Dissecting Tumor Mutational Burden and Microsatellite Instability in mCRPC: Differential Responses to Immune Checkpoint Inhibitors - Nicolas Sayegh
July 10, 2025
Evan Yu speaks with Nicolas Sayegh about his research examining tumor mutational burden (TMB) and microsatellite instability (MSI) in metastatic castration-resistant prostate cancer. Using Flatiron/Foundation Medicine data from 3,000 patients, the study found TMB high in 3.2% and MSI high in 1.7%, with all MSI high patients also being TMB high. Importantly, they identified a rare subset of eight patients with TMB high but not MSI high, showing enrichment in RAD21 gene alterations. Both TMB high groups demonstrated improved outcomes on pembrolizumab compared to biomarker-negative patients, with TMB high-only patients achieving higher overall survival than MSI high/TMB high patients. The research emphasizes the importance of biomarker selection, as docetaxel outperformed immune checkpoint inhibitors in biomarker-negative patients while the reverse was true for biomarker-positive cases, supporting precision medicine approaches in prostate cancer immunotherapy.
Biographies:
Nicolas Sayegh, MD, Internal Medicine Resident, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT
Evan Yu, MD, Professor of Medicine Division of Oncology, University of Washington School of Medicine, Section Head of Cancer Medicine, Medical Director of Clinical Research Support, Fred Hutchinson Cancer Center, The University of Washington School of Medicine, Seattle, WA
Biographies:
Nicolas Sayegh, MD, Internal Medicine Resident, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT
Evan Yu, MD, Professor of Medicine Division of Oncology, University of Washington School of Medicine, Section Head of Cancer Medicine, Medical Director of Clinical Research Support, Fred Hutchinson Cancer Center, The University of Washington School of Medicine, Seattle, WA
Related Content:
ASCO 2025: Additive Clinical Utility of Tissue Biomarkers of Microsatellite Instability Status and Tumor Mutational Burden to Predict Immune Checkpoint Inhibitor Effectiveness for Real-World Patients with mCRPC
ASCO GU 2025: Survival Outcomes of Patients with Metastatic Castration-Resistant Prostate Cancer (mCRPC) Receiving Lutetium-177-PSMA-617 (Lu) Based on Line of Therapy
ASCO 2025: Additive Clinical Utility of Tissue Biomarkers of Microsatellite Instability Status and Tumor Mutational Burden to Predict Immune Checkpoint Inhibitor Effectiveness for Real-World Patients with mCRPC
ASCO GU 2025: Survival Outcomes of Patients with Metastatic Castration-Resistant Prostate Cancer (mCRPC) Receiving Lutetium-177-PSMA-617 (Lu) Based on Line of Therapy
Read the Full Video Transcript
Evan Yu: Good day. It's great to be here at UroToday again at ASCO 2025. And right now, I'm here with Dr. Nicolas Sayegh who's a second year resident at UT Southwestern. But prior to being at UT Southwestern, he did his postdoc at University of Utah Huntsman Cancer Institute and worked with Dr. Neeraj Agarwal, who we all know well. So today, we're going to be talking about the abstract that you're presenting here at ASCO. And it's looking at one of my favorite topics, which is looking at tumor mutational burden and looking at microsatellite instability.
And traditionally, we think about that with colon cancer because that's where you get the most press. But it does happen in prostate cancer. It happens in metastatic castration resistant prostate cancer. And yes, we can use things like pembrolizumab for that. So my understanding is that you looked at, especially tumor mutational burden and also microsatellite instability, the frequency in patients with prostate cancer and looked at response to different therapies. Is that right?
Nicolas Sayegh: Yes, that is right. So usually when we think about microsatellite instability, as well as tumor mutational burden in prostate cancer, we think of them going together.
Evan Yu: Right.
Nicolas Sayegh: So in our study, we try to separate them a little bit and try to dissect the characteristics of the smaller subset of patients that only have a high TMB without testing positive for a high MSI.
Evan Yu: Well, it does happen. I mean, I've seen it before where you have high TMB and you're not MSI high, but you're right. We usually think about it tying together. And we also think about it tying together with the mismatch repair genes, MSH2, MSH6, all those different gene alterations. Did you guys look at those as well?
Nicolas Sayegh: Yes. So we definitely looked at the genomic landscape for this small subset of patients of having TMB high without MSI high and compared it to the patients who do have MSI high. And in this small subset, we saw alterations that we usually expect in patients with high microsatellite instability or a mismatch repair deficiency, such as MSH2, MSH6, as well as tumor suppressor genes, such as TP53, PTEN, and other expected genes.
