WEBVTT - Measles: The Cancer Killer? 0:00:02.200 --> 0:00:04.280 I thought I knew what I needed to know about 0:00:04.360 --> 0:00:08.080 what happens when you get measles. You get a fever 0:00:08.360 --> 0:00:12.120 and a rash. Maybe you get very sick. If you're 0:00:12.160 --> 0:00:17.000 really unlucky, you die. But chances are you get measles, 0:00:17.040 --> 0:00:20.280 you get better, and that's the end of it as 0:00:20.320 --> 0:00:20.920 it happens. 0:00:21.120 --> 0:00:21.959 I was wrong. 0:00:22.600 --> 0:00:24.840 I did not know what I needed to know about measles, 0:00:24.960 --> 0:00:28.680 because a recent discovery has blown open our whole idea 0:00:29.080 --> 0:00:31.640 of what the measles virus does to our bodies. 0:00:32.000 --> 0:00:35.479 The world thought that measles was done being discovered, and 0:00:35.520 --> 0:00:40.680 then boom, all of a sudden, there's this new idea 0:00:40.960 --> 0:00:45.120 of something that really had massive, massive consequences on humans 0:00:45.120 --> 0:00:46.520 that we didn't even realize. 0:00:47.320 --> 0:00:51.160 I'm Jacob Goldstein and this is Incubation, a show about viruses. 0:00:51.600 --> 0:00:55.040 Today on the show, how measles attacks your immune system 0:00:55.600 --> 0:00:59.520 and how researchers are trying to use measles to cure cancer. 0:01:09.160 --> 0:01:11.360 My guest for the first half of today's show is 0:01:11.440 --> 0:01:17.160 Michael Minna. He's an epidemiologist slash immunologist slash physician, and 0:01:17.200 --> 0:01:20.200 he's kind of a measles superfan. He did a lot 0:01:20.200 --> 0:01:22.160 of work we'll talk about today while he was a 0:01:22.200 --> 0:01:26.160 professor at Harvard. He's now chief scientific officer at a 0:01:26.200 --> 0:01:30.080 company called Emed. We started by talking about a surprising 0:01:30.160 --> 0:01:33.080 thing that happened after the measles vaccine was introduced in 0:01:33.120 --> 0:01:36.520 the nineteen sixties. As more and more kids were vaccinated 0:01:36.560 --> 0:01:39.920 against measles, the rate at which kids were dying of 0:01:39.959 --> 0:01:44.480 infectious disease went down way more than anybody expected. It 0:01:44.520 --> 0:01:47.280 went down so much that it couldn't be explained by 0:01:47.319 --> 0:01:48.480 measles alone. 0:01:49.040 --> 0:01:54.440 After the vaccine was introduced, we saw market reductions in 0:01:54.560 --> 0:02:00.200 childhood mortality overall following the vaccine, which drove a a 0:02:00.200 --> 0:02:04.080 lot of questions. Why did that happen? Is it the 0:02:04.160 --> 0:02:09.200 vaccine actually acting directly to somehow prevent other infections, or 0:02:09.240 --> 0:02:10.600 is there something else at play? 0:02:11.120 --> 0:02:14.079 Even if zero people died of measles, Even if zero 0:02:14.280 --> 0:02:17.760 children died of measles, you wouldn't get that large of 0:02:17.800 --> 0:02:21.560 a reduction immortality, Right, some weird thing is going. 0:02:21.360 --> 0:02:23.040 On, that's exactly right. 0:02:23.160 --> 0:02:25.519 Weird good thing, weird usually. 0:02:25.320 --> 0:02:27.880 That's right, A very weird good thing was going on. 0:02:28.280 --> 0:02:31.600 So now we have this interesting kind of happy mystery 0:02:31.680 --> 0:02:35.000 in a way, Why are so few children dying of 0:02:35.000 --> 0:02:38.720 infectious disease after the rollout of the measles vaccine. What 0:02:38.800 --> 0:02:41.359 do you do to try and figure out what's going on? 0:02:41.840 --> 0:02:47.359 We said, well, maybe it's because measles had detrimental effects 0:02:47.440 --> 0:02:51.600 on somebody's immune memory that might be putting them at 0:02:51.720 --> 0:02:54.760 risk for other stuff, other infections, And so what we 0:02:54.800 --> 0:02:57.359 did was we said, well, if that's the case, then 0:02:57.360 --> 0:03:00.640 if we look at a lot of data, we map 0:03:01.080 --> 0:03:04.200 the numbers of cases of measles to the numbers of 0:03:04.320 --> 0:03:07.919 deaths from