Genes that drive myeloma growth and why new discoveries of myeloma’s complexities are hopeful with Dr. Jens Lohr, MD of The Broad Institute and Dana Farber Cancer Institute

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Originally posted on mPatient Myeloma Radio

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Dr. Jens Lohr, MD
Broad Institute and Dana Farber Cancer Institute

Interview date: February 28, 2014

Summary

Dr. Jens Lohr describes the recent discovery published in Cancer Cell that shows the genetic complexity of my multiple myeloma. While other cancers may have all of the same types of cancer cells presented, multiple myeloma is a mix of different cancer cell types, even in the same patient. He shares his recent work with the BROAD Institute to determine why myeloma is so complicated, why it returns and why it is so aggressive when it does return. He describes the three driver myeloma genes that promote growth and how he tested a BRAF inhibitor to target one of these genes. In the study they found that the inhibitor was effective but that depending on how much of that gene mutation a patient had, the inhibitor had the possibility of actually making other driver myeloma genes grow. He is optimistic that this gives us more information about how to treat myeloma and uses an example of how a BRAF inhibitor and a MEK inihibitor were combined to help overcome situations like this. He also shares that other approaches can be used to kill myeloma cells without regard to the genetics of the myeloma cell. He explained his use of both whole genome and whole exome sequencing and how it was used to come to this study’s important conclusions. He gives a preview of the future where this type of sequencing can be done from blood instead of bone marrow samples (thank you!). His conclusions support the continued use of combination therapies to target the various types of subclones (or myeloma types) until we can learn in greater detail how to profile patients’ myeloma more specifically.

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Full Transcript
Jenny: Welcome to today’s episode of mPatient myeloma Radio, a show that connects patients with myeloma researchers.

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We’re keeping a calendar of all myeloma events, a directory of myeloma specialists, the latest news, and links to all the myeloma news sources, highlighting myeloma clinical trials and helping you find patient support groups.

Now we are very privileged today to have with us Dr. Jens Lohr of the Broad Institute and Dana-Farber Cancer Institute.

Welcome, Dr. Lohr, and thank you for joining us.

Dr. Lohr: Thank you very much for having me.

Jenny: Well, let me give an introduction for you so people have a little bit of background.

Dr. Lohr is a physician-scientist who is board-certified in internal medicine and medical oncology. He obtained his medical degree and PhD from Ruprecht-Karls University in Heidelberg, Germany, followed by his postdoctoral research training at UCSF in California. After his residency in internal medicine at the University of California San Francisco, he completed his scholarship in the combined Dana-Farber/Partners Cancer Care Hematology/Oncology Fellowship Program in Boston.

As an instructor in medicine, Dr. Lohr provides care to patients with blood cancers at Dana-Farber and he’s leading a research effort on the genomics of myeloma together with Dr. Todd Golub at Eli and Edythe L. Broad Institute of Harvard and MIT. This effort is focusing on the genetic heterogeneity of multiple myeloma which we’ll talk about today, and this is supported by the Multiple Myeloma Research Foundation and the Multiple Myeloma Research Consortium.

Welcome, Dr. Lohr.

Dr. Lohr: Thank you very much.

Jenny: We’re very fortunate to have you. Maybe you would like to start with giving us an overview of the work of the Broad Institute and what your work focuses on.

Dr. Lohr: Yes, definitely. The Broad Institute is quite a unique place. So it’s a scientific institute which, as you mentioned, is affiliated with the MIT in Harvard. I would say the general difference of the Broad Institute when you compare it to other academic institutions is that it takes on scientific challenges that are sometimes difficult to address in the academic setting.

How do we do this? Essentially, the scientific projects are typically very multi-disciplinary and extremely collaborative. Most of the projects, for example, the project that we are going to talk about today, use modern technology that for an individual lab would be probably sometimes too expensive to afford. There are two major structural umbrellas for those scientific efforts and one of them are programs and I am, for example, part of the Cancer Program that is led by Dr. Todd Golub and then there are platforms.

For example, there is a number of other disease-focused programs like the cancer program and there are a lot of platforms which provide technology that otherwise couldn’t be used because it’s simply too expensive. I think the myeloma project that we have conducted is a prime example of that. The underlying rationale for this project was to find out which genetic defects really cause and drive multiple myeloma. We wanted to do this as comprehensively as possible and because we need to know what’s the problem before we can fix something, we wanted to comprehensively get the DNA sequence of, in the end, samples from more than 200 myeloma patients.

What we did is basically together with the MMRC and the MMRF, we got that samples from more than 200 patients and subjected them to whole genome sequencing to whole exome sequencing, and we also did copy number arrays on them, and then integrated all of this information and tried to find out what really causes and what really drives myeloma. In order to do this, we have worked together with one of the platforms, the Genome Analysis Platform and the Genome Platform, which basically provided us with a power to sequence all those samples. And then the Genome Analysis Platform, which has a very strong computational focus, provided us with the resources to process this huge amount of data. And then in the wet lab we performed experiments to basically test hypothesis that we generated from a data that we got from the sequencing.

