Once, when a cancer was suspected, the next move often involved a biopsy — literally cutting out human tissue to ascertain malignancy.
But that highly invasive model is now being overshadowed by the promise of “liquid biopsies.” In these non-invasive approaches, blood, spinal fluid and other bodily liquids are drawn and tested for the presence of cancer cells, bits of DNA or other molecules that are the unmistakable markers of serious disease. Often, such non-invasive biopsies can be done before clinical symptoms appear.
Ash Alizadeh is an authority on the rapidly evolving technologies and techniques of oncology. He says that information is reshaping not only how we detect cancer but also how we treat it. The data we gather about any given cancer is being combined with knowledge about the patients themselves, leading to highly personalized approaches that did not exist just a few years ago. No two cancers, nor two patients, are exactly the same, Alizadeh says. Cancer cells grow differently in each patient and cancer treatments should be personalized accordingly.
Join host Russ Altman and Ash Alizadeh as they explore the exciting new age of cancer diagnosis and treatment on this episode of The Future of Everything. You can listen to The Future of Everything on Sirius XM Insight Channel 121, iTunes, Google Play, SoundCloud, Spotify, Stitcher or via Stanford Engineering Magazine.
Russ Altman: Today on The Future of Everything, the future of cancer diagnosis and treatment.
Well I don’t think I even need to say that cancer is a terrible and scary disease or really a set of diseases that affect many people worldwide. Loved ones, friends and people themselves have to struggle. Very few people are not affected by this disease, and recently, there’s been great progress and generation of hope for improved diagnosis and treatment of cancer based on really, progress in many areas. Improved imaging methods to take pictures and detect the cancer. Ability to sequence the DNA of the cancer cells to understand exactly what’s wrong and what might need to be fixed. Better medications that are focused on specific defects in these cells to give them a more focused treatment. Improvements in radiation therapy and many other areas.
The U.S. government, the National Institutes of Health, has created a Cancer Moonshot, which is a large, well-funded research program to accelerate progress in cancer research in the development of treatments and diagnostics. Now, and important trend in cancer research is personalized medicine.
And what do I mean by that? Well, can we use information about the individual patients to more sensitively detect the cancer in the first place? Can we use information about how the patient responds over time, to choose the right sequence of treatments and combinations. Can we help the patient understand the likely outcomes of their treatment, so they have less uncertainty. One of the big scary things about cancer is not just the diagnosis, but all the uncertainty that that brings to the patient in terms of, what does that mean for my health and my life. Am I talking months, years, decades, what’s going on?
Dr. Ash Alizadeh is a professor of medicine and oncology at Stanford University. His lab has focused on understanding the biology of cancer, how it begins, grows and how you can treat it from multiple perspectives, including the transition from normal cell to cancer cell, the role of the immune system, and the creation of new tools to study cancer.
Ash, one area you have focused on recently is forecasting how a cancer will progress over time. Is it aggressive, will it respond to treatment, how should we monitor it, how frequently should we monitor it? Why have you focused on this and what could be the benefits to patients and their physicians?
Ash Alizadeh: Thank you, Russ. So in addition to the things you talked about I happen to be an oncologist and take care of some of these folks, and in large part, focusing on this problem’s been motivated by the personal experience of looking in the patients eyes and having a conversation with them as they go through this journey that you’re going through with them, and it’s really sobering to look how blunt our tools are for getting a sense for whether you’re making progress as you’re going through the course of your therapy. So the disease I take care of clinically is one of the most common blood cancers, aggressive lymphoma that we cure in the majority of patients, but it’s not 100% and having a conversation with the patient about the likelihood of being in one of those, in the group that is cured as opposed to the group that isn’t is something that takes months, if not years to determine. So, in —
Russ Altman: In all that time, you and the patient are extremely worried.
Ash Alizadeh: Exactly, and so the thought was, we’ve historically, in the past, looked at various time points during this journey, and said, “What information do we have, and how can that information help predict the future?” But, you know, in part motivated by seeing how and other folks for making such forward progress using statistical tools to look at dynamic data. In particular — in relation to elections, Nate Silver, and some others to take longitudinal data, and build a framework for saying, “Who’s gonna win this election? “Who’s gonna win this baseball match? “Who’s gonna win this football game?” Are you smarter as you integrate information over a timeframe when you’re looking at, let’s say a version of a film as opposed to still shots during —
Russ Altman: Right
Ash Alizadeh: During the transitions.
Russ Altman: Now certainly I’m sure doctors and you yourself in your practice over the years have tried to do this, so what has changed that makes you optimistic that you can do an even better job?