other things besides measles from year to year. 0:03:09.000 --> 0:03:13.760 And what we found was profoundly predictive. Is if you 0:03:13.840 --> 0:03:16.760 asked what were the number of measles cases in nineteen 0:03:16.840 --> 0:03:20.519 forty nine and what were the numbers of deaths from 0:03:20.600 --> 0:03:25.720 non measles infections from nineteen forty nine, nineteen fifty and 0:03:25.840 --> 0:03:29.640 nineteen fifty one. When you occrued all three years, it 0:03:29.680 --> 0:03:35.040 became extraordinarily predictive of how many children would die over 0:03:35.080 --> 0:03:38.840 the next three years of non measles infectious related deaths. 0:03:39.440 --> 0:03:41.640 So, just to be clear, what you found is that 0:03:41.920 --> 0:03:45.000 when there's a measle's outbreak in one year, the rate 0:03:45.040 --> 0:03:48.240 at which kids died from other infectious diseases went up 0:03:48.360 --> 0:03:49.440 in the next few years. 0:03:49.560 --> 0:03:50.560 That's exactly right. 0:03:50.680 --> 0:03:53.680 So you used in your answer just there this phrase 0:03:53.760 --> 0:03:57.280 that I just want to spend a moment on immune memory. 0:03:58.000 --> 0:03:59.360 What is immune memory. 0:04:00.040 --> 0:04:05.520 Immune memory is very similar to our regular memory. All 0:04:05.560 --> 0:04:08.680 of our body is memories, whether it be muscle memory, 0:04:08.880 --> 0:04:13.280 brain memory, or immune memory is stored in cells. The 0:04:13.320 --> 0:04:17.480 way that immune memory works is when you bump up 0:04:17.520 --> 0:04:21.440 against a pathogen, as let's say, a virus like measles 0:04:21.520 --> 0:04:26.560 or coronavirus, whatever it might be, your body actually sees it, 0:04:26.560 --> 0:04:30.719 it recognizes that virus, it learns from it, and it 0:04:30.760 --> 0:04:34.440 actually remembers it in B cells and T cells and 0:04:34.520 --> 0:04:39.159 plasma cells. And that's how our immune system works in 0:04:39.240 --> 0:04:42.359 terms of developing immune memory and utilizing it to combat 0:04:43.120 --> 0:04:45.080 infections that we see in the future. 0:04:45.800 --> 0:04:47.960 Is what you're finding that in some way measles is 0:04:48.040 --> 0:04:53.239 attacking the kid's immune memory. Is that the hypothesis that follows. 0:04:53.680 --> 0:04:58.240 That's exactly the hypothesis that follows. For example, if if 0:04:58.279 --> 0:05:02.760 a six year old got measles, then maybe that measles 0:05:02.800 --> 0:05:07.360 infection could destroy some of the immune memory the defenses 0:05:07.360 --> 0:05:11.560 that that child gained over the last six years and therefore, 0:05:11.839 --> 0:05:15.039 when they are seven or eight years old, are actually 0:05:15.160 --> 0:05:19.480 more vulnerable than they otherwise would have been to those 0:05:19.480 --> 0:05:21.680 infections that they gained the immunity to when they were 0:05:21.680 --> 0:05:22.240 two or three. 0:05:23.360 --> 0:05:27.000 So, okay, you have this hypothesis, how do you test it? 0:05:27.120 --> 0:05:29.280 How do you investigate what's really going on? 0:05:29.800 --> 0:05:35.359 There's a long, rich history of how to predict where 0:05:35.400 --> 0:05:38.039 measles is going to go next. It's actually famous for 0:05:38.120 --> 0:05:42.280 how predictive it is because it is so infectious that 0:05:42.320 --> 0:05:44.920 you just need to know how many people are vaccinated 0:05:44.960 --> 0:05:47.400 in a community, and if there's any measles anywhere in 0:05:47.440 --> 0:05:51.320 the region, you can expect that pretty soon at below 0:05:51.360 --> 0:05:53.520 certain levels, there's going to be an outbreak. 0:05:53.360 --> 0:05:55.560 Below certain levels of vaccination. 