I think that this project is really the blueprint for many other projects that are conducted in a similar way at the Broad. What you do is you bring together a group of people and then you use the best resources of those platforms and of those individual disease groups to tackle a certain problem. Just to mention what other platforms and what other disease-focused programs there are at the Broad, for example, there is a therapeutics program where we manufacture our own drugs that then can be tested for a certain question. So it’s very similar to what pharmaceutical companies do, but we don’t have any pressure to basically ask a specific question, but we can actually go in whatever direction our research takes us.

Then there’s a number of different disease centers. For example, there is the Stanley Center for Psychiatric Research and there’s an Infectious Disease Program. So that’s essentially the basic idea of the Broad Institute is to ask scientific questions that cannot be addressed in a traditional academic lab. And in the cancer program in particular, we’re always interested in interesting biology but our main pursuit is really identifying new treatments for patients.

Jenny: Wow, that’s a lot of work. When you say it’s too expensive to do something like this in an academic center, where does the Broad Institute get their funding? I know the MMRF was very instrumental in helping to fund this project that we’re going to talk about today, and I want to commend them for the amazing work that they do. But overall, in the Broad Institute for programs like these, where does the funding come from? Then how could we maybe replicate what you’re doing?

Dr. Lohr: Actually, as you mentioned, for this particular program, that was actually the MMRF. That has been instrumental. So the MMRF provided all the funding for the study. The MMRC which is the consortium of many myeloma centers, they provided the samples for the study. So none of that would have been possible without that.

That, again, is also the blueprint for many of the other projects. There is a lot of NIH-based research going on but for a project of this scale, we’re actually very dependent either on philanthropic money or money from foundations who basically want to make a project like this happen. I would say it’s a bit mixture of money from foundations and philanthropic money but also NIH-funded research. For those kinds of research of that scale, I think the philanthropic money and the money from disease foundations is the most important actually.

Jenny: All right, great. We’re very appreciative for all the MMRF does and for the people who support them. Let’s talk a little bit about the goal of this study because this was — I didn’t mention yet — but this was research that was just published in Cancer Cell. I saw it really everywhere that it was a really important discovery.

We’ve been talking a lot on the series about personalized medicine and getting really excited about potentially being able to treat not necessarily even like a localized cancer, like a liver cancer, or a myeloma cancer in the blood, but being able to target genetically. That’s an exciting promise. So can you tell us what your overall objective of treating myeloma in a gene-specific way was for the study or what you were trying to determine?

Dr. Lohr: Yeah, absolutely. I’m sure you’ve heard many times on your program that traditional chemotherapy and you know for yourself that traditional chemotherapy is very non-specific in terms of treatment. So what it does most of the time is really that cells are inhibited or killed based on the fact that they divide faster than normal cells. And as you can imagine, that’s a very non-specific way of killing or inhibiting tumor or myeloma cells because there’s other cells in the body which also divide very fast. As an example, hair follicles, intestines, blood cells and so on. So if, basically, this is your only way of achieving of specificity, you will also get a lot of side effects because you are also hitting the tissues that divide fast in the body naturally.

The promise of targeted therapy is that you know exactly the vulnerability of a particular cell. If one tumor cell or one myeloma cell has a specific mutation, you know for a fact that that mutation is not in any of the normal cells. If there is a way to target this particular mutation, one would expect that this is a favor that that results in a very favorable side effect profile. So you’d expect in principle that when you hit this particular mutation, you only hit the myeloma cells but you do not hit any of the normal cells. That is the underlying principle so that you get less toxicity when you have a targeted therapy.

The other conceptual advantage of highly specific therapy is that because it is so specific, you may also be able to administer a much higher dose and that may make the therapy more efficacious. All of that always obviously has to be proven in a clinical trial, but the concept of highly targeted therapy is that you have less side effects and greater efficacy.

Jenny: Let’s talk about maybe for a minute where you started with the data. Where did you find the data and what patient samples were you using? Start with where you began.

Dr. Lohr: Essentially, the general idea of the study was to really provide a resource to researchers about what’s going on in myeloma. We want it to be as comprehensive as possible, so we wanted to identify the genetic basis of what drives myeloma. By drive, I mean, first of all, what initiates myeloma so why do you get it in the first place? Then, second, why is it aggressive and why does it become more aggressive over time? Then also what is the genetic basis for drug resistance? Why does it happen that when you give a drug, at some point, suddenly the drug doesn’t work anymore.

Those were all the underlying questions. As I mentioned earlier, before you can tackle a problem, before you fix it, you need to identify the problem. We wanted to get as many patient samples as possible and just define what’s broken. So the MMRC actually has collected over many years many samples for purposes like this. We basically teamed up with them and said, “Okay. Can we actually take those samples and can we define as comprehensively as possible genetically what is the effect in myeloma cells?”