Ash Alizadeh: Right, so yeah I had the same thoughts, but I don’t think we have ever really done this in a longitudinally integrated statistical framework that makes an accurate forecast, and I think even in my own practice and in chatting with most of my peers, we almost treat the most recent data as the best data. What’s the score at half time as a best predictor of the game, forgetting that maybe, quarterback’s out, even though the score is tied, you know that —
Russ Altman: He was injured on the last play of the half.
Ash Alizadeh: Yes exactly, if you didn’t watch the first half, and you just tune in at half time, you probably, in assuming that the score half time is more important than having watched the first half, you would be less likely to make a good prediction, and so we set out to answer this question, if you integrate information over time using a couple statistical frameworks, do we do better? And I surprised actually because I sent out the guys to prove me wrong that the most recent information would be the best information, and it seems to be true that in integrating information dynamically, you make much better forecasts.
Russ Altman: So can you, how does this actually work —
Ash Alizadeh: Sure.
Russ Altman: For real patients and real data, are they coming, I’m sure they’re not coming to the hospital every day for a measurement, but there must be some sense of longitudinally following them, monitoring them.
Ash Alizadeh: Sure, so we’ve done this now for three types of cancers, and we’re working on a bunch more, but we took the most common lymphoma, which is large B-cell lymphoma, that’s the most common blood cancer, we also took the most common leukemia, chronic lymphocytic leukemia. I worked with a European cooperative group that had collected large numbers of patients and longitudinal measurements. We took early stage breast cancer, and we said, okay, there are established still shots in the film that have been defined as predicting risks, stage of the disease, age of the patient, burden of disease, etc, and then still shots as the response to the patient drop or have the pathology clear, etc. But, now we are going to staple this information together in a statistical framework that says, “Okay, I’ll either consider these things an isolation, or I’ll roll them up into an equation to give you a number and that number will make the forecast a calibrated probability.”
Russ Altman: So if I’m understanding, in the olden days —
Ash Alizadeh: Yes
Russ Altman: You might get two patients who they come to their, let’s say, two year appointment —
Ash Alizadeh: Sure
Russ Altman: And they look identical.
Ash Alizadeh: Yeah
Russ Altman: They have a similar blood test, they have similar imaging, you can’t detect the disease perhaps, and in those days, in the olden days, you might say, “these patients are essentially equivalent.”
Ash Alizadeh: Exactly.
Russ Altman: And then what I’m hearing you say now is the path by which they got to that point, might actually make them have different expected futures.
Ash Alizadeh: That’s right.
Russ Altman: And so you might say, “You two look the same, but I’m gonna” Well, to sound harsh, “I’m gonna give you good news, “and I’m gonna give you bad news, “because the history of how you got here is very different.”
Ash Alizadeh: Exactly. So this path dependence, so if you start in looking exactly the same way, you have the same respect, you’re stage two disease, you’re a certain age, and you get the same treatment, and one patient has a response, one doesn’t, of course that information is different, and then you staple that information forward, and you make a prediction, or you get to the same point that, you know, scores tied, but you had prior histories.
Russ Altman: Right. This is The Future of Everything, I’m Russ Altman, I’m speaking with Doctor Ash Alizadeh about cancer, and new ways to follow it and prognosticate about it. Is this a purely research result, or has it started to change practice, and in what ways?
Ash Alizadeh: Yeah, since the paper’s published as a theoretical article, and I was surprised by how much excitement we’d gotten from the community, our collaborators in Europe, and the broader community of American oncologists about trying to take this framework and now that we’ve done it, several diseases to use it for a predictive therapeutic change idea, we’re still in the midst of designing it with clinical trial where we take the information and say, “Okay now we’re gonna be changing treatment based “on a number, not based on a —
Russ Altman: Feeling.
Ash Alizadeh: A feeling, or let’s say an image, say, right, a picture of, here’s this much disease I have, and that doesn’t have a whole lot of history, so we’ve got to be careful about how to do that right so that we have the best chance of having the result mean something.
Russ Altman: Were there surprising results in terms of as you looked at this data, not only the current data but all the past data, are there sources of data that were surprisingly more useful than expected, or less useful than expected, or did it actually play out mostly how you would expect in terms of what the most valuable pieces of information are?
Ash Alizadeh: You know, I don’t think, I think I was surprised by how well the data complemented each other, I don’t think I have a bias, of course my lab has spent a lot of effort on trying to develop non- invasive diagnostics. Liquid biopsies for helping make these movies to get a sense of what’s happening —
Russ Altman: And for those who are not familiar the liquid biopsies are samples of blood where you can detect the cancer —
Ash Alizadeh: The cancer.
