New Genomic Models for Leiomyosarcoma Treatment
Josephine K. Dermawan, MD, PhD, a soft tissue pathologist at Cleveland Clinic, joins the Cancer Advances podcast to discuss the development of novel genomic risk stratification models for soft tissue and uterine leiomyosarcomas. Given the complexity and variety of sarcomas, accurately identifying subtypes is key to effective treatment. Listen as Dr. Dermawan explains the challenges of risk stratification and how genomic profiling enhances our ability to predict tumor behavior, leading to more precise treatment decisions.
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New Genomic Models for Leiomyosarcoma Treatment
Podcast Transcript
Dale Shepard, MD, PhD: Cancer Advances, a Cleveland Clinic podcast for medical professionals, exploring the latest innovative research and clinical advances in the field of oncology.
Thank you for joining us for another episode of Cancer Advances. I'm your host, Dr. Dale Shepard, a Medical Oncologist here at Cleveland Clinic directing the Taussig Early Cancer Therapeutics Program and Co-Director of the Cleveland Clinic Sarcoma Program.
Today I'm happy to be joined by Dr. Josephine Dermawan, a Soft Tissue Pathologist here at the Cleveland Clinic. She's here today to discuss developing novel genomic risk stratification models and soft tissue and uterine leiomyosarcomas. So welcome.
Josephine K. Dermawan, MD, PhD: Thank you for having me.
Dale Shepard, MD, PhD: Absolutely. So give us a little bit of an idea of what you do here. You're a pathologist and you see a lot of soft tissue sarcomas. What does a day look like for you?
Josephine K. Dermawan, MD, PhD: Yeah, so pathologists are kind of like doctors who work behind the scenes. And so whenever a surgeon or a radiologist take a tissue out of a patient's body, they send it to pathology and we process a tissue and I look at the tissue under the microscope to try to make diagnosis. Most of the time we try to answer whether it is a mass growing in the body, if it is tumor or not tumor. And if it's like a tumor, we decide whether it's cancer or not. And if it's cancer, which means that it's malignant, then we try to subtype it to help the doctors, mostly oncologists who are treating the patients to decide how best to manage the tumor that is in the patient's body. So we work very closely with oncologists and we do a lot of things behind the scenes to make diagnosis.
Dale Shepard, MD, PhD: Because you are behind the scenes, it's really, really important that everybody realize that really treatment of sarcomas specifically can't happen unless you guys are around doing what you do because it's a really complex area. So appreciate all the work you do.
We are going to talk about a subtype of sarcoma, so a lot of different people listening in. Let's start really, really basic. What is a sarcoma?
Josephine K. Dermawan, MD, PhD: That actually is a very good question. I think of sarcomas as opposed to carcinomas. They're both different types of cancer. Carcinomas are very common derived from the linings of, for example, our respiratory tract and gastrointestinal tract. Basically the linings are exposed to environmental carcinogens. And so some of the most common cancer types like lung cancer, colon cancer for example, they are carcinomas. So they are derived from what we call epithelium.
Sarcomas, on the other hand, they usually originate from the connective tissue in the body. For example, muscle, bone, tendons, fibrous tissue. And sarcomas, significantly more rare than carcinomas in general. And they are very tricky to diagnose because they are more than 100 different subtypes of sarcomas. And being able to accurately classify the type of sarcomas really is the cornerstone of getting a correct treatment for the patients because how we manage those patients really very widely depending on what sarcoma type it is. And because they are so rare, a lot of pathologists, they might find it challenging to classify the sarcomas. And even when we are able to subtype the sarcoma, sometimes it's not easy to predict how it's going to behave. And so this is a very challenging area in pathology. And so yeah, that is a long answer to a short question,
Dale Shepard, MD, PhD: But it's important to point out because I think people sometimes don't realize that second opinion consults, for instance with us really, I mean really starts and stops oftentimes with pathology because if someone has read the pathology and they're not used to reading these, we can only treat people as well as we know what it is.
Josephine K. Dermawan, MD, PhD: Yeah, absolutely. So the oncologists here at Cleveland Clinic, they are very aware of this as you know. So basically any patients who come to seek care here, our clinical team, they are very good at requesting any external pathology material. And we always do a second round of review to make sure we agree with the diagnosis. And as a tertiary academic medical center, we also receive a lot of consults from other pathologists. They send cases to us to get an opinion because they might have trouble classifying the cases.
So yeah, I agree. Having an experienced soft tissue pathologist reviewing sarcoma cases, to me it's very important and it should be a part of any adequate patient care for sarcomas, in my opinion.