So we did whole genome sequencing. We did whole exome sequencing. We also did copy number studies and then our partners at TGen in Phoenix, they also did RNA sequencing. We tried to be really comprehensive about finding out what’s broken in the myeloma cells and then provide a resource to the community about those defects.

Jenny: Can I ask you a question? Can you explain the difference between whole genome sequencing and whole exome sequencing and the different types? Because we’ve been talking a lot about different testing and I’ve been really encouraging patients to have tests like these run. Well, maybe not the whole genome sequencing because that’s only happening in clinical trials but knowing as much about their myeloma biology as they possibly can.

Dr. Lohr: Yes, absolutely. The difference between the whole genome and whole exome sequencing is actually that the whole genome is present in each of our cells which is basically one very long DNA strand. It’s basically partitioned in certain chromosomes, but the code is essentially 3 billion what we call bases long. So it’s a very simple code. It only essentially consists of four letters: A, C, T, and G but there are 3 billion of them. You can essentially just read this as series of A’s, C’s, T’s, and G’s.

If you want to identify the entire genome, then you’ll have to read all those 3 billion base pairs. But it turns out that we only have quite a limited number of genes. This is about only 2% of them. When you want to sequence only all genes, there is a trick that you can use to pull out only the genes and then you’re down to 30 million of those coding base pairs.

The difference is between sequencing the entire genome and only the genome that code for genes. That is a lot faster. It’s a lot cheaper. You can also get information that is deeper in certain ways. In general, there is nothing that you couldn’t do with whole genome sequencing as well but it comes down to a price issue. Whole genome sequencing because as I have said, more than twenty times more sequencing data, it’s also much more expensive as you can imagine.

From a clinical standpoint, I can’t tell you anything about the pricing but from a research standpoint, when we sequence a sample just to give you a ballpark idea, sequencing an entire exome is less than a thousand dollars and sequencing an entire genome these days is less than $10,000. Obviously, those are not then certified tests that you can use like this in the clinic because there goes more into this. From a research perspective, that’s about the difference.

Jenny: Will this whole exome test be available at some point in the clinic?

Dr. Lohr: Yes. It’s actually sold at the Dana Farber and also at the Broad and I believe also at the Mass General Hospital, they have basically exactly that is being instituted right now to make this clinically available. That is basically just being started but that, I think, within two years’ time or so, that will be offered routinely in a clear, certified way so that you can actually get — not the genome because that I think is still way too expensive but that whole exome sequencing will be performed up front as soon as you step foot into the clinic.

Jenny: Do you believe it gives you everything you would need to know?

Dr. Lohr: That’s the question. There’s never everything that we need to know. I think it will give us a great deal, but I think there’s also going to be a lag period between basically identifying lots of mutations and then knowing what to do with them because once you have identified certain mutations and you see that mutations occur in a lot of different patients, then it’s actually a big step to then find a therapy against it.

So you will have to first functionally find out what those genes do. Is that a mutation that is just a passenger or is that a mutation that actually drives the myeloma? That still will be nitty-gritty work in the wet lab. In finding all about it, you have to see in cell lines and then in mice what those mutations do. Once you know that a mutation actually plays a functional role and that it drives myeloma, then as a next step, then you have to find a treatment for it. I think getting the genetic information, that will happen routinely in the clinic probably within the next two years, maybe even within a year at major centers but knowing what exactly to do with this information, I think this will take a much longer time.

Jenny: I have a question. Is this data that was provided by the MMRC part of the CoMMpass study?

Dr. Lohr: No, it’s not.

Jenny: Oh, it’s separate.

Dr. Lohr: That’s separate, yes. The CoMMpass study is led by TGen as I was pointing out in Phoenix. That is a prospective study. So this is exactly what you mentioned so that when a patient starts his treatment that he gets the genomic information performed before he starts the treatment. Then at the treatment — I don’t know exactly how many time points — I think it’s actually multiple times point but at least it’s one other time points after the patient starts treatment then you perform the same test again. And then you see actually how the genomics change in the patients.

Do certain mutations go away with treatment? Do you see other mutations that suddenly arise that haven’t been there before? Those are all questions that can be answered in a prospective way. I think the goal of the CoMMpass study is somewhere around a thousand patients. Because it’s all prospective and because we get the genomic information before and after treatment, I think we will learn a great deal from this.

Jenny: Well, I advocate every patient whether they’re in a study, which would be a good idea, or not is to know these biomarkers because once you start treatment, that information is lost. I think that contains exceptionally valuable information.