0:05:55.400 --> 0:05:57.760 That's right, and that's why measles is considered the canary 0:05:57.760 --> 0:06:01.839 and the coal mine for vaccine rates. Literally the thing 0:06:01.920 --> 0:06:04.719 that pops up on the radar when you say who's 0:06:04.920 --> 0:06:08.039 what communities are having trouble vaccinating their population, and boom, 0:06:08.080 --> 0:06:10.440 if you see measles, you know they're having trouble vaccinating 0:06:10.440 --> 0:06:14.240 their populations. And so what we can do is we 0:06:14.279 --> 0:06:19.479 can leverage everything we know about measles epidemiology to help 0:06:19.560 --> 0:06:24.800 identify where might outbreaks happen, And that's exactly what Rick 0:06:24.839 --> 0:06:28.640 de Swart and his team did. They are in the Netherlands. 0:06:28.640 --> 0:06:32.039 He's at Erasmus which is in Rotterdam, and so he 0:06:32.120 --> 0:06:34.719 was able to say, hey, right in our backyard, there's 0:06:34.760 --> 0:06:39.159 a community that for religious reasons, they chose not to 0:06:39.240 --> 0:06:42.600 vaccinate their children against measles. So they said, well, if 0:06:42.640 --> 0:06:44.159 you're not going to get a vaccine, would you be 0:06:44.240 --> 0:06:47.720 interested or willing to have us just draw a little 0:06:47.720 --> 0:06:51.720 sample of blood from your kids today and should measles 0:06:51.800 --> 0:06:53.840 catch up to them in the future, could we come 0:06:53.880 --> 0:06:55.800 back and draw another sample of blood. 0:06:56.720 --> 0:07:00.279 You have the before measles blood samples, and you have 0:07:00.400 --> 0:07:04.120 from the same children the after measles blood samples. We 0:07:04.200 --> 0:07:08.000 have everything ready to go. What happened there was a. 0:07:07.920 --> 0:07:11.560 Big outbreak, and almost immediately we start seeing that we 0:07:11.600 --> 0:07:15.560 can measure all of these antibodies in the blood samples. 0:07:15.840 --> 0:07:18.640 And then when we actually look at the blood samples 0:07:19.240 --> 0:07:21.840 from right before the kids got measles to those same 0:07:22.120 --> 0:07:25.720 kids blood samples that they collected after, we saw market 0:07:25.840 --> 0:07:30.440 reductions not just in a couple antibodies, but some kids 0:07:30.520 --> 0:07:34.920 lost eighty percent of all of the diversity of their 0:07:35.000 --> 0:07:39.280 antibodies that existed in that blood sample before they got measles, 0:07:39.560 --> 0:07:42.320 and we compared it. We said, well, maybe that's normal. 0:07:42.360 --> 0:07:45.480 So we looked at kids who had gotten vaccinated for measles. 0:07:45.800 --> 0:07:48.400 We look the kids who just had no infections, and 0:07:48.440 --> 0:07:51.520 what we saw was the average person with from any 0:07:51.560 --> 0:07:54.880 two time points, there'd be like five percent difference in 0:07:54.920 --> 0:07:58.800 their overall antibody repertoire. But the measles kids, the kids 0:07:58.840 --> 0:08:02.760 who got measles lost anywhere from twenty percent to eighty 0:08:02.840 --> 0:08:07.360 percent of their whole immunological memory pool. This is the 0:08:07.400 --> 0:08:12.679 whole lifetime of immune memory protection that they've spent years 0:08:12.720 --> 0:08:17.080 building up and building up, just poof wiped away because 0:08:17.120 --> 0:08:20.640 of this measles infection and these kids. What that means 0:08:20.720 --> 0:08:23.160 is now, across millions and millions of kids who were 0:08:23.800 --> 0:08:27.280 before the vaccines, almost every child got measles. And so 0:08:28.520 --> 0:08:31.280 at that scale, when you have so many people getting 0:08:31.320 --> 0:08:36.480 measles and this effect happening, which we call immunological amnesia, 0:08:36.559 --> 0:08:40.920 essentially they forgot their body, forgot because of the infection 0:08:41.920 --> 0:08:45.199 the immune memories that they formed before the infection. What 0:08:45.240 --> 0:08:47.439 that means is that you have all of these kids 0:08:47.440 --> 0:08:51.600 that are more susceptible to other infectious diseases. So most 0:08:52.000 --> 0:08:55.440 most kids would survive. But it turned out that of 0:08:55.480 --> 0:09:00.400 those kids who did die from other things, about half 0:09:00.480 --> 0:09:06.080 of those deaths could be attributed to the immune amnesia 0:09:06.120 --> 0:09:08.280 associated with measles. 