Dale Shepard, MD, PhD: Yeah. So we're going to focus on, you mentioned about being able to predict how tumors might react, so we're going to be talking about risk stratification. We're just going to specifically talk about leiomyosarcoma and so much like generically, we ask about what sarcoma is. What is a leiomyosarcoma?
Josephine K. Dermawan, MD, PhD: Yeah, so leiomyosarcomas are sarcomas that originate from the smooth muscle in the body and many body structures contain smooth muscle. For example, blood vessels in the wall of blood vessels, there's a layer of smooth muscle and the large vessels inside our body in the retroperitoneum, for example, the inferior vena cava, that's a very common site where soft tissue leiomyosarcoma originate from. Another big category is gynecologic leiomyosarcoma, and for the most part they come from the uterus. And so leiomyosarcomas, they are one of the most common sarcomas that we see on a day-to-day basis.
Even though they come from smooth muscle, depending on what type of smooth muscle it comes from. For example, if it is a soft tissue leiomyosarcoma that comes from large vessels versus a uterine leiomyosarcoma that comes from the uterus. The way pathologists diagnose and think about them, it's different and the management is also not the same. And leiomyosarcomas in general, they have very poor prognosis. It is an aggressive type of sarcoma. They often would have distant metastasis. And so being able to predict how it's going to behave really help our oncologists decide how to manage a patient if the patient only needs surgery or they might benefit from additional chemo or radiation therapy.
Dale Shepard, MD, PhD: So in terms of that risk stratification, give us a little bit of an idea of how traditionally we've done risk stratification and then how you've been working toward using DNA changes or genomic changes to change that risk stratification.
Josephine K. Dermawan, MD, PhD: Yeah, thank you for that question. And so traditionally, it's not just for leiomyosarcoma, for most cancer types, we do two things to risk stratify them. We perform tumor staging, which is basically looking at things like the size of the tumor and what structures is it involving. So tumor size is a big thing. Under the microscope we can also see certain changes that can help us tell how aggressive this tumor may behave. They include mitotic rate, which is basically we can see cells, they are dividing rapidly. And as you can imagine, if there are many tumor cells that are dividing, then you can imagine that this is a tumor that is growing very quickly.
Another thing is tumor necrosis. Contrary to what one may think, if we see necrosis meaning that the cells are dying in the tumor, it's actually a bad sign rather than a good sign because it means that the tumor is also growing so rapidly that it's outstripping its blood supply. And so seeing tumor necrosis in a tumor that has not been previously treated, it's also a sign that this is a high grade or aggressive tumor. And then finally we also look at the morphology of the cells themselves. So we grade the cells based on the grid of nuclear atypia. So there are certain ways a tumor cell can look like when they are considered high grade. Some of the things that we look at is the shape of the nuclei, how the chromatin look, if it is hyperchromatic, which is a very dark nuclei, all that would kind of tell us if this is likely a hybrid tumor.
So in summary, for tumor grading, we use a combination of cytologic atypia, mitotic activity and tumor necrosis to grade leiomyosarcomas. And for soft tissue leiomyosarcomas, we give it a three tier grading system, which is a traditional tumor grading system for sarcomas, we call it the FNCLCC grading system.
Dale Shepard, MD, PhD: And so how did you go about incorporating genomic changes into a restratification model?
Josephine K. Dermawan, MD, PhD: So as you know, increasingly more and more tumors, they actually receive genomic profiling. So in the molecular laboratory, we look at the sequence of the DNA and see if there are any mutations or changes in the DNA of the tumor. And the reason why we're trying to do that is because traditional system of risk stratification is imperfect. Sometimes there are tumors that we would classify as low grade, but they will still behave aggressively. For example, they might undergo distal metastasis in a short period of time. So that tells us that the way we are doing it traditionally it is a useful system, but it's not always perfect. So we want to see if genomic profiling can help us improve the way we risk stratified tumors.
And so for this study, we look at the DNA sequencing of a large series of soft tissue and uterine leiomyosarcoma, and we try to look at what kind of genetic changes correlate with worse overall and progression free survival, and we're able to identify some changes that can help potentially propose a risk stratification that is based on genomics.
Dale Shepard, MD, PhD: Again, you looked at soft tissue disease as well as uterine disease, and I guess when you came into this, we know they're sort of called the same sort of sarcoma, but they kind of behave differently. Were you surprised by what you found in terms of risk stratification?