Dr. Lohr: Yeah, I agree. It’s definitely — even though we don’t know yet what to do with most of those mutations, some mutations with which we do already know, it will certainly gives us information about which mutations are the most valuable ones that we should pursue. Because as you can imagine, for the ones that are really worth pursuing, there’s also a lot of noise. We’ll get a lot of what we call passenger mutations which they really occur in cells randomly, which really occur in normal cells as well but they don’t really drive the myeloma. They are basically the innocent bystanders and we see them, but they introduce a lot of noise. I think the more data we have — and particularly if you have data before and after treatment, that will actually help to define which mutations are really the true drivers, which mutations are the ones that are the most worthwhile therapeutic targets.

Jenny: That’s what you were looking at in this study. So let’s talk about what you found in your study.

Dr. Lohr: As I was saying, the first thing that we found was basically we wanted to make a list of the most significant mutations and the most likely driver mutations. We did this and we got a very long list of drivers and that basically we put out there in the community. Now, basically, these mutations can be validated in the wet lab.

But one thing that was very interesting that’s noticed is that we got a lot of true driver mutations. They have already been described by us and others in myeloma or also in other cancers to be true oncogenes, true drivers of the disease. For example, we had three genes that we focused on because we knew that were true oncogenes, true cancer genes. That was the KRAS cancer gene, the BRAF cancer gene, and the NRAS cancer gene.

What we noticed is that we saw more than one of those in the same patient, and that is highly unusual because they are actually somewhat in the same biochemical pathway. We would not have necessarily expected that that happens. But we see them in the same patient. Because of the analytical technology that we developed, we saw that those mutations in those genes are in the same patient but they’re not in the same cell.

In some of the patients, they were in completely different cells. If you believe that the mutation that one of those mutations is what drives the cancer, you would have to assume that you’re actually dealing with two or more different cancers in the same patient. These cancers are actually all myeloma still, but if they have completely different driver genes and, therefore, completely different vulnerabilities from a clinical perspective, you kind of have to regard them as different diseases. Because we had such a wealth of genomic data, we could actually quantify this really well.

So we could say that, for example, one cancer gene is in only 20% of the myeloma cells and another cancer gene is in 100% of the myeloma cells. What does that mean? We have asked that question and we tried to model this in-vitro. We said, “Okay.” Let’s say that, for example, 50% of the cells in one myeloma patient have Mutation A and the other 50% in the same myeloma patient have Mutation B. What does that mean exactly? We used those three oncogenes: BRAF, NRAS, and KRAS because for BRAF, we actually have a drug.

BRAF is an oncogene that is mutated in other cancers as well and there’s actually an FDA-approved inhibitor for BRAF that can be used. So we could actually test from a therapeutic perspective, if we have 50% with the BRAF mutation, 50% of the cells with another mutation and we give the inhibitor, experimentally what happens? What we found was actually very interesting. As we would have expected, the cells that have the BRAF mutation, they actually get killed with the BRAF inhibitor or at least they stopped proliferating. But depending on what kind of mutation is in the other type of myeloma, either this other clone, what we call it, is not affected at all or in the worst-case scenario is actually stimulated by the drug.

Jenny: Oh, that’s a problem.

Dr. Lohr: That’s the problem, exactly. If you say, okay, you don’t have a distribution of 50% and 50%, but instead you have only 10% of the cells with BRAF mutation and 90% of the other cells your net effect when you give this inhibitor, maybe that, yes, you kill the 10% of cells with the BRAF mutation, but you stimulate the other 90% so your net effect could be actually progression of the disease. That’s obviously a problem.

Jenny: I know there are some clinical trials that are running right now for the BRAF mutation. This would mean that you really have to completely understand the person’s biology, and then you would have to have a very expert myeloma specialist who would know what to tweak.

Dr. Lohr: Right. So we’ll have to basically — so all of this is essentially experimental data and we have to see how that pans out in the clinic. So one thing we know for sure is that — I shouldn’t say we know for sure but there is data at least now that at least the first part is actually correct that if there is a patient with the BRAF mutation and myeloma patient with the BRAF mutation, the drug actually seems to work.

We basically did all of these in-vitro, but by the end of last year there was actually a study so far in single myeloma patient by a German group — that study was conducted — a single myeloma patient who was apparently refractory to all standard treatments who had the BRAF mutation and they gave this BRAF inhibitor which, as I said, is not approved yet for the treatment of myeloma but it’s approved for other cancers. Apparently, this patient had a dramatic response with reduction of disease, with reduction of immunoglobulins, with reduction of plasmacytomas by imaging and at least what they wrote in the paper, I think they treated him for eight cycles and after that the patient was still in remission.

The first part is true that if you have this particular mutation, apparently, in myeloma, you also get a response. The second part now that has to be investigated, if this particular mutation is not in every single cell but only in small percentage of the myeloma cells, if you give the drug then, what really happens then?

Jenny: What’s the name of this drug? In what cancer is it used?

Dr. Lohr: It’s called Regorafenib and it is used in melanoma. That has been published in The New England Journal paper and melanoma is really a tough disease to treat if it’s disseminated, and they saw massive responses. So this I think the duration between — the study to actually approve it was less than two years because it had such dramatic responses.

