Episode 74Multiple Myeloma.wav
Karie Dozer [00:00:03] I'm Karie Dozer and this is TGen Talks. Scientists at TGen recently published the results of a 12-year study into multiple myeloma. A study that looked at more than 1,100 patients from four different countries. This comprehensive study collected patient data every three months and identified unique types of this blood cancer, which is treatable but has no cure. What's more, researchers identified a special subgroup of multiple myeloma patients whose disease fails to respond to more traditional therapies. By confirming that a patient is indeed part of this special subgroup. Doctors can save time and bypass certain treatments in favor of newer therapies, leading to longer survival rates and better outcomes for their patients. And our guest on this episode of T Jen Talks is Jonathan Keates. Thanks for taking the time to talk today.
Dr. Jonathan Keats [00:00:53] No problem. I hope you do.
Karie Dozer [00:00:55] What is the gist of your paper? What did you present?
Dr. Jonathan Keats [00:00:58] So this is the culmination of a study that's been ongoing here at TJ and for about 12 years, called the Multiple Myeloma Research Foundation Compass study, which really was set up because therapy had completely changed in this disease over the early part of the 2000. To really understand if patients that we thought used to do bad with our old therapies still do bad, or now have they been fixed with the new therapies? And then largely because the therapies have changed and technology has changed to really understand, is there just one type of multiple myeloma, or are there many types of multiple myeloma? And historically, we already knew there was more than one type. But this study is really tightly refined down that there are definitely different types of myeloma with different types of outcome.
Karie Dozer [00:01:41] It's never a simple answer. Let's back up a little bit and talk about what is multiple myeloma and how common is it.
Dr. Jonathan Keats [00:01:47] So it's still considered a rare cancer like it becomes more frequent as we age. But the overall things is generally, in any given year, five out of 100,000 people will get this. But really, when you're talking about friends and family, about one out of 180 people will be diagnosed with the disease during their life span, especially if they live in to become a grandparent.
Karie Dozer [00:02:07] Coming of age and what is it? What happens to a patient diagnosed with it?
Dr. Jonathan Keats [00:02:11] So this is a cancer of the cells that make antibodies in our body, so called plasma cells. So naturally we see an infection. For a lot of us Covid recently we made antibodies against Covid. Those plasma cells went to your bone marrow, and they sit in your bone marrow for the better part of your life, secreting antibody to fight off that infection, should you ever be exposed to it again. So, this is a cancer, those cells that generally a lot of the errors that caused the cancer happened when it first saw that antigen. We know now, most of myeloma started over 30 years before they were diagnosed. But they sit in the bone marrow and slowly grow, slowly accumulate other genetic changes until they become a disease that usually presents with people being very tired because they're anemic, getting infections. And this usually is because the disease causes your bone marrow to start to fail and not produce all your normal white blood cells or red blood cells. The other huge side effect is it causes severe osteoporosis. So, the other way a lot of patients get diagnosed is they just spontaneously broke a bone. You go into the E.R., they do an X-ray and go, okay, yeah, we got to get your femur reset. And you also need to talk to hematologist because you actually have a blood cancer.
Karie Dozer [00:03:18] What's the genetic risk? What role do genetics play into whether or not you're diagnosed?
Dr. Jonathan Keats [00:03:23] So right now we don't really have good genetic features to say who's at risk of getting it. Unlike say, breast cancer, we know a certain percentage are caused by hereditary factors. What we do know in the disease is that people of African descent get this disease about two times more than people that are of European descent, who get it two times more than people who are of Asian descent. So, there's definitely some ethnic bias in the incidence. And then also about 60% of the patients are male versus 40% are female. So, there is also a bit of a gender bias that we're still trying to understand. And it definitely is one of the few cancers that kind of universally around the world has this gender and also racial background incidence difference.
Karie Dozer [00:04:06] This was a big study. Classify for me how many patients and how it compares to other studies that have been done at TGen.
Dr. Jonathan Keats [00:04:13] Yeah. So, this was a study that when it's all said and done, involved 1143 patients, that were accrued over a four-year period from clinical sites in the United States, Canada, Spain and Italy, by scale, at TJ and this is probably about 2 to 3 times bigger than any other study we've done. Probably the best way to compare it is when we think of cancer. There's been a lot of government funded studies looking at different cancers. And in there the biggest study is breast cancer that's looked at just under 1200 patients. And the next biggest one is in the around 800. So, this is actually the second biggest cancer sequencing study historically in the world.
Karie Dozer [00:04:51] What's so hard about putting a study this large together? I mean, you're studying one disease that has a bunch of subtypes, but why is it so hard to get that many patients who have a similar diagnosis under one roof for a period of time.