What was striking to us was the significant enrichment in the RAD21 gene that we saw in patients with TMB high without MSI high. Usually, this gene plays a role in the cohesin complex with the homologous recombination repair. So when this is inhibited, there is more proliferation, more error in DNA replication, and possibly potentially more neoantigen presentation. So a possible mechanism of enhanced response to immune checkpoint inhibitors in this setting.
Evan Yu: Great, great. So before we jump into the responses of immune checkpoint inhibitors and potentially other drugs, I think you looked at some other drugs in the responses as well. Why don't you start off with the 30,000 foot view of the study, how you designed it, what you actually looked at, where you got the clinical data, what testing technology, all that of stuff? So go ahead.
Nicolas Sayegh: Yeah. So what actually pushed us to go ahead with this study is all the different results and a little bit negative/disappointing results that we had with immune checkpoint inhibitors in mCRPC and notably in unselected populations. So different studies and big trials have been done. Immune checkpoint inhibitor monotherapies, immune checkpoint inhibitors combined with chemotherapy, such as docetaxel with ARPI, such as enzalutamide.
And in all those trials, the populations that were studied were all unselected for any biomarker, and all those studies were negative and did not show any advantage of adding immune checkpoint inhibitors to any standard of care.
Evan Yu: I'm very familiar with those.
Nicolas Sayegh: Yes. And it somehow is a little bit frustrating because we do feel that there is some potential in-- some potential to add or combine immune checkpoint inhibitors with something later on. So we try to characterize more the populations that would benefit from that. So our study is a composite study where we, like I said, try to characterize the TMB high population, also compared and expanded the comparative effectiveness of immune checkpoint inhibitors versus taxanes, or namely docetaxel or cabazitaxel, in later line therapies.
Because when patients usually exhaust all the previous lines and mCRPC, we tend to rechallenge them with the chemotherapy. So we try to do a small comparison with that. And something that we found a little bit pretty novel and striking that there is not much evidence about was MSI high detected in blood ctDNA. So we also tried to expand on that.
Evan Yu: OK. But you used Foundation Medicine. is that right?
Nicolas Sayegh: Yes.
Evan Yu: And their database. Is that correct? It wasn't all data from Utah. It was their big data-- national database.
Nicolas Sayegh: We actually do have a lot of data from Utah. But for this study, we did use Flatiron, which is a huge national database that was coupled with the Foundation Medicine database. So it's, on an individual level, very mindfully coupled the genomic and clinical data that helped us do this analysis, especially that Foundation is the actually FDA approved companion diagnostic for pembrolizumab in prostate cancer.
Evan Yu: Got it. OK. So give me the key findings. What did you find?
Nicolas Sayegh: The key findings, we definitely-- so we divided the patients in three groups. Let me take-- let me take a step back. To test for frequencies actually of TMB high and MSI high among patients with mCRPC, we selected those patients who have mCRPC in the Flatiron database. We had around 3,000 patients. And among those patients, the frequency of MSI high was close to 3% and TMB high was also 1.7%.
But all patients with MSI high were actually TMB high. The opposite was not true. We did have a small subset of patients with TMB high only, and this was our population of interest. So in terms of comparing--
Evan Yu: So let me clarify those numbers because your numbers for MSI high were higher than your TMB high. When you said the 1.7%, I think that was TMB high that was MSI non-high or-- let me clarify your numbers.
Nicolas Sayegh: Oh, yeah. My bad. My bad. I might have inverted both. So TMB high was 3.2% and MSI high was 1.7%.
Evan Yu: That makes sense.
Nicolas Sayegh: Yes, that makes sense. Thank you for catching that. So in terms of outcomes, all of those-- so 84 of those 3,000 patients were actually treated with single-agent pembrolizumab. And our outcomes were TTNT, time to next treatment, and overall survival.
Evan Yu: OK.
Nicolas Sayegh: So we divided those patients treated with immune checkpoint inhibitors in three subsets. The first subset was patients with MSI high with TMB high, TMB high without MSI high, and a third population with neither of both.
Evan Yu: Got it.
Nicolas Sayegh: So outcomes. So both the first two populations, MSI high with TMB high and TMB high without MSI high, had higher outcomes, better outcomes as we expected compared to those without those biomarkers. But also patients with TMB high only had same outcomes in terms of TTNT compared to those with MSI high and TMB high.
