JCO Precision Oncology Conversations

In this JCO PO Article Insights episode, host Jordan Goldstein summarizes the article, "Generic Protocols for Analytical Validation of Tumor-Informed Circulating Tumor DNA Assays for Molecular Residual Disease: The Blood Profiling Atlas in Cancer's Molecular Residual Disease Analytical Validation Working Group Consensus Recommendation" by Baden et al. TRANSCRIPT JCOPOAI 26E03 Jordan Goldstein: Hello, and welcome to JCO Precision Oncology Article Insights. I'm your host, Jordan Goldstein from Stanford University. Today we're discussing a consensus recommendation published in JCO Precision Oncology titled "Generic Protocols for Analytical Validation of Tumor-Informed Circulating Tumor DNA Assays for Molecular Residual Disease" by lead author Jonathan Baden, senior author Lauren Leiman, and colleagues on behalf of the BLOODPAC Consortium. The liquid biopsy space is one of the most exciting frontiers in oncology right now, with rapid development and many potential uses. However, the field has really lacked a shared framework for how these assays should actually be validated. This paper attempts to solve part of that problem. Before going further, I want to mention that BLOODPAC stands for Blood Profiling Atlas in Cancer Consortium. This was developed in 2016 with the goal of accelerating liquid biopsy development through shared standards. It includes the leading cancer diagnostics companies alongside academics, pharmaceutical companies, not for profits, and regulatory agencies. So, what actually is ctDNA MRD, and why does it matter? ctDNA is short for circulating tumor DNA, which is DNA shed by tumors into the bloodstream and can be detected by genomic profiling of a simple blood draw. Compared to tissue biopsies, it's minimally invasive, easily accessible, and can reflect the genetic diversity of the entire tumor across anatomic sites. This can allow for comprehensive genomic profiling, identifying target mutations, and understanding anatomic heterogeneity prior to treatment. It also allows for repeated sampling during and after treatment to explore evolutionary dynamics and, most promisingly, to detect molecular residual disease or MRD, which is what we focus on in this article. MRD is the presence of tumor-derived DNA in blood following therapy at levels below the threshold of conventional imaging or standard pathologic assessment. Accurate MRD detection can transform therapeutic strategies, enabling more precise risk-adapted approaches. But detecting MRD is not simple. There's often a very small amount of tumor DNA in plasma after treatment, even going below one part per million or 0.0001% of the total circulating DNA, most of which is healthy, normal, cell-free DNA. Detecting a signal that faint, reliably and reproducibly, is quite technically demanding. Tumor-informed ctDNA assays address this by first sequencing the patient's primary tumor to identify somatic variants that are unique to that cancer. A personalized panel is then constructed to track those exact variants in serial blood samples. This allows greater sensitivity. However, the methods and protocols for pre-analytical, analytical, and clinical validation for tumor-informed MRD assays can vary greatly. This presents major challenges for regulatory approval and clinical implementation. With these consensus recommendations in this article, BLOODPAC focuses on developing a standardized framework for the analytical validation of any tumor-informed ctDNA MRD assay. Analytical validation ensures these assays are in fact measuring what they claim to measure with defined performance characteristics. BLOODPAC intentionally set out to keep their protocols as generic as possible with the only requirements being intended uses of the assay for: one, patients with cancer who have undergone curative-intent therapy; and two, for prognosis, treatment efficacy, detection of residual disease or recurrence, or serving as the basis for a novel clinical trial strategy. With the goal of accelerating the clinical development and validation of tumor-informed MRD assays, BLOODPAC worked closely with the FDA throughout this process, holding three separate pre-submission meetings, precisely to ensure that assay developers who follow these protocols are well positioned for regulatory approval. Now, let's delve deeper into this paper and highlight the significant challenges of validating tumor-informed MRD assays. These challenges primarily stem from the low concentration of ctDNA found in the bloodstream. These levels can be further impacted by tumor characteristics such as tumor type, heterogeneity, histology, size, stage, and cell turnover or proliferative rate that can impact ctDNA shedding. One complex problem here is sampling heterogeneity or stochastic variation when looking for a single specific variant. When ctDNA is extremely low, a given variant may be present in one blood draw but may be absent in a replicate taken at the same time point, not because the biology changed, but due to random sampling effects at low levels. Tumor-informed assays handle this by evaluating MRD at the sample level rather than at the variant level. If enough variants from the personalized panel are detected collectively, the sample is called positive, even if no single variant is consistently detected. This is a strength for sensitivity, but it complicates traditional validation designs that assume consistent variant level assessments. Additionally, as we previously discussed, tumor-informed assays use personalized panels of mutations unique to the tumor to their advantage to improve their sensitivity. They filter out normal germline variants and non-tumor-derived somatic variants such as those from clonal hematopoiesis or CHIP. This leads to a smaller but highly specific assay. The smaller panel enables more targeted, deeper sequencing, focused on the most likely tumor-derived variants, and reduces the risk of false positives. However, the personalized nature also makes validation difficult because each patient's panel is different. For this, novel approaches are needed to really validate that key performance measures are acceptable and consistent. A final challenge here is the blood sample volume required for ctDNA detection at low levels. A standard blood draw simply doesn't yield enough ctDNA to support the extensive replication and dilution series that conventional analytical validation requires. To address this, test developers can use contrived samples, synthetic DNA sequences from a known cancer patient spiked at defined allele frequencies into healthy donor plasma. These serve as a surrogate for true clinical material when volumes are constrained. The test developer should then perform a contrived sample functional characterization study to demonstrate to the FDA that the contrived samples actually perform equivalently to real clinical specimens. So now that we've actually covered some of the major challenges here, let's dig into the analytical validation protocols that are recommended for the seven key performance characteristics that are defined in this paper. The first two performance characteristics, limit of blank and limit of detection, focus on establishing the analytical performance of the assay, which is the assay's ability to detect a known signal when present in the sample or vice versa. To be clear, this is distinct from the clinical performance, which is defined by the assay's ability to correctly identify patients who do or do not have residual cancer and ultimately relapse. The first performance metric is limit of blank or LOB. This is the analytical specificity, or the highest signal expected in a sample that does not contain tumor DNA. To establish this, BLOODPAC suggests using a minimum of 60 blank samples from healthy donors, in a minimum of two replicates with two reagent lots and multiple panel designs across a range of DNA inputs. Then, the LOB should be set to zero and 60 blank samples should again be tested to determine the false positive rate on a per-sample basis. Typically, the LOB represents the 95th percentile of signal observed in samples without tumor variants, also known as the background signal. The limit of detection or LOD, on the other hand, is the analytical sensitivity, or the lowest concentration of tumor-derived molecules that can be reliably detected in a sample. To establish the LOD, an appropriate number of low allele fraction contrived positive samples or specimen blend panels should be tested in five different dilution levels with a minimum of 10 replicates per dilution level. Two reagent lots must be used with each testing across these 50 measurements. If developers are to use a probit regression model approach to determine the LOD, they should use at least 100 of these measurements. The LOD is ultimately determined as the tumor concentration corresponding to a 95% hit rate. The next two performance metrics prove the accuracy and precision of the assay. The analytical accuracy is how often the assay correctly identifies positive and negative samples. This should be determined by testing a minimum of 100 specimens, ideally from a clinical trial or procured from clinical care that are known to be negative for ctDNA, as well as 10 to 20 cancer positive samples. From this, the sample level percent positive, percent negative, and overall agreement can be used to determine the accuracy. Precision of the assay is determined in two different ways: repeatability and reproducibility, using true patient samples. Repeatability assesses the intra-assay precision. It is measured by assessing the consistency of the assay under the same operating conditions over a short period. For this, multiple samples are tested in replicates of two, using a single operator and single testing site with a minimum 20-day testing interval for 80 total observations. Reproducibility, on the other hand, measures the inter-assay precision. This evaluates the assay's performance across different variables to ensure stable results. To validate this, positive samples at or near the LOD and at least one negative sample need to be included. Then, a minimum of two operators, three manufacturer reagent lots, and two technical replicates per sample per run must be assessed again spanning at least a 20-day interval. Agreement metrics are calculated based on the assay's binary output, detected or undetected, for both to establish the precision of the assay. The final three performance characteristics focus on demonstrating the durability of the assay under stress. This includes measuring interfering substances, robustness, and the prepared specimen stability. All of these can be validated using pooled patient or contrived samples. Interfering substances are evaluated by spiking known clinical interference into ctDNA positive and negative samples. Robustness, also known as guard banding, intentionally perturbs critical steps in collection or NGS processing to validate operational guardrails. Stability testing evaluates specimen viability using three positive specimens near the LOD and one negative baseline at 3-month intervals up to the desired stability claim. You may have noticed that analytical validation for each of these seven performance characteristics requires multi-variable studies varying tumor fraction, lots, operators, and instruments and would demand massive sample volumes that go far beyond what's clinically realistic. BLOODPAC addresses this by endorsing fractional factorial designs. These reduce the number of replicates per clinical sample by modeling performance characterization of the tumor-informed MRD assay across a spectrum of tumor fractions and inputs. When sample yields are too low for multiple replicates of a sample, using more diverse clinical samples can allow maintenance of degrees of freedom and statistical robustness without exhausting the material. It's worth noting that analytical validation is just one very important piece of the puzzle. Many other aspects can affect ctDNA assay performance that are not addressed in this paper including pre-analytical aspects such as sample collection, genomic profiling, bioinformatics software, and CHIP processing, as well as clinical aspects, which also require adequate testing and validation. Ultimately, these consensus recommendations from BLOODPAC for analytical validation of tumor-informed ctDNA MRD assays are much needed. They should lead to faster clinical validation and regulatory approval, getting these vital, highly sensitive MRD assays into clinical trials and ultimately to patients. For clinicians, it provides a concrete lens for evaluating the performance claims of commercially available ctDNA MRD assays. If you're interested in learning more about the details of these protocols for analytical validation, I highly encourage you to read the full article at JCO Precision Oncology. Thank you for joining me at JCO Precision Oncology Article Insights. Please subscribe and join us next time as we explore groundbreaking research shaping the future of precision oncology. The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.

JCO PO author Dr. Foldi at UPMC Hillman Cancer Center and University of Pittsburgh School of Medicine shares insights into the JCO PO article, "Personalized Circulating Tumor DNA Testing for Detection of Progression and Treatment Response Monitoring in Patients With Metastatic Invasive Lobular Carcinoma of the Breast." Host Dr. Rafeh Naqash and Dr. Foldi discuss how serial ctDNA testing in patients with mILC is feasible and may enable personalized surveillance and real-time therapeutic monitoring. TRANSCRIPT Dr. Rafeh Naqash: Hello, and welcome to JCO Precision Oncology Conversations, where we bring you engaging conversations with authors of clinically relevant and highly significant JCO PO articles. I am your host, Dr. Rafeh Naqash, podcast editor for JCO Precision Oncology and Associate Professor at the OU Health Stephenson Cancer Center at the University of Oklahoma. Today, we are thrilled to be joined by Dr. Julia Foldi, Assistant Professor of Medicine in the Division of Hematology-Oncology at University of Pittsburgh School of Medicine and the Magee-Womens Hospital of the UPMC. She is also the lead and corresponding author of the JCO Precision Oncology article entitled "Personalized Circulating Tumor DNA Testing for Detection of Progression and Treatment Response Monitoring in Patients with Metastatic Invasive Lobular Carcinoma of the Breast." At the time of this recording, our guest's disclosures will be linked in the transcript. Julia, welcome to our podcast, and thank you for joining us today. Dr. Julia Foldi: Thank you so much for having me. It is a pleasure. Dr. Rafeh Naqash: Again, your manuscript and project address a few interesting things, so we will start with the basics, since we have a broad audience that comprises trainees, community oncologists, and obviously precision medicine experts as well. So, let us start with invasive lobular breast carcinoma. I have been out of fellowship for several years now, and I do not know much about invasive lobular carcinoma. Could you tell us what it is, what some of the genomic characteristics are, why it is different, and why it is important to have a different way to understand disease biology and track disease status with this type of breast cancer? Dr. Julia Foldi: Yes, thank you for that question. It is really important to frame this study. So, lobular breast cancers, which we shorten to ILC, are the second most common histologic subtype of breast cancer after ductal breast cancers. ILC makes up about 10 to 15 percent of all breast cancers, so it is relatively rare, but in the big scheme of things, because breast cancer is so common, this represents actually over 40,000 new diagnoses a year in the US of lobular breast cancers. What is unique about ILC is it is characterized by loss of an adhesion molecule, E-cadherin. It is encoded by the CDH1 gene. What it does is these tumors tend to form discohesive, single-file patterns and infiltrate into the tumor stroma, as opposed to ductal cancers, which generally form more cohesive masses. As we generally explain to patients, ductal cancers tend to form lumps, while lobular cancers often are not palpable because they infiltrate into the stroma. This creates several challenges, particularly when it comes to imaging. In the diagnostic setting, we know that mammograms and ultrasounds have less sensitivity to detect lobular versus ductal breast cancer. When it comes to the metastatic setting, conventional imaging techniques like CT scans have less sensitivity to detect lobular lesions often. One other unique characteristic of ILC is that these tumors tend to have lower proliferation rates. Because our glucose-based PET scans depend on glucose uptake of proliferating cells, often these tumors also are not avid on conventional FDG-PET scans. It is a challenge for us to monitor these patients as they go through treatment. If you think about the metastatic setting, we start a new treatment, we image people every three to four cycles, about every three months, and we combine the imaging results with clinical assessment and tumor markers to decide if the treatment is working. But if your imaging is not reliable, sometimes even at diagnosis, to really detect these tumors, then really, how are we following these patients? This is really the unique challenge in the metastatic setting in patients with lobular breast cancer: we cannot rely on the imaging to tell if patients are responding to treatment. This is where liquid biopsies are really, really important, and as the field is growing up and we have better and better technologies, lobular breast cancer is going to be a field where they are going to play an important role. Dr. Rafeh Naqash: Thank you for that easy-to-understand background. The second aspect that I would like to have some context on, to help the audience understand why you did what you did, is ctDNA, tumor informed and non-informed. Could you tell us what these subtypes of liquid biopsies are and why you chose a tumor informed assay for your study? Dr. Julia Foldi: Yes, it is really important to understand these differences. As you mentioned, there are two main platforms for liquid biopsy assays, circulating tumor DNA assays. I think what is more commonly used in the metastatic setting are non-tumor informed assays, or agnostic assays. These are generally next-generation sequencing-based assays that a lot of companies offer, like Guardant, Tempus, Caris, and FoundationOne. These do not require tumor tissue; they just require a blood sample, a plasma sample, essentially. The next-generation sequencing is done on cell-free DNA that is extracted from the plasma, and it is looking for any cell-free DNA and essentially, figuring out what part of the cell-free DNA comes from the tumor is done through a bioinformatics approach. Most of these assays are panel tests for cancer-associated mutations that we know either have therapeutic significance or biologic significance. So, the results we receive from these tests generally read out specific mutations in oncogenic genes, or sometimes things like fusions where we have specific targeted drugs. Some of the newer assays can also read out tumor fraction; for example, the newest generation Guardant assay that is methylation-based, they can also quantify tumor fraction. But the disadvantage of the tumor agnostic approach is that it is a little bit less sensitive. Opposed to that, we have our tumor informed tests, and these require tumor tissue. Essentially, the tumor is sequenced; this can either be whole exome or whole genome sequencing. The newer generation assays are now using whole genome sequencing of the tumor tissue, and a personalized, patient-specific panel of alterations is essentially barcoded on that tumor tissue. This can be either structural variants or it can be mutations, but generally, these are not driver mutations, but sort of things that are present in the tumor tissue that tend to stay unchanged over time. For each particular patient, a personalized assay, if you want to call it a fingerprint or barcode, is created, and then that is what then is used to test the plasma sample. Essentially, you are looking for that specific cancer in the blood, that barcode or fingerprint in the blood. Because of this, this is a much more sensitive way of looking for ctDNA, and obviously, this detects only that particular tumor that was sequenced originally. So, it is much more sensitive and specific to that tumor that was sequenced. You can argue for both approaches in different settings. We use them in different settings because they give us different information. The tumor agnostic approach gives us mutations, which can be used to determine what the next best therapy to use is, while the tumor informed assay is more sensitive, but it is not going to give us information on therapeutic targets. However, it is quantified, and we can follow it over time to see how it changes. We think that it is going to tell us how patients respond to treatment because we see our circulating tumor DNA levels rise and fall as the cancer burden increases or decreases. We decided to use the tumor informed approach in this particular study because we were really interested in how to determine if patients are having response to treatment versus if they are going to progress on their treatment, more so than looking for specific mutations. Dr. Rafeh Naqash: When you think about these tumor informed assays and you think about barcoding the mutations on the original tumor that you try to track or follow in subsequent blood samples, plasma samples, in your experience, if you have done it in non-lobular cancers, do you think shedding from the tumor has something to do with what you capture or how much you capture? Dr. Julia Foldi: Absolutely. I think there are multiple factors that go into whether someone has detectable ctDNA or not, and that has to do with the type of cancer, the location, right, where is the metastatic site? This is something that we do not fully understand yet: what are tumors that shed more versus not? There is also clearance of ctDNA, and so how fast that clearance occurs is also something that will affect what you can detect in the blood. ctDNA is very short-lived, only has a half-life of hours, and so you can imagine that if there is little shedding and a lot of excretion, then you are not going to be detecting a lot of it. In general, in the metastatic setting, we see that we can detect ctDNA in a lot of cases, especially when patients are progressing on treatment, because we imagine their tumor burden is higher at that point. Even with the non-tumor informed assays, we detect a lot of ctDNA. Part of this study was to actually assess: what is the proportion of patients where we can have this information? Because if we are