We are now actually at the Mass General, there already is a trial open using BRAF inhibitors. That’s actually a study that includes also other cancers with this particular BRAF mutation, but it also includes myeloma. We are initiating now a new study where we combine a BRAF inhibitor to MEK inhibitor for patients with multiple myeloma.

Jenny: Maybe you can talk about the MEK inhibitor and the MEK gene, what that does.

Dr. Lohr: It’s been known for quite some time that the MEK kinase pathway which MEK is a part of is actually activated in myeloma regardless of whether there are any mutations in any of those genes or not. MEK inhibitors have been used in clinical trials. In melanoma, what has been very interesting is that when you give the BRAF inhibitor in melanoma, you get those dramatic responses but you also get side effects with it, and that’s mostly skin toxicities. So you can actually even cause skin cancer with this drug.

And what’s been found in melanoma is that when you give a MEK inhibitor, in addition to the BRAF inhibitor, you can actually prevent this to a large degree, which is also surprising because the BRAF inhibitor and the MEK inhibitor are targeting the same pathway so you wouldn’t necessarily expect that, but there’s actually a good reason why this may work. This is, therefore, a very attractive combination, at least theoretically, in multiple myeloma because in patients with the BRAF mutation, if you could give a BRAF inhibitor and a MEK inhibitor as a combination, you would not only likely increase the efficacy but you would also decrease those skin side effects.

I think that at least for patients who have one of those BRAF mutations, a combination of a BRAF inhibitor and a MEK inhibitor is very interesting and that’s why we are writing this clinical trial. The MEK inhibitor alone is being studied in clinical trials, and I don’t know exactly where those clinical trials stand. I think you have people on your program who are much more familiar with those trials and where they stand right now.

Jenny: Is that MEK inhibitor a driver gene too, or it’s just an activated gene?

Dr. Lohr: From our data, we would say it’s basically the pathway is activated and we find a few mutations, but they weren’t really significant in a statistical sense. So the BRAF mutations we found to be statistically significant, but the MEK mutations we did not find to be. It’s very well possible that those mutations do something, but we didn’t find them at a high enough frequency to really say statistically rigorously, yes, that is clearly a driver gene. I would say that the pathway is activated but only in few cases we have mutations in those genes which may actually activate this pathway.

Jenny: Going backwards just a little bit, how did you narrow down the number of genes you studied as targets, how you did that?

Dr. Lohr: Yeah, from a sequencing perspective, we didn’t have to narrow them down because we were just sequencing all of them. It was nice because we did whole exome or whole genome sequencing. So for either one of those techniques, we were basically looking at all genes in the human genome.

From a wet lab perspective, when we pick genes to go after and then try to model this scenario of myeloma heterogeneity, basically those were practical reasons because we wanted to provide the proof of concept that this heterogeneity is actually very relevant from a therapeutic standpoint. Therefore, we picked genes of which we knew that they were really cancer drivers. We pick this one gene, the BRAF gene, for which we actually had a drug.

We could actually model this in-vitro, mix different cell lines as a model for different sub-clones and then give this drug and see what happens. That’s when we saw that when we did this that we inhibit one clone, but we are actually increasing and boosting the other clone. So picking those were really just practical reasons because we had all the tools available to provide that proof of concept.

Jenny: Well, I’m glad you’re being thorough. Now, I have a question. Can you kind of explain what the phrase “clonal heterogeneity” means in myeloma?

Dr. Lohr: Yes. The textbook knowledge of cancer is really that it’s a clonal disease. What that means is that all cancer cells are supposed to be identical and from a genetic standpoint and from all other standpoints. So in principle, the textbook knowledge is that when you look at cancer and you look at the genome, every single cancer cell is identical. Our work and also the work of others show that this is really not the case but that the individual cells in the same myeloma patients in the same myeloma may actually be very different, what I meant by saying that you can actually find more than one type of myeloma in most patients.

When you say “clonal,” what that means is that a particular mutation or really any genetic defect is in every single cell in the body or in every single myeloma cell in a particular patient. So if you find a certain mutation or another genetic defect in every single cell, then we would say it’s clonal. When you find a certain mutation or a genetic defect only in a certain percentage of the myeloma cells in the same patient, for example, only in 10% or in 20% of all the myeloma cells, then we call it subclonal. You can imagine now that you can have 10% of the myeloma cells in a given patient. With one mutation you have another 10%. With another mutation you have another 10% with another mutation.

All of these we would call subclones and that’s basically what it means “subclonal heterogeneity”. It means that not all the cells are the same in the patient and you can define percentages of the cells with given mutations in the same patients. And then you can basically regard those subclones individually.

Jenny: That might be why one single drug is not going to ever cut it maybe in myeloma.

Dr. Lohr: Exactly. You could imagine that one single drug only kills one subclone and 10% of those, but there are two other subclones which basically comprise 10% each and the drug doesn’t touch those at all.