Russ Altman: And so it’s much less invasive than a biopsy or a surgery.
Ash Alizadeh: That’s right, that’s right, and I, you know, if we measure these things, these are — let’s say the DNA from a tumor that you can measure quickly after the start of treatment for a patient with chemotherapy, within a few days of getting chemotherapy, these levels change so dramatically, because the half-life, or the life span of these DNA molecules is so short that you can see dramatic predictive power in and of themselves.
Of course those, us and many other groups have shown that those measurements are great at predicting the future, but it’s the ability to use that information and what was there before, and also the additional information in the course of disease, radiographically — we’re not going to get rid of radiology any time soon, and it does provide information. Let’s say a procedure has a pathologist evaluate the result of new adjuvant chemotherapy as before the surgeon does the definitive job cutting out a tumor, we’re not gonna throw that information out, it has information in it. I think the thing I was surprised by was the complementarity more so than any one piece being the most important —
Russ Altman: Yeah that’s actually good to hear that the medical the oncology profession has chosen its tools relatively wisely, maybe not even realizing how wise it was. So, I’m struck by this and thinking about it, because a lot of it is predicting, forecasting the future that, what the patients state is gonna be. How does it effect So, maybe since many of us are not oncologists, how does knowing whether a patient has a relatively good prognosis, or a relatively bad prognosis, how does that effect the way you treat them?
Ash Alizadeh: Right.
Russ Altman: Do you give up sooner, or do you get more aggressive?
Ash Alizadeh: Right
Russ Altman: Take us through this.
Ash Alizadeh: Sure.
Russ Altman: Information changes care.
Ash Alizadeh: Sure, so let’s say we’re talking about an aggressive lymphoma, so we’re talking about just using, on like let’s say breast cancer or lung cancer, it’s not a disease that we have surgeons help us with, cut out as a way to cure the disease, we need to use drugs in combination. When a patient comes to see me, let’s say like, yesterday in my clinic with a new diagnosis, we get a picture of where this disease is, what’s the stage, what’s the risk, etc, and you have a conversation with the patient. In general you say, “Yep, we think we have a 60% chance of curing you with this regimen.” and that’s good information but it’s not a whole lot better than a coin flip, right?
Russ Altman: I would go home nervous.
Ash Alizadeh: Right you would go home nervous, and your oncologist is nervous, right, the whole team is nervous, you’re fighting a battle together to save a life, and the question is, the things you’re doing are toxic, they’re expensive, and a human being’s life is not a trivial thing to be playing a coin flip with.
Russ Altman: Right.
Ash Alizadeh: Can you through the course of this treatment, help, even if it’s not for changing treatment, help set priorities, right, so do I prepare for my grandkids wedding in a couple years, or do I prioritize writing my will? Right, that’s the —
Russ Altman: Harsh, but real.
Ash Alizadeh: Harsh but real situation, these are conversations I have regularly with patients. On the flip side, well if this treatment is unlikely to work, could we imagine this strategy as a quick change of treatment, that’s the experiment we need to do, but yep, this is chemotherapy, it works for 60% of patients to cure them, you’re not one of the 60%, we should be putting you on a clinical study of a new drug, Let’s say, these engineered immune cells, chimeric antigen receptor T cells, expensive but profoundly effective with a single dose, curing a large fraction of patients of the disease, could we imagine doing such a thing and we’ve been talking with a lot of folks about that kind of strategy.
Russ Altman: This is The Future of Everything, I’m Russ Altman, I’m speaking with Doctor Ash Alizadeh about chemotherapy and the value of having better predictive information about what the future of the cancer looks like. It sounds from your last answer that a lot of this is risk management, and knowing that it’s an aggressive cancer might make you more willing to subject the patient to very harsh or even investigational therapies, but if the patient looks like they’re going to likely respond well to the standard treatments for that cancer, then your level of risk taking might go down because you’re pretty confident that the existing methods will be, is that a fair summary of —
Ash Alizadeh: I think so, I think you know, in part, this disease is a poster child for oncologists because, the lymphoma one, but the other ones are also relevant. I don’t think it’s about intensity, as much as it about honing the strategy based on the information. I could imagine for a significant fraction of patients, we give everybody six treatment cycles with the chemotherapy recipe, that’s the recipe for the average patient, but not for the individual patient, maybe you should get one treatment, or two treatments and be done, so you could imagine this as down, lowering or deescalating, on the flip side, it could help us pick drugs that are more effective than chemotherapy but we can’t ignore the history of 50 years of research to show that these recipes cure such a large fraction of patients.