only going to be able to detect ctDNA in less than 50 percent of patients, then it is not going to be a useful method to follow them with. Because this field is new and we have not been using a lot of tumor informed assays in the metastatic setting, we did not really know what to expect when we set out to look at this. We did not know what was going to be the baseline detection rate in this patient population, so that was one of the first things that we wanted to answer. Dr. Rafeh Naqash: Excellent. Now going to this manuscript in particular, what was the research question, what was the patient population, and what was the strategy that you used to investigate some of these questions? Dr. Julia Foldi: So, we partnered with Natera, and the reason was that their Signatera tumor-informed assay was the first personalized, tumor-informed, really an MRD assay, minimal residual disease detection assay. It has been around the longest and has been pretty widely used commercially already, even though some of our data is still lacking. but we know that people are using this in the real world. We wanted to gather some real-world data specifically in lobular patients. So, we asked Natera to look at their database of commercial Signatera testing and look for patients with stage 4 lobular breast cancer. The information all comes from the submitting physicians sending in pathologic reports and clinical notes, and so they have that information from the requisitions essentially that are sent in by the ordering physician. We found 66 patients who were on first-line or close to first-line endocrine-based therapies for their metastatic lobular breast cancer and had serial collections of Signatera tests. The way we defined baseline was that the first Signatera had to be sent within three months of starting treatment. So, it is not truly baseline, but again, this is a limitation of looking at real-world data is that you are not always going to get the best time point that you need. We had over 350 samples from those 66 patients, again longitudinal ctDNA samples, and our first question was what is the baseline detection rate using this tumor informed assay? Then, most importantly, what is the concordance between changes in ctDNA and clinical response to treatment? That is defined by essentially radiologic response to treatment. Dr. Rafeh Naqash: Interesting. So, what were some of your observations in terms of ctDNA dynamics, whether baseline levels made a difference, whether subsequent levels at different time points made a difference, or subsequent levels at, let us say, cycle three made a difference? Were there any specific trends that you saw? Dr. Julia Foldi: So, first, at baseline, 95 percent of patients had detectable ctDNA, which is, I think, a really important data point because it tells us that this can be a really useful test. If we can detect it in almost all patients before they start treatment, we are going to be able to follow this longitudinally. And again, these were not true baseline samples. So, I think if we look really at baseline before starting treatment, almost all patients will have detectable ctDNA in the metastatic setting. The second important thing we saw was that disease progression correlated very well with increase in ctDNA. So, in most patients who had disease progression by imaging, we saw increase in ctDNA. Conversely, in most patients who had clinical benefit from their treatment, so they had a response or stable disease, we saw decrease in ctDNA levels. It seems that what we call molecular response based on ctDNA is tracking very nicely along with the radiographic response. So, those were really the two main observations. Again, this is a small cohort, limited by its real-world nature and the time points that ctDNA assay was sent was obviously not mandated. This is a real-world data set, and so we could not really look at specific time points like you asked about, let us say, cycle three of therapy, right? We did not have all of the right time points for all of the patients. But what we were able to do was to graph out some specific patient scenarios to illustrate how changes in ctDNA correlate with imaging response. I can talk a little bit about that. Dr. Rafeh Naqash: That was going to be my question. Did you see patients who had serial monitoring using the tumor informed ctDNA assay where the assay became positive a few months before the imaging? Did you have any of those kinds of observations? Dr. Julia Foldi: Yes, so I think this is where the field is going: are we able to use this technology to maybe detect progression before it becomes clinically apparent? Of course, there are lots of questions about: does that really matter? But it seems like, based on some of the patient scenarios that we present in the paper, that this testing can do that. So, we had a specific scenario, and this is illustrated in a figure in the paper, really showing the treatment as well as the changes in ctDNA, tumor markers, and also radiographic response. So, this particular patient was on first-line endocrine therapy and CDK4/6 inhibitor with palbociclib. Initially, she had a low-level detectable ctDNA. It became undetectable during treatment, and the patient had a couple of serial ctDNA assays that were negative, so undetectable. And then we started, after about seven months on this combination therapy, the ctDNA levels started rising. She actually had three serial ctDNA assays with increasing level of ctDNA before she even had any imaging tests. And then around the time that the ctDNA peaked, this patient had radiographic evidence of progression. There was also an NGS-based assay sent to look for specific mutations at that point. The patient was found to have an ESR1 mutation, which is very common in this patient population. She was switched to a novel oral SERD, elacestrant, and the ctDNA fell again to undetectable within the first couple months of being on elacestrant. And then a very similar thing happened: while she was on this second-line therapy, she had three serial negative ctDNA assays, and then the fourth one was positive. This was two months before the patient had a scan that showed progression again. Dr. Rafeh Naqash: And Julia, like you mentioned, this is a small sample size, limited number of patients, in this case, one patient case scenario, but provides insights into other important aspects around escalation or de-escalation of therapy where perhaps ctDNA could be used as an integral biomarker rather than an exploratory biomarker. What are some of your thoughts around that and how is the breast cancer space? I know like in GI and bladder cancer, there has been a significant uptrend in MRD assessments for therapeutic decision making. What is happening in the breast cancer space? Dr. Julia Foldi: So, super interesting. I think this is where a lot of our different fields are going. In the breast cancer space, so far, I have seen a lot of escalation attempts. It is not even necessarily in this particular setting where we are looking at dynamics of ctDNA, but in the breast cancer world, of course, we have a lot of data on resistance mutations. I mentioned ESR1 mutation in a particular patient in our study. ESR1 mutations are very common in patients with ER-positive breast cancer who are on long-term endocrine therapy, and ESR1 mutations confer resistance to aromatase inhibitors. So, that is an area that there has been a lot of interest in trying to detect ESR1 mutations earlier and switching therapy early. So, this was the basis of the SERENA-6 trial, which was presented last year at ASCO and created a lot of excitement. This was a trial where patients had non-tumor-informed NGS-based Guardant assay sent every three to six months while they were on first-line endocrine therapy with a CDK4/6 inhibitor. If they had an ESR1 mutation detected, they were randomized to either continue the same endocrine therapy or switch to an oral SERD. The trial showed that the population of patients who switched to the oral SERD did better in terms of progression-free survival than those who stayed on their original endocrine therapy. There are a lot of questions about how to use this in routine practice. Of course, it is not trivial to be sending a ctDNA assay every three to six months. The rate of detection of these mutations was relatively low in that study; again, the incidence increases in later lines of therapy. So, there are a lot of questions about whether we should be doing this in all of our first-line patients. The other question is, even the patients who stayed on their original endocrine therapy were able to stay on that for another nine months. So, there is this question of: are we switching patients too early to a new line of therapy by having this escalation approach? So, there are a lot of questions about this. As far as I know, at least in our practice, we are not using this approach just yet to escalate therapy. Time will tell how this all pans out. But I think what is even more interesting is the de-escalation question, and I think that is where tumor informed assays like Signatera and the data that our study generated can be applied. Actually, our plan is to generate some prospective data in the lobular breast cancer population, and I have an ongoing study to do that, to really be able to tease out the early ctDNA dynamics as patients first start on endocrine therapy. So, this is patients who are newly diagnosed, they are just starting on their first-line endocrine therapy, and measure, with sensitive assays, measure ctDNA dynamics in the first few months of therapy. In those patients who have a really robust response, that is where I think we can really think about de-escalation. In the patients whose ctDNA goes to undetectable after just a few weeks of therapy with just an endocrine agent, they might not even need a CDK4/6 inhibitor in their first-line treatment. So, that is an area where we are very interested in our group, and I know that other groups are looking at this too, to try to de-escalate therapy in patients who clear their ctDNA early on. Dr. Rafeh Naqash: Thank you so much. Well, lots of questions, but at the same time, progress comes through questions asked, and your project is one of those which is asking an interesting question in a rarer cancer and perhaps will lead to subsequent improvement in how we monitor these individuals and how we escalate or de-escalate therapy. Hopefully, we will get to see more of what you are working on in subsequent submissions to JCO Precision Oncology and perhaps talk more about it in a couple of years and see how the space and field is moving. Thanks again for sharing your insights. I do want to take one to two quick minutes talking about you as an investigator, Julia. If you could speak to your career pathway, your journey, the pathway to mentorship, the pathway to being a mentor, and how things have shaped for you in your personal professional growth. Dr. Julia Foldi: Sure, yeah, that is great. Thank you. So, I had a little bit of an unconventional path to clinical medicine. I actually thought I was going to be a basic scientist when I first started out. I got a PhD in Immunology right out of college and was studying not even anything cancer-related. I was studying macrophage signaling in inflammatory diseases, but I was in New York City. This was right around the time that the first checkpoint inhibitors were approved. Actually, some of my friends from my PhD program worked in Jim Allison's lab, who was the basic scientist responsible for ipilimumab. So, I got to kind of first-hand experience the excitement around bringing something from the lab into the clinic that actually changed really the course of oncology. And so, I got very excited about oncology and clinical medicine. So, I decided to kind of switch gears from there and I went back to medical school after finishing my PhD and got my MD at NYU. I knew I wanted to do oncology, so I did a research track residency and fellowship combined at Yale. I started working early on with the breast cancer team there. At the time, Lajos Pusztai was the head of translational research there at Yale, and I started working with him early in my residency and then through my fellowship. I worked on several trials with him, including a neoadjuvant checkpoint inhibitor trial in triple-negative breast cancer patients. During my last year in fellowship, I received a Conquer Cancer Young Investigator Award to study estrogen receptor heterogeneity using spatial transcriptomics in this subset of breast cancers that have intermediate estrogen receptor expression. From there, I joined the faculty at the University of Pittsburgh in 2022. So, I have been there about almost four years at this point. My interests really shifted slowly from triple-negative breast cancers towards ER-positive breast cancers. When I arrived in Pittsburgh, I started working very closely with some basic and translational researchers here who are very interested in estrogen signaling and mechanisms of resistance to endocrine therapy, and there is a large group here interested in lobular breast cancers. During my training, I was not super aware even that lobular breast cancer was a unique subtype of breast cancers, and that is, I think, changing a little bit. There is a lot more awareness in the breast cancer clinical and research community about ILC being a unique subtype, but it is not even really part of our training in fellowship, which we are trying to change. But I have become a lot more aware of this because of the research team here and through that, I have become really interested also on the clinical side. And so, we do have a Lobular Breast Cancer Research Center of Excellence here at the University of Pittsburgh and UPMC, and I am the leader on the clinical side. We have a really great team of basic and translational researchers looking at different aspects of lobular breast cancers, and some of the work that I am doing is related to this particular manuscript we discussed and the next steps, as I mentioned, a prospective study of early ctDNA dynamics in lobular patients. I also did some more clinical research work in collaboration with the NSABP looking at long-term outcomes of patients with lobular versus ductal breast cancers in some of their older trials. And so, that is, in a nutshell, a little bit about how I got here and how I became interested in ILC. Dr. Rafeh Naqash: Well, thank you for sharing those personal insights and personal journey. I am sure it will inspire other trainees, fellows, and perhaps junior faculty in trying to find their niche. The path, as you mentioned, is not always straight; it often tends to be convoluted. And then finding an area that you are interested in, taking things forward, and being persistent is often what matters. Dr. Julia Foldi: Thank you so much for having me. It was great. Dr. Rafeh Naqash: It was great chatting with you. And thank you for listening to JCO Precision Oncology Conversations. Don't forget to give us a rating or review, and be sure to subscribe so you never miss an episode. You can find all ASCO shows at asco.org/podcasts. The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.

JCO PO author Dr. Wainberg at UCLA shares insights into the JCO PO article, "Prevalence of FGFR2b Protein Overexpression in Advanced Gastric Cancers During Prescreening for the Phase III FORTITUDE-101 Trial." Host Dr. Rafeh Naqash and Dr. Wainberg discuss how FGFR2b prevalence was similar across geographic regions and within defined patient and sample variables regardless of the level of expression. TRANSCRIPT TO COME

JCO PO author Dr. Shilpa Gupta at Cleveland Clinic Children's Hospital shares insights into her article, "Fibroblast Growth Factor Receptor 3 (FGFR3) Alteration Status and Outcomes on Immune Checkpoint Inhibitors (ICPI) in Patients with Metastatic Urothelial Carcinoma". Host Dr. Rafeh Naqash and Dr. Gupta discuss how FGFR3 combined with TMB emerged as a biomarker that may be predictive for response to ICPI in mUC. TRANSCRIPT Dr. Rafeh Naqash: Hello and welcome to JCO Precision Oncology Conversations, where we bring you engaging conversations with authors of clinically relevant and highly significant JCO PO articles. I'm your host, Dr. Rafeh Naqash, podcast editor for JCO Precision Oncology and Associate Professor at the OU Health Stephenson Cancer Center. Today I am excited to be joined by Dr. Shilpa Gupta, Director of Genitourinary Medical Oncology at the Cancer Institute and co-leader of the GU Oncology Program at the Cleveland Clinic, and also lead author of the JCO PO article titled "Fibroblast Growth Factor Receptor 3 Alteration Status and Outcomes on Immune Checkpoint Inhibitors in Patients With Metastatic Urothelial Carcinoma." At the time of this recording, our guest's disclosures will be linked in the transcript. Shilpa, welcome again to the podcast. Thank you for joining us today. Dr. Shilpa Gupta: Thank you, Rafeh. Honor to be here with you again. Dr. Rafeh Naqash: It is nice to connect with you again after two years, approximately. I think we were in our infancy of our JCO PO podcast when we had you first time, and it has been an interesting journey since then. Dr. Shilpa Gupta: Absolutely. Dr. Rafeh Naqash: Well, excited to talk to you about this article that you published. Wanted to first understand what is the genomic landscape of urothelial cancer in general, and why should we be interested in FGFR3 alterations specifically? Dr. Shilpa Gupta: Bladder cancer or urothelial cancer is a very heterogeneous cancer. And while we find there is a lot of mutations can be there, you know, like BRCA1, 2, in HER2, in FGFR, we never really understood what is driving the cancer. Like a lot of old studies with targeted therapies did not really work. For example, we think VEGF can be upregulated, but VEGF inhibitors have not really shown definite promise so far. Now, FGFR3 receptor is the only therapeutic target so far that has an FDA approved therapy for treating metastatic urothelial cancer patients, and erdafitinib was approved in 2019 for patients whose tumors overexpressed FGFR3 mutations, alterations, or fusions. And in the landscape of bladder cancer, it is important because in patients with non-muscle invasive bladder cancer, about 70 to 80% patients can have this FGFR3. But as patients become metastatic, the alterations are seen in, you know, only about 10% of patients. So the clinical trials that got the erdafitinib approved actually used archival tumor from local cancer. So when in the real world, we don't see a lot of patients if we are trying to do metastatic lesion biopsies. And why it is important to know this is because that is the only targeted therapy available for our patients right now. Dr. Rafeh Naqash: Thank you for giving us that overview. Now, on the clinical side, there is obviously some interesting data for FGFR3 on the mutation side and the fusion side. In your clinical practice, do you tend to approach these patients differently when you have a mutation versus when you have a fusion? Dr. Shilpa Gupta: We can use the treatment regardless of that. Dr. Rafeh Naqash: I recently remember I had a patient with lung cancer, squamous lung cancer, who also had a synchronous bladder mass. And the first thought from multiple colleagues was that this is metastatic lung. And interestingly, the liquid biopsy ended up showing an FGFR3-TACC fusion, which we generally don't see in squamous lung cancers. And then eventually, I was able to convince our GU colleagues, urologists, to get a biopsy. They did a transurethral resection of this tumor, ended up being primary urothelial and synchronous lung, which again, going back to the FGFR3 story, I saw in your paper there is a mention of FGFR3-TACC fusions. Anything interesting that you find with these fusions as far as biology or tumor behavior is concerned? Dr. Shilpa Gupta: We found in our paper of all the patients that were sequenced that 20% had the pathognomonic FGFR3 alteration, and the most common were the S249C, and the FGFR3-TACC3 fusion was in 45 patients. And basically I will say that we didn't want to generate too much as to fusion or the differences in that. The key aspect of this paper was that historically there were these anecdotal reports saying that patients who have FGFR alterations or mutations, they may not respond well to checkpoint inhibitors because they have the luminal subtype. And these were backed by some preclinical data and small anecdotal reports. But since then, we have seen that, and that's why a lot of people would say that if somebody's tumor has FGFR3, don't give them immunotherapy, give them erdafitinib first, right? So then we had this Phase 3 trial called the THOR trial, which actually showed that giving erdafitinib before pembrolizumab was not better. That debunked that myth, and we are actually reiterating that because in our work we found that patients who had FGFR3 alterations or fusions, and if they also have TMB-high, they actually respond very well to single agent immunotherapy. And that is, I think, very important because it tells us that we are not really seeing that so-called potential of resistance to immunotherapy in these patients. So to answer your question, yeah, we did see those differences, but I wouldn't say that any one marker is more prominent. Dr. Rafeh Naqash: The analogy is kind of similar to what we see in lung cancer with these mutations called STK11/KEAP1, which are also present in some other tumors. And one of the questions that I don't think has been answered is when you have in lung cancer, if you extrapolate this, where doublet or single agent immunotherapy doesn't do as well in tumors that are STK11 mutated. But then if you have a high TMB, question is does that TMB supersede or trump the actual mutation? Could that be one reason why you see the TMB-high but FGFR3 altered tumors in your dataset responding or having better outcomes to immunotherapy where potentially there is just more neoantigens and that results in a more durable or perhaps better response to checkpoint therapy? Dr. Shilpa Gupta: It could be. But you know, the patients who have FGFR alterations are not that many, right? So we have already seen that just patients with TMB-high respond very well to immunotherapy. Our last podcast was actually on that, regardless of PD-L1 that was a better predictor of response to immunotherapy. So I think it's not clear if this is adding more chances of response or not, because either way they would respond. But what we didn't see, which was good, that if they had FGFR3, it's not really downplaying the fact that they have TMB-high and that patients are not responding to immunotherapy. So we saw that regardless, and that was very reassuring. Dr. Rafeh Naqash: So if tomorrow in your clinic you had an individual with an FGFR3 alteration but TMB-high, I guess one could be comfortable