And what's even more striking is that in terms of overall survival, patients with only TMB high did better actually on single-agent pembrolizumab than patients with both MSI high and TMB high.
Evan Yu: Well, that's interesting. What do you think that is?
Nicolas Sayegh: Actually, we do not have a clear explanation for what we have. But I could hypothesize that most of these outcomes could be related to some genomic differences. In relation to the small sample size that we have, we cannot draw some definitive conclusions, but I do think that the mechanism could be in relationship to some homologous recombination genes or also some other tumor suppressor genes that we actually don't know about.
Evan Yu: Did you look at the cutoffs for TMB high? Like so, for instance, if the TMB high only patients were doing better, was it because their actual numerical TMB numbers were much higher than 10? Maybe they were very, very high. Even though they might not have been driven by traditional pathways, they came through microsatellite instability. So were you able to look at what those actual numbers were, and could that potentially explain why those patients did better?
Nicolas Sayegh: Yeah, unfortunately, we the sample size was pretty too small to categorize those patients. So we would go on an individual-- on a patient level basis, very individual patient level basis. So we were not able to draw any conclusions in terms of those. But in terms of the level, the threshold that we use for TMB high, we use the approved one related to the foundation sample.
Evan Yu: Yeah.
Nicolas Sayegh: Yeah.
Evan Yu: OK All right. Well, that's great. And then, in the ones that were TMB high but not MSI high, I'm most interested in that group, of course, were you able to discern what the actual drivers might have been for the high tumor mutational burden? Were there consistent findings on your sequencing data that you're like, aha, OK, a lot of them had PTEN alteration or PTEN and P53, or-- I'm just curious. I'm making this stuff up. But did you look at that and see if you could find any consistent messages there?
Nicolas Sayegh: We saw that they had similar enrichment in PTEN or TP53 and the tumor suppressor genes that we compared to their MSI high counterparts, but they did have a similar level of MSH2 and 6. However, the other microsatellite instability genes were not as enriched as the other counterparts, at the MSI high counterparts. So if this might have played a role, but from my opinion, it does not seem like it.
Some more drivers would be some other less known also tumor suppressor genes, like also AXL gene much less explored. So literature is pretty scarce compared to this in terms of this subpopulation. So we do-- yeah, we do need to expand this cohort. In the entire Flatiron database and Foundation database, we only found eight patients with high TMB without MSI high, so we're--
Evan Yu: So it's a small number.
Nicolas Sayegh: It's a very small number.
Evan Yu: OK. Were you able to say anything about other treatments, not just the IO treatments, but how did were there any interesting findings with response to docetaxel or anything else, androgen receptor pathway inhibitors or anything else?
Nicolas Sayegh: Yes. Actually, we tried to explore also the off-label use of immune checkpoint inhibitors and compare it with docetaxel in the setting. Sometimes in the community, some physicians are, as a last resort, sometimes use immune checkpoint inhibitors in patients that do not test positive for a high TMB or high MSI. And in this patient subset and this patient subpopulation, we did see that docetaxel had better outcomes.
However, in patients who tested positive for those, the difference was striking-- was very striking and there was a huge OS and both TTNT benefit between those treatments. Another thing is we did an intrapatient comparison where we compared the same patients who initially started on docetaxel, then were transitioned to an immune checkpoint inhibitor.
So those who tested positive for a biomarker for an MSI or TMB did better on a subsequent immune checkpoint inhibitor than they did on an initial taxane or a taxane rechallenge. So in this intrapatient analysis, actually immune checkpoint inhibitors are a disadvantage because they come in a later line compared to-- compared to docetaxel. And still, despite that, survival was better and improved on that subsequent line compared to the initial line.
Evan Yu: There weren't any patients that received really early checkpoint inhibitor, were there?
Nicolas Sayegh: No.
Evan Yu: OK. I'm interested in that because you probably have seen what's happening in colon cancer, where they're using it really early. And in prostate cancer literature out there with immune checkpoint inhibitors, even in this finely selected patient population, the response rates aren't 80%, 90%. They might be like 40% or something. And some of us have hypothesized that's just because it's used really, really late.
I'd be really curious to see what happens if you find the microsatellite instability or tumor mutational burden high status very early and treat them early, even before docetaxel. That would be great to have that. But it sounds like that wasn't available or just there aren't patients like that in this database.
Nicolas Sayegh: Yeah. We didn't find any of the patients like that. But I hope that could be an idea for some future trials where we can start-- when we start this immune checkpoint inhibitors a little sooner in the treatment sequencing, but also always based on some biomarkers and never blindly.