0:09:08.720 --> 0:09:11.760 Is there something particularly insidious if that happens at a 0:09:11.800 --> 0:09:15.000 population level? If you imagine a group of people in 0:09:15.040 --> 0:09:18.079 the absence of a vaccine entirely, where it's like, not 0:09:18.120 --> 0:09:21.480 only is each kid more vulnerable, but because all the 0:09:21.520 --> 0:09:24.600 other kids are more vulnerable, everybody is more vulnerable. Is 0:09:24.640 --> 0:09:26.320 there something like that that happens? 0:09:26.480 --> 0:09:28.960 I am so happy you asked that question. 0:09:29.800 --> 0:09:30.400 You're welcome. 0:09:31.320 --> 0:09:36.040 So yes, it is. It's a much much harder thing 0:09:36.280 --> 0:09:36.960 to measure. 0:09:37.320 --> 0:09:39.160 I mean, it's sort of like the reverse of herd 0:09:39.160 --> 0:09:42.360 immunity in some weird broad spectrum way, right. 0:09:42.440 --> 0:09:45.400 So what's so interesting that you bring that up? Because 0:09:45.440 --> 0:09:48.560 before my measles work, I was working on influenza and 0:09:48.600 --> 0:09:52.520 its impacts on other bacterial infections, And during my PhD, 0:09:52.600 --> 0:09:58.400 I coined a term called generalized herd effects, and I 0:09:58.600 --> 0:10:02.319 explicitly didn't call it herd immuni because maybe it's not 0:10:02.360 --> 0:10:05.280 going to reduce things but maybe you could exacerbate things. 0:10:05.400 --> 0:10:08.559 Yeah, how about herd vulnerability? I want the opposite. What's 0:10:08.600 --> 0:10:09.960 the opposite of herding units? 0:10:10.280 --> 0:10:13.040 That's exactly. Herd vulnerability is a great term, and so 0:10:13.120 --> 0:10:15.200 the idea there as well. If you have a pathogen 0:10:15.720 --> 0:10:19.880 that's impacting your susceptibility to a lot of other pathogens, 0:10:20.280 --> 0:10:24.360 you could, you know, create a herd vulnerability because of 0:10:24.440 --> 0:10:28.880 infections of that initial pathogen. And on the contrary, if 0:10:28.920 --> 0:10:31.839 you figure out a vaccine against that initial pathogen, like 0:10:31.920 --> 0:10:37.480 the measles vaccine, you create massive benefits in getting rid 0:10:37.559 --> 0:10:39.559 of that herd vulnerability. 0:10:40.240 --> 0:10:43.680 So what's going on on a cellular level? 0:10:44.320 --> 0:10:48.720 As far as we know, measles is unique in its class. 0:10:49.000 --> 0:10:51.319 It's actually it's an amazing story. So if you give 0:10:51.360 --> 0:10:54.079 me forty seconds to describe it, I. 0:10:54.040 --> 0:10:56.960 Will, Oh, go, you got a minute if you need it. 0:10:57.800 --> 0:11:00.920 So, every virus has a receptor that it binds to 0:11:01.000 --> 0:11:03.880 and needs to latch onto on a cell. For measles, 0:11:04.040 --> 0:11:08.160 it's this molecule that's called CD one fifty, or it's 0:11:08.200 --> 0:11:13.800 called SLAM. SLAM stands for a signaling of Lymphocyte activation molecule, 0:11:14.160 --> 0:11:19.199 and it's when somebody gets a measles infection. The virus 0:11:19.440 --> 0:11:22.439 comes into somebody's lungs and we have these cool dendritic cells. 0:11:22.440 --> 0:11:24.480 And dendritic cells are like these cells of big arms, 0:11:24.520 --> 0:11:26.760 and they go out and reach pathogens that they that 0:11:26.800 --> 0:11:29.640 they know shouldn't be there, and they capture them and 0:11:29.640 --> 0:11:32.679 bring them in and then they shuttle them into the 0:11:32.800 --> 0:11:35.720 lymphoid system, which is where all of our immune cells are. 0:11:36.160 --> 0:11:39.040 And so normally what would happen is the dendritic cells 0:11:39.120 --> 0:11:43.319 would say, hey, immune system, you know, here's a pathogen, 0:11:43.720 --> 0:11:46.679 take it and develop immune memory against it, and so 0:11:46.720 --> 0:11:49.400 it literally hands it off to B cells and T cells. 