just going ahead with immunotherapy, which is what the THOR trial as you mentioned. Dr. Shilpa Gupta: Yes, absolutely. And you know, when you look at the toxicity profiles of pembrolizumab and erdafitinib, really patients really struggle with using the FGFR3 inhibitors. And of course, if they have to use it, we have to, and we reserve it for patients. But it's not an easy drug to tolerate. Currently the landscape is such that, you know, frontline therapy has now evolved with an ADC and immunotherapy combinations. So really if patients progress and have FGFR3 alterations, we are using erdafitinib. But let's say if there were a situation where a patient has had chemotherapy, no immunotherapy, and they have FGFR3 upregulation and TMB-high, yes, I would be comfortable with using only pembrolizumab. And that really ties well together what we saw in the THOR trial as well. Dr. Rafeh Naqash: Going to the clinical applications, you mentioned a little bit of this in the manuscript, is combination therapies. You alluded to it a second back. Everything tends to get combined with checkpoint therapy these days, as you've seen with the frontline urothelial, pembrolizumab with an ADC. What is the landscape like as far as some of these FGFR alterations are concerned? Is it reasonable to combine some of those drugs with immune checkpoint therapy? And what are some of the toxicity patterns that you've potentially seen in your experience? Dr. Shilpa Gupta: So there was indeed a trial called the NORSE trial. It was a randomized trial but not a comparative cohort, where they looked at FGFR altered patients. And when they combined erdafitinib plus cetrelimab, that did numerically the response rates were much higher than those who got just erdafitinib. So yeah, the combination is definitely doable. There is no overlapping toxicities. But unfortunately that combination has not really moved forward to a Phase 3 trial because it's so challenging to enroll patients with such kind of rare mutations on large trials, especially to do registration trials. And since then the frontline therapy has evolved to enfortumab vedotin and pembrolizumab. I know there is an early phase trial looking at a next generation FGFR inhibitor. There is a triplet combination looking in Phase 1 setting with a next generation FGFR inhibitor with EV-pembro. However, it's not a randomized trial. So you know, I worry about such kinds of combinations where we don't have a path for registration. And in the four patients that have been treated, four or five patients in the early phase as a part of basket trial, the toxicities were a lot, you know, when you combine the EV-pembro and an FGFR3 inhibitor, we see more and more toxicity. So the big question is do we really need the "kitchen sink" approach when we have a very good doublet, or unless the bar is so high with the doublet, like what are we trying to add at the expense of patient toxicity and quality of life is the big question in my mind. Dr. Rafeh Naqash: Going back to your manuscript specifically, there could be a composite biomarker. You point out like FGFR in addition to FGFR TMB ends up being predictive prognostic there. So that could potentially be used as an approach to stratify patients as far as treatment, whether it's a single agent versus combination. Maybe the TMB-low/FGFR3 mutated require a combination, but the TMB-high/FGFR mutated don't require a combination, right? Dr. Shilpa Gupta: No, that's a great point, yeah. Dr. Rafeh Naqash: But again, very interesting, intriguing concepts that you've alluded to and described in this manuscript. Now, a quick take on how things have changed in the bladder cancer space in the last two years. We did a podcast with you regarding some biomarkers as you mentioned two years back. So I really would like to spend the next minute to two to understand how have things changed in the bladder cancer space? What are some of the exciting things that were not there two years back that are in practice now? And how do you anticipate the next two years to be like? Maybe we'll have another podcast with you in another two years when the space will have changed even more. Dr. Shilpa Gupta: Certainly a lot has happened in the two years, you know. EV-pembro became the universal frontline standard, right? We have really moved away from cisplatin eligibility in metastatic setting because anybody would benefit from EV-pembro regardless of whether they are candidates for cisplatin or not, which historically was relevant. And just two days ago, we saw that EV-pembro has now been approved for localized bladder cancer for patients who are cisplatin ineligible or refusing. So, you know, this very effective regimen moving into earlier setting, we now have to really think of good treatment options in the metastatic setting, right? So I think that's where a lot of these novel combinations may come up. And what else we've seen is in a tumor agnostic trial called the DESTINY-PanTumor trial, patients who had HER2 3+ on immunohistochemistry, we saw the drug approval for T-DXd, and I think that has kind of reinvigorated the interest in HER2 in bladder cancer, because in the past targeting HER2 really didn't work. And we still don't know if HER2 is a driver or not. And at ESMO this year, we saw an excellent study coming out of China with DV which is targeting HER2, and toripalimab, which is a Chinese checkpoint inhibitor, showing pretty much similar results to what we saw with EV-pembro. Now, you know, not to do cross-trial comparisons, but that was really an amazing, amazing study. It was in the presidential session. And I think the big question is: does that really tell us that HER2-low patients will not benefit? Because that included 1+, 2+, 3+. So that part we really don't know, and I think we want to study from the EV-302 how the HER2 positive patients did with EV and pembro. So that's an additional option, at least in China, and hopefully if it gets approved here, there is a trial going on with DV and pembro. And lastly, we've seen a very promising biomarker, like ctDNA, for the first time in bladder cancer in the adjuvant setting guiding treatment with adjuvant atezolizumab. So patients who were ctDNA positive derived overall survival and recurrence-free survival benefit. So that could help us select moving forward with more studies. We can spare unnecessary checkpoint inhibitors in patients who are not going to benefit. So I think there is a lot happening in our field, and this will help do more studies because we already have the next generation FGFR inhibitors which don't have the toxicities that erdafitinib comes with. And combining those with these novel ADCs and checkpoint inhibitors, you know, using maybe TMB as a biomarker, because we really need to move away from PD-L1 in bladder cancer. It's shown no utility whatsoever, but TMB has. Dr. Rafeh Naqash: Well, thank you so much, Shilpa, for that tour de force of how things have changed in bladder cancer. There used to be a time when lung and melanoma used to lead this space in terms of the number of approvals, the biomarker development. It looks like bladder cancer is shifting the trend at this stage. So definitely exciting to see all the new changes that are coming up. I'd like to spend another minute and a half on your career. You've obviously been a leader and example for many people in the GU space and beyond. Could you, for the sake of our early career especially, the trainees and other listeners, describe how you focused on things that you're currently leading as a leader, and how you shaped your career trajectory over the last 10 years? Dr. Shilpa Gupta: That's a really important question, Rafeh, and you and I have had these discussions before, you know, being an IMG on visas like you, and being in different places. I think I try to make the most of it, you know, instead of focusing on the setbacks or the negative things. Like tried to grab the opportunities that came along. When I was at Moffitt, got to get involved with the Phase 1 trial of pembrolizumab in different tumor types. And just keeping my options open, you know, getting into the bladder cancer at that time when I wanted to really do only prostate, but it was a good idea for me to keep my options open and got all these opportunities that I made use of. I think an important thing is to, like you said, you know, have a focus. So I am trying to focus more on biomarkers that, you know, we know that 70% patients will respond to EV-pembro, right? But what about the remaining 30%? Like, so I'm really trying to understand what determines hyperprogressors with such effective regimens who we really struggle with in the clinic. They really don't do well with anything we give them after that. So we are doing some work with that and also trying to focus on PROs and kind of patient-reported outcomes. And a special interest that I've now developed and working on it is young-onset bladder cancer. You know, the colorectal cancer world has made a lot of progress and we are really far behind. And bladder cancer has historically been a disease of the elderly, which is not the case anymore. We are seeing patients in their 30s and 40s. So we launched this young-onset bladder cancer initiative at a Bladder Cancer Advocacy Network meeting and now looking at more deep dive and creating a working group around that. But yeah, you know, I would say that my philosophy has been to just take the best out of the situation I'm in, no matter where I am. And it has just helped shape my career where I am, despite everything. Dr. Rafeh Naqash: Well, thank you again. It is always a pleasure to learn from your experiences and things that you have helped lead. Appreciate all your insights, and thank you for publishing with JCO PO. Hopefully we will see more of your biomarker work being published and perhaps bring you for another podcast in a couple of years. Dr. Shilpa Gupta: Yeah, thank you, Rafeh, for the opportunity. And thanks to JCO PO for making these podcasts for our readers. So thanks a lot. Dr. Rafeh Naqash: Thank you for listening to JCO Precision Oncology Conversations. Don't forget to give us a rating or review and be sure to subscribe so you never miss an episode. You can find all ASCO shows at asco.org/podcast. The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement. DISCLOSURES Dr. Shilpa Gupta Stock and Other Ownership Interests: Company: BioNTech SE, Nektar Consulting or Advisory Role: Company: Gilead Sciences, Pfizer, Merck, Foundation Medicine, Bristol-Myers Squibb/Medarex, Natera, Astellas Pharma, AstraZeneca, Novartis, Johnson & Johnson/Janssen Research Funding: Recipient: Your Institution Company: Bristol Myers Squibb Foundation, Merck, Roche/Genentech, EMD Serono, Exelixis, Novartis, Tyra Biosciences, Pfizer, Convergent Therapeutics, Acrivon Therapeutics, Flare Therapeutics, Amgen Travel, Accommodations, Expenses: Company: Pfizer, Astellas Pharma, Merck

Authors Drs. Jessica Ross and Alissa Cooper share insights into their JCO PO article, "Clinical and Pathologic Landscapes of Delta-Like Ligand 3 and Seizure-Related Homolog Protein 6 Expression in Neuroendocrine Carcinomas" Host Dr. Rafeh Naqash and Drs. Ross and Cooper discuss the landscape of Delta-like ligand 3 (DLL3) and seizure-related homolog protein 6 (SEZ6) across NECs from eight different primary sites. TRANSCRIPT Dr. Rafeh Naqash: Hello and welcome to JCO Precision Oncology Conversations, where we bring you engaging conversations with authors of clinically relevant and highly significant JCO PO articles. I'm your host, Dr. Rafeh Naqash, podcast editor for JCO PO and an Associate Professor at the OU Health Stephenson Cancer Center. Today, I'm excited to be joined by Dr. Jessica Ross, third-year medical oncology fellow at the Memorial Sloan Kettering Cancer Center, as well as Dr. Alissa Cooper, thoracic medical oncologist at the Dana-Farber Cancer Institute and instructor in medicine at Harvard Medical School. Both are first and last authors of the JCO Precision Oncology article entitled "Clinical and Pathologic Landscapes of Delta-like Ligand 3 and Seizure-Related Homolog Protein 6 or SEZ6 Protein Expression in Neuroendocrine Carcinomas." At the time of this recording, our guest disclosures will be linked in the transcript. Jessica and Alissa, welcome to our podcast, and thank you for joining us today. Dr. Jessica Ross: Thanks very much for having us. Dr. Alissa Cooper: Thank you. Excited to be here. Dr. Rafeh Naqash: It's interesting, a couple of days before I decided to choose this article, one of my GI oncology colleagues actually asked me two questions. He said, "Rafeh, do you know how you define DLL3 positivity? And what is the status of DLL3 positivity in GI cancers, GI neuroendocrine carcinomas?" The first thing I looked up was this JCO article from Martin Wermke. You might have seen it as well, on obrixtamig, a phase 1 study, a DLL3 bi-specific T-cell engager. And they had some definitions there, and then this article came along, and I was really excited that it kind of fell right in place of trying to understand the IHC landscape of two very interesting targets. Since we have a very broad and diverse audience, especially community oncologists, trainees, and of course academic clinicians and some people who are very interested in genomics, we'll try to make things easy to understand. So my first question for you, Jessica, is: what is DLL3 and SEZ6 and why are they important in neuroendocrine carcinomas? Dr. Jessica Ross: Yeah, good question. So, DLL3, or delta-like ligand 3, is a protein that is expressed preferentially on the tumor cell surface of neuroendocrine carcinomas as opposed to normal tissue. It is a downstream target of ASCL1, and it's involved in neuroendocrine differentiation, and it's an appealing drug target because it is preferentially expressed on tumor cell surfaces. And so, it's a protein, and there are several drugs in development targeting this protein, and then Tarlatamab is an approved bi-specific T-cell engager for the treatment of extensive-stage small cell lung cancer in the second line. SEZ6, or seizure-like homolog protein 6, is a protein also expressed on neuroendocrine carcinoma cell surface. Interestingly, so it's expressed on neuronal cells, but its exact role in neuroendocrine carcinomas and oncogenesis is actually pretty poorly understood, but it was identified as an appealing drug target because, similarly to DLL3, it's preferentially expressed on the tumor cell surface. And so this has also emerged as an appealing drug target, and there are drugs in development, including antibody-drug conjugates, targeting this protein for that reason. Dr. Alissa Cooper: Over the last 10 to 15 years or so, there's been an increasing focus on precision oncology, finding specific targets that actually drive the cancer to grow, not just within lung cancer but in multiple other primary cancers. But specifically, at least speaking from a thoracic oncology perspective, the field of non-small cell lung cancer has completely exploded over the past 15 years with the discovery of driver oncogenes and then matched targeted therapies. Within the field of neuroendocrine carcinomas, including small cell lung cancer but also other high-grade neuroendocrine carcinomas, there has not been the same sort of progress in terms of identifying targets with matched therapies. And up until recently, we've sort of been treating these neuroendocrine malignancies kind of as a monolithic disease process. And so recently, there's been sort of an explosion of research across the country and multiple laboratories, multiple people converging on the same open questions about why might patients with specific tumor biologies have different kind of responses to different therapies. And so first this came from, you know, why some patients might have a good response to chemo and immunotherapy, which is the first-line approved therapy for small cell lung cancer, and we also sort of extrapolate that to other high-grade neuroendocrine carcinomas. What's the characteristic of that tumor biology? And at the same time, what are other targets that might be identifiable? Just as Jesse was saying, they're expressed on the cell surface, they're not necessarily expressed in normal tissue. Might this be a strategy to sort of move forward and create smarter therapies for our patients and therefore move really into a personalized era for treatment for each patient? And that's really driving, I think, a lot of the synthesis of this work of not only the development of multiple new therapies, but really understanding which tumor might be the best fit for which therapy. Dr. Rafeh Naqash: Thank you for that explanation, Alissa. And as you mentioned, these are emerging targets, some more further along in the process with approved drugs, especially Tarlatamab. And obviously, DLL3 was something identified several years back, but drug development does take time, and readout for clinical trials takes time. Could you, for the sake of our audience, try to talk briefly about the excitement around Tarlatamab in small cell lung cancer, especially data that has led to the FDA approval in the last year, year and a half? Dr. Alissa Cooper: Sure. Yeah, it's really been an explosion of excitement over, as you're saying, the last couple of years, and work really led by our mentor, Charlie Rudin, had identified DLL3 as an exciting target for small cell lung cancer specifically but also potentially other high-grade neuroendocrine malignancies. Tarlatamab is a DLL3-targeting bi-specific T-cell engager, which targets DLL3 on the small cell lung cancer cells as well as CD3 on T cells. And the idea is to sort of introduce the cancer to the immune system, circumventing the need for MHC class antigen presentation, which that machinery is typically not functional in small cell lung cancer, and so really allowing for an immunomodulatory response, which had not really been possible for most patients with small cell lung cancer prior to this. Tarlatamab was tested in a phase 2 registrational trial of about 100 patients and demonstrated a response rate of 40%, which was very exciting, especially compared with other standard therapies which were available for small cell lung cancer, which are typically cytotoxic therapies. But most excitingly, more than even the response rate, I think, in our minds was the durability of response. So patients whose disease did have a response to Tarlatamab could potentially have a durable response lasting a number of months or even over a year, which had previously not ever been seen in this in the relapsed/refractory setting for these patients. I think the challenge with small cell lung cancer and other high-grade neuroendocrine malignancies is that a response to therapy might be a bit easier to achieve, but it's that durability. The patient's tumors really come roaring back quite aggressively pretty quickly. And so this was sort of the most exciting prospect is that durability of response, that long potential overall survival tail of the curve really being lifted up. And then most recently at ASCO this year, Dr. Rudin presented the phase 3 randomized controlled trial which compared Tarlatamab to physician's choice of chemotherapy in a global study. And the choice of chemotherapy did vary depending on the part of the world that the patients were enrolled in, but in general, it was a really markedly positive study for response rate, for progression-free survival, and for overall survival. Really exciting results which really cemented Tarlatamab's place as the standard second-line therapy for patients with small cell lung cancer whose disease has progressed on first-line chemo-immunotherapy. So that has been very exciting. This drug was FDA approved in May of 2024, and so has been used extensively since then. I think the adoption has been pretty widespread, at least in the US, but now in this global trial that was just presented, and there was a corresponding New England Journal paper, I think really confirms that this is something we really hopefully can offer to most of our patients. And I think, as we all know, that this therapy or other therapies like it are also being tested potentially in the first-line setting. So there was data presented with Tarlatamab incorporated into the maintenance setting, which also showed exciting results, albeit in a phase 1 trial, but longer overall survival than we're used to seeing in this patient population. And we await results of the study that is incorporating Tarlatamab into the induction phase with chemotherapy as well. So all of this is extraordinarily exciting for our patients to sort of move the needle of how many patients we can keep alive, feeling functional, feeling well, for as long as possible. Dr. Rafeh Naqash: Very exciting session at ASCO. I was luckily one of the co-chairs for the session that Dr. Rudin presented it, and I remember somebody mentioning there was more progress seen in that session for small cell lung cancer than the last 30, 35 years for small cell, very exciting space and time to be in as far as small cell lung cancer. Now going to this project, Jessica, since you're the first author and Alissa's the last, I'm assuming there was a background conversation that you had with Alissa before you embarked on this project as an idea. So could you, again, for other trainees who are interested in doing research, and it's never easy to do research as a resident and a fellow when you have certain added responsibilities. Could you give us a little bit of a background on how this started and why you wanted to look at this question? Dr. Jessica Ross: Yeah, sure. So, as with many exciting research concepts, I think a lot of them are derived from the clinic. And so I think Alissa and I both see a good number of patients with small cell, large cell lung cancer, and then high-grade neuroendocrine carcinomas. And so I think this was really born out of a basic conversation of we have these drugs in development targeting these two proteins, DLL3 and SEZ6, but really what is the landscape of cancers that express these proteins and who are the patients that really might benefit from these exciting new therapies. And of course, there was some data out there, but sort of less than one would imagine in terms of, you know, neuroendocrine carcinomas can really come from anywhere in the body. And so when you're seeing a patient with small cell of the cervix, for example, like what are the chances that their cancer expresses DLL3 or expresses SEZ6? So it was really derived from this pragmatic, clinically oriented question that we had both found ourselves thinking about, and we were lucky enough at MSK, we had started systematically staining patients' tumors for DLL3, tumors that are high-grade neuroendocrine carcinomas, and then we had also more recently started staining for SEZ6 as well. And so we had this nice prospectively