Evan Yu: Well, that's great. I mean, you have time. You're here at a new institution and you have a great new mentor, I believe Dr. Tian Zhang.
Nicolas Sayegh: Definitely. Yes.
Evan Yu: Right? So you could propose that as a possible future study to do. Of course, you'd have to have multi-institutions involved. It'd be tough for one center to pull off, but that might be something to consider, is the early use of a--
Nicolas Sayegh: Yes, that sounds like a great idea. Actually, I've been reading about some composite biomarkers that yielded some good response to immune checkpoint blockade, also dual immune checkpoint blockade, mainly when we're not basing ourselves on a single biomarker, but on a constellation of biomarkers, either genomic, clinical, or even immunologic or pathologic, to determine patients that would benefit best from those treatments.
Evan Yu: Great, great. All right. Well, hey, thanks for joining us today. Really, really interesting work. I'm always very impressed and motivated the fact that we're seeing more and more people earlier in their training coming to ASCO, I'm enthusiastic about that. We didn't used to have a lot of residents, et cetera, but you're not the first one I've interviewed here at ASCO 2025. So congratulations to you and your mentors for great work and looking forward to more to come from you.
Nicolas Sayegh: Thank you, doctor, for having me. It's my pleasure to be here.
Evan Yu: Good day. It's great to be here at UroToday again at ASCO 2025. And right now, I'm here with Dr. Nicolas Sayegh who's a second year resident at UT Southwestern. But prior to being at UT Southwestern, he did his postdoc at University of Utah Huntsman Cancer Institute and worked with Dr. Neeraj Agarwal, who we all know well. So today, we're going to be talking about the abstract that you're presenting here at ASCO. And it's looking at one of my favorite topics, which is looking at tumor mutational burden and looking at microsatellite instability.
And traditionally, we think about that with colon cancer because that's where you get the most press. But it does happen in prostate cancer. It happens in metastatic castration resistant prostate cancer. And yes, we can use things like pembrolizumab for that. So my understanding is that you looked at, especially tumor mutational burden and also microsatellite instability, the frequency in patients with prostate cancer and looked at response to different therapies. Is that right?
Nicolas Sayegh: Yes, that is right. So usually when we think about microsatellite instability, as well as tumor mutational burden in prostate cancer, we think of them going together.
Evan Yu: Right.
Nicolas Sayegh: So in our study, we try to separate them a little bit and try to dissect the characteristics of the smaller subset of patients that only have a high TMB without testing positive for a high MSI.
Evan Yu: Well, it does happen. I mean, I've seen it before where you have high TMB and you're not MSI high, but you're right. We usually think about it tying together. And we also think about it tying together with the mismatch repair genes, MSH2, MSH6, all those different gene alterations. Did you guys look at those as well?
Nicolas Sayegh: Yes. So we definitely looked at the genomic landscape for this small subset of patients of having TMB high without MSI high and compared it to the patients who do have MSI high. And in this small subset, we saw alterations that we usually expect in patients with high microsatellite instability or a mismatch repair deficiency, such as MSH2, MSH6, as well as tumor suppressor genes, such as TP53, PTEN, and other expected genes.
What was striking to us was the significant enrichment in the RAD21 gene that we saw in patients with TMB high without MSI high. Usually, this gene plays a role in the cohesin complex with the homologous recombination repair. So when this is inhibited, there is more proliferation, more error in DNA replication, and possibly potentially more neoantigen presentation. So a possible mechanism of enhanced response to immune checkpoint inhibitors in this setting.
Evan Yu: Great, great. So before we jump into the responses of immune checkpoint inhibitors and potentially other drugs, I think you looked at some other drugs in the responses as well. Why don't you start off with the 30,000 foot view of the study, how you designed it, what you actually looked at, where you got the clinical data, what testing technology, all that of stuff? So go ahead.
Nicolas Sayegh: Yeah. So what actually pushed us to go ahead with this study is all the different results and a little bit negative/disappointing results that we had with immune checkpoint inhibitors in mCRPC and notably in unselected populations. So different studies and big trials have been done. Immune checkpoint inhibitor monotherapies, immune checkpoint inhibitors combined with chemotherapy, such as docetaxel with ARPI, such as enzalutamide.
And in all those trials, the populations that were studied were all unselected for any biomarker, and all those studies were negative and did not show any advantage of adding immune checkpoint inhibitors to any standard of care.