0:11:50.200 --> 0:11:54.319 In this case, when the dendritic cell does exactly that 0:11:54.400 --> 0:11:58.200 same process, it hands off Measles virus to B cells 0:11:58.200 --> 0:12:00.840 and T cells. And this is a big mistake because 0:12:00.840 --> 0:12:03.520 now you have a virus that, instead of being handed 0:12:03.520 --> 0:12:05.280 off to a B and T cell and having that 0:12:05.320 --> 0:12:08.920 B and T cell you know, ingested and learn from it, 0:12:09.000 --> 0:12:12.840 the measles flips on its receptor utilization and grabs City 0:12:12.920 --> 0:12:17.320 one fifty or slam these molecules on the outside of 0:12:17.400 --> 0:12:20.120 the B cells and the T cells, and it actually 0:12:20.960 --> 0:12:22.800 invades them like a trojan horse. 0:12:23.160 --> 0:12:26.400 Aha. So It's like a like a trick, right, Like 0:12:26.800 --> 0:12:30.720 measles is there acting like a normal virus until it 0:12:30.760 --> 0:12:32.880 gets to the B cells in the T cells in 0:12:32.880 --> 0:12:35.760 the immune system. And normally the B cells in the 0:12:35.760 --> 0:12:39.240 T cells would destroy measles, would destroy the virus. But 0:12:39.360 --> 0:12:42.520 in that case, this doesn't happen, right, So what does happen? 0:12:43.000 --> 0:12:43.200 Now? 0:12:43.200 --> 0:12:46.720 It's in the cushy lymphoid system and it's just full 0:12:46.760 --> 0:12:50.880 of food and it just replicates like crazy inside the 0:12:50.880 --> 0:12:56.240 immune system, all the while sell by cell destroying the 0:12:56.400 --> 0:13:00.360 valuable immune memory is stored inside each of those that 0:13:00.400 --> 0:13:01.080 it's destroying. 0:13:01.559 --> 0:13:05.760 That is very compelling that it's like a virological horror 0:13:05.800 --> 0:13:07.560 movie inside your body. 0:13:08.200 --> 0:13:12.200 It absolutely is. And what we see when we see 0:13:12.200 --> 0:13:15.839 the prototypic measles rash, which is like dots all over 0:13:15.920 --> 0:13:19.600 a child's body, red dots, it is truly the tip 0:13:19.640 --> 0:13:22.680 of the iceberg in terms of where the damage is 0:13:22.720 --> 0:13:27.040 being done. The real damage inside a child is much 0:13:27.200 --> 0:13:30.160 much deeper and much much more profound in terms of, 0:13:30.559 --> 0:13:34.800 you know, destroying a huge, huge population of very important 0:13:34.840 --> 0:13:36.400 cells inside of our body. 0:13:37.200 --> 0:13:41.280 So if you sort of step back and think about 0:13:41.320 --> 0:13:44.960 this idea that measles not only gives you measles but 0:13:45.080 --> 0:13:49.439 makes you vulnerable to lots of other infectious diseases. Does 0:13:49.480 --> 0:13:52.240 it make you think differently about virus? Is about the 0:13:52.280 --> 0:13:54.240 immune system? Like where do you land? 0:13:54.920 --> 0:14:01.560 Measles brings together for me mathematics, biology, ecology and evolution 0:14:02.520 --> 0:14:10.440 and vaccinology, and I love bringing those pieces together, and 0:14:10.480 --> 0:14:14.120 it gives you a very deep appreciation for the delicate 0:14:14.160 --> 0:14:20.280 balance we have between infectious diseases, immunity, cancer, and autoimmune disease, 0:14:20.560 --> 0:14:24.640 and how those all interplay with each other. You know, 0:14:24.840 --> 0:14:28.320 the world thought that measles was done being discovered, and 0:14:28.360 --> 0:14:34.000 then boom, all of a sudden, there's this new idea 0:14:34.280 --> 0:14:38.680 of something that really had massive, massive consequences on humans 0:14:38.680 --> 0:14:42.160 that we didn't even realize. And so it drives this 0:14:42.680 --> 0:14:46.560 renewed excitement around measles vaccination and the importance of it. 0:14:46.560 --> 0:14:49.760 It's not just a cool finding. It hopefully helps us 0:14:50.040 --> 0:14:53.760 move further and further towards eradication of the virus altogether. 