Jenny: Are there other cancers that are similar to this? Or is this really unique in this type of cancer?

Dr. Lohr: Actually, there are other cancers that are similar but what we did — and those are all studies that are being done in other cancers as we speak. I think it will take another two or three years before we have a landscape across cancers and can compare them in terms of this subclonal heterogeneity. What we did for our study, we at least compared this to one other cancer, to ovarian cancer. One thing that we found very interesting is that in ovarian cancer, we found that there are some patients for which we could not detect any subclones.

At least in some patients with ovarian cancer, it really seems like everything is clonal. So all cells look the same and at least considering our detection threshold, the mutations seem to be in all cells. So one would assume that in those patients, it may be easier to cure a cancer because either you have a successful drug or you don’t. It’s not like there are some — there’s a small percentage of cells that look different from the other cells. Interestingly, we didn’t find that in myeloma.

In myeloma, pretty much all patients have subclones. That may have to do with the fact that myeloma evolved over a long period of time. So it starts out with MGUS and then the progression to smoldering myeloma before it becomes clinically active myeloma. I think over that evolution of time, you get basically the subclonal heterogeneity.

I think all cancers are similar in a way that in the end, there will be a lot of heterogeneity. But there are definitely or there seem to be at least some cancers where you have some patients where this heterogeneity is actually not very extensive at all.

Jenny: To go into a little more depth about that, when you studied the patients, were you looking at newly diagnosed patients or previously untreated patients or treated patients? You mentioned this at the beginning of our interview. You were saying that it evolves over time. It becomes more aggressive. Can you talk about that a little bit, about what you saw in the different stages of patients?

Dr. Lohr: Absolutely. One of the limitations of our study was that we did not have samples of the same patient before and after treatment. I think that would give you the most accurate data and this is what the CoMMpass study now is trying to achieve. But basically, half of the samples from patients that we had were from untreated patients and the other half was from treated patients. We basically compared the types of genes that we had in untreated and in treated patients and we compared this clonal heterogeneity and the subclonal composition that we had in untreated and treated patients.

What we did find is that our most prominent driver genes, so genes like the BRAF, the KRAS, and NRAS genes and other genes that are known to be cancer drivers and that we identified in our study to be likely highly significant cancer drivers, we saw that these actually are present at an increased subclonal fraction in treated patients. What that means, for example, that if you have one of those cancer genes that when you look in untreated patients, it may be present in 10%. But then when you look in treated patients, on the average, it’s present in 90% of the cells or in 100% of the cells.

Jenny: These are patients where it’s come back? Obviously, I guess you couldn’t test for it if it hadn’t come back, right? When it comes back, you’re saying it comes back in greater force.

Dr. Lohr: That is the problem that we don’t have samples from the same patient before and after treatment. So we basically have a group of half of our patients that we had samples from were before treatment and the other half was after treatment but they were different patients. So those were not the same patients. What we could is just look at what is the frequency of the group of patients that we had from before treatment, and what is the frequency of mutations of the group of patients that we had after treatment. There we just saw statistically significant differences that basically those significant mutations that we identified overall increased in frequency.

When we asked, for example, the BRAF mutation, in the hundred untreated patients also that we had, what is the percentage of myeloma cells in which they occur? Then we found maybe like — I’m just making up a number– and then what we found 30%. Then when we looked at the treated patients, then we saw that the mutations occur in 100% of the myeloma cells. What we conclude from this is that those mutations that we have identified are being selected by standard treatments. That means that those are not only cancer drivers, but they also seem to be responsible for the resistance that develops over time because you may kill other subclones, but those are the clones that make it through.

So in the end even if they are in the beginning only in 10% of the cells, after treatment they seem to be in 100% of the cells, that tells us that, yes, those are probably the cells that are most resistant to the standard treatment.

Jenny: Then what do you do with that?

Dr. Lohr: That is the big question. I think that generates a number of interesting questions. For example, the question is when — let’s stick with this example of a BRAF mutation. When you detect a patient who has a BRAF mutation in 10% of his myeloma cells, should you start treating him then or should you start treating the patient once the mutation has progressed to 100%?

And that is a question that is completely unresolved. That may actually be, as we learn more, that may be a paradigm shift because right now we do not treat patients at the MGUS stage, and we do not treat patients at the smoldering myeloma stage. I think all of this study will raise a lot of questions about what the ideal time point is to start treating of a patient. Is it the right time point when the mutation is in only 10% of the myeloma cells or is it the right time point once the mutation has reached 100% of the myeloma cells?

That is something that we’ll have to move along as we learn more about what happens to those mutations over time. I think over the next five years or even a decade, this will be one of the crucial questions that we have to figure out.

Jenny: Well, it’s really critical and it’s really complicated. When this paper first came out, I had been asking a lot of different people about different genetic mutations. And it made me a little discouraged to hear about the potential BRAF treatment inhibitor that you talked about. How do you overcome that?

