46:59.580 of people's heads saying downstream of the epidermal growth factor receptor is RAS, and in colorectal
02:47:05.440 cancer, RAS is mutated in a substantial fraction of patients. I bet that if you have a RAS mutation
02:47:12.480 downstream of the receptor, that tumor is not going to care about having the receptor blocked with the
02:47:17.560 antibody. Brief run through the lab confirmed that hypothesis. An attempt then to carve out
02:47:23.660 the RAS mutant population from an approved epidermal growth factor receptor antibody was a ground war
02:47:28.880 that took years and years. The number of constituents, first the drug developer themselves and regulators
02:47:35.680 joining them, who stood in the way of the most obvious scientific hypothesis I've ever seen in my
02:47:40.840 academic career, it was terrible. So this is what I'm getting about misalignment, is that basically,
02:47:45.720 if you do this too late and you're now carving out populations from an approved therapy, disaster.
02:47:51.860 Because then you're relying on the diagnostic to be the tool, the business incentive generating tool
02:47:57.360 to carve that population out, and it doesn't exist. Now, if we had single payer healthcare and
02:48:02.140 we had one ecosystem constituents talking about this, we could talk about the savings and not having
02:48:08.380 patients get ineffective therapy, and we could align on who takes ownership and responsibility. But that's
02:48:13.220 not the world we live in. So in the meantime, it's a mad panic as an academic to try to translate the
02:48:18.620 science to medicine with a diagnostic and therapeutic pair prospectively. So you get there at the finish
02:48:24.000 line with a heroically effective therapy that's benefiting 80 plus percent of patients. You're always
02:48:28.160 going to be wrong in some fraction, let's say. But you're almost nailing it in terms of assigning
02:48:34.120 patient in a true precision medicine way. If you can do it prospectively, which is a mad panic,
02:48:38.760 because cancer drug development has moved more quickly in recent years, you've got to now develop
02:48:43.660 that diagnostic, show that your biomarker positive, biomarker negative population do and don't
02:48:48.500 benefit to the satisfaction of FDA in time to then have that diagnostic locked down, ready to roll with
02:48:55.020 its approval supporting data set. So this is a long-winded way of saying that I've traveled this path
02:49:01.160 enough times as a collaborator with industry and seen it go well and go poorly. I've also seen lots of
02:49:08.320 decisions made in drug development in terms of compromises in chemistry, shortcuts that are
02:49:13.620 driven by just artificial deadlines. Like, look, this program's got to advance or we're going to
02:49:18.560 kill it either in a young company with venture capital backing or in a big pharma company that
02:49:22.580 says, look, we've got a huge pipeline. We've got teams competing against each other. We've got to
02:49:27.220 win this pipeline down to best candidates. So we're going to make some decisions next quarter.
02:49:31.900 So you show me what you've got in terms of chemistry advances towards your development candidate
02:49:36.600 and we're just going to make a decision. I don't care if you think you've in another quarter you
02:49:40.660 could do better. We're just drawing a line and making a deadline. That's the big company version.
02:49:44.780 The venture investors draw different timelines in the small company context. I watch these things
02:49:50.480 happen as an external collaborator for enough times and different compromises and what I thought
02:49:57.000 bad decisions being made to say, I think there's an opportunity here to do what I say the best of
02:50:02.380 academic medical work can be, which is to lead by example. Go into companies as a founder, meaning
02:50:08.540 with an idea, and try to do it the way that I think has the greatest integrity to the hypothesis
02:50:14.100 that you're trying to test. Not everything's going to work. That's not the point. It's just don't make
02:50:18.880 decisions for the wrong reasons. Make them for the right reasons that the hypothesis is basically not
02:50:23.600 held up and needs to be abandoned. You need to spend more time in optimization on the chemistry side.
02:50:29.300 Your regulatory path needs to be innovative because it turns out that next generation sequencing is or
02:50:35.440 isn't being adopted in the way that you thought it would be. I'm touching on some real examples here.
02:50:40.760 Being in the boardroom, being around the table, the smallest table where these decisions are made,
02:50:47.600 I had no idea how satisfying that would be. Do I suggest it for everybody? Well, but I would suggest
02:50:54.080 for everybody who cares about therapeutics-related research. Lab investigators, but particularly
02:51:00.080 clinical investigators, is you need to understand to the best of your ability how people's worlds turn.
02:51:07.040 You really need to develop that understanding. Otherwise, you cannot be an effective
02:51:11.420 constituent. You can't be an advocate within your field for your current patients, for the future
02:51:16.660 patients, next generation patients, patients worldwide who you're trying to advocate for.