0:14:56.720 --> 0:14:58.440 It was great to talk with you. Thank you so 0:14:58.520 --> 0:14:59.160 much for your time. 0:15:00.000 --> 0:15:00.600 Thank you so much. 0:15:00.720 --> 0:15:03.960 It was a lot of fun. Michael Minna is Chief 0:15:04.000 --> 0:15:07.880 Science Officer at EMED Digital Healthcare. He was previously a 0:15:07.920 --> 0:15:11.360 professor at the Harvard School of Public Health. When we 0:15:11.400 --> 0:15:25.920 come back using measles to fight cancer, going back all 0:15:25.960 --> 0:15:29.400 the way to the eighteen hundreds, which was before anybody 0:15:29.520 --> 0:15:32.640 even knew what a virus really was, there have been 0:15:32.760 --> 0:15:36.400 occasional reports of cancer patients who get some kind of 0:15:36.480 --> 0:15:41.200 viral infection and then go into remission from cancer, and 0:15:41.320 --> 0:15:44.760 at a certain level this makes sense. Viruses are highly 0:15:44.800 --> 0:15:48.920 evolved to enter and destroy cells. Normally we think of 0:15:48.920 --> 0:15:51.280 this as a bad thing, but if a virus is 0:15:51.440 --> 0:15:55.000 entering and destroying cancer cells, this inter a cell and 0:15:55.040 --> 0:15:58.880 destroy it property might be a very good thing. By 0:15:58.960 --> 0:16:02.880 the nineteen fifties, researchers were actively trying to figure out 0:16:03.160 --> 0:16:07.080 how to use viruses to treat cancer. But then new 0:16:07.160 --> 0:16:12.120 kinds of cancer drugs were discovered, basically chemotherapy, and researchers 0:16:12.120 --> 0:16:16.360 got less interested in that virus cancer link. My guest 0:16:16.360 --> 0:16:19.400 for this half of the show is Stephen Russell. Stephen 0:16:19.480 --> 0:16:23.280 has spent his career trying to use viruses to cure cancer, 0:16:23.680 --> 0:16:26.440 and as you'll hear, he and other researchers in the 0:16:26.440 --> 0:16:30.240 field have made real progress. When Stephen was starting his 0:16:30.280 --> 0:16:33.360 career in the nineteen eighties, he was interested in using 0:16:33.480 --> 0:16:37.640 retroviruses as possible cancer treatments. Then he told me he 0:16:37.760 --> 0:16:39.360 turned his attention to measles. 0:16:39.880 --> 0:16:42.080 Yeah, well, measles became the next love. 0:16:42.440 --> 0:16:45.560 You fell in love with measles? Yeah, of course, why'd 0:16:45.600 --> 0:16:46.920 you fall in love with measles? 0:16:47.720 --> 0:16:50.880 Well? All viruses are quite beautiful, I have to say, 0:16:50.920 --> 0:16:56.320 and the life cycles are extraordinarily elegant. But measles I 0:16:56.400 --> 0:17:00.040 could do things with. I knew that there was a 0:17:00.120 --> 0:17:04.240 very remarkable case of a boy with a retro orbital 0:17:04.480 --> 0:17:08.119 Burkitt lymphoma, a very aggressive lymphoma that was sort of 0:17:08.200 --> 0:17:11.760 bulging his eye out, And he went to a clinic 0:17:11.800 --> 0:17:13.919 and was told, well, come back in a couple of 0:17:13.920 --> 0:17:17.280 weeks and we'll start the therapy. And he came back 0:17:17.320 --> 0:17:20.920 in a couple of weeks and the tumor had just resolved. 0:17:21.320 --> 0:17:25.760 But in the meantime he'd had a severe measles infection. Huh, 0:17:25.800 --> 0:17:28.560 And so it looked like it was pretty certain that 0:17:28.600 --> 0:17:31.520 the measles infection had driven this response. 0:17:31.600 --> 0:17:36.520 That he had Burko lymphoma also caused by a virus. Right, 0:17:36.600 --> 0:17:39.359 the first tumor we knew was caused by a virus 0:17:39.359 --> 0:17:42.359 Epstein by yeah, so go on, I apologize. 0:17:42.720 --> 0:17:46.720 So anyway, I looking at measles, it seemed to tick 0:17:46.760 --> 0:17:49.520 a lot of boxes. But there was this whole history 0:17:49.560 --> 0:17:53.119 of the development of a vaccine strain of measles, and 0:17:53.200 --> 0:17:57.359 measles had been the vaccine had been created by taking 0:17:57.400 --> 0:18:01.520 a virus from the throat of a patient with measles. 0:18:02.160 --> 0:18:04.240 He was an eleven year old boy at the time, 0:18:04.359 --> 0:18:08.560 David Edmonstone in nineteen fifty four, and then growing that 0:18:08.720 --> 0:18:13.200 virus on cancer cells in tissue culture, and the virus 0:18:13.240 --> 0:18:18.199 had quired the ability to propagate efficiently in cancer cells, 0:18:18.240 --> 0:18:21.200 but it lost the ability to cause measles. 