Dr. Lohr: The history over the last ten years has kind of told us how we could overcome this. For example, the big achievements that we have had over the last five to ten years with the development of proteasome inhibitors, for example, bortezomib or the IMID drugs, lenalidomide, the complexity of the disease did not stop the progress and did not stop the efficacy of those drugs. I think the big question is this whole complexity, the biological complexity of the disease is it really relevant?

So our studies, I think, demonstrate that it may be relevant in some cases, but it looks like proteasome inhibitors and the IMID drugs are basically kind of negligent about this complexity. The fact that there is this complexity and that you have so many subclones doesn’t mean that you have to target every single subclone. It could be that a drug actually hits multiple subclones simultaneously with equal efficacy and certainly the proteasome inhibitors and the IMID drugs seem to do that.

I think the complexities that we see biologically doesn’t mean that we have to target every single subclone individually, but there may be drugs which may hit the entire disease regardless of this genetic complexity. So that is one thing.

The other thing is that the hope is that the more targeted therapies are actually a lot more specific. You could give them in combination. What you could do, you could maybe give them even subsequently. If there is a certain subclone for which you have a particular drug, you could try to hit this particular subclone and then you perform genetics again. If there’s another subclone reoccurring, you take the next drug.

I think most of us actually believe that before we reach a cure, I think the more immediate goal is to turn myeloma into a chronic disease. I’m sure people on your program have basically compared this to what’s happening in HIV therapy where the disease is not really cured, but it’s basically turned into a chronic disease quite successfully. I think this is our more immediate goal in myeloma to turn this into a chronic disease. That may mean that you have combinations of drugs and that you may have many different drugs in succession with the goal to eventually turn it into a chronic disease.

Jenny: It sounds like that you just have to know what you’re working with —

Dr. Lohr: Exactly.

Jenny: It seems like in personalized medicine, there are three different approaches. Some treatments target by translocation or by chromosome deletion like 17 — like I’ve heard that bortezomib is important for people with deletion 17. Then you have this gene way of targeting therapies. Then you have a more broad way of targeting CD138 with drugs like daratumumab.  and things like that.

Dr. Lohr: Exactly.

Jenny: I guess you could talk about personalized medicine in a lot of different ways.

Dr. Lohr: Exactly. I think basically going after every single individual subclone is certainly not the only answer. I think what you are saying is exactly right. There are different ways to approach this. Drugs that basically target — if you think about it, a plasma cell is very different from most other cells in the body and if you essentially eliminated all plasma cells in the body that there is obviously certain risk with that but you can live with that. That does not have anything to do with cancer, right?

If you have a therapy like you were saying, for example, CD138 or something that specifically targets plasma cells, you may actually be already in very good shape because you have eliminated all the plasma cells, but that’s something you can live with but you would have cured the cancer. That wouldn’t be specific at all to any particular mutation or anything that has to do with cancer. What you’re doing is really eliminating a population from the body that causes trouble. I think there’s a number of ways that it can be targeted. That would be personalized medicine too. As you were pointing out, I think there are many ways to tackle that.

Jenny: In your research with this discovery, where do you go from here?

Dr. Lohr: I have a very personal flavor of what I think that should be done. I think some of the things you already pointed out. As the sequencing is getting cheaper and as the sequencing is being employed into clinical routine, I think we need to learn a lot more about what happens. We need to get more data about what defects cause myeloma. But then more importantly I think even what happens over time.

If we get the genomic data before therapy and not only once after therapy but multiple times, I think we’ll learn a great deal about what happens and then it will inform us about what we can do about it. My personal bias and this is now what I’m focusing my own research on is that sometimes it may be hard to get samples for multiple time points after treatment because that usually involves the bone marrow biopsy which is associated with risk. Right now, what we’re trying to do in the group is to do all these genomic diagnoses from blood. What we have found in other people and I have found this too that myeloma cells are actually circulating in the blood, and you can actually retrieve genomic information quite comprehensively from those circulating cells in the blood and how they relate to what’s happening in the bone and in the bone marrow. And what we can learn from this that remains to be seen. But I think that is another interesting area of the future that you can make those genomic diagnoses from the blood of the patient. And that is obviously associated with much less risk and it can be done in an easier fashion.

Jenny: And pain.

Dr. Lohr: And pain.

Jenny: Most patients hate the bone marrow biopsy, but they’re willing to do them if it’s going to give you key critical information but blood is even better. In your opinion, what can patients do to accelerate your genetic work in myeloma to find new and better targets?

Dr. Lohr: The most important thing is really what you pointed out is enrolling into clinical trials. It doesn’t mean necessarily that there’s a new drug being tested, but just basically obtaining the data in the context of a clinical trial. Even if we give standard therapy in the context of a clinical trial and in a clinical trial that is linked to those genomic studies, I think we’ll learn a great deal about what’s going on and that will basically generate a lot of incentives to test new therapeutics and develop new therapies.