collected dataset with which to answer this question. Dr. Rafeh Naqash: Excellent. And Alissa, could you try to go into some of the details around which patients you chose, how many patients, what was the approach that you selected to collect the data for this project? Dr. Alissa Cooper: This is perhaps a strength but also maybe a limitation of this dataset is, as Jesse alluded to, our pathology colleagues are really the stars of this paper here because we were lucky enough at MSK that they were really forethinking. They are absolute experts in the field and really forward-thinking people in terms of what information might be needed in the future to drive treatment decision-making. And so, as Jesse had said, small cell lung cancer tumor samples reflexively are stained for DLL3 and SEZ6 at MSK if there's enough tumor tissue. The other high-grade neuroendocrine carcinomas, those stains are performed upon physician request. And so that is a bit of a mixed bag in terms of the tumor samples we were able to include in this dataset because, you know, upon physician request depends on a number of factors, but actually at MSK, a number of physicians were requesting these stains to be done on their patients with high-grade neuroendocrine cancers of of other histologies. So we looked at all tumor samples with a diagnosis of high-grade neuroendocrine carcinoma of any histology that were stained for these two stains of interest. You know, I can let Jesse talk a bit more about the methodology. She was really the driver of this project. Dr. Jessica Ross: Yeah, sure. So we had 124 tumor samples total. All of those were stained for DLL3, and then a little less than half, 53, were stained for SEZ6. As Alissa said, they were from any primary site. So about half of them were of lung origin, that was the most common primary site, but we included GI tract, head and neck, GU, GYN, even a few tumors of unknown origin. And again, that's because I think a lot of these trials are basket trials that are including different high-grade neuroendocrine carcinomas no matter the primary site. And so we really felt like it was important to be more comprehensive and inclusive in this study. And then, methodologically, we also defined positivity in terms of staining of these two proteins as anything greater than or equal to 1% staining. There's really not a defined consensus of positivity when it comes to these two novel targets and staining for these two proteins. But in the Tarlatamab trials, for some of the correlative work that's been done, they use that 1% cutoff, and we just felt like being consistent with that and also using a sort of more pragmatic yes/no cutoff would be more helpful for this analysis. Dr. Alissa Cooper: And that was a point of discussion, actually. We had contemplated multiple different schemas, actually, for how to define thresholds of positivity. And I know you brought up that question before, what does it mean to be DLL3 positive or DLL3 high? I think you were alluding to prior that there was a presentation of obrixtamig looking at extra-pulmonary neuroendocrine carcinomas, and they actually divvied up the results between DLL3 50% or greater versus DLL3 low under 50%. And they actually did demonstrate differential efficacy certainly, but also some differential safety as well, which is very provocative and that kind of analysis has not been presented for other novel therapies as far as I'm aware. I could be wrong, but as far as I'm aware, that was sort of the first time that we saw a systematic presentation of considering patients to be, quote unquote, "high" or "low" in these sort of novel targets. I think it is important because the label for Tarlatamab does not require any DLL3 expression at all, actually. So it's not hinging upon DLL3 expression. They depend on the fact that the vast majority of small cell lung cancer tumors do express DLL3, 85% to 90% is what's been demonstrated in a few studies. And so, there's not prerequisite testing needed in that regard, but maybe for these extra-pulmonary, other histology neuroendocrine carcinomas, maybe it does matter to some degree. Dr. Rafeh Naqash: Definitely agree that this evolving landscape of trying to understand whether an expression for something actually really does correlate with, whether it's an immune cell engager or an antibody-drug conjugate is a very evolving and dynamically moving space. And one of the questions that I was discussing with one of my friends was whether IHC positivity and the level of IHC positivity, as you've shown in one of those plots where you have double positive here on the right upper corner, you have the double negative towards the left lower, whether that somehow determines mRNA expression for DLL3. Obviously, that was not the question here that you were looking at, but it does kind of bring into question certain other aspects of correlations, expression versus IHC. Now going to the figures in this manuscript, very nicely done figures, very easy to understand because I've done the podcast for quite a bit now, and usually what I try to do first is go through the figures before I read the text, and and a lot of times it's hard to understand the figures without reading the text, but in your case, specifically the figures were very, very well done. Could you give us an overview, a quick overview of some of the important results, Jessica, as far as what you've highlighted in the manuscript? Dr. Jessica Ross: Sure. So I think the key takeaway is that, of the tumors in our cohort, the majority were positive for DLL3 and positive for SEZ6. So about 80% of them were positive for DLL3 and 80% were positive for SEZ6. About half of the tumors were stained for both proteins, and about 65% of those were positive as well. So I think if there's sort of one major takeaway, it's that when you're seeing a patient with a high-grade neuroendocrine carcinoma, the odds are that their tumor will express both of these proteins. And so that can sort of get your head thinking about what therapies they might be eligible for. And then we also did an analysis of some populations of interest. So for example, we know that non-neuroendocrine pathologies can transform into neuroendocrine tumors. And so we specifically looked at that subset of patients with transformed tumors, and those were also- the majority of them were positive, about three-quarters of them were positive for both of these two proteins. We looked at patients with brain met samples, again, about 70% were positive. And then I'd say the last sort of population of interest was we had a subset of 10 patients who had serial biopsies stained for either DLL3 or SEZ6 or both. In between the two samples, these patients were treated with chemotherapy. They were not treated with targeted therapy, but interestingly, in the majority of cases, the testing results were concordant, meaning if it was DLL3 positive to begin with, it tended to remain DLL3 positive after treatment. And so I think that's important as well as we think about, you know, a patient who maybe had DLL3 testing done before they received their induction chemo-IO, we can somewhat confidently say that they're probably still DLL3 positive after that treatment. And then finally, we did do a survival analysis among specifically the patients with lung neuroendocrine carcinomas. We looked at whether DLL3 expression affected progression-free survival on first-line platinum-etoposide, and then we looked at did it affect overall survival. And we found that it did not have an impact or the median progression-free survival was similar whether you were DLL3 positive or negative. But interestingly, with overall survival, we found that DLL3 positivity actually correlated with slightly improved overall survival. These were small numbers, and so, you know, I think we have to interpret this with caution, for sure, but it is interesting. I think there may be something to the fact that five of the patients who were DLL3 positive were treated with DLL3-targeting treatments. And so this made me think of, like in the breast cancer world, for example, if you have a patient with HER2-positive disease, it initially portended worse prognosis, more aggressive disease biology, but on the other hand, it opens the door for targeted treatments that actually now, at least with HER2-positive breast cancer, are associated with improved outcomes. And so I think that's one finding of interest as well. Dr. Rafeh Naqash: Definitely proof-of-concept findings here that you guys have in the manuscript. Alissa, if I may ask you, what is the next important step for a project like this in your mind? Dr. Alissa Cooper: Jesse has highlighted a couple of key findings that we hope to move forward with future investigative studies, not necessarily in a real-world setting, but maybe even in clinical trial settings or in collaboration with sponsors. Are these biomarkers predictive? Are they prognostic? You know, those are still- we have some nascent data, data has been brewing, but I think that we we still don't have the answers to those open questions, which I think are critically important for determining not only clinical treatment decision-making, but also our ability to understand sequencing of therapies, prioritization of therapies. I think a prospective, forward-looking project, piggybacking on that paired biopsy, you know, we had a very small subset of patients with paired biopsies, but a larger subset or cohort looking at paired biopsies where we can see is there evolution of these IHC expression, even mRNA expression, as you're saying, is there differential there? Are there selection pressures to targeted therapies? Is there upregulation or downregulation of targets in response not just to chemotherapy, but for example, for other sort of ADCs or bi-specific T-cell engagers? I think those are going to be critically important future studies which are going to be a bit challenging to do, but really important to figure out this key clinical question of sequencing, which we're all contemplating in our clinics day in and day out. If you have a patient, and these patients often can be sick quite quickly, they might have one shot of what's the next treatment that you're going to pick. We can't guarantee that every patient is going to get to see every therapy. How can you help to sort of answer the question of like what should you offer? So I think that's the key question sort of underlying any future work is how predictive or prognostic are these biomarkers? What translational or correlative studies can we do on the tissue to understand clinical treatment decision-making? I think those are the key things that will unfold in the next couple of years. Dr. Rafeh Naqash: The last question for you, Alissa, that I have is, you are fairly early in your career, and you've accomplished quite a lot. One of the most important things that comes out from this manuscript is your mentorship for somebody who is a fellow and who led this project. For other junior investigators, early-career investigators, how did you do this? How did you manage to do this, and how did you mentor Jessica on this project with some of the lessons that you learned along the way, the good and other things that would perhaps help other listeners as they try to mentor residents, trainees, which is one of the important things of what we do in our daily routine? Dr. Alissa Cooper: I appreciate you calling me accomplished. Um, I'm not sure how true that is, but I appreciate that. I didn't have to do a whole lot with this project because Jesse is an extraordinarily smart, driven, talented fellow who came up with a lot of the clinical questions and a lot of the research questions as well. And so this project was definitely a collaborative project on both of our ends. But I think what was helpful from both of our perspectives is from my perspective, I could kind of see that this was a gap in the literature that really, I think, from my work leading clinical trials and from treating patients with these kinds of cancers that I really hoped to answer. And so when I came to Jessica with this idea as sort of a project to complete, she was very eager to take it and run with it and also make it her own. You know, in terms of early mentorship, I have to admit this was the first project that I mentored, so it was a great learning experience for me as well because as an early-career clinician and researcher, you're used to having someone else looking over your shoulder to tell you, "Yes, this is a good journal target, here's what we can anticipate reviewers are going to say, here are other key collaborators we should include." Those kind of things about a project that don't always occur to you as you're sort of first starting out. And so all of that experience for me to be identifying those more upper-level management sort of questions was a really good learning experience for me. And of course, I was fantastically lucky to have a partner in Jesse, who is just a rising star. Dr. Jessica Ross: Thank you. Dr. Rafeh Naqash: Well, excellent. It sounds like the first of many other mentorship opportunities to come for you, Alissa. And Jessica, congratulations on your next step of joining and being faculty, hopefully, where you're training. Thank you again, both of you. This was very insightful. I definitely learned a lot after I reviewed the manuscript and read the manuscript. Hopefully, our listeners will feel the same. Perhaps we'll have more of your work being published in JCO PO subsequently. Dr. Alissa Cooper: Hope so. Thank you very much for the opportunity to chat today. Dr. Jessica Ross: Yes, thank you. This was great. Dr. Rafeh Naqash: Thank you for listening to JCO Precision Oncology Conversations. Don't forget to give us a rating or review and be sure to subscribe so as you never miss an episode. You can find all ASCO shows at asco.org/podcasts. The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement. Disclosures: Dr. Alissa Jamie Cooper Honoraria Company: MJH Life Scienes, Ideology Health, Intellisphere LLC, MedStar Health, Physician's Education Resource, LLC, Gilead Sciences, Regeneron, Daiichi Sankyo/Astra Zeneca, Novartis, Research Funding: Merck, Roche, Monte Rosa Therapeutics, Abbvie, Amgen, Daiichi Sankyo/Astra Zeneca Travel, Accommodations, Expenses: Gilead Sciences

JCO PO author Dr. Bryson Katona at the University of Pennsylvania Perelman School of Medicine shares insights into his article, "Areas of Uncertainty in Pancreatic Cancer Surveillance: A Survey Across the International Pancreatic Cancer Early Detection (PRECEDE) Consortium" Host Dr. Rafeh Naqash and Dr. Katona discuss how, given differing guidelines as well as lack of detail about how PC surveillance should be performed, approaches to PC surveillance across centers often differs. TRANSCRIPT Naqash: Hello and welcome to JCO Precision Oncology Conversations, where we bring you engaging conversations with authors of clinically relevant and highly significant JCO PO articles. I am your host, Dr. Rafeh Naqash, podcast editor for JCO Precision Oncology and Associate Professor at the OU Health Stephenson Cancer Center at the University of Oklahoma. Today, I am thrilled to be joined by Dr. Bryson Katona, Director of the Gastrointestinal Cancer Genetics Program and Director of the Lynch Syndrome Program at the Penn Medicine's Abramson Cancer Center, and also lead author of the JCO PO article entitled "Areas of Uncertainty in Pancreatic Cancer Surveillance: A Survey Across the International Pancreatic Cancer Early Detection or PRECEDE Consortium." Bryson, thanks for joining us again. Dr. Bryson Katona: Well, thank you so much for having me. I appreciate the opportunity. Dr. Rafeh Naqash: It is exciting to see that this work will be presented concurrently with the upcoming CGA meeting. Dr. Bryson Katona: Yes, it has been a fantastic partnership between JCO PO and the CGA-IGC and their annual meeting. And for those who may not be familiar, the CGA-IGC is the Collaborative Group of the Americas on Inherited Gastrointestinal Cancer. It is basically a professional organization dedicated to individuals who have hereditary GI cancer risk and focusing on providing education, promoting research, and really bringing together providers in this space from not just throughout the US but from across the globe as well. Dr. Rafeh Naqash: That is exciting to hear the kind of work you guys are doing. These are definitely interesting, exciting things. Now, going to what you have published, it is an area that is very evolving in the space of cancer screening, cancer surveillance, especially for a very aggressive cancer such as pancreatic cancer. Could you tell us currently, what are the general consensus? I know there are a lot of differences between different guidelines or societies, but what are the some of the commonalities if we were to start there first for pancreas cancer screening? If you are not a GI oncologist, you may not be aware that there is something with regards to pancreas cancer screening. Could you give us an overview and a background on that? Dr. Bryson Katona: Yeah, I think that pancreatic cancer screening really is one of the most controversial areas of all cancer screening. Part of that controversy is just because all the guidelines, the many different guidelines that are out there, do not always match up with one another, which I think leads to a lot of confusion, not just for providers but for patients who are trying to go through this, and then also the insurance companies in trying to get these screening tests covered. You know, when we think about who is eligible for pancreatic cancer screening, you know, it is important that these are not average-risk individuals. So really, we are only offering screening to high-risk individuals. And those can include people that have a strong family history of pancreatic cancer without a germline genetic susceptibility that has been identified. And those individuals we refer to as having familial pancreatic cancer. And the other big cohort is those individuals that carry hereditary pancreatic cancer predisposition. These are due to cancer risk mutations in many different genes, including many of the breast cancer risk genes like BRCA1 and BRCA2, as well as ATM and PALB2, but then other genes such as the Lynch syndrome genes, and then some of the higher risk genes such as those leading to Peutz-Jeghers syndrome as well as FAM, which is due to CDKN2A mutations. Dr. Rafeh Naqash: Thank you for that. Again, another practical question, and this may or may not be exactly related to your specific topic here, but perhaps to some extent there might be an overlap. If I get a patient from a colleague, and I see people in the early-phase clinical trial setting, so many different tumors for novel drugs, and I find an individual with, let us say, lung cancer who has a pathogenic BRCA2, which is somatic, should I be worried about pancreas cancer screening in that individual? Or have we not met that threshold yet in that circumstance? Dr. Bryson Katona: A lot of times these variants or these genes that are associated with pancreatic cancer risk get picked up on the somatic tumor profiles. Now, you know, whether or not those are truly germline variants typically requires the next step of referring the patient for germline genetic testing. So you know, I would not screen or make any kind of screening choices based on a somatic variant alone, but nowadays germline testing is so easy, so efficient, and relatively cheap that it is easy enough to confirm whether or not these somatic hits are in fact just somatic or may confer some germline risk in addition. Dr. Rafeh Naqash: So from what I understand from what you have said, there is debate about it, but it is something that should be done or is important enough that you need to figure out a path moving forward. Was that one of the reasons why you performed this project through this very interesting consortium called the PRECEDE Consortium? Dr. Bryson Katona: Yeah, that was one of our main reasons for doing this. And for those who do not know about the PRECEDE Consortium, this is a very large international, multi-institutional organization really focused on reducing death and improving survival from pancreatic cancer, primarily through increased and more effective use of screening and early detection strategies. This is an international consortium. There are over 50 sites now with nearly 10,000 patients who are enrolled in the consortium. So it really is at this point the largest prospective study of individuals who are at high risk for pancreatic cancer who are undergoing screening. And you know, I think amongst all of us in the consortium, just amongst discussions between colleagues and then, you know, often times when I see patients that are transferring their care to Penn who maybe had their screening done in another center before, what we were realizing is that, you know, although we all do a lot of screening, it seems that people are doing it slightly differently. And it does not seem that there is a real consensus approach across all centers about how pancreatic cancer screening should really be done. And it is one thing if you are thinking comparing, okay, well, maybe in the US we do it differently than, you know, in Europe or in other locations, but even among centers within the United States, we were still seeing very large differences in how pancreatic cancer screening in high-risk individuals were done. And so that led us to really pursue this survey of pancreatic cancer screening practices across the PRECEDE Consortium. So for this survey, we actually have 57 centers who the survey was sent out to. As you know, surveys are oftentimes very difficult to get good response rates back on, but we were fortunate to have 54 of the 57, or 95% of the centers, actually get back to us about their screening practices for this particular project. Dr. Rafeh Naqash: That is good to know. I hope you did not have to use any kind of gift cards for people to respond to the survey. But nevertheless, you got the information that you needed. Could you tell us what are some of the common denominators that you did identify and some of the differences that you identified? From your perspective, it sounds like there is no established consensus guidelines. There are different societies that have different perspectives on it. So I am sure some of what you found will probably have implications in maybe creating some guidelines. Is that a fair statement? Dr. Bryson Katona: Definitely a fair statement, and we found some very interesting results. I think one important result is really just the heterogeneity in the consortium. And so even before we got into pancreatic cancer screening practices, we also, we were asking consortium sites, "At your particular site, who is the individual that is leading these in-depth discussions about pancreatic