0:18:21.440 --> 0:18:24.520 And wait, I just just to be clear, this was 0:18:24.600 --> 0:18:27.280 just they weren't trying when they were doing this to 0:18:27.320 --> 0:18:31.960 fight cancer. They were just trying to develop a measles vaccine. 0:18:31.960 --> 0:18:34.400 They were just saying, we're going to grow this measles 0:18:34.720 --> 0:18:37.679 in culture over time and make it be attenuator, make 0:18:37.720 --> 0:18:40.600 it be weaker. And it adapted in such a way 0:18:40.640 --> 0:18:43.879 that it preferred to infect tumor cells and not to 0:18:44.000 --> 0:18:45.200 infect non tumor. 0:18:45.040 --> 0:18:48.200 Cells because of the way they adapted it. Because remember 0:18:48.240 --> 0:18:51.679 that the cells that they were growing in the lab 0:18:51.840 --> 0:18:54.560 that they could put the measles virus on were basically 0:18:54.600 --> 0:18:55.440 cancer cells. 0:18:55.800 --> 0:18:58.080 And is that just because those are easy cells to grow? 0:18:58.119 --> 0:18:59.400 Because they liked to propagate. 0:18:59.520 --> 0:19:03.680 Yeah, yeah, it's very, very difficult to grow non cancerous cells. Yeah. 0:19:03.880 --> 0:19:06.200 It's like the problem with cancer, right, it just loves 0:19:06.240 --> 0:19:07.680 to divide. 0:19:07.840 --> 0:19:12.040 Yeah. Yeah. So they put this virus on the cells 0:19:12.080 --> 0:19:16.520 in culture, and the virus had actually adapted and it 0:19:16.560 --> 0:19:21.680 had learned to use a receptor that is more abundant 0:19:21.760 --> 0:19:25.040 on cancer cells than on normal cells, and it was 0:19:25.200 --> 0:19:28.680 losing all sorts of things that it needed in order 0:19:28.720 --> 0:19:32.280 to cause disease because it didn't need them to be 0:19:32.400 --> 0:19:36.959 able to propagate the cancer cells. So it spontaneously attenuated 0:19:37.000 --> 0:19:40.800 through a lot of mutations that arose in the viral genome. 0:19:41.600 --> 0:19:43.960 And so there it was and had been given to 0:19:44.040 --> 0:19:49.160 billions of people, and it looked like it was fairly 0:19:49.320 --> 0:19:54.600 well adapted to test in human studies against cancer. 0:19:55.760 --> 0:19:59.040 The measles virus used in the vaccine didn't make people sick, 0:19:59.280 --> 0:20:03.159 and it tended to attack cancer cells. So Stephen started 0:20:03.200 --> 0:20:05.959 using that form of the virus in studies to see 0:20:06.000 --> 0:20:09.879 if measles could treat cancer. Eventually, he landed on a 0:20:09.960 --> 0:20:13.520 kind of cancer called multiple myeloma that can take hold 0:20:13.560 --> 0:20:16.800 in the bone marrow and suppress the immune system. And 0:20:16.960 --> 0:20:21.080 there was one multiple myeloma patient in particular who had 0:20:21.080 --> 0:20:24.440 a huge effect on how Stephen thought about using measles 0:20:24.440 --> 0:20:27.920 to fight cancer. The patient's name was Stacy. 0:20:27.720 --> 0:20:33.560 Rholtz, So Stacy. She had multiple myeloma. She had been 0:20:34.359 --> 0:20:39.280 on treatment for ten years, on and off, but probably 0:20:39.320 --> 0:20:42.200 more on and off treatment for the first ten years 0:20:42.240 --> 0:20:46.040 of her diagnosis, because every time she stopped the treatment, 0:20:46.800 --> 0:20:49.480 or even if she continued on it, the disease would 0:20:49.480 --> 0:20:52.920 come back, and then she needs switch to something else. 0:20:53.480 --> 0:20:56.119 She had a large tumor on her forehead that was 0:20:56.200 --> 0:21:01.080 destroying the underlying bone and compressing her brain. She had 0:21:01.400 --> 0:21:04.960 four other solid tumors, and then her bone marrow was 0:21:05.040 --> 0:21:09.439 diffusely infiltrated with myeloma and it was moving fast, and 0:21:09.520 --> 0:21:12.240 she was out of treatment options at the time. I mean, 0:21:12.240 --> 0:21:12.840 there was nothing. 