Josephine K. Dermawan, MD, PhD: Yeah. So part of the study is we try to compare how the two different ways of risk stratification perform. So one of the main findings in the study is that for uterine leiomyosarcoma using criteria such as tumor size and tumor grade, they actually perform equally well compared to genomic risk stratification. However, for soft tissue leiomyosarcoma seems like tumor size didn't really correlate with worse survival, at least in the cohort that we study. And it seems like using genomic risk ratification, it may potentially do a more accurate job to risk stratify soft tissue leiomyosarcoma. Of course, the caveat is that this also observation would need to be validated in an external cohort. We were able to validate our genomic risk ratification model in an independent cohort from the AACR GENIE cohort, but that cohort didn't include clinical pathologic information, and so it would be essential to see how they compare.
But the purpose of our study is not to say traditional way of doing this should be thrown away. That's really not the goal of the study. It really is to see if there are additional ways to risk stratify tumors and maybe they can be complementary. For example, if we have a leiomyosarcoma that was called low grade just by pure morphology. However, if we sequence it and we see things like ovoid mutation, ATRX mutation for example, we know that the presence of those mutations are significantly associated with worse survival in at least two large cohorts. So then maybe with this information we might consider treating the tumor a bit more aggressively because it might behave worse than what the histology might suggest.
Dale Shepard, MD, PhD: And so the genes that you used for your genomic testing are relatively common genes, right?
Josephine K. Dermawan, MD, PhD: Yes.
Dale Shepard, MD, PhD: So RB1 and ATRX and P53. And so I guess that would sort of enable people to fairly easily get the data that would be necessary to do this, right?
Josephine K. Dermawan, MD, PhD: Yeah, absolutely. So there are many different types of molecular testing. However, like you said, those genes are usually present in most genomic panels. Even if they are targeted panels, a lot of times they would include those genes including RB1, ATRX, P53. So the purpose of this is to develop a risk stratification model that is relatively readily accessible by most oncologists. That they don't have to always do very expensive testing or whole exome sequencing in order to get this information to help them. We also included a modified model that includes chromosomal arm level changes. However, we do understand that that is not always available on most genomic panels, however, just having those three genes alone themselves actually would be sufficient to have a pretty accurate risk stratification.
Dale Shepard, MD, PhD: And I guess the other piece is that we think about risk stratification, that's sort of like as we diagnose a tumor, how likely is it to come back and it can kind of guide therapies or surveillance and things like that. What did you learn about changes in tumors over time, sort of changes in mutations as people live with this disease for a longer period of time?
Josephine K. Dermawan, MD, PhD: Yeah, that's a really good question. So for example, if a tumor first presents localized, in that it came back or it metastasized to a distant location, the question is when do those genomic changes occur if they only show up later in the stage or are they present from the get-go? The reason why that is important is because if those changes, say ovoid mutation, if they only happen late in the stage after the tumor has already declared itself to be aggressive and it came back or it metastasized, then sequencing the tumor from the get-go may not actually be helpful because they are not present in the beginning.
However, in our study, we were able to look at longitudinal sequencing, meaning that we were able to sequence tumors from the same patient at an early and a late stage. And what we found was that most of those critical changes that we observed that were predictive of aggressive behavior, they were present at the get go, at beginning when the tumor was still localized. That told us that we can actually use this information and sequence the tumor before it came back or recurred and use that to inform us maybe to predict how the tumor might behave in the future.
Dale Shepard, MD, PhD: Makes sense. You talked about validation and you did have a set of data that you looked at and worked on validation. What's it going to take to verify what we have found, get this more into standard practice?
Josephine K. Dermawan, MD, PhD: In our study, our validation cohort, it only included genomic inflammation and basic histologic classification, whether it's soft tissue or uterine leiomyosarcoma. It didn't include inflammation for all tumor size or tumor grade. And so to really validate all our findings, it will require a set of very well annotated cohort that integrates traditional clinical pathologic information and genomic profile. Such a cohort is not easy to find. That really brings up the point of data sharing, how that is a challenge but how important that is for us to do better research, better studies to make sure any findings generally applicable to every patient. And so this will require a concerted effort from many different institutions to when they deposit data in probably available database to maybe also include additional annotation, detailed clinical pathologic information. The more information we share, the easier it is to validate this kind of study and the better informed we'll be.
Dale Shepard, MD, PhD: Well, this is a particularly difficult tumor type and you're doing good work to try to help us to treat these patients. And appreciate your insights today.
Josephine K. Dermawan, MD, PhD: Thank you so much, Dr. Shepard.
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