cancer screening?" And while about 50% of the sites had a gastroenterologist leading it, about a quarter of the sites had a medical oncologist, a quarter had a surgeon leading these discussions as well. And we also found heterogeneity in who is the physician or the provider actually ordering these screening tests, again, with multiple different specialties across the different sites. But really one of the main areas that we wanted to hone in and focus on was how the different pancreatic cancer screening guidelines were actually utilized in each of the particular centers. The biggest controversial area in the field is for the gene mutation carriers, whether or not we should be requiring that a family history of pancreatic cancer be present in order for those individuals to qualify for pancreatic cancer screening. And the reason that is so controversial, let us take an example of BRCA1 and BRCA2 carriers. Currently, if you look through the guidelines, NCCN and the ASGE guidelines recommend that really all BRCA2 carriers undergo pancreatic cancer screening regardless of whether or not there is a family history, starting at age 50. However, other guidelines such as the AGA guidelines, or the AGA Clinical Practice Statement, as well as guidelines from the CAPS consortium, do recommend that a family history of pancreatic cancer be present in order to qualify for screening. But then we have different things for other genes. So for BRCA1 carriers, in fact, it is the ASGE guidelines that recommend all BRCA1 and 2 carriers undergo screening, whereas NCCN and the other guidelines that are out there do not recommend those individuals undergo screening. Again, this huge heterogeneity in guidelines is quite striking. And so when we assessed all the sites in the PRECEDE Consortium, we found some really interesting results with respect to these particular genes. For BRCA2 carriers specifically, we found that about half of the sites required a family history for recommending pancreatic cancer screening, but about half of the sites would offer it to all BRCA2 carriers regardless of if there was a family history of pancreatic cancer screening. Rates for BRCA1, PALB2, and ATM carriers were a little bit lower, where about a third of sites would offer screening really regardless of whether or not there is a family history of pancreatic cancer. And for Lynch syndrome, those rates were very, very low, with only about 13% of sites offering screening to Lynch patients in the absence of a family history. But I think, you know, we are all in the same consortium, but there is still just a lot of heterogeneity in how our own individual practices are run. Dr. Rafeh Naqash: Definitely different thoughts, different practices. But from what you saw, did it matter as far as outcomes are concerned whether it was a gastroenterologist doing the screening, or it was a medical oncologist, or a geneticist? Or is it a combination of all of these that actually makes the most difference? Dr. Bryson Katona: So I think we do need to get some more information about specialty-specific screening preferences. We just had one response per site in this particular survey, and so I think we are going to need a larger sample size in order to get that data. But I think that is certainly possible that, you know, certain subspecialties may prefer, you know, screening more aggressively or not including family history. That is definitely a question that we will be asking in future studies. Dr. Rafeh Naqash: Definitely more gift cards that will be needed as well. Moving on to another aspect of the implications for early detection, from a breast cancer, colon cancer standpoint, there is health economics research that shows it saves cost in the bigger picture. Has there been anything for pancreas cancer where early detection, early identification, early treatment actually ends up saving a lot more versus detecting metastatic pancreas cancer later? Dr. Bryson Katona: It is a great question. And of course, for any screening modality, you know, we would ultimately want it to be a cost-effective measure. In pancreas cancer screening, the jury is still a little bit out about whether or not pancreas cancer screening is truly cost-effective or not. There have been several different studies that have assessed this. And I think in general, the thought is that it is a cost-effective endeavor. But I think most of these cost-effectiveness estimates are actually related to what is the risk of pancreatic cancer in the population you are studying. And so when you have very, very high-risk individuals that have over a 10% lifetime risk of pancreatic cancer, it is almost a certainty that pancreatic cancer screening is going to be cost-effective. However, you know, if you have, say for example, BRCA1 carriers where lifetime risk of pancreatic cancer may be less than 5%, likely around like 3%, those individuals, I think it is going to be a tougher sell to say that it is cost-effective. But as we get more data on pancreatic cancer screening, that will be a very important question to ask. And you know, when you mentioned how does it save money, our goal at least in pancreatic cancer screening is to really downstage pancreatic cancer at the time of diagnosis and allow someone to undergo, you know, ideally a curative-intent surgery. There is data out there showing that we can downstage the cancers, that survival after the time of diagnosis is substantially increased after detection in a pancreatic cancer screening program. But again, these are studies that are based on fairly small numbers of converters. And so I think we need more data in that space as well, which is one of the main questions that the PRECEDE Consortium is trying to answer with all of our prospective data. Dr. Rafeh Naqash: Excellent. Well, I hope we see more interesting, exciting work from the PRECEDE Consortium at meetings as well as as a publication in JCO PO. I would like to shift gears briefly for a minute or two, Bryson, to you as an individual, your career. How have you evolved over the last 5, 7 years? How did you end up doing cancer genetics? What were some of the lessons that you learned along the way and some of those that you would want to share with our listeners, especially trainees and early-career faculty? Dr. Bryson Katona: Just to give you and others listening a little bit of background, but I am a physician-scientist, gastroenterologist, but a physician-scientist. And so my clinical practice is exclusively focused on individuals with hereditary GI cancer risk. I run a basic science lab where we do a lot of studies in organoids and mouse models of these hereditary GI cancer risk syndromes. And then I also have a clinical research group where we do early-phase clinical trials and screening and early detection trials, again in these same individuals with hereditary GI cancer risk. I think probably the most important thing that kind of allowed me to get to this stage in my career where I am trying to, you know, essentially try to juggle all three of these balls at the same time is that I absolutely love what I do. And I am so incredibly interested in what I do. And I think for young individuals that are coming through the pipeline and going through training, you know, I mean, finding a specialty and a clinical niche where you truly just enjoy the work and you enjoy the patients and you enjoy your colleagues is by far the most important thing. I ended up getting into the hereditary GI cancer space because a lot of my work earlier on in my career during my PhD and then in my postdoc work in the lab really focused on colorectal cancer. And I thought that focusing on cancer genetics could allow me to really continue to think from the molecular side of things while simultaneously being a gastroenterologist and taking care of patients with hereditary cancer risk. Dr. Rafeh Naqash: Well, thank you so much for giving us a sneak peek of your journey and insights on what perhaps works best, especially when you love what you do. I think that is one of the most important reasons a work tries to keep you going and keep you interested, keep you passionate. So thank you again. Thank you for listening to JCO Precision Oncology Conversations. Do not forget to give us a rating or a review, and be sure to subscribe so you never miss an episode. You can find all ASCO shows at asco.org/podcasts. The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.

In this JCO Precision Oncology Article Insights episode, Dr. Jiasen He summarizes JCO PO article "Synthetic Lethal Co-Mutations in DNA Damage Response Pathways Predict Response to Immunotherapy in Pan-Cancer" by Hua Zhong et al. TRANSCRIPT Jiasen He: Hello and welcome to the JCO Precision Oncology Article Insights. I am your host, Jiasen He, and today we will be discussing the JCO Precision Oncology article, "Synthetic Lethal Co-mutations in DNA Damage Response Pathway Predict Response to Immunotherapy in Pan-Cancer" by Dr. Zhang and colleagues. Immunotherapy has emerged as a groundbreaking treatment option for many types of cancer. However, the overall response rate to immunotherapy is low, around 10% to 30%. This highlights the critical need to identify which patients are most likely to benefit from immunotherapy. Two of the most extensively studied biomarkers are PD-L1 expression and tumor mutation burden (TMB). High levels of PD-L1 and TMB have been associated with better response to immune checkpoint inhibitors, which are now widely used in clinical practice. The predictive value of these markers is inconsistent across all settings. Some tumors with high PD-L1 or TMB still respond poorly to immunotherapy. One reason is that TMB reflects new antigen production, but recent studies suggest that new antigen levels do not always correlate with tumor immunogenicity. Many new antigens are not effectively recognized by T cells, limiting the immune response. Emerging evidence indicates that mutations in the DNA damage response (DDR) pathway play a critical role in moderating tumor immune interactions. Tumors harboring DDR pathways frequently exhibit increased genome instability, which may enhance their sensitivity to immune checkpoint inhibitors. While all these pathways are under active investigation, the optimal DDR pathway biomarkers for patient selection remain unclear. Notably, tumor cells with a defect in one DDR pathway may acquire greater reliance on alternative DDR pathways. Recent studies suggest that synthetic lethal co-mutations within DDR pathways are associated with immune-inflamed or hot tumor microenvironments. Based on this rationale, Dr. Zhang is investigating if synthetic lethal co-mutations in DDR pathway response pathway can serve as a treatment biomarker for immune checkpoint inhibitors. To address this question, Dr. Zhang and colleagues first utilized SynLethDB 2.0, a comprehensive database that integrated multiple data sets. Synthetic lethal (SL) gene pairs in this resource are identified through both experimental and computational approaches, with confidence scores assigned to each pair. These SL pairs were then mapped to gene sequencing results from several clinical cohorts. SL co-mutation status was defined as positive when both genes in a synthetic lethal pair were mutated. From this, SL co-mutation pairs specifically involving DDR pathway genes were selected. Patients were classified as DDR co-mutation positive if both genes in a synthetic lethal pair, each belonging to the defined DDR pathways, were mutated. In total, 431 DDR-related SL pairs were identified and matched to sequencing data from clinical cohorts. Clinical information was extracted from the cBioPortal, while further analysis of immune infiltration was performed using DNA mutation and RNA expression data from The Cancer Genome Atlas (TCGA) pan-cancer data set. The author first examined the correlation between SL co-mutation status and response to ICI therapy. They discovered that patients with SL co-mutation showed significantly improved outcome to ICI therapy across various clinical cohorts. Notably, in patients who did not receive ICI treatment, patients with SL co-mutation showed markedly compromised overall survival. Further analysis focused on the predictive value of SL co-mutation within DDR pathway genes. The author found that patients with DDR SL co-mutation had a longer overall survival compared to those with mutations in a single DDR gene, implying that SL co-mutations may be more effective biomarkers within the DDR pathway. To explore this further, in the TMB-MSKCC cohort, the author found that patients with DDR co-mutation constituted approximately 20% of various cancer types, including non-small cell lung cancer, melanoma, and bladder cancer. These patients demonstrated significantly better survival outcomes and disease control rates when treated with ICIs compared to DDR co-mutation negative patients. Notably, the TMB level was substantially higher in patients with DDR co-mutation, a finding consistent with data from the Miao-lung cohort. Furthermore, in cohorts not treated with ICIs, patients with DDR co-mutation had a shorter overall survival compared to their counterparts. Upon stratifying by PD-L1 expression, the author observed that patients with DDR co-mutation who were also PD-L1 positive derived the greatest clinical benefit from ICI therapy. Upon analyzing the frequency of co-mutation within the DDR pathway, the authors found that patients with SL co-mutation in the CPF-CPF pathway experienced remarkable survival benefit from ICIs. Within this group, one of the most common co-mutation combinations was TP53-ATM, observed in approximately 45% of cases, which was associated with a better response to ICI therapy. Further analysis of immune cell infiltration revealed that patients with TP53-ATM co-mutation exhibited a distinct tumor immune microenvironment. As the authors stated, the study's main limitation lies in the nature of retrospective analysis, which lacked the control over confounding variables and was subject to non-random sampling. For instance, patients with both SL co-mutations and DDR SL co-mutations exhibited high TMB, and TMB was known to be associated with improved response to ICI therapy itself. So, these findings require validation through prospective studies, and immune infiltration analysis needs confirmation via laboratory experiments. In conclusion, the authors found that patients with SL co-mutations in DDR pathways showed favorable clinical response and prolonged survival following ICI therapy. They also identified TP53-ATM co-mutations as a clinically relevant biomarker for predicting ICI treatment response. Thank you for tuning in to JCO Precision Oncology Article Insights. Don't forget to subscribe and join us next time as we explore more groundbreaking research shaping the future of oncology. The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.

In this JCO PO Article insights episode, Dr. Jiasen He summarized the JCO PO article "Mucin 16–Directed Therapy in Pediatric Sarcomas: Case Evidence of Ubamatamab Efficacy in Epithelioid Sarcoma and Its Implications for Other Sarcoma Subtypes" by Connolly et al. TRANSCRIPT Jiasen He: Hello, and welcome to JCO Precision Oncology Article Insights. I'm your host, Jiasen He, and today we'll be discussing the JCO Precision Oncology article, "Mucin 16-Directed Therapy in Pediatric Sarcomas: Case Evidence of Ubamatamab Efficacy in Epithelioid Sarcoma and Its Implication for Other Sarcoma Subtypes" by Connolly et al. Epithelioid sarcoma and malignant rhabdoid tumor are rare pediatric soft tissue sarcomas, characterized by INI1 loss, high recurrence rates, and poor outcome despite multimodal treatments. Emerging evidence has shown that Mucin 16 is expressed in both tumor types. Mucin 16 is a transmembrane glycoprotein whose extracellular domain can be cleaved and released as CA-125. Both Mucin 16 and CA-125 are well-established biomarkers in several adult epithelioid malignancies, particularly ovarian cancer. Ubamatamab is a specific T-cell engager targeting CD3 and Mucin 16. It has demonstrated antitumor activity in patients with recurrent ovarian cancer, and clinical trials are ongoing to evaluate its efficacy as monotherapy or in combination regimens. In this manuscript, Connolly et al. present the first reported case of a heavily pretreated patient with epithelioid sarcoma who responded to ubamatamab, followed by an investigation into mechanisms of resistance after disease progression. Furthermore, the authors retrospectively assessed Mucin 16 expression in a cohort of pediatric and young adult sarcomas, finding high expression in both epithelioid sarcoma and malignant rhabdoid tumor. In this case report, the authors describe a 23-year-old woman with relapsed metastatic epithelioid sarcoma. Initially diagnosed at age 12, she had received multiple lines of treatments, including surgery, radiotherapy, targeted therapy, and immunotherapy. Following disease progression after all these treatments, her tumor was tested for Mucin 16 expression and it demonstrated 100% positivity with markedly elevated CA-125 levels, providing a rationale for treatment with the Mucin 16-CD3 bispecific T-cell engager, ubamatamab. Ubamatamab was administered in an escalating dose schedule up to 250 mg once weekly during cycle one and continued for a total of 162 weeks. The best response was observed at week 11, with a 40% reduction and a marked decline in CA-125 levels. Disease progression was first detected in a single left lower lobe lung nodule, which on biopsy showed a reduction in Mucin 16 expression from 100% to less than 5%. Post-treatment analysis revealed changes in the tumor microenvironment, including increased expression of T-cell exhaustion markers such as PD-1 and LAG-3. Ubamatamab was generally well tolerated. Cytokine release syndrome occurred during the escalating phase of cycle one, presenting with fever and hypoxia. Other notable adverse events included pleural and pericardial effusion, both of which resolved spontaneously. Given its favorable safety profile and limited alternative treatment options, ubamatamab was continued beyond the initial progression. The patient ultimately received 28 cycles of treatment before she passed away due to disease progression. In the second part of the paper, the authors examined Mucin 16 expression in a cohort of pediatric and young adult sarcomas. Among 91 samples, Mucin 16 was expressed in six out of eight epithelioid sarcomas and two out of four malignant rhabdoid tumors. H-score analysis showed that all Mucin 16-positive tumors showed moderate to high expression levels. In conclusion, this manuscript presents the first reported use of a Mucin 16-CD3 bispecific T-cell engager for epithelioid sarcoma, along with an investigation into resistance mechanisms following progression. The treatment achieved a substantial partial response with a favorable safety profile. The findings suggest that resistance may be associated with loss of Mucin 16 expression and T-cell exhaustion. Follow-up studies are needed to confirm these mechanisms. Notably, the study also identifies INI1-deficient sarcoma as a group with high Mucin 16 expression, warranting additional validation and mechanism exploration. These findings offer valuable insight for future therapeutic strategies and support the use of Mucin 16/CA-125 as both a treatment target and a biomarker for patient selection and disease monitoring. Thank you for tuning in to JCO Precision Oncology Article Insights. Don't forget to subscribe and join us next time as we explore more groundbreaking research shaping the future of oncology. The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.

In this JCO Precision Oncology Article Insights episode, Natalie DelRocco summarizes "Prognostic Value of the G2 Expression Signature and MYC Overexpression in Childhood High-Grade Osteosarcoma" by Roelof van Ewijk et al. published on May 29, 2025. TRANSCRIPT Natalie Del Rocco: Hello, and welcome to JCO Precision Oncology Article Insights. I'm your host, Natalie DelRocco, and today we will be discussing the original report, "Prognostic Value of the G2 Expression Signature and MYC Overexpression in Childhood High-Grade Osteosarcoma." This original report by van Ewijk et al. describes a study of the association between 2 biomarkers and survival outcomes among patients with high-grade osteosarcoma. Osteosarcoma is a disease where not much progress has been made in risk stratification factors that could potentially help patients target lower-risk therapies, less toxic therapies, or therapies that might be more toxic but could help their high-risk osteosarcoma. So, it's important to identify risk factors that can help target therapies. The G1/G2 gene expression signature is a prognostic risk score developed by a French osteosarcoma group in 2022. They showed in a cohort of 79 osteosarcoma patients that risk score was associated with poorer event-free survival and overall survival. This considers expression of 15 individual genes. MYC amplification was shown in 2023 by a North American osteosarcoma group to be associated with poor overall survival in a cohort of 92 osteosarcoma patients, and this group validated that finding in a localized cohort in the same publication. The goal of this particular original report was to assess the prognostic significance of each of these biomarkers in a population independent to those prior publications and, hence, to serve as an external validation of prior findings and to assess these 2 biomarkers in the same study. The investigators considered MYC amplification, defined as having greater than 7 copies; MYC expression as a continuous rather than the previously categorized variable; and G2 expression defined as a continuous variable; and then G2 expression defined as a dichotomous variable with the cut point at the median, as done in the original paper. What the investigators found in their primary multivariable Cox proportional hazards regression model, which controlled for additional clinical risk factors such as age, tumor site, tumor size, is that G2 expression and MYC expression as continuous variables were associated with increased hazard of EFS and OS event. MYC amplification was not found to be prognostic. This is not surprising. When we have continuous variables, we have greater statistical power, we decrease the likelihood that an identified cut point in a previous study does not generalize well to either our genetic assay or our patient population. So, we don't have to worry about finding the optimal cut point in our particular patient sample. Thank you for listening to our JCO Precision Oncology Article Insights. Don't forget to give us a rating or review, and be sure to like and subscribe so that you never miss an episode. You can find all ASCO shows at asco.org\podcasts. The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.