02:51:20.420 You can't do that if you don't understand what's constraining on the other side. That has been
02:51:27.700 the lesson that I've learned. So the fact that I was approached and offered serially to take light
02:51:33.340 bulb moments and park them into companies, I couldn't have seen that coming eight years ago.
02:51:37.620 Clinical investigators didn't have those opportunities. Should they have those opportunities? Well,
02:51:41.540 you can imagine from what I've just said, absolutely. I mean, this is to me, I've got mentees
02:51:47.200 in my own group and mentees elsewhere in the country who I look at and say, oh, this field needs more
02:51:53.320 people like you around a board table. The thing that I've learned, and I hope that all of my co-board
02:51:58.300 members, if they heard this, would understand how much I'm saying this with a lot of respect and even
02:52:04.080 affection. These are super bright people who have accomplished in multiple dimensions. But if they are
02:52:10.100 not an MD or MD-PhD or straight PhD in biomedical research, let's say in cancer, there's a component
02:52:17.560 that they don't see, where if you're able to provide that as a single person around a board of
02:52:23.680 eight, that contribution can be disproportionate. Not on the financing side, not on domains that I'm
02:52:29.740 not very clever about and certainly not very experienced about. Learn to appreciate those
02:52:35.220 things. This is a seat that is currently not filled. I can only speak to cancer biomedical
02:52:40.240 research in the private sector. This is a seat that's not filled. It's empty. There have been
02:52:45.660 board seats held for basic investigators historically, but not the translational clinical investigator.
02:52:53.620 And to me, I think this is, I'm not looking for more work. So this isn't at all about me,
02:52:58.420 but I've seen that as cancer science has become so much more translational, the opportunity unfolded
02:53:06.140 for me. And I think it would be a major benefit to the field for the private sector basically to engage
02:53:12.860 more voices at the table of those who are involved in the truly applied science down to the patient
02:53:20.120 level. So you've got stakeholder representation in those discussions that includes the people who
02:53:25.700 actually, in the case of cancer, hold the hand of a dying cancer patient, understand what the
02:53:31.800 ramifications are of clinical trial decisions that are the most expedient path to approval versus the
02:53:37.520 let's make this really stick and matter for patients. Doing this through scientific advisory boards,
02:53:43.800 advisory boards, ad hoc consulting, which is the whole rest of my travels before I got into the
02:53:49.640 entrepreneurial mode of actually launching companies. Been there, done that. Those meetings are held.
02:53:55.200 They conclude and life goes on. You don't have a fiduciary responsibility.
02:54:00.260 That's exactly it. All of these companies, every single one of them, I mean, every company I've
02:54:05.120 interacted with in biotech slash pharma, they will all say that they're trying to move the needle for
02:54:10.280 patients, right? This is their stated goal and I believe them. How do you do that if you don't have
02:54:16.880 in the room, exactly as you say, invested responsible leaders of the company in the case of the board
02:54:22.960 who actually have career-long skin in that game? In retrospect, I don't get it, even though it wasn't
02:54:29.260 there 10 years ago when I wouldn't have imagined that these doors would begin to open.
02:54:33.680 Well, that's a great way to close this discussion, Keith. I hadn't actually thought of it through the
02:54:38.060 lens of the gap, the translational gap per se. Well, I want to thank you very much. You've been
02:54:42.660 incredibly gracious with your time and even more gracious with your insights. This is an episode where
02:54:48.020 I learned a lot along the way, which always makes it fun for me as well. Thank you very much.
02:54:52.360 Well, I appreciate the opportunity. Wouldn't be able to talk this long were it not for the fact
02:54:57.100 that you're pulling out of me all the talking points that I've used in different venues at
02:55:02.460 different times, but in one conversation. I think this is an incredibly exciting time in terms of
02:55:08.900 understanding the molecular underpinnings of health and disease. Cancer is incredibly anxiety-provoking.
02:55:15.260 It's actually why I got into the field, to be honest. It was the translating science to medicine
02:55:19.060 and the most disproportionately havoc-wreaking entity. And so I really appreciate opportunities,
02:55:26.740 this being a really unique one, to try to help people understand this seemingly impossible to
02:55:33.240 understand entity that is this kind of revolution within our bodies or betrayal within our bodies.
02:55:38.300 But we'll get there. The pace is quickening of progress. So I hope I've communicated that,
02:55:44.340 but I hope you circle back to revisit this topic with others in the field because you will see
02:55:49.660 year over year that the pace of progress will continue to advance.
02:55:52.980 That'd be great. Or maybe I'll just come back to Boston once a year and
02:55:55.460 I'll always time it in a nice time of year.
02:55:57.640 Sounds great.
02:55:58.200 All right. Thanks, Keith.
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