#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
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
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Hey everyone, welcome to the Peter Atiyah drive. I'm your host, Peter Atiyah. The drive
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is a result of my hunger for optimizing performance, health, longevity, critical thinking, along
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with a few other obsessions along the way. I've spent the last several years working
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with some of the most successful top performing individuals in the world. And this podcast
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is my attempt to synthesize what I've learned along the way to help you live a higher quality,
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more fulfilling life. If you enjoy this podcast, you can find more information on today's episode
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and other topics at peteratiyahmd.com. Hey everybody, welcome to this week's episode
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of the drive. I'd like to take a couple of minutes to talk about why we don't run ads on this podcast
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you probably already know, but the two things I care most about professionally are how to live
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excited about. I want my supporters to get the best deals possible on the products that I love.
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And as I said, we're not taking ad dollars from anyone, but instead, what I'd like to do is work
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with companies who make the products that I already love and would already talk about for free and have
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them pass savings on to you. Again, the podcast will remain free to all, but my hope is that many of
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you will find enough value in one, the podcast itself, and two, the additional content exclusive
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for members to support us at a level that makes sense for you. I want to thank you for taking a moment
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to listen to this. If you learn from and find value in the content I produce, please consider
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supporting us directly by signing up for a monthly subscription. My guest this week is Dr. Keith
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Flaherty. Keith is a physician scientist at Massachusetts General Hospital in Boston,
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where he's the director of clinical research, as well as targeted therapies. His research focuses
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on the understanding of targeted therapies in cancer. And if that term is a bit nebulous to you,
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don't worry about it. We define it quite clearly. And he focuses on the development of responses and
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predictive biomarkers to define the mechanisms of action and resistance of novel therapies.
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He's researched a lot of stuff in immunotherapy. So this is really the first podcast that I discuss
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immunotherapy in, which for me is super exciting because I've been looking forward to discussing this
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topic for quite some time. And you'll see why when we get into it, because immunobased therapies
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are basically the most exciting recent development in cancer therapy. And we talk quite a bit about
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these checkpoint inhibitors for which actually the Nobel prize in medicine and physiology was awarded
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last year. He's been a PI in a too numerous account first in human clinical trials using novel
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therapies. What else can I say? He's a professor of medicine at Harvard medical school and serves as
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editor in chief of the journal clinical cancer research. Overall, Keith is really a wealth of knowledge
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in cancer. We talk about a bunch of stuff. Now, honestly, the first 20 minutes, we're just talking
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general life medicine. We don't even touch on cancer. So if you're short on time and you really just want
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to get into the stuff on cancer, definitely jump ahead to 20 minutes into this stuff. We talk quite a bit
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about the history of chemotherapy, what its successes were, why they asymptoted, same with radiation
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therapy, surgical therapy, and ultimately what took place and what didn't take place, maybe more to the
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point in the period of time between when the war on cancer was declared in 1974 and the sequencing of
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the entire human genome about 25 years later. And then we talk about what took place in the two
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decades since that time. And you'll see that, well, at least even for me, I think you'll tell, I was
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actually learning quite a lot here vis-a-vis how some of those changes took place. And again, for that
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reason, this was a highly enjoyable experience. Even if not one person listens to this podcast, I got a ton
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out of it. We basically got into this notion of what's a different approach to cancer. And again,
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clinically, I found this very helpful because this is a problem I think a lot about. So I do think
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people will enjoy this. We talk a little bit about liquid biopsies, even touch on roles of potentially
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CRISPR and overhyped with respect to cancer therapies, potentially even at the end, talk about stem cell
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therapy, vitamin D, melanoma, sun exposure, the list goes on. This is a pretty long episode. So
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hopefully we talk slow enough that you can listen to it at a slightly higher speed. And the show notes,
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as always, will contain a ton of information, not just links to the studies we talk about, but a lot
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of the semantics. I wouldn't be discouraged if you find this topic and particularly this episode to be
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somewhat challenging based on how technical it gets at times. I think we both do a pretty good job
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of remembering that we're not just talking with each other. And I try to ask questions to bring
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us back 30,000 feet and focus on the big stuff. But in many ways, I think this will be probably the
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deepest podcast I've done to date on cancer, though certainly not the last. So without further delay,
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please enjoy my conversation with Dr. Keith Flaherty.