JCO PO author Dr. Philip Philip at Henry Ford Cancer Institute and Wayne State University shares insights into his JCO PO article, "Incorporating Circulating Tumor DNA Testing Into Clinical Trials: A Position Paper by the National Cancer Institute GI Oncology Circulating Tumor DNA Working Group." Host Dr. Rafeh Naqash and Dr. Philip discuss how prospective trials are required to clarify the role of ctDNA as a valid surrogate end point for progression-free or overall survival in GI cancers. Transcript Dr. Rafeh Naqash: Hello and welcome to JCO Precision Oncology Conversations, where we bring you engaging conversations with authors of clinically relevant and highly significant JCO PO articles. I'm your host, Dr. Rafeh Naqash, Podcast Editor for JCO Precision Oncology and Assistant Professor at the OU Health Stephenson Cancer Center at the University of Oklahoma. Today, we are excited to be joined by Dr. Philip Philip, Chair of Hematology and Oncology, as well as leader of GI and Neuroendocrine Oncology. He's also the Professor of Oncology and Pharmacology, as well as Co-Leader of the Pancreatic Cancer Program and Medical Director of the Cancer Clinical Trial and Translational Research Office at the Henry Ford Cancer Institute at Wayne State University. Dr. Philip is also the Senior Corresponding Author of the JCO Precision Oncology article entitled, "Incorporating Circulating Tumor DNA Testing into Clinical Trials: A Position Paper by the National Cancer Institute GI Oncology Circulating Tumor DNA Working Group." At the time of this recording, our guest's disclosures will be linked in the transcript. Dr. Philip, welcome to our podcast, and thank you so much for joining us today. Dr. Philip Philip: Thank you so much, Dr. Naqash, for providing me this opportunity to be discussing this with you. Dr. Rafeh Naqash: This is a very timely and interesting topic. We've done a couple of podcasts on ctDNA before, but none that is an opinion piece or a guidance piece based on what you guys have done. Could you tell us what led to this perspective piece or guidance manuscript being published? There is some background to this. Could you tell us, for the sake of our listeners, what was the initial thought process of why you all wanted to do this? Dr. Philip Philip: The major reason for this was the fact that investigators were considering using ctDNA as a primary endpoint in clinical trials. Obviously, you hear my focus will be on gastrointestinal cancers. So, the idea was, can we use ctDNA instead of using the traditional endpoints such as disease-free survival, progression-free survival, or overall survival? And the question was, do we have enough data to support that in patients with gastrointestinal cancers? Now, the article obviously goes over some review of the data available, but the core of the article was not to do a comprehensive review of ctDNA use and the evidence so far, although we used that in really putting our recommendations. So, we really had to evaluate available data. But the focus was, what are the gaps? What do we need to do? And are we ready to use ctDNA as a primary endpoint in clinical trials? Dr. Rafeh Naqash: Thank you for giving us that background. Obviously, a very broad, complicated topic with a bunch of emerging data that you've highlighted. But most importantly, for the sake of, again, trainees and listeners, could you help us understand the difference between tumor-informed and non-tumor-based ctDNA assessments? Dr. Philip Philip: Sure. So, the tumor-informed is simply meaning that you're taking the genomic makeup or the DNA fingerprint of the cancer in a given patient, and you create a profile, and then use that profile to see whether that DNA is present in the blood. So, it's very simple. It's like barcoding DNA and then going and looking for it in the blood, which means that you have to have the primary tumor. When I say primary tumor, you need to have the tumor to start off with. It doesn't really apply, maybe easily, if you just have a fine-needle aspirate and things like that. So, you really have to have a good amount of the tumor for you to be able to do that. So, that's a tumor-informed, and from the name, you can easily understand how it's done, compared to the other one, which is uninformed, whereby off-the-shelf probes are used to look for tumor DNA. And again, they're based on prior experience and prior identification of the key DNA changes that will be seen in tumors. So, that's the difference between the two in terms of the principle of the test. The uninformed will not require you to send the original tumor that you're trying to test. However, the informed, you do. The turnaround time is, again, a bit different because, as you would expect, it's shorter in the uninformed. And the reason for that, again, is the initial preparation of the profile that is going to be used in the future when you do serial testing. The sensitivity has been a bit of a discussion. Initially, people have thought that tumor-informed assays are more sensitive, more specific, more sensitive, et cetera. But in our review, we come to the conclusion saying that we don't think that's going to be a major difference. And there are obviously improvements happening in both types of assays. The sensitivities have been improving. So, at this point in time, we do feel that you have two types of assays, and we didn't feel strongly about recommending one over the other. Dr. Rafeh Naqash: Thank you for that description. You mentioned something about sensitivity, specificity. Obviously, many of us who have ordered both tumor-informed and tumor-uninformed, we understand the differences with respect to the timing. The tumor-informed one can take more time. The uninformed one, being a sort of a liquid biopsy, may not necessarily have as much of a turnaround time. Could you briefly speak to those limitations or advantages in the context of the two versions? Dr. Philip Philip: I just really want to also highlight that when we say turnaround time, so for the tumor-informed assays, the first assay that we do will be requiring a turnaround time. But once the pattern has been set and the profile has been documented, the subsequent testing doesn't require much in the way of waiting. However, when you're using this for the minimal residual disease, then you have a window of opportunity to work at. That's number one. So, it means that in patients who have resected cancer, you may end up having to wait longer than the tumor-uninformed assay, especially if you don't have easy access to your material for the baseline material to send. And also, what we'd like to do is not do the test immediately after the operation or soon after the operation. Give it some time. There's a window where you can work at, and starting minimally two weeks after the surgery. But in my experience, I'd like to wait at least four weeks just to make sure that we got an accurate reading. Sometimes when you do it very early after surgery, because of the effect of the surgery and the release of the normal DNA is also, it may dilute the tumor DNA, and then you may get a false negative. So, basically, it depends on the clinical situation. And your question is, is one better to be used than the other? I think ultimately, it ends up with the turnaround time not being as much of an issue. It might be in certain situations, depending on when you see the patients after the operation or any definitive treatment you've done and you want to look for minimal residual disease. But in general, I don't think that's going to be a real major issue. Dr. Rafeh Naqash: I remember discussing this with one of the tumor-informed platforms with regards to this barcode you mentioned. They generate a fingerprint of sorts for the tumor on the tissue, then they map it out in the blood and try to assess it longitudinally. And one of the questions and discussions we had was around the fact that most of the time, these barcoded genes are not the driver genes. If you have a KRAS mutant tumor, it's not going to be the KRAS gene that they map out. It's something that is specific. So, is there a possibility that when you are mapping out, let's say, a metastatic tumor where there is truncal and subclonal mutations at different sites, that you capture something that is not necessarily truncal, and that does not necessarily reflect some other metastatic site having a recurrence? So basically, over time, you don't see a specific mutational pattern or the signature on the tumor-informed, and then you see something on the scan which makes you think, "Well, it was not the right test," but actually it could be a different subclone or a clone mutation at a different site. Is there a concept that could help us understand that better? Dr. Philip Philip: I think you raise a very important point. Although, I have to say from my practical experience, that is not a common thing to see. In fact, for some reason, we don't see it that often in any frequency that should, at this point in time, make us concerned about the serial testing. But what you were mentioning is a real challenge which can happen. Now, the question is, how often does the clonal evolution or the divergence happen to the point that it's going to be like a false negative, is what you're saying. At this point in time, we don't really have good information on that, or any good information, practical information. And when we went through the literature and we were looking for the evidence, that wasn't something which was there clearly telling us. Although, this is something that has to be studied further prospectively. And I don't know of a study, but I might be missing it, I don't know of a study which is systematically looking at this. Although it's a very valid hypothesis and theoretical basis for it, but in real life, we still have to see how much does it really interfere with the validity of this kind of testing. Dr. Rafeh Naqash: Which brings us to the more important discussion around your manuscript. And I think that the overarching theme here is the consensus panel that you guys had recommended that ctDNA-based metrics be used as a co-primary endpoint. Could you tell us, for early-phase trials, maybe phase two studies for that matter, could you tell us what were some of the aspects that led to this consensus being formed from your working group? Dr. Philip Philip: Well, there were a number of reasons, in any order of priority, but one of them is we don't have a good sense of dynamics of the ctDNA. And again, remember this article was about gastrointestinal cancers. Maybe we know more about colon cancer, but, or colorectal cancer, but we don't know that well about the upper GI, like gastroesophageal, pancreatic, et cetera. So, we don't know what is the false negative percentages. And in fact, we know that there are certain sites of the disease, metastases, that do not lead to enough shedding of the DNA into the circulation. So, that was something else. I mean, false negativity, not knowing exactly what the dynamics are, especially in different disease types. So, that was another reason, which we felt that it may not be at this time primetime to really have those ctDNA tests as a primary endpoint. We wanted to make sure that, on the other hand, we wanted to make sure that people consider including ctDNA more like a secondary endpoint so that we can gain the information that we're lacking, at least the ones I mentioned to you. So, that was an important point of our discussions and deliberations when we were writing the article. Dr. Rafeh Naqash: And I myself have been on both sides of the aisle where - I treat people with lung cancer, you mentioned appropriately that most of the data that we have for ctDNA is generated from GI cancers, especially colorectal - on the lung cancer side, I myself had a patient with an early-stage cancer, had treatment, surgery, immunotherapy, and then had ctDNA that was tumor-informed, was positive four to five months before the imaging actually showed up. And on the other side, I've also had an individual where early-stage lung cancer, surgery, immunotherapy, and then had PET scans that showed a positive finding, but the ctDNA, tumor-informed ctDNA, was negative multiple times. So, I've seen both aspects of it, and your paper tries to address some of these questions on how to approach a negative, radiologically negative imaging but positive ctDNA potentially, and vice versa. Could you elaborate upon that a little bit? Dr. Philip Philip: Well, obviously, we do see this in practice. Again, I do GI oncology. I have patients who, you do ctDNA. I mean, my advice to anyone, when you order a test, you have to make sure that you know what you're going to do with the test, because that's the most important thing. You get a positive test, you do something. You get a negative test, you do something. But most importantly, our patients who you're following up, they are very anxious for a diagnosis they have that is not- I mean, it's cancer. If you're doing these tests, if we get continuous, repeatedly negative testing, then you really have to also tell the patient that there's a false negativity. And I mentioned to you earlier, there are certain sites of disease, like peritoneal, they may not be producing enough, or there are some tumors, their biology is such that they don't release as much to be detected in the blood. Now, one day we will get maybe a more sensitive test, but I'm talking about the tests we have now. On the other hand, if you get a positive testing, you have to make a distinction for ctDNA in the minimal residual disease situation. If you get a positive test, there is enough evidence that the patient has a worse prognosis. There's evidence for that. No one can dispute that. Again, I'm talking about colorectal cancer where there are a lot of data for that. So, in that situation, there are studies that are looking, if you get a positive test in someone who you're not intending to give any adjuvant treatment, there are studies looking into that, both in terms of intensifying, like chemotherapy, in certain patients. And also, there's work being done, if you have a negative test in someone who has stage III disease, for example, or definitely stage II disease, they may not need to give them chemo. Those things are happening. But in metastatic disease, it's a different situation. Or even in someone who has received surgery, adjuvant chemotherapy, in those patients where they, whether they're now under, in the surveillance mode, those patients, if you have a positive, it may be positive. I had a recent patient like those, eight months before we saw anything on the scans. So, the question is, if you have a positive test, is there any advantage in giving them treatment, systemic treatment? Of course, we're assuming that the PET scan is negative. So, is there really any advantage in giving someone treatment ahead of time, before you see the imaging changes? That kind of data, in my opinion, is not really available or strong. You can always think of it in different ways, explain it in different ways. It's minimal disease, maybe you get a better response. But I don't know if we really can justify at this time. Therefore, in my practice, my own practice, I do not treat just a positive ctDNA. Again, that's different than after surgery when you're thinking of whether to give adjuvant treatment, no adjuvant treatment. But someone who's finished treatments and then you're just serially monitoring the disease, those patients, I do not treat them with chemotherapy. And that was something which, based on the literature we reviewed, there was nothing out there to definitely- I mean, if you see something positive, you will do a scan earlier, you will talk to the patient, examine the patient, whatever. But if there's nothing there, starting a treatment, that's not justified at this point in time. Now, you need to do a study like that. Definitely, you need to do a study. But I can tell you that from my experience, having been involved with study design and all that, it's not an easy trial to do. It's going to be a trial- at a minimum, it will take many patients, it will take longer time to complete, and there are a number of variables there. If someone is willing to put a lot of money into it, it can be done. But I can tell you that that kind of intention to do a study like that has been very much a challenge at this time. Dr. Rafeh Naqash: Of course, as you mentioned, the follow-up time that you need for a study like that is going to be very long to get to meaningful outcomes. Dr. Philip Philip: You need to be very patient to do such a study. But the problem with a very long study is that things change, standard of care changes with time, and the assays will change. So, that's why we don't have that kind of data. I'm not sure if there are people in the community or in the academic centers who do treat based on only positive ctDNA. The other thing is that you really have to always consider the psychological impact of these tests on patients and caregivers. Sometimes it can be really very stressful, burdensome to people to sit there just waiting for the disease to show up on a scan. And therefore, in my opinion, I'm not saying definitely don't use it in that situation, I'm just saying that you have to personalize it also, to see the patient who you would like to do it and then other patients who may not do it, or you think that it's not good for them to do it. And the patient also has to understand the outcome of the test and how you're going to be interpreting it. Dr. Rafeh Naqash: That's a lot of great insights, Dr. Philip, and I know you've been involved in trial designs. I'm sure NCT and cooperative groups are actively thinking and incorporating ctDNA-based metrics as one of the endpoints in their trial. I know of a GU study that's, I think it's an Alliance study, trying to de-escalate treatment based on ctDNA. I have one of my colleagues who's also a GU investigator at OU, he's doing a ctDNA-based, tumor-informed-based de-escalation. So, obviously, more and more data, hopefully, that'll be generated in the next couple of years. Dr. Philip Philip: But remember, these studies are not using it as an endpoint. They're using it as a means of optimizing treatment, which is a bit different. So, as an endpoint, can you do a phase III trial of, let's say, a thousand patients, and your primary endpoint is not survival, but you're saying, "Can I reduce the ctDNA, clear it earlier, or whatever?" That's the sort of thing this article was about. We can't do that at this time. Dr. Rafeh Naqash: I totally understand. Thank you for explaining the difference, and hopefully more to come in this space in the next couple of years. I briefly wanted to touch upon your personal career and journey based on all that you've done and accomplished. Could you tell us about how you started, what your journey has been like, and how that connects with what you're doing right now, including mentoring other trainees and junior faculty? Dr. Philip Philip: Well, when I was in high school, I wanted to be an engineer, but I grew up in Baghdad, and all my friends wanted to do medicine, so I went with the tide, so I did medicine. I don't regret that. I would do it again if I had the opportunity. The reason why I did oncology was, I left the country and did a PhD in clinical pharmacology at the University of London. And that really got me, it was a topic which included, which was on cancer. So, I really got interested in a disease that is really a lot of science, and things are new, or were new at the time. And if I want to look back what I was doing, the beginning of my training in the 80s, second half of the 80s, and now, it's unbelievable how things have changed. But one of the things which I really have to say is that almost all my life I've been in what we call academic institutions. But I firmly believe that for people, whether academic or not, you have to be a very good, astute clinician, because many of the things we do, really, we're trying to put the patients in the center. It's not only doing fancy science, it's to do things that help the patients. And you can bring in bits and pieces of fancy science or less fancy science, but that's something which is really extremely important for us to think about, being a very good clinician, very good doctor, because medicine is a science, whether you're practicing as a solo practitioner or you're part of a large academic center. It's the way you think, the way you interrogate things that you're not sure of, the way you collaborate, the way you learn every day. I mean, at my age, I still don't like to miss any tumor board, because in each tumor board, there's something you learn, even if you think that you know everything. So, that's really the whole thing of it, is that be a very good clinician, be open-minded. Always, you have to think of things that, they look interesting, they look somehow unexplained. Always try to help find the solutions and do that. One of the major things that I feel that people should do is being also very focused on things. I mean, you have to also know what you want to do in the next 5, 10, 15 years. Because although everyone is in it in the same way when we start, but there are different things that drive people, people who want to do more of the formal research, like being an academic-like institution. But there are also a lot of people who are very successful outside of a- what we call an academic setting. In the United States, most people are not working in an academic kind of setting. Although, for me, the distinction between academic and community is getting less and less, because if you think that you do phase I trials in academia only, that's not true, because there are, in fact, in the state of Michigan, the most active phase I doctor is not even in academia, he's in private practice. So, you can do all these things. It's a matter of what you like to do, and you really have to make sure you know what you want to do. Because sometimes people are, especially early on, they get a bit confused, "What I want to do." There's an issue of doing general oncology versus subspecialist. If you're a subspecialist doing only GI, you have to make sure that you really also have some kind of recognition that you're only a GI oncologist, recognition regional, national, international, but some degree of recognition that you feel that people are coming to you for advice as a second opinion or whatever it is. But again, you have to decide what you think you want to be, how you want to be, because there's a lot of options here between community practice, academic practice, industry, and of course, there's always the administrative thing. Some people tend to be more like going into the line of being an administrator. So, there's a lot of options for you. Dr. Rafeh Naqash: Well, thank you again, Dr. Philip, for those pearls of wisdom. I think that was very insightful. I'm sure all the trainees and early-career investigators will find all that advice very helpful. Thank you again for joining us today. Thank you for listening to JCO Precision Oncology Conversations. Don't forget to give us a rating or review, and be sure to subscribe so you never miss an episode. You can find all ASCO shows at asco.org/podcast. The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement. Dr. Philip Philip Disclosures Honoraria: Bayer, Ipsen, incyte, Taiho Pharmaceutical, Astellas Pharma, BioNTech SE, Novocure, TriSalus Life Sciences, SERVIER, Seagen Consulting or Advisory Role: Celgene, Ipsen, Merck, TriSalus Life Sciences, Daiichi Sankyo, SynCoreBio, Taiho Pharmaceutical Speakers' Bureau: Incyte Research Funding: Bayer (Inst), incyte (Inst), Merck (Inst), Taiho Pharmaceutical (Inst), novartis (Inst), Regeneron (Inst), Genentech (Inst), halozyme (Inst), Lilly (Inst), Taiho Pharmaceutical (Inst), merus (Inst), BioNTech SE (Inst) Uncompensated Relationships: Rafael Pharmaceuticals, Caris MPI