Russ Altman: So this is very exciting, obviously, and for the three diseases you mentioned with presumably were in your first theoretic, as you called it the theoretical paper. It sounds to me like it would have general applicability now, and I think you even made a reference to that, the community is excited about this, and it is now kind of a part of the research agenda to see if this can work and be applied to numerous other cancers, prostate you didn’t mention, brain, etc.
Ash Alizadeh: Yeah actually that’s pretty much, that prostate’s the next one on the radar we’ve been working on. Brain tumors, we are also working on. The need for these things is data, so but can we, the theoretical framework needs data, so applying it to other tumor types and then doing the clinical studies to say all right, you know, risk management, but a therapeutic risk management, what’s next for these folks.
Russ Altman: This is The Future of Everything, I’m Russ Altman, more with Doctor Ash Alizadeh about oncology, the future of cancer diagnosis and treatment, next on SiriusXM Insight 121.
Welcome back to The Future of Everything, I’m Russ Altman, I’m speaking with Doctor Ash Alizadeh about cancer, and current trends in cancer diagnosis and treatment. So, two things that we made brief mention of this in the last segment, is this idea of a liquid biopsy.
Biopsies are usually scary, because it usually means a surgery, and liquid is just confusing, so could you take us a little bit more deliberately through this relatively new technology that we’re hearing a lot about even in the popular press?
Ash Alizadeh: Sure, so, you’re right in that liquid refers to a liquid that we’re trying to sample, whether it’s blood, whether it’s urine, whether it’s cerebral spinal fluid, etc., but by and large most people talk about blood, and in the blood, there are a variety of types of molecules, or analytes that can give us some window into what the primary tumor looks like. These include, maybe whole cells in intact form, you know, circulating tumor cells —
Russ Altman: So these are the cells that have broken off —
Ash Alizadeh: Broken off and —
Russ Altman: — and they’re just sitting there in the blood?
Ash Alizadeh: That’s right so for blood cancers, that’s not so unusual, because they tend to circulate, but for solid tumors, we’ve known for some time that even in early stage tumors, some fraction of the cells get loose and circulate, and that’s, those are called circulating —
Russ Altman: So that’s remarkable, just to punctuate that. That means, there might be some of my breast cancer cells if I had breast cancer, in my circulating blood.
Ash Alizadeh: That’s right.
Russ Altman: So you could take it from my arm.
Ash Alizadeh: That’s right. Then the, that’s one class, the other class is forget the cellular portion of blood, let’s look in the juice that floats on top of the blood cells when you spin the blood, and that plasma or serum, in large, folks have focused on plasma as molecules in it, that don’t necessarily need to be in intact cells, they could’ve broken off, and one class of molecules that people have spent a lot of time on are called cell free DNA molecules.
It’s fascinating because these molecules were recognized by a couple of French scientists in the 1940’s before the Nobel Prize, before the structured DNA was even solved in that they recognized that these molecules were free and abundant, in cell free DNA, but not that abundant, it’s still a needle in a haystack problem, so if one were to take that DNA and look for things that tell you something special about some part of the body, you can find and detect and forego a biopsy, so at Stanford, the work of Steve Quake and others has been transformative for medicine for example —
Russ Altman: Now are we thinking about using this to detect the cancer in the first place, or to follow its progress as you treat or whatever?
Ash Alizadeh: So both of those are areas of active research. So, the analogy I was mentioning to, what Steve Quake has worked on is for figuring out whether pregnancy is associative with down syndrome, and in the past we used to use biochemical markers and ultrasound, and being able to look for that’s cause by an extra copy of a single chromosome, chromosome 21, but if you look for that in the blood of the mom, because by a few weeks of the pregnancy, a few percent of the DNA is coming from the fetus even though a few percent of the cells don’t circulate, this makes it very easy to noninvasively, without putting a needle through the uterine wall —
Russ Altman: The amniocentesis.
Ash Alizadeh: The amniocentesis — I get a look into this environment noninvasively, but that’s a disease or a condition I should say, where you have a whole chromosome and that you know what you’re looking for, cancer’s much more heterogeneous, and the mutations happen all over all the chromosomes, and you can’t take a single mutation and detect it, so the liquid biopsy ideas are to look for mutations in DNA and help it inform you about early diagnosis, but also what mutations might be there that could help you inform a therapy, and then also monitor response, is there disease remaining or not, or are there things evolving?