0:21:12.880 --> 0:21:14.800 She was going to die soon. 0:21:14.920 --> 0:21:18.400 She was going to die, yeah, and she had three 0:21:18.520 --> 0:21:22.359 children still at school and everything to play for. She 0:21:22.440 --> 0:21:25.760 was fifty years old at the time. We'd moved up 0:21:25.840 --> 0:21:30.040 through every dose level that FDA had negotiated with us, 0:21:30.080 --> 0:21:33.480 based on a starting dose level of a million, we'd 0:21:33.520 --> 0:21:36.960 gone up to just tenfold short of a billion. 0:21:37.440 --> 0:21:39.800 Like, how much did she get compared to how much 0:21:39.800 --> 0:21:41.439 somebody gets when they get the measles vaxing. 0:21:41.800 --> 0:21:45.280 It's about ten million doses of vaccine. 0:21:44.920 --> 0:21:48.040 Okay for this one person, So she's getting quite a lot. 0:21:48.560 --> 0:21:49.800 And what happens. 0:21:50.320 --> 0:21:55.280 Well as with other patients, she had a reaction to 0:21:55.480 --> 0:21:59.359 the infusion of virus. So she got the virus infused. 0:21:59.440 --> 0:22:03.640 She felt fine for a couple of hours, and then 0:22:03.840 --> 0:22:08.160 she started shivering and shaking and her temperature rose and 0:22:08.240 --> 0:22:11.920 she felt pretty unwell overnight, but by the following morning 0:22:12.000 --> 0:22:13.119 it had settled down. 0:22:13.359 --> 0:22:16.600 And is that essentially like a response to a massive infection. 0:22:16.840 --> 0:22:18.680 She's essentially has this massive infection. 0:22:19.400 --> 0:22:24.439 Yes, it's similar to that, although it wasn't causing measles 0:22:24.480 --> 0:22:27.720 in her so it was it was more the body 0:22:27.800 --> 0:22:31.439 reacting to the foreign stuff in the blood and a 0:22:31.560 --> 0:22:35.399 very kind of rapid reaction. That settled down and then 0:22:35.840 --> 0:22:40.720 she left hospital, went home and after a few days 0:22:41.440 --> 0:22:46.280 she started noticing that the tumor on her forehead she 0:22:46.400 --> 0:22:51.480 and her family had named it Evan, and this tumor Evan, 0:22:51.640 --> 0:22:56.280 started to shrink and actually melted away. And you know, 0:22:56.359 --> 0:23:04.000 we conducted thorough evaluates on her intervals thereafter and we 0:23:04.000 --> 0:23:07.000 were staggered to see that she went into a complete 0:23:07.280 --> 0:23:12.360 disease remission. She felt fantastic. You know. We thought at 0:23:12.400 --> 0:23:14.960 the time, Okay, we've got it. This is the way 0:23:15.000 --> 0:23:19.760 to cure multiple myeloma. And so we gave it to 0:23:19.800 --> 0:23:23.439 a lot of other multiple myeloma patients and it didn't 0:23:23.440 --> 0:23:27.480 work nearly so well. There were some partial responses, but 0:23:27.560 --> 0:23:31.479 there was really nothing as dramatic as Stacy. So we 0:23:31.600 --> 0:23:36.240 studied Stacy pretty intensively to try and understand what was 0:23:36.320 --> 0:23:40.399 special about her because that would be the key to 0:23:40.720 --> 0:23:43.440 the success of virotherapy. I mean, what we knew from 0:23:43.480 --> 0:23:46.920 Stacy as Wow, this can actually happen. You can give 0:23:46.960 --> 0:23:52.359 a virus systemically nothing else, and you can get a 0:23:52.440 --> 0:23:57.440 dramatic resolution of tumor at all sites. So the studies 0:23:57.480 --> 0:24:00.040 that we did on Stacy showed that number one, she 0:24:00.119 --> 0:24:05.920 had no anti measles antibody detectable. She had, however, been 0:24:06.040 --> 0:24:10.119 vaccinated as a child and then she had lost her 0:24:10.160 --> 0:24:15.080 immunity and she'd been revaccinated after her first stem cell transplant. 0:24:15.840 --> 0:24:19.760 The immunity had come back, and she'd lost it again 0:24:20.119 --> 0:24:23.880 after the second stem cell transplant. Huh, So she had 0:24:23.920 --> 0:24:27.680 no antibodies to block the virus from getting to the target. 0:24:27.920 --> 0:24:31.679 So basically her immune system was the same as the 0:24:31.680 --> 0:24:34.360