JCO PO author Dr. Dean A. Regier at the Academy of Translational Medicine, University of British Columbia (UBC), and the School of Population and Public Health, BC Cancer Research Institute shares insights into his JCO PO article, "Clinical Effectiveness and Cost-Effectiveness of Multigene Panel Sequencing in Advanced Melanoma: A Population-Level Real-World Target Trial Emulation." Host Dr. Rafeh Naqash and Dr. Regier discuss the real-world clinical effectiveness and cost-effectiveness of multigene panels compared with single-gene BRAF testing to guide therapeutic decisions in advanced melanoma. Transcript Dr. Rafeh Naqash:Hello and welcome to JCO Precision Oncology Conversations, where we bring you engaging conversations with authors of clinically relevant and highly significant JCO PO articles. I'm your host, Dr. Rafeh Naqash, Podcast Editor for JCO Precision Oncology and Assistant Professor at the OU Health Stephenson Cancer Center in the University of Oklahoma. Today, we are excited to be joined by Dr. Dean A. Regier, Director at the Academy of Translational Medicine, Associate Professor at the School of Population and Public Health, UBC Senior Scientist at the British Columbia Cancer Research Institute, and also the senior author of the JCO Precision Oncology article entitled "Clinical Effectiveness and Cost-Effectiveness of Multigene Panel Sequencing in Advanced Melanoma: A Population-Level Real-World Target Trial Emulation." At the time of this recording, our guest's disclosures will be linked in the transcript. Dean, welcome to our podcast and thank you for joining us today. Dr. Dean Regier:Thank you. I'm delighted to be here. Dr. Rafeh Naqash:So, obviously, you are from Canada, and medicine, or approvals of drugs to some extent, and in fact approvals of gene testing to some extent is slightly different, which we'll come to learn about more today, compared to what we do in the US—and in fact, similarly, Europe versus North America to a large extent as well. Most of the time, we end up talking about gene testing in lung cancer. There is a lot of data, a lot of papers around single-gene panel testing in non-small cell lung cancer versus multigene testing. In fact, a couple of those papers have been published in JCO PO, and it has shown significant cost-effectiveness and benefit and outcomes benefit in terms of multigene testing. So this is slightly, you know, on a similar approach, but in a different tumor type. So, could you tell us first why you wanted to investigate this question? What was the background to investigating this question? And given your expertise in health economics and policy, what are some of the aspects that one tends or should tend to understand in terms of cost-effectiveness before we go into the results for this very interesting manuscript? Dr. Dean Regier:Yeah, of course, delighted to. So, one of the reasons why we're deeply interested in looking at comparative outcomes with respect to single- versus multigene testing— whether that's in a public payer system like Canada or an insurer system, a private system in the United States— is that the question around does multigene versus single-gene testing work, has not typically tested in randomized controlled trials. You don't have people randomized to multigene versus single-gene testing. And what that does, it makes the resulting evidence base, whether it's efficacy, safety, or comparative cost-effectiveness, highly uncertain. So, the consequence of that has been uneven uptake around the world of next-generation sequencing panels. And so if we believe that next-gen sequencing panels are indeed effective for our patients, we really need to generate that comparative evidence around effectiveness and cost-effectiveness. So we can go to payers, whether it be single payer or a private insurer, to say, "Here are the comparative outcomes." And when I say that uptake has been uneven, uptake there's been actually plenty, as you know, publications around that uneven uptake, whether it be in Europe, in the United States, in Canada. And so we're really interested in trying to produce that evidence to create the type of deliberations that are needed to have these types of technologies accessible to patients. And part of those deliberations, of course, is the clinical, but also in some contexts, cost-effectiveness. And so, we really start from the perspective of, can we use our healthcare system data, our learning healthcare system, to generate that evidence in a way that emulates a randomized controlled trial? We won't be able to do these randomized controlled trials for various, like really important and and reasons that make sense, quite frankly. So how can we mimic or emulate randomized controlled trials in a way that allows us to make inference around those outcomes? And for my research lab, we usually think through how do we do causal inference to address some of those biases that are inherent in observational data. So in terms of advanced melanoma, we were really interested in this question because first of all, there have been no randomized controlled trials around next-gen sequencing versus single-gene testing. And secondly, these products, these ICIs, immune checkpoint inhibitors, and BRAF and MEK inhibitors, they are quite expensive. And so the question really becomes: are they effective? And if so, to what extent are they cost-effective? Do they provide a good reason to have information around value for money? Dr. Rafeh Naqash:So now going to the biology of melanoma, so we know that BRAF is one of the tumor-agnostic therapies, it has approvals for melanoma as well as several other tumor types. And in fact, I do trials with different RAF-RAS kinase inhibitors. Now, one of the things that I do know is, and I'm sure some of the listeners know, is the DREAMseq trial, which was a melanoma study that was an NCI Cooperative Group trial that was led by Dr. Mike Atkins from Georgetown a couple of years back, that did show survival benefit of first-line immunotherapy sequencing. It was a sequencing study of whether to do first-line BRAF in BRAF-mutant melanoma followed by checkpoint inhibitors, or vice versa. And the immune checkpoint inhibitors followed by BRAF was actually the one that showed benefit, and the trial had to stop early, was stopped early because of the significant benefit seen. So in that context, before we approach the question of single-gene versus multigene testing in melanoma, one would imagine that it's already established that upfront nivolumab plus ipilimumab, for that matter, doublet checkpoint inhibitor therapy is better for BRAF-mutant melanoma. And then there's no significant other approvals for melanoma for NRAS or KIT, you know, mucosal melanomas tend to have KIT mutations, for example, or uveal melanomas, for that matter, have GNAQ, and there's no targeted therapies. So, what is the actual need of doing a broader testing versus just testing for BRAF? So just trying to understand when you started looking into this question, I'm sure you kind of thought about some of these concepts before you delved into that. Dr. Dean Regier:I think that is an excellent question, and it is a question that we asked ourselves: did we really expect any differences in outcomes between the testing strategies? And what did the real-world implementation, physician-guided, physician-led implementation look like? And so, that was kind of one of the other reasons that we really were interested is, why would we go to expanded multigene panel sequencing at all? We didn't really expect or I didn't expect an overall survival a priori. But what we saw in our healthcare system, what happened in our healthcare system was the implementation in 2016 of this multigene panel. And this panel covered advanced melanoma, and this panel cost quite a bit more than what they were doing in terms of the single-gene BRAF testing. And so when you're a healthcare system, you have to ask yourself those questions of what is the additional value associated with that? And indeed, I think in a healthcare system, we have to be really aware that we do not actually follow to the ideal extent randomized controlled trials or trial settings. And so that's the other thing that we have to keep in mind is when these, whether it's an ICI or a BRAF MEK inhibitor, when these are implemented, they do not look like randomized controlled trials. And so, we really wanted to emulate not just a randomized controlled trial, but a pragmatic randomized controlled trial to really answer those real-world questions around implementation that are so important to decision making. Dr. Rafeh Naqash:Sure. And just to understand this a little better: for us in the United States, when we talk about multigene testing, we generally refer to, these days, whole-exome sequencing with whole-transcriptome sequencing, which is like the nuclear option of of the testings, which is not necessarily cheap. So, when you talk about multigene testing in your healthcare system, what does that look like? Is it a 16-gene panel? Is it a 52-gene panel? What is the actual makeup of that platform? Dr. Dean Regier:Excellent question. Yeah, so at the time that this study is looking at, it was 2016, when we, as BC Cancer—so British Columbia is a population right now of 5.7 million people, and we have data on all those individuals. We are one healthcare system providing health care to 5.7 million people. In 2016, we had what I call our "home-brew" multigene panel, which was a 53-gene panel that was reimbursed as standard of care across advanced cancers, one of them being advanced melanoma. We have evolved since then. I believe in 2022, we are using one of the Illumina panels, the Focus panel. And so things have changed; it's an evolving landscape. But we're specifically focused on the 53-gene panel. It was called OncoPanel. And that was produced in British Columbia through the Genome Sciences Centre, and it was validated in a single-arm trial mostly around validity, etc. Dr. Rafeh Naqash:Thank you for explaining that. So now, onto the actual meat and the science of this project. So, what are some of the metrics from a health economy standpoint that you did look at? And then, methodology-wise, I understand, in the United States, we have a fragmented healthcare system. I have data only from my institution, for that matter. So we have to reach out to outside collaborators and email them to get the data. And that is different for you where you have access to all the data under one umbrella. So could you speak to that a little bit and how that's an advantage for this kind of research especially? Dr. Dean Regier:Yeah. In health economics, we look at the comparative incremental costs against the incremental effectiveness. And when we think about incremental costs, we think not just about systemic therapy or whether you see a physician, but also about hospitalizations, about all the healthcare interactions related to oncology or not that a patient might experience during their time or interactions with the healthcare system. You can imagine with oncology, there are multiple interactions over a prolonged time period depending on survival. And so what we try to do is we try to—and the benefit of the single-payer healthcare system is what we do is we link all those resource utilization patterns that each patient encounters, and we know the price of that encounter. And we compare those incremental costs of, in this case, it's the multigene panel versus the single-gene panel. So it's not just the cost of the panel, not just the cost of systemic therapy, but hospitalizations, physician encounters, etc. And then similarly, we look at, in this case, we looked at overall survival - we can also look at progression-free survival - and ask the simple question, you know, what is the incremental cost per life-year gained? And in that way, we get a metric or an understanding of value for money. And how we evaluate that within a deliberative priority setting context is we look at safety and efficacy first. So a regulatory package that you might get from, in our case, Health Canada or the FDA, so we look at that package, and we deliberate on, okay, is it safe and is it effective? How many patients are affected, etc. And then separately, what is the cost-effectiveness? And at what price, if it's not cost-effective, at what price would it be cost-effective? Okay, so for example, we have this metric called the incremental cost-effectiveness ratio, which is incremental cost in the numerator, and in this case, life-years gained in the denominator. And if it is around $50,000 or $100,000 per life-year gained—so if it's in that range, this ratio—then we might say it's cost-effective. If it's above this range, which is common in oncology, especially when we talk about ICIs, etc., then you might want to negotiate a price. And indeed, when we negotiate that price, we use the economic evaluation, that incremental cost-effectiveness ratio, as a way to understand at what price should we negotiate to in order to get value for money for the healthcare system. Dr. Rafeh Naqash:Thank you for explaining those very interesting terminologies. Now, one question I have in the context of what you just mentioned is, you know, like the drug development space, you talked about efficacy and safety, but then on the safety side, we talk about all-grade adverse events or treatment-related adverse events—two different terminologies. From a healthcare utilization perspective, how do you untangle if a patient on a BRAF therapy got admitted for a hypoxic respiratory failure due to COPD, resulting in a hospitalization from the cost, overall cost utilization, or does it not matter? Dr. Dean Regier:We try to do as much digging into those questions as possible. And so, this is real-world data, right? Real-world data is not exactly as clean as you'd get from a well-conducted clinical trial. And so what we do is we look at potential adverse event, whether it's hospitalization, and the types of therapies around that hospitalization to try- and then engage with clinicians to try to understand or tease out the different grades of the adverse event. Whether it's successful or not, I think that is a real question that we grapple with in terms of are we accurate in delineating different levels of adverse events? But we try to take the data around the event to try to understand the context in which it happens. Dr. Rafeh Naqash:Thank you for explaining that, Dean. So, again to the results of this manuscript, could you go into the methodology briefly? Believe you had 147 patients, 147 patients in one arm, 147 in the other. How did you split that cohort, and what were some of the characteristics of this cohort? Dr. Dean Regier:So, the idea, of course, is that we have selection criteria, study inclusion criteria, which included in our case 364 patients. And these were patients who had advanced melanoma within our study time period. So that was 2016 to 2018. And we had one additional year follow. So we had three total years. And what we did is that we linked our data, our healthcare system data. During this time, because the policy change was in 2016, we had patients both go on the multigene panel and on the single-gene BRAF testing. So, the idea was to emulate a pragmatic randomized controlled trial where we looked at contemporaneous patients who had multigene panel testing versus single-gene BRAF testing. And then we did a matching procedure—we call it genetic matching. And that is a type of matching that allows us to balance covariates across the patient groups, across the multigene versus BRAF testing cohorts. The idea again is, as you get in a randomized controlled trial, you have these baseline characteristics that look the same. And then the hope is that you address any source selection or confounding biases that prohibit you to have a clean answer to the question: Is it effective or cost-effective? So you address all those biases that may prohibit you to find a signal if indeed a signal is there. And so, what we did is we created—we did this genetic matching to balance covariates across the two cohorts, and we matched them one-to-one. And so what we were able to do is we were able to find, of those 364 patients in our pool, 147 in the multigene versus 147 in the single-gene BRAF testing that were very, very similar. In fact, we created what's called a directed acyclic graph or a DAG, together with clinicians to say, "Hey, what biases would you expect to have in these two cohorts that might limit our ability to find a signal of effectiveness?" And so we worked with clinicians, with health economists, with epidemiologists to really understand those different biases at play. And the genetic matching was able to match the cohorts on the covariates of interest. Dr. Rafeh Naqash:And then could you speak on some of the highlights from the results? I know you did survival analysis, cost-effectiveness, could you explain that in terms of what you found? Dr. Dean Regier:We did two analyses. The intention-to-treat analysis is meant to emulate the pragmatic randomized controlled trial. And what that does is it answers the question, for all those eligible for multigene or single-gene testing: What is the cost-effectiveness in terms of incremental life-years gained and incremental cost per life-years gained? And the second one was around a protocol analysis, which really answered the question of: For those patients who were actually treated, what was the incremental effectiveness and cost-effectiveness? Now, they're different in two very important ways. For the intention-to-treat, it's around population questions. If we gave single-gene or multigene to the entire population of advanced melanoma patients, what is the cost-effectiveness? The per-protocol is really around that clinical question of those who actually received treatment, what was the incremental cost and effectiveness? So very different questions in terms of population versus clinical cost and effectiveness. So, for the intention-to-treat, what we found is that in terms of life-years gained is around 0.22, which is around 2.5 months of additional life that is afforded to patients who went through the multigene panel testing versus the single-gene testing. That was non-statistically significant from zero at the 5% level. But on average, you would expect this additional 2.5 months of life. The incremental costs were again non-statistically significant, but they're around $20,000. And so when we look at incremental cost-effectiveness, we can also look at the uncertainty around that question, meaning what percentage of incremental cost-effectiveness estimates are likely to be cost-effective at different willingness-to-pay thresholds? Okay? So if you are willing to pay $100,000 to get one gain of life-years, around 52.8% of our estimates, in terms of when we looked at the entire uncertainty, would be cost-effective. So actually that meets the threshold of implementation in our healthcare system. So it's quite uncertain, just over 50%. But what we see is that decision-makers actually have a high tolerance for uncertainty around cost-effectiveness. And so, while it is uncertain, we would say that, well, the cost-effectiveness is finely balanced. Now, when we looked at the population, the per-protocol population, those folks who just got treatment, we actually have a different story. We have all of a sudden around 4.5 or just under 5 months of life gained that is statistically significantly different from zero, meaning that this is a strong signal of benefit in terms of life-years gained. In terms of the changes in costs or the incremental costs, they are larger again, but statistically insignificant. So the question now is, to what extent is it cost-effective? What is the probability of it being cost-effective? And at the $100,000 per life-year gained willingness-to-pay, there was a 73% chance that multigene panel testing versus single-gene testing is cost-effective. Dr. Rafeh Naqash:So one of the questions I have here, this is a clarification both for myself and maybe the listeners also. So protocol treatment is basically if you had gene testing and you have a BRAF in the multigene panel, then the patient went on a BRAF treatment. Is that correct? Dr. Dean Regier:It's still physician choice. And I think that's important to say that. So typically what we saw in both in our pre- and post-matching data is that we saw around 50% of patients, irrespective of BRAF status, get an ICI, which is appropriate, right? And so the idea here is that you get physician-guided care, but if the patient no longer performs on the ICI, then it gives them a little bit more information on what to do next. Even during that time when we thought it wasn't going to be common to do an ICI, but it was actually quite common. Dr. Rafeh Naqash:Now, did you have any patients in this study who had the multigene testing done and had an NRAS or a KIT mutation and then went on to those therapies, which were not captured obviously in the single-gene testing, which would have just tried to look at BRAF? Dr. Dean Regier:So I did look at the data this morning because I thought that might come up in terms of my own questions that I had. I couldn't find it, but what we did see is that some patients went on to clinical trials. So, meaning that this multigene panel testing allowed, as you would hope in a learning healthcare system, patients to move on to clinical trials to have a better chance at more appropriate care if a target therapy was available. Dr. Rafeh Naqash:And the other question in that context, which is not necessarily related to the gene platform, but more on the variant allele frequency, so if you had a multigene panel that captured something that was present at a high VAF, with suspicion that this could be germline, did you have any of those patients? I'm guessing if you did, probably very low number, but I'm just thinking from a cost-effective standpoint, if you identify somebody with germline, their, you know, first-degree relative gets tested, that ends up, you know, prevention, etc. rather than somebody actually developing cancer subsequently. That's a lot of financial gains to the system if you capture something early. So did you look at that or maybe you're planning to look at that? Dr. Dean Regier:We did not look at that, but that is a really important question that typically goes unanswered in economic