Russ Altman: This is The Future of Everything, I’m Russ Altman and we’re speaking about liquid biopsy and cancer diagnosis, so let me ask, one, I know, as you know I’m also a physician, one of the things that happens when we have these new capabilities is they allow us to look at diseases, in this case much earlier than we might normally see the disease, and that means we often don’t know what to do with the information.
Ash Alizadeh: Right.
Russ Altman: So now that I can detect a cancer that’s in the blood perhaps before it has any clinical symptoms and before the “normal way,” I’m using scare quotes, the “normal way” to diagnosis which is because of the onset of clinical symptoms or something, it becomes a little bit challenging to know what to do with this information. That actually leads me to the topic which is that there’s this immune system that there’s, I know there are theories that the immune system is actually doing some kind of surveillance, and maybe helping us with very early cancers in terms of recognizing, getting rid of them before we ever have problems. So pulling back a little bit, can you tell me a little bit, cause I also know this is another very hot area, about how our understanding of the immune system relates to cancer and new treatments for cancer?
Ash Alizadeh: Oh sure, so the last decade has been a remarkable time for setting the immune system, and its relationship to cancer, in fact, the most exciting drugs of the last decade involved the immune system, so instead of directly attacking the tumor cells with drugs that kill the cancer cells, you now have drugs that engage the immune system to say, “Hey, wake up.” and then the same drug working for many cancers has an effect in curing a substantial minority of patients with, who’d otherwise be deceased of their —
Russ Altman: And obviously the immune system needs a little help.
Ash Alizadeh: Right
Russ Altman: because it’s not doing it on its own.
Ash Alizadeh: That’s right, and this imbalance that happens, we’re still trying to understand all the rules of the system, what are the nuts and bolts that keep this system from doing its job the way that it was designed to. But we figured out a few of those and to basically take the brakes that are put on the immune system by cancer cells and say, “Hey this isn’t right, we can get in the middle of this with an antibody or something.”
Russ Altman: So they’re diabolical, I wanna highlight what you just said, the cancer has figured out ways to get the immune system to calm down, arguably inappropriately.
Ash Alizadeh: right
Russ Altman: Because it, there’s been pressure on the cancer to do that so it can grow and survive, so we need to stop, and you called them brakes, which is a great, I love that analogy, so we have to figure out how to get the foot off the break.
Ash Alizadeh: Exactly
Russ Altman: For the immune system.
Ash Alizadeh: Exactly, now how, I think once liquid biopsies become good enough to detect cancers at an early time, that might afford us opportunities to leverage immunity. I don’t think we are near that time in the next year or two, I think it’s an emerging area, there are lots of folks that have been working on this problem, to build tools that are sharp enough that you detect a significant fraction of early stage cancers. But, there are versions of these things that I think could work towards it for example, I don’t know if you’ve heard of a test called Cologuard, this is — you poop in the proverbial box instead of having a colonoscopy. It finds a significant fraction of colon cancers that would otherwise have been missed because a large fraction of healthy adults who are eligible for colonoscopies aren’t willing to have that.
Russ Altman: So perhaps not a liquid biopsy, but another kind of —
Ash Alizadeh: Yes, I guess it depends on what state your bowels are in but, yes.
Russ Altman: So this is exciting, what are the diseases that are looking like the most promising for these immune therapies, I’m sure there are people listening who themselves or their loved ones are struggling with cancer, which of the cancers where these immune based therapies are starting to appear, and what’s on the horizon?
Ash Alizadeh: Sure, the earliest was a disease called melanoma where chemotherapy and many other approaches had not been all that effective, and melanoma is the poster child for these kinds of therapies, lung cancer’s been the second.
Russ Altman: So you’re picking pretty bad cancers, I noticed.
Ash Alizadeh: Picking pretty bad cancer’s and seeing this result, but a range of other cancer types now, in fact these drugs are approved for half a dozen cancers broadly at various stages of the disease, but also in any cancer that has certain molecular features, if the mutations look a certain way.
Russ Altman: So this is happening now, and physicians in the community are aware of these drugs, and if you’re lucky enough to have a cancer that’s, well that’s a terrible thing to say, but if your cancer does happen to be and looks susceptible to these drugs, it’s out there now.
Ash Alizadeh: Absolutely.
Russ Altman: Very good.
Ash Alizadeh: Absolutely.
Russ Altman: Thank you for listening to The Future of Everything, I’m Russ Altman, if you missed any of this episode, listen anytime on demand with the SiriusXM app.