Evan Yu: I'm very familiar with those.
Nicolas Sayegh: Yes. And it somehow is a little bit frustrating because we do feel that there is some potential in-- some potential to add or combine immune checkpoint inhibitors with something later on. So we try to characterize more the populations that would benefit from that. So our study is a composite study where we, like I said, try to characterize the TMB high population, also compared and expanded the comparative effectiveness of immune checkpoint inhibitors versus taxanes, or namely docetaxel or cabazitaxel, in later line therapies.
Because when patients usually exhaust all the previous lines and mCRPC, we tend to rechallenge them with the chemotherapy. So we try to do a small comparison with that. And something that we found a little bit pretty novel and striking that there is not much evidence about was MSI high detected in blood ctDNA. So we also tried to expand on that.
Evan Yu: OK. But you used Foundation Medicine. is that right?
Nicolas Sayegh: Yes.
Evan Yu: And their database. Is that correct? It wasn't all data from Utah. It was their big data-- national database.
Nicolas Sayegh: We actually do have a lot of data from Utah. But for this study, we did use Flatiron, which is a huge national database that was coupled with the Foundation Medicine database. So it's, on an individual level, very mindfully coupled the genomic and clinical data that helped us do this analysis, especially that Foundation is the actually FDA approved companion diagnostic for pembrolizumab in prostate cancer.
Evan Yu: Got it. OK. So give me the key findings. What did you find?
Nicolas Sayegh: The key findings, we definitely-- so we divided the patients in three groups. Let me take-- let me take a step back. To test for frequencies actually of TMB high and MSI high among patients with mCRPC, we selected those patients who have mCRPC in the Flatiron database. We had around 3,000 patients. And among those patients, the frequency of MSI high was close to 3% and TMB high was also 1.7%.
But all patients with MSI high were actually TMB high. The opposite was not true. We did have a small subset of patients with TMB high only, and this was our population of interest. So in terms of comparing--
Evan Yu: So let me clarify those numbers because your numbers for MSI high were higher than your TMB high. When you said the 1.7%, I think that was TMB high that was MSI non-high or-- let me clarify your numbers.
Nicolas Sayegh: Oh, yeah. My bad. My bad. I might have inverted both. So TMB high was 3.2% and MSI high was 1.7%.
Evan Yu: That makes sense.
Nicolas Sayegh: Yes, that makes sense. Thank you for catching that. So in terms of outcomes, all of those-- so 84 of those 3,000 patients were actually treated with single-agent pembrolizumab. And our outcomes were TTNT, time to next treatment, and overall survival.
Evan Yu: OK.
Nicolas Sayegh: So we divided those patients treated with immune checkpoint inhibitors in three subsets. The first subset was patients with MSI high with TMB high, TMB high without MSI high, and a third population with neither of both.
Evan Yu: Got it.
Nicolas Sayegh: So outcomes. So both the first two populations, MSI high with TMB high and TMB high without MSI high, had higher outcomes, better outcomes as we expected compared to those without those biomarkers. But also patients with TMB high only had same outcomes in terms of TTNT compared to those with MSI high and TMB high.
And what's even more striking is that in terms of overall survival, patients with only TMB high did better actually on single-agent pembrolizumab than patients with both MSI high and TMB high.
Evan Yu: Well, that's interesting. What do you think that is?
Nicolas Sayegh: Actually, we do not have a clear explanation for what we have. But I could hypothesize that most of these outcomes could be related to some genomic differences. In relation to the small sample size that we have, we cannot draw some definitive conclusions, but I do think that the mechanism could be in relationship to some homologous recombination genes or also some other tumor suppressor genes that we actually don't know about.
Evan Yu: Did you look at the cutoffs for TMB high? Like so, for instance, if the TMB high only patients were doing better, was it because their actual numerical TMB numbers were much higher than 10? Maybe they were very, very high. Even though they might not have been driven by traditional pathways, they came through microsatellite instability. So were you able to look at what those actual numbers were, and could that potentially explain why those patients did better?
Nicolas Sayegh: Yeah, unfortunately, we the sample size was pretty too small to categorize those patients. So we would go on an individual-- on a patient level basis, very individual patient level basis. So we were not able to draw any conclusions in terms of those. But in terms of the level, the threshold that we use for TMB high, we use the approved one related to the foundation sample.
Evan Yu: Yeah.
Nicolas Sayegh: Yeah.