Dr. Jonathan Keats [00:05:04] Yeah, again, a lot of it is caught is rare. The other one is just coordinating, getting all those samples submitted to a central place to be processed. One thing we do that makes a lot of the genetic studies in myeloma very easy from once it's in the lab, is we purify the tumor out so we can use an antibody, and it recognizes rare things that are in plasma cells. And we can pull them out of all the other cells that we sample from the bone marrow. So, when we do, genetic studies were generally looking at about 90% to 95% of the sample being pure tumor. When we do an average breast cancer study that we're lucky if it's 50%. So, it really has allowed us to do work that we can't do in a lot of other diseases. But that extra event of having to purify the tumor and getting enough cells, actually, there's a relatively high failure rate of doing that. So really, we actually brought into the study it was almost 1800 patients who were screened, but quite a few over 700 fell out because they didn't have enough tumor.
Karie Dozer [00:06:02] So what was the goal? What were the questions that you set out to answer?
Dr. Jonathan Keats [00:06:07] So the number one question that we were asked to answer is do different types of multiple myeloma exist? And if so, what is their relationship to response to therapy. Because we have a lot of different therapies. And also, what is their difference in clinical outcome? The second issue there was to really understand what genes are important in the disease, to really hone in on where therapeutic development should focus in the future. We have groups of patients who, on average, don't survive for more than two years. And we have other groups of patients who are 75% are alive at nine years. So, it really does vary on which therapies, or how they respond. What we found so far with this study is we couldn't really identify which therapies worked in different subsets uniquely. But definitely we can say which groups need better therapies and which groups are doing well with the therapies that we had in the early 2010 2015 range.
Karie Dozer [00:07:04] Within the scientific community. What's the headline? What are you most excited about having found, having proven so that the next stage of research can continue.
Dr. Jonathan Keats [00:07:14] For patients, the thing that we're really the most focused on is there had been a group of patients previously identified that were considered high risk, and we've re identified those. But there's a lot of debate within the field if we should use that as a moniker for patients, because we didn't know the genetic reason for why they were. When we look this is looking at it from an RNA standpoint, which we think is more of a phenotype. So in the community, there was a lot of arguments should be looking at phenotypes or hard cut. Yes. No genetic observations. And in that group of patients there was no historical hard cut. That's why patients look like this. And definitely one of the things we found in this study is we now know the genetic reasons why those patients are doing so poorly. Unfortunately, is not one event. It's a series of multiple different events that create the same phenotype. But that's really helped us identify that group of patients who are going to do poorly and definitely need to be put into different kind of clinical management situations.
Karie Dozer [00:08:12] When you say high risk, you mean high risk in terms of risk of failure of a particular treatment. I think most people listening from a nonscientific standpoint think of high risk as risk of contracting the disease. But there's an entirely different set of risks when you are diagnosed with a particular disease, and you bring with it your set of genetics.
Dr. Jonathan Keats [00:08:31] Yeah. And I think it's maybe the one that people would know best. So, like we think of breast cancer and you have stage one or stage two, stage three or stage four. We have similar stagings and they have a little bit of relationship to therapy. But historically in the field, we found genetics was the best way to really identify those and prioritize putting them on to new clinical trials so that we are trying to find something that worked in that patient population.
Karie Dozer [00:08:56] How soon do you hope that your findings turn into regular day to day care of somebody with multiple myeloma?
Dr. Jonathan Keats [00:09:04] So one of the observations we had was just purely looking at the DNA, like how many copies of different chromosomes the patients had. And we do a lot of those measurements today in the clinic. And an important thing that we found there was, twofold. One, identifying that group of patients who did really, really well. And now physicians will be able to look at their standard report they get and correlate it to our observation and say, like, hey, you're in this really good category. The other one that I think is important there for patients today is there was there's one group of patients that today's technology will identify that when a physician sees it, you sit in all our meetings, we say, hey, if you have this phenotype that's standard risk or actually almost good disease, good news, don't worry about it too much. But actually, if it had this extra feature, what we found is I was actually the one of the worst performing groups of patients we'd identified. So, it will help physicians not communicate like, hey, you have good risk disease, so let's maybe not do your transplant. We'll wait and watch. Now, if you have that, maybe they can have the conversation of I'm not so comfortable doing a wait and watch with this one because of this study. So, I think there are observations here that will translate really quickly. The other one from the Tien side, because so much of this we really discovered it's not this one thing that causes disease or causes you to have bad risk disease. It's a lot of random events in a small set of genes around the genome. On the one side, what we're doing is we're going to bring what is kind of the basic technology we use in the research here, which was whole genome sequencing into a formal clinical test. So, we'll be able to offer this kind of detailed information on patients from around the country.