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Keith, thank you so much for letting me intrude in the middle of your living room on a rainy Monday
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afternoon. My pleasure, Peter. Is this normal Boston April weather?
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This is the wet season, mud season as they call it, but it's a welcome break from winter. Hasn't
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been a particularly harsh one, but yeah, it's a good transition time. It was brown last week,
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so everything's just finally waking up. Now you've pretty much spent your whole life
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from basically Connecticut to, or actually Connecticut south of Boston, right? So
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sort of basically Boston to Baltimore has been most of your life.
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That's right. Born and raised in Baltimore, broke away to boarding school in Massachusetts for four
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years, Connecticut for college, four years, then back to Baltimore, four years in medical school,
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Boston for the first time, three years of residency, and then Philadelphia for nine years,
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which was both medical oncology fellowship and my first faculty stint. And now 10 years ago,
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moved back up to Boston to Mass General. So this fall will be 10 years, but as you say,
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Yeah. That's always my defense of the Northeast to Californians is I need the seasons. And certainly
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during my educational years, I always thought if I had San Francisco, LA, or God forbid, San Diego,
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weather, I'm not sure I really would have been able to keep my nose to the grindstone. Seasons are good
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to kind of force you inside and take your breaks when you need them.
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Well, I think there's something else about it that I sort of lament. Both my wife grew up in
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Baltimore. I grew up in Toronto. And there is an intestinal fortitude that comes from being in a
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climate that is not particularly hospitable. You get a little tougher as a kid, I think,
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when it's, you have to pay attention. Like if you forget your gloves, like you're hosed.
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I suppose that's true. I think resilience comes from a few parts of one's upbringing, but
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climate is probably, you're right. It's at least a bias of mine that it's a good thing to have.
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Even as the years keep passing and I think about, well, where would I want to spend the next 10
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years, 20 years beyond? I love it up here. I mean, for me, it's really the, it gets just brutal
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Although Boston is its own little, Boston and Toronto are not that different.
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Yeah. I've just had more figuring latitude drives harshness of winter. I have more respect for
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Canadian winters, but maybe it isn't that different. I feel like, again, just gets harsh enough.
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And then in the summertime, get the payoff for the flip side, which is just so pleasant,
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but not like Baltimore burdensome in terms of the heat and humidity.
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So you're kind of one of these guys who was exposed to medicine throughout, right? But I know
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your father is a physician. Your mother was as well, right?
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Yeah, that's right. My father was an academic cardiologist for 25 years and then almost an
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equal stint in industry, pharma and biotech. And my mom was an academic psychiatrist, actually
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really still is at the age of now 70, will be 76 end of this month. Very different career in
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psychiatry versus cardiology, but an academic career nonetheless. So a bit of research, a lot of
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teaching, mentoring, and that bit continues. She has incredible stamina for staying connected with
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her field. She's retired from patient care a good long time ago, but couldn't give up the rest. And so
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continues to haul herself off to conferences and oral examinations that are still required for,
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for psychiatric boarding and so on. So kind of a inspiration in terms of longevity in the field.
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You knew pretty early that you wanted to go into medicine or was that not even clear when you went
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off to college? Yeah, no, it wasn't clear to me at all. I mean, I honestly would have to admit that I
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didn't really understand how my parents' worlds turned. They were perfectly transparent and happy to
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talk about their careers. I just didn't know to ask the questions. The two older brothers who then and
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now had no interest in science or medicine. I guess all that I could say from a young age,
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maybe by the time I was in boarding school and going to college, was that some way, somehow I
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wanted to help people. This is a phrase that I recall saying, but I had no idea what that might mean
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and what the different versions of it were. As years passed, I got more and more of the sense that
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a lot of how the world turned was kind of transactional business transactions, I suppose,
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people making careers on some version of transaction. I had this aversion, or developing
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this aversion to that idea that I didn't want to be involved in what I broadly construed to be
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business. Now, we'll come back to this later. I was about to say the irony, but okay.