I think it’s always worth asking for patients if there is the opportunity to get those genomic analyses on the material. And I think over the next one or two years in many of the major centers that is something that will happen, and I think enrolling in clinical trials and just inquiring about the opportunity to get this kind of genomic data, I think that will go a long way.

Jenny: Is the number of additional patients donating tissue samples better or can you do your study based on 200 like you did? Would it really be much, much better if you had 1,000 or 2,000 or 5,000?

Dr. Lohr: I think it will always get better. Actually, we have done some modeling about what you get. I think it’s a question of how far down you want to go in terms of the mutations that you want to identify. For example, I think everything that occurs in 10% of patients or more, that I think we have identified but mutations that occur in 5% of the patients or less, I think those we have not identified yet. I think we’ll always learn more. Because of this heterogeneity, I think we are statistically powered only to, I would say, something around 5% but everything that is below this, we won’t pick up. I think from more patients, we may actually then also pick up those mutations that occur in a much smaller population of patients.

Jenny: I attended a patient conference and the author of The Emperor of All Maladies, Dr. Siddthartha, he was talking about breast cancer. And he mentioned the same thing that you were studying in myeloma is that he found certain driver mutations, but he found so many variations. So I think the deeper that we go — is this whole exome test when you say it’s going to become available in the clinic, is there a company that’s working on it or what’s the progress of that?

Dr. Lohr: I think there are also now companies that are offering that, and I think that just basically going online but it’s mostly the institutes themselves. So I know that the Dana-Farber is trying to institute this into clinical routine and then also the Broad Institute is kind of offering that as a service. I’m not sure because this is all very new, but I think the setup is in a way that, for example, other institutions can send the samples to the Broad Institute and then the sequencing is performed there, and then basically the results get sent back. All of this is very new and very much in flux. But over the next year or so, I think there’s going to be massive progress.

Jenny: Well, it’s very exciting.

Dr. Lohr: Yes, it definitely is.

Jenny: Yeah, very exciting. Well, I’m taking up all the time, but I want to open it up for caller questions. So if you have a question for Dr. Lohr, please call 347-637-2631 and press 1 on your keypad.

Okay. We have our first caller, please go ahead.

Caller: Great show today. Thank you so much for taking my call. Can you hear me?

Jenny: Yes, we can.

Caller: All right. Great. The genetic tests or the genomic profiling was of most interest to me. Specifically, if I would like to do that today, where could I go and do that? You mentioned Dana-Farber, but I probably have to be a patient at Dana Farber. Is there someplace else I could go and get that done, not only get it done but where it would be helpful to push forward the work being done in myeloma?

Dr. Lohr: Because all of this is very new so I know that the Broad Institute got the certifications, which basically means that they can actually provide the genetic profiling from clinical samples because you obviously have to meet certain quality standards which is a way of what you need for research. And I know they’ve just got this, but this is really a development of the last two or three months because I don’t even know if they are officially accepting samples yet. I know of a couple of companies who are providing a very similar service. But I also don’t know if this is really online yet.

So what I can do is I can find out about this because this is all very much in development and then maybe with Jenny post this on the website.

Jenny: Oh, sure.

Caller: I guess because is the goal is how can we gather and then combine more of the data especially the patients that have the less common genetic subtypes.

I have one more follow-up question. If a patient has been through two bone marrow transplants, is relapsed within a year, is it possible to get into a medical trial at that point? Do you fall outside of what most clinical trials are looking for?

Dr. Lohr: Not at all. Many clinical trials are actually designed specifically for that situation. One has to take a very close look at the history about what’s already been given. Definitely, if there is a failure after transplant, that does not preclude you from enrolling into clinical trials at all. As I said, many of the clinical trials are actually designed for specifically that situation.

About the first question that you had, what do we do to compile all the data ideally in the whole world that has been generated and then define even those rare subtypes? That is something that is definitely highly desirable and there are efforts about this as well. Because just the size of the data is so large, it’s just logistically a big challenge. As you can imagine, for example, if you have a whole genome that takes up space off several computer hard drives and if you have many of those, that alone you need a place to store them. But there are actually efforts going on about this.

Caller: All right. Thank you for taking my call.

Dr. Lohr: Sure. My pleasure.

Jenny: Dr. Lohr, we’re out of time so we better close. But we so appreciate you joining us today. We hope that you will continue your excellent research and care for myeloma patients. We believe your discoveries will help find a cure for this disease, and we’re so grateful for your amazing work.

Dr. Lohr: Thank you very much. It’s my pleasure to talk to you.

Jenny: Oh, well, thank you so much for joining us.

Thank you for listening to another episode of Innovation in Myeloma. Join us next week for our next mPatient Radio interview as we learn more about how we as patients can help drive to a cure for myeloma by participating in clinical trials.

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