Karie Dozer [00:10:41] What does it mean to have almost 1200 patients, 1800 who signed up and were willing to be available for this study and to stick with it, and every three months, see someone give that clinical information and take part in this in this research.
Dr. Jonathan Keats [00:10:56] Yeah, definitely. This couldn't have been done had patients not enrolled. The real important thing with this from an eligibility is we wanted people who had never received any therapy before, so they had to be newly diagnosed, and they had to actually start therapy within 45 days of enrolling, which, again, when a lot of patients, you're diagnosed with a new cancer that if you Google it, it still says really horrible thing. Yes. That's not their first concern of signing up into some observational study to help us understand the disease. So, if it wasn't for those people going through that, not none of this would have been possible. And again, you go back to this and those other studies and other cancers like this is a rare disease. And to make it one of the second biggest overall studies, it's transformed our field. Like you go to a meeting like our big hematology conference in December, there's usually 20 to 30 presentations that leverage this data set. So, like the field is building all of our observations is this is being one of those core things that justify every step the field takes forward.
Karie Dozer [00:11:58] Will you build on this study with a second study. Is there a chapter two.
Dr. Jonathan Keats [00:12:02] So we have an interest in kind of this was a study of really those patients at early at die early diagnosis and trying to follow them through, from my side, one that we're very interested in continuing of a similar scale is really looking at patients as they get near the end of their disease to really understand, because what we're seeing here is how patients change with time is what do those tumors look like that we can't deal with today. So, we have better ideas, because I think what we're starting to appreciate is what a tumor looks like when someone's diagnosed. The therapies we have today do a pretty good job. And the therapies that have been developed the last five years are even more impressive. But now understanding what a tumor looks like at the end will help us develop that next generation of therapies to really salvage patients in that situation.
Karie Dozer [00:12:50] What have I missed anything I failed to ask that you want to make sure people know about your findings or your research.
Dr. Jonathan Keats [00:12:57] One of the biggest ones, I think, from our side is that this isn't a monotone disease. Depending on how we looked at it, we said there was either 8 or 11 different types of the disease. And for some of those, we're now even appreciating that there's certain very specific drivers of that subtype of disease. So, coming from the gen perspective, we're always really interested in understanding different genetic driving events because that becomes a therapeutic target. And then from the auspices of where we like to where patient comes in, we're going to sequence them and find the drug on the shelf that works for that patient. Now having those identified events that they seem rare across a thousand patients. But when you say these is in 80% of this group of patients, that's 10% of all patients, also not becomes something that's a valid therapeutic target because now we understand it has core biology in that type of disease. When we look at something that's only in 8% of all patients, it's like, well, that's hard to justify. And most pharmaceutical companies don't want to invest in a rare disease in a rare subset. But when you can make the argument that that is a really beneficial target and the interest in developing against it becomes much more real, and it obviously leads to better outcomes for patients.
Karie Dozer [00:14:13] Thank you for taking the time. Obviously talking about it takes much less time than actually doing it. How do you feel when you wrap up something that takes this long?
Dr. Jonathan Keats [00:14:23] I usually tell people it's been like birthing an elephant. So, there's like, the joy that it's done, the sadness that it's done from the current workload. But really, there's over 400TB of data to mine through with this. So, like as we and others around the world dig into deeper and deeper layers, that you keep finding new things that let us understand what caused the disease, what caused a certain type of disease. And what's exciting now is seeing how some of these things are related to the new immunotherapies that we have of predicting who's going to respond, who's not going to respond, who are super responder should be. And like. From my side. We focus a lot on high-risk disease. But the thing I want to do the most is to be able identify that patient, go like, hey, if we give them that therapy, that's today FDA approved, we expect a cure in that person. That's really the ones that we want to highlight. And it's always sad when you realize you saw one of those patients in this cohort. And we have therapies that are approved today. Can we find a way to get that therapy to that patient? Because from all scientific rationale, they should melt that tumor and there should be no way for the tumor to get around it.
Karie Dozer [00:15:32] That's what we're all about. Jonathan Keates, thanks for taking the time to talk about it.
Dr. Jonathan Keats [00:15:32] Thank you.
Karie Dozer [00:15:32] For more on TGen’s research, go to TGen dot org slash news. The Translational Genomics Research Institute, part of city of Hope, is an Arizona based nonprofit biomedical research institution dedicated to conducting groundbreaking research with life changing results. You can find more of these podcasts at TGen dot org slash TGen Talks, Apple and Spotify and most podcast platforms. For TGen Talks, I’m Karie Dozer.