Evan Yu: OK All right. Well, that's great. And then, in the ones that were TMB high but not MSI high, I'm most interested in that group, of course, were you able to discern what the actual drivers might have been for the high tumor mutational burden? Were there consistent findings on your sequencing data that you're like, aha, OK, a lot of them had PTEN alteration or PTEN and P53, or-- I'm just curious. I'm making this stuff up. But did you look at that and see if you could find any consistent messages there?
Nicolas Sayegh: We saw that they had similar enrichment in PTEN or TP53 and the tumor suppressor genes that we compared to their MSI high counterparts, but they did have a similar level of MSH2 and 6. However, the other microsatellite instability genes were not as enriched as the other counterparts, at the MSI high counterparts. So if this might have played a role, but from my opinion, it does not seem like it.
Some more drivers would be some other less known also tumor suppressor genes, like also AXL gene much less explored. So literature is pretty scarce compared to this in terms of this subpopulation. So we do-- yeah, we do need to expand this cohort. In the entire Flatiron database and Foundation database, we only found eight patients with high TMB without MSI high, so we're--
Evan Yu: So it's a small number.
Nicolas Sayegh: It's a very small number.
Evan Yu: OK. Were you able to say anything about other treatments, not just the IO treatments, but how did were there any interesting findings with response to docetaxel or anything else, androgen receptor pathway inhibitors or anything else?
Nicolas Sayegh: Yes. Actually, we tried to explore also the off-label use of immune checkpoint inhibitors and compare it with docetaxel in the setting. Sometimes in the community, some physicians are, as a last resort, sometimes use immune checkpoint inhibitors in patients that do not test positive for a high TMB or high MSI. And in this patient subset and this patient subpopulation, we did see that docetaxel had better outcomes.
However, in patients who tested positive for those, the difference was striking-- was very striking and there was a huge OS and both TTNT benefit between those treatments. Another thing is we did an intrapatient comparison where we compared the same patients who initially started on docetaxel, then were transitioned to an immune checkpoint inhibitor.
So those who tested positive for a biomarker for an MSI or TMB did better on a subsequent immune checkpoint inhibitor than they did on an initial taxane or a taxane rechallenge. So in this intrapatient analysis, actually immune checkpoint inhibitors are a disadvantage because they come in a later line compared to-- compared to docetaxel. And still, despite that, survival was better and improved on that subsequent line compared to the initial line.
Evan Yu: There weren't any patients that received really early checkpoint inhibitor, were there?
Nicolas Sayegh: No.
Evan Yu: OK. I'm interested in that because you probably have seen what's happening in colon cancer, where they're using it really early. And in prostate cancer literature out there with immune checkpoint inhibitors, even in this finely selected patient population, the response rates aren't 80%, 90%. They might be like 40% or something. And some of us have hypothesized that's just because it's used really, really late.
I'd be really curious to see what happens if you find the microsatellite instability or tumor mutational burden high status very early and treat them early, even before docetaxel. That would be great to have that. But it sounds like that wasn't available or just there aren't patients like that in this database.
Nicolas Sayegh: Yeah. We didn't find any of the patients like that. But I hope that could be an idea for some future trials where we can start-- when we start this immune checkpoint inhibitors a little sooner in the treatment sequencing, but also always based on some biomarkers and never blindly.
Evan Yu: Well, that's great. I mean, you have time. You're here at a new institution and you have a great new mentor, I believe Dr. Tian Zhang.
Nicolas Sayegh: Definitely. Yes.
Evan Yu: Right? So you could propose that as a possible future study to do. Of course, you'd have to have multi-institutions involved. It'd be tough for one center to pull off, but that might be something to consider, is the early use of a--
Nicolas Sayegh: Yes, that sounds like a great idea. Actually, I've been reading about some composite biomarkers that yielded some good response to immune checkpoint blockade, also dual immune checkpoint blockade, mainly when we're not basing ourselves on a single biomarker, but on a constellation of biomarkers, either genomic, clinical, or even immunologic or pathologic, to determine patients that would benefit best from those treatments.
Evan Yu: Great, great. All right. Well, hey, thanks for joining us today. Really, really interesting work. I'm always very impressed and motivated the fact that we're seeing more and more people earlier in their training coming to ASCO, I'm enthusiastic about that. We didn't used to have a lot of residents, et cetera, but you're not the first one I've interviewed here at ASCO 2025. So congratulations to you and your mentors for great work and looking forward to more to come from you.
Nicolas Sayegh: Thank you, doctor, for having me. It's my pleasure to be here.