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Absolutely. I'm laying that right out there for you. There's so many ways in which I turned on that.
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I mean, in a good way, I've turned on those initial principles. But yeah, in any case,
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I thought this idea that I needed to find a path where I felt like I was very directly helping people
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was going to be the most sort of satisfying career and something that would get me out of
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bed in the morning without having to really try. That part, I'd say, really did work out.
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So I think that's probably the one piece that I think I did get from my parents. So I didn't know
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exactly what they did when they got to the hospital.
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But you had some sense that it involved people and they were in probably a more direct way of
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helping them. I mean, you could argue most people are helping people in some way, but you knew that
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there was fewer degrees of separation. That's right. And then that final point that they were
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super motivated by their careers, it was never a complaint. There was one thing about their marriage
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they would talk about just inside baseball of division department, hospital level politics and
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issues that were kind of headwind for them. And you hear them talk about their real mechanistic
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elements of their careers. And it just was never a complaint about it. They were very kind of focused
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on results and group dynamic and so on. But I guess my point is that you never had a notion that they
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did not love what they did. And end of every vacation, end of every weekend, I mean, they were just
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like hard charging back at work. My parents, because they were both building academic careers
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when we were young, they were oftentimes alternating evening duty. One of them, even for a whole week
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at a time, tied up either on service or something that was keeping them in the hospital. So watching
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that conviction and how much they just loved doing that thing that I didn't understand, that was
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probably the very nebulous notion that I kept with me. So that as I kept kind of crossing off like
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vast segments of American economy had to offer in terms of careers, medicine's kind of the thing
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that remained. Yeah. It's an interesting point you raise about the fine line for parents in terms of
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the example setting versus the time there. I mean, both are really important, right? I mean, I know
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this now. I have kids, met your daughter earlier. There's in some ways no substitute for this term
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quality time sort of always struck me as a little bit of a hoity-toity term. I mean, there's time and
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there's no time, right? But call it quality time. And there's no substitute for that, but there's
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something to be said when a child sees their mom or dad feeling incredibly passionate about what
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they're doing and how without saying a word about that, it sets an exam. Yeah. I hear my daughters
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talk about this in relation to my wife. She's an internist at Mass General and she's part-time,
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but because of Epic, the electronic medical record, she's full-time and then some because for every
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minute she takes care of a patient directly, she's taking care of their medical record for three to
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five minutes easily. That sounds like an excellent ratio. Yeah. And of course the kids see that side,
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right? Because they're not with her in the hospital, but they see the constant overflow.
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They know what she does in principle and internists, I guess, maps to a pediatrician. They have direct
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experience with that, but they watch her pour herself into the indirect care of patients through the
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electronic medical record and constantly reflect that she's the hardest working person they know.
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And that example, like this, that kind of willingness to like give, give, give outside of
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one's personal time, family time, it's related to what I was trying to put words to, but this very
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nebulous notion of what it is that qualified as a satisfying career. I've spent my adult life,
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particularly raising kids, making this comment that in my imagination, a number that I often comes back
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to is like 95% of people don't like what they do. And they're just holding their breath, trying to get
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to the weekend or vacations. And maybe I'm vastly off base, but I guess I'm partly using a high number
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like that because I just feel incredibly fortunate to have been brought up in a household and educational
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environment serially that my parents made available to me that allowed me to be in that, what I think is
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a relatively small group where I just always loved what I did and just, and felt like I had absolute
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choice and could engineer my schedule in every respect in a totally sort of suicidal, not respectful
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of balance way. I mean, I just developed a career that was ridiculously off the rails in terms of
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being overcommitted and trying to juggle way too many things in some respects. For me, I would defend
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it also and say it was exactly the optimal amount of chaos that one needs to really feel like you're
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kind of pushing on all fronts simultaneously. But, but how do you both find the, the outlet and
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define the scope of a career that allows you to do that? Man, what a challenge and what a different
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challenge I think that our children will have versus what it was like to try to build a career
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in this case in medicine starting decades ago versus what they're looking at.
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And medicine still may be one of the slightly easier places to do it because the path to quote
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unquote academic success, non-academic clinical success, it's still relatively unperturbed from
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so many other paths, right? Outside of medicine. Or is that not even true anymore?
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I don't see it that way, but I'd be interested in your perspective as a surgeon, because I think
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maybe we have a different angle on that being in medicine versus surgery, which obviously culturally
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we've always had some real differences, not just culturally, sort of skill sets. So the thing that
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I've been deliberating on, let's say this, I've had a 20 year oncology career, almost 20 years,
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a few months away from that. And so I divide my career up into these two decades and I've watched
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technology advance and the field-wide body of knowledge accelerate in a 2000 to 2010 interval
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and then these past 10 years. And this is true in so many areas of technology advance, but in
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biomedical research and in cancer, which is my only area of any expertise, I thought 2000, 2010 was
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mind-blowing and I thought we were going to spend time catching up with the mind-blowing advances.
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That was my talking point coming into the field in 2000, that I thought we've got this huge wave
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of molecular insights, mostly genetic insights in terms of cancer that had built up, but hadn't
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been transformed into medicine. That was my unbelievably naive, simple-minded pitch as I
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was entering the field. And I said, I want to make myself useful in that translation of science
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to medicine. Anyway, 2000, 2010, then you could say we're the first chapter of translating molecular
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insights into medicine and oncology. Well, 2010 to 2020 makes that first decade look unbelievably
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slow. And where it was every two years, there was maybe a monumental event, whereas now it's like six
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at a time. So that's in terms of like crossing the finish line, but in terms of data generation,
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ability to produce high-dimensional data, analyze it, try to make sense of it, raise hypotheses,
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test hypotheses. Yeah, the cycle time is changing a lot. And the constituents that we now need to
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interact with are totally different. The point I'm coming to, to answer your question, is I see
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medicine now as this terrifying arena in which to try to assemble a multi-decade long career. Like,
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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
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an absolute dinosaur. Mentoring is the thing that I think I can still do with some relevance to the
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younger generation. And in mentoring them, I tell them, look, you need to learn how to talk to a
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bioinformatician, computational biologist. I couldn't have even imagined 10 years ago that I'd
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be telling my mentees that, much less that I would have this notion that I need to understand
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the world from that degree of mathematical modeling complexity. But it's having now mentees
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who were in computational biology myself, I've come to realize that it's, I didn't have the skill set at
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the dawn of my career. Is it possible for people, broadly speaking, to actually retrain themselves and
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grow a new lobe of their brain? It's possible, but it's going to force a totally different
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paradigm in terms of how one thinks about taking breaks, taking sabbaticals, gaining that knowledge
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base. So I was actually thinking of something different, but what you're bringing up is more
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interesting. So I want to double click on that before we jump into the meat of what we're going to
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talk about. Based on the way you're describing it, Keith, I would say doctors coming out of training
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are hosed because medical school, and I'm going to really make a lot of enemies by saying this,
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but I guess it's my podcast I'm allowed to say this. I think medical school might be one of the
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most anti-intellectual forms of higher education that exists. I mean, when you contrast it with even
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the experience that many people have in college, where you really get to think creatively, you really
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get to problem solve, you really get to explore the limits of what is known and what is not known and ask
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questions, not having gone to law school, but my brother did. I got to see my brother do that in
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law school, having more friends than I can count who did PhDs in everything from the humanities to
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the sciences. They got to do that. Well, I went to a good medical school, but that's not the way my
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education was. And I'm not sure it's that much more like it today. In other words, I'm not sure
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medical school teaches you how to be a thinker or a problem solver, or even, and maybe again, I hope
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I'm wrong. But if you don't learn how to learn and God forbid the people who go into medical school
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as pre-meds. So then they've missed out on at least taking an engineering degree or taking a
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humanities degree where you would have got some of that stuff. So, so yeah, then I think you're in
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real trouble. I totally agree with you. And the word that you didn't use that I'll use is
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investigation. That's not taught. And at best it's taught in a retrospective field-wide
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introspective way. And by that, I mean like diagnostics. I mean, thinking about how to
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diagnose illness in medical school is the beginnings of teaching that concept.
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I actually tell people the one type of statistics that physicians get very well trained in without
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explicitly being told what they're doing is Bayesian statistic, because that really is
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clinical medicine. Clinical medicine is pure Bayesian statistics. It is learning how to update your
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pre-test probability with new information over and over again. And the reality of it is that doctors get
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very good at that. It's never codified and formalized such that they understand that that's
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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
00:24:32.480
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
00:25:45.400
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,
00:26:24.760
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.
00:30:39.780
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.
00:30:59.640
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.
00:33:10.240
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
00:33:56.880
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
00:34:12.120
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
00:34:37.780
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
00:35:45.900
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...
00:41:47.260
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...
00:42:41.040
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?
00:43:03.480
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
00:44:59.220
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
00:45:14.300
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
00:45:24.800
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.
00:46:04.720
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.
00:46:39.140
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-
00:54:56.980
Yep. But narrow therapeutic index, as in the asymptote was reached awfully early. What were
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.
00:57:35.680
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
01:00:29.900
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
01:01:44.280
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,
01:03:13.000
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
01:03:37.760
Although for a totally different reason, right? It doesn't really metastasize. I mean,
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
01:04:29.520
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.
01:05:00.960
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
01:06:15.800
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.
01:12:39.620
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,
01:13:46.200
And before we leave HER2-new, what's the success rate? So if a woman... HER2-new is used pretty commonly
01:13:52.560
Yeah. But the naked antibodies produced a 10% to 20% response rate. So tumor shrinkage by the
01:14:01.940
Yeah. So notable benefit in a pretty small fraction of patients when given as monotherapy.
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
01:14:41.240
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,
01:15:57.540
So what, explain what's the tyrosine kinase? What is that whole thing that you just said? And
01:16:04.660
So there's four leukemias, broadly speaking, right? Acute and chronic, myeloid and lymphoid
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-
01:16:22.260
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
01:17:53.700
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
01:20:36.760
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.
01:20:46.400
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
01:21:05.540
And extrons and introns for folks is coding. I mean, it's part that actually gets turned into
01:21:11.980
Exactly. But they still play an important regulating role. And again, at least scaffolding,
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...
01:21:23.600
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
01:21:46.180
What percentage of cancers do not have a P53 mutation?
01:21:52.220
I would have guessed that fewer people with cancer do not have a P53 mutation.
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.
01:25:33.000
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-
01:34:28.880
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.
01:36:38.420
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
01:38:18.580
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
01:38:27.980
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
01:38:49.100
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?
01:40:30.820
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
01:41:07.400
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,
01:41:29.540
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.
01:41:52.480
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,
01:43:41.180
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
01:44:00.100
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.
01:44:22.360
But in this context, it's aptly named. It's very ABLE. It's an ABLE kinase that has become much
01:44:27.280
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,
01:44:38.040
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?
01:44:59.960
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
01:48:22.660
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.
01:52:09.700
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
01:52:31.660
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.
01:56:55.600
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.
01:57:10.140
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
01:57:30.240
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
02:09:51.020
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-
02:10:07.100
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,
02:10:22.960
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
02:10:59.560
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,
02:11:18.240
Right. So even though Merck or Pfizer could have a program under each pillar,
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,
02:11:57.200
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-
02:16:57.080
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,
02:20:47.660
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,
02:22:23.960
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.
02:22:34.540
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
02:24:25.220
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...
02:30:28.620
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,
02:32:07.280
Yeah. You don't want a proto-cancer cell to be getting more telomere length.
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?
02:32:48.740
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.
02:36:59.040
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.
02:41:15.800
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
02:41:39.100
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-
02:41:48.560
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.
02:44:47.280
But you can't direct a patient to therapy and use the phrase precision medicine.
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,
02:45:03.380
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
02:55:58.920
You can find all of this information and more at peteratiamd.com forward slash podcast.
02:56:06.460
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