evaluations. And so, the short answer is yes, that result, if there was a germline finding, would be returned to the patient, and then the family would be able to be eligible for screening in the appropriate context. What we have found in economic evaluations, and we've recently published this research, is that that scope of analysis is rarely incorporated into the economic evaluation. So those downstream costs and those downstream benefits are ignored. And when you- especially also when you think about things like secondary or incidental findings, right? So it could be a germline finding for cancer, but what about all those other findings that we might have if you go with an exome or if you go with a genome, which by the way, we do have in British Columbia—we do whole-genome and transcriptome sequencing through something called the Personalized OncoGenomics program. That scope of evaluation, because it's very hard to get the right types of data, because it requires a decision model over the lifetime of both the patients and potentially their family, it becomes very complicated or complex to model over patients' and families' lifetime. That doesn't mean that we should not do it, however. Dr. Rafeh Naqash:So, in summary Dean, could you summarize some of the known and unknowns of what you learned and what you're planning in subsequent steps to this project? Dr. Dean Regier:Our North Star, if you will, is to really understand the entire system effect of next-generation sequencing panels, exome sequencing, whole genomes, or whole genomes and transcriptome analysis, which we think should be the future of precision oncology. The next steps in our research is to provide a nice base around multigene panels in terms of multigene versus single-gene testing, whether that be colorectal cancer, lung cancer, melanoma, etc., and to map out the entire system implications of implementing next-generation sequencing panels. And then we want to answer the questions around, "Well, what if we do exomes for all patients? What if we do whole genomes and transcriptomes for all patients? What are the comparative outcomes for a true tumor-agnostic precision oncology approach, accounting for, as you say, things like return of results with respect to hereditary cancers?" I think the challenge that's going to be encountered is really around the persistent high costs of something like a whole-genome and transcriptome sequencing approach. Although we do see the technology prices going down—the "$1,000 genome" or "$6,000 genome" on whatever Illumina machine you might have—that bioinformatics is continuing to be expensive. And so, there are pipelines that are automated, of course, and you can create a targeted gene report really rapidly within a reasonable turnaround time. But of course, for secondary or what I call level two analysis, that bioinformatics is going to continue to be expensive. And so, we're just continually asking that question is: In our healthcare system and in other healthcare systems, if you want to take a precision oncology approach, how do you create the pipelines? And what types of technologies really lend themselves to benefits over and above next-generation sequencing or multigene panels, allowing for access to off-label therapies? What does that look like? Does that actually improve patients? I think some of the challenges, of course, is because of heterogeneity, small benefiting populations, finding a signal if a signal is indeed there is really challenging. And so, what we are thinking through is, with respect to real-world evidence methods and emulating randomized controlled trials, what types of evidence methods actually allow us to find those signals if indeed those signals are there in the context of small benefiting populations? Dr. Rafeh Naqash:Thank you so much, Dean. Sounds like a very exciting field, especially in the current day and age where cost-effectiveness, financial toxicity is an important aspect of how we improve upon what is existing in oncology. And then lots more to be explored, as you mentioned. The last minute and a half I want to ask about you as an individual, as a researcher. There's very few people who have expertise in oncology, biomarkers, and health economics. So could you tell us for the sake of our trainees and early career physicians who might be listening, what was your trajectory briefly? How did you end up doing what you're doing? And maybe some advice for people who are interested in the cost of care, the cost of oncology drugs - what would your advice be for them very briefly? Dr. Dean Regier:Sure. So I'm an economist by training, and indeed I knew very little about the healthcare system and how it works. But I was recruited at one point to BC Cancer, to British Columbia, to really try to understand some of those questions around costs, and then I learned also around cost-effectiveness. And so, I did training in Scotland to understand patient preferences and patient values around quality of care, not just quantity of life, but also their quality of life and how that care was provided to them. And then after that, I was at Oxford University at the Nuffield Department of Population Health to understand how that can be incorporated into randomized control trials in children. And so, I did a little bit of learning about RCTs. Of course, during the way I picked up some epidemiology with deep understanding of what I call econometrics, what others might call biostatistics or just statistics. And from there, it was about working with clinicians, working with epidemiologists, working with clinical trialists, working with economists to understand the different approaches or ways of thinking of how to estimate efficacy, effectiveness, safety, and cost-effectiveness. I think this is really important to think through is that we have clinical trialists, we have people with deep understanding of biostatistics, we have genome scientists, we have clinicians, and then you add economists into the mix. What I've really benefited from is that interdisciplinary experience, meaning that when I talk to some of the world's leading genome scientists, I understand where they're coming from, what their hope and vision is. And they start to understand where I'm coming from and some of the tools that I use to understand comparative effectiveness and cost-effectiveness. And then we work together to actually change our methods in order to answer those questions that we're passionate about and curious about better for the benefit of patients. So, the short answer is it's been actually quite a trajectory between Canada, the UK. I spent some time at the University of Washington looking at the Fred Hutch Cancer Research Center, looking at precision oncology. And along the way, it's been an experience about interdisciplinary research approaches to evaluating comparative outcomes. And also really thinking through not just at one point in time on-off decisions—is this effective? Is it safe? Is it cost-effective?—not those on-off decisions, but those decisions across the lifecycle of a health product. What do those look like at each point in time? Because we gain new evidence, new information at each point in time as patients have more and more experience around it. And so what really is kind of driving our research is really thinking about interdisciplinary approaches to lifecycle evaluation of promising new drugs with the goal of having these promising technologies to patients sooner in a way that is sustainable for the healthcare system. Dr. Rafeh Naqash:Awesome. Thank you so much for those insights and also giving us a sneak peek of your very successful career. Thank you for listening to JCO Precision Oncology Conversations. Don't forget to give us a rating or review, and be sure to subscribe so you never miss an episode. You can find all ASCO shows at asco.org/podcast. Thank you. The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.

JCO PO author Dr. Timothy Showalter at Artera and University of Virginia shares insights into his JCO PO article, "Digital Pathology–Based Multimodal Artificial Intelligence Scores and Outcomes in a Randomized Phase III Trial in Men With Nonmetastatic Castration-Resistant Prostate Cancer" . Host Dr. Rafeh Naqash and Dr. Showalter discuss how multimodal AI as a prognostic marker in nonmetastatic castration-resistant prostate cancer may serve as a predictive biomarker with high-risk patients deriving the greatest benefit from treatment with apalutamide. TRANSCRIPT Dr. Rafeh Naqash: Hello and welcome to JCO Precision Oncology Conversations where we'll bring you engaging conversations with authors of clinically relevant and highly significant JCO PO articles. I'm your host, Dr. Rafeh Naqash, podcast Editor for JCO Precision Oncology and assistant professor at the OU Health Stephenson Cancer Center at the University of Oklahoma. Today, we are excited to be joined by Dr. Timothy Showalter, Chief Medical Officer at Artera and professor of Radiation Oncology at the University of Virginia and author of the JCO Precision Oncology article entitled, "Digital Pathology Based Multimodal Artificial Intelligence Scores and Outcomes in a Randomized Phase 3 Trial in Men with Non-Metastatic Castration Resistant Prostate Cancer." At the time of this recording, our guest's disclosures will be linked in the transcript. Dr. Showalter, it's a pleasure to have you here today. Dr. Timothy Showalter: It's a pleasure to be here. Thanks for having me. Dr. Rafeh Naqash: I think this is going to be a very interesting discussion, not just from a biomarker perspective, but also in terms of how technologies have evolved and how we are trying to stratify patients, trying to escalate or deescalate treatments based on biomarkers. And this article is a good example of that. One of the things I do want to highlight as part of this article is that Dr. Felix Feng is the first author for this article. Unfortunately, Dr. Felix Feng passed away in December of 2024. He was a luminary in this field of prostate cancer research. He was also the Chair of the NRG GU Committee as well as Board of Directors for RTOG Foundation and has mentored a lot of individuals from what I have heard. I didn't know Dr. Feng but heard a lot about him from my GU colleagues. It's a huge loss for the community, but it was an interesting surprise for me when I saw his name on this article as I was reviewing it. Could you briefly talk about Dr. Feng for a minute and how you knew him and how he's been an asset to the field? Dr. Timothy Showalter: Yeah. I'm always happy to talk about Felix whenever there's an opportunity. You know, I was fortunate to know Felix Feng for about 20 years as we met during our residency programs through a career development workshop that we both attended and stayed close ever since. And you know, he's someone who made an impact on hundreds of lives of cancer researchers and other radiation oncologists and physicians in addition to the cancer patients he helped, either through direct clinical care or through his innovation. For this project in particular, I first became involved soon after Felix had co-founded Artera, which is, you know the company that developed this. And because Felix was such a prolific researcher, he was actually involved in this and this research project from all different angles, both from the multimodal digital pathology tool to the trial itself and being part of moving the field forward in that way. It's really great to be able to sort of celebrate a great example of Felix's legacy, which is team science, and really moving the field forward in terms of translational projects based on clinical trials. So, it's a great opportunity to highlight some of his work and I'm really happy to talk about it with you. Dr. Rafeh Naqash: Thanks, Tim. Definitely a huge loss for the scientific community. And I did see a while back that there was an international symposium organized, showcasing his work for him to talk about his journey last year where more than 200, 250 people from around the globe actually attended that. That speaks volumes to the kind of impact he's had as an individual and impact he's had on the scientific side of things as well. Dr. Timothy Showalter: Yes. And we just had the second annual Feng Symposium the day before ASCO GU this year with, again, a great turnout and some great science highlighted, as well as a real focus on mentorship and team science and collaboration. Dr. Rafeh Naqash: Thank you so much for telling us all about that. Now going to what you guys published in JCO Precision Oncology, which is this article on using a biomarker approach to stratify non-metastatic prostate cancer using this artificial intelligence based H&E score. Could you tell us the background for what started off this project? And I see there is a clinical trial data set that you guys have used, but there's probably some background to how this score or how this technology came into being. So, could you superficially give us an idea of how that started? Dr. Timothy Showalter: Sure. So, the multimodal AI score was first published in a peer reviewed journal back in 2022 and the test was originally developed through a collaboration with the Radiation Therapy Oncology Group or Energy Oncology Prostate Cancer Research Team. The original publication describes development and validation of a risk stratification tool designed to predict distant metastasis and prostate cancer specific mortality for men with localized prostate cancer. And the first validation was in men who were treated with definitive radiation therapy. There have been subsequent publications in that context and there's a set of algorithms that have been validated in localized prostate cancer and there's a test that's listed on NCCN guidelines based on that technology. The genesis for this paper was really looking at extending that risk stratification tool that was developed in localized prostate cancer to see if it could one, validate in a non-metastatic castrate refractory prostate cancer population for patients enrolled on the SPARTAN trial. And two, whether there was a potential role for the test output in terms of predicting benefit from apalutamide for patients with non-metastatic prostate cancer. For patients who are enrolled on the SPARTAN study, almost 40% of them had H&E stain biopsy slide material available and were eligible to be included in this study. Dr. Rafeh Naqash: Going a step back to how prostate cancer, perhaps on the diagnostic side using the pathology images is different as you guys have Gleason scoring, which to the best of my knowledge is not necessarily something that most other tumor types use. Maybe Ki-67 is somewhat of a comparison in some of the neuroendocrine cancers where high Ki-67 correlates with aggressive biology for prognosis. And similarly high Gleason scores, as we know for some of the trainees, correlates with poor prognosis. So, was the idea behind this based on trying to stratify or sub-stratify Gleason scoring further, where you may not necessarily know what to do with the intermediate high Gleason score individual tumor tissues? Dr. Timothy Showalter: Well, yeah. I mean, Gleason score is a really powerful risk stratification tool. As you know, our clinical risk groupings are really anchored to Gleason scores as an important driver for that. And while that's a powerful tool, I think, you know, some of the original recognition for applying computer vision AI into this context is that there are likely many other features located in the morphology that can be used to build a prognostic model. Going back to the genesis of the discovery project for the multimodal AI model, I think Felix Feng would have described it as doing with digital pathology and computer vision AI what can otherwise be done with gene expression testing. You know, he would have approached it from a genomic perspective. That's what the idea was. So, it's along the line of what you're saying, which is to think about assigning a stronger Gleason score. But I think really more broadly, the motivation was to come up with an advanced complementary risk stratification tool that can be used in conjunction with clinical risk factors to help make better therapy recommendations potentially. So that was the motivation behind it. Dr. Rafeh Naqash: Sure. And one of the, I think, other important teaching points we try to think about, trainees of course, who are listening to this podcast, is trying to differentiate between prognostic and predictive scores. So, highlighting the results that you guys show in relation to the MMAI score, the digital pathology score, and outcomes as far as survival as well as outcomes in general, could you try to help the listeners understand the difference between the prognostic aspect of this test and the predictive aspect of this test? Dr. Timothy Showalter: So let me recap for the listeners what we found in the study and how it kind of fits into the prognostic and the predictive insights. So, one, you know, as I mentioned before, this is ultimately a model that was developed and validated for localized prostate cancer for risk stratification. So, first, the team looked at whether that same tool developed in localized prostate cancer serves as a prognostic tool in non-metastatic castrate-refractory prostate cancer. So, we applied the tool as it was previously developed and identified that about 2/3 of patients on the SPARTAN trial that had specimens available for analysis qualified as high risk and 1/3 of patients as either intermediate or low risk, which we called in the paper 'non-high risk'. And we're able to show that the multimodal AI score, which ranges from 0 to 1, and risk group, was associated with metastasis free survival time to second progression or PFS 2 and overall survival. And so that shows that it performs as a prognostic tool in this setting. And this paper was the first validation of this tool in non-metastatic castrate-refractory prostate cancer. So, what that means to trainees is basically it helps you understand how aggressive that cancer is or better stratify the risk of progression over time. So that's the prognostic performance. Dr. Rafeh Naqash: Thank you for trying to explain that. It's always useful to get an example and understand the difference between prognostic and predictive. Now again, going back to the technology, which obviously is way more complicated than the four letter word MMAI, I per se haven't necessarily done research in this space, but I've collaborated with some individuals who've done digital pathology assessments, and one of the projects we worked on was TIL estimation and immune checkpoint related adverse events using some correlation and something that one of my collaborators had sent to me when we were working on this project as part of this H&E slide digitalization, you need color deconvolution, you need segmentation cell profiling. Superficially, is that something that was done as part of development of this MMAI score as well? Dr. Timothy Showalter You need a ground truth, right? So, you need to train your model to predict whatever the outcome is. You know, if you're designing an AI algorithm for Ki-67 or something I think you mentioned before, you would need to have a set of Ki-67 scores and train your models to create those scores. In this case, the clinical annotation for how we develop the multimodal AI algorithm is the clinical endpoints. So going back to how this tool was developed, the computer vision AI model is interpreting a set of features on the scan and what it's trying to do is identify high risk features and make a map that would ultimately predict clinical outcomes. So, it's a little bit different than the many digital pathology algorithms where the AI is being trained to predict a particular morphological finding. In this case, the ground truth that the model is trained to predict is the clinical outcome. Dr. Rafeh Naqash: Sure. And from what you explained earlier, obviously, tumors that had a high MMAI score were the ones that were benefiting the most from the ADT plus the applausive. Is this specific for this androgen receptor inhibitor or is it interchangeable with other inhibitors that are currently approved? Dr. Timothy Showalter: That's a great question and we don't know yet. So, as you're alluding to, we did find that the MMAI risk score was predictive for benefit from apalutamide and so it met the statistical definition of having a significant interaction p value so we can call it a predictive performance. And so far, we've only looked in this population for apalutamide. I think you're raising a really interesting point, which is the next question is, is this generalizable to other androgen receptor inhibitors? There will be future research looking at that, but I think it's too early to say. Just for summary, I think I mentioned before, there are about 40% of patients enrolled on the SPARTAN study had specimens available for inclusion in this analysis. So, the SPARTAN study did show in the entire clinical trial set that patients with non-metastatic castrate-refractory prostate cancer benefited from apalutamide. The current study did show that there seems to be a larger magnitude of benefit for those patients who are multimodal AI high risk scores. And I think that's very interesting research and suggests that there's some interaction there. But I certainly would want to emphasize that we have not shown that patients with intermediate or low risk don't benefit from apalutamide. I think we can say that the original study showed that that trial showed a benefit and that we've got this interesting story with multimodal AI as well. Dr. Rafeh Naqash: Sure. And I think from a similar comparison, ctDNA where ctDNA shows prognostic aspects, I treat people with lung cancer especially, and if you're ctDNA positive at a 3 to 4-month period, likely chances of you having a shorter disease-free interval is higher. Same thing I think for colorectal cancers. And now there are studies that are using ctDNA as an integral biomarker to stratify patients positive/negative and then decide on escalation/de-escalation of treatment. So, using a similar approach, is there something that is being done in the context of the H&E based stratification to de-intensify or intensify treatments based on this approach? Dr. Timothy Showalter: You're hitting right on the point in the most promising direction. You know, as we pointed out in the manuscript, one of the most exciting areas as a next step for this is to use a tool like this for stratification for prospective trials. The multimodal AI test is not being used currently in clinical trials of non-metastatic castrate-refractory prostate cancer, which is a disease setting for this paper. There are other trials that are in development or currently accruing where multimodal AI stratification approach is being taken, where you see among the high-risk scores, at least in the postoperative setting for a clinical trial that's open right now, high risk score patients are being randomized to basically a treatment intensification question. And then the multimodal AI low risk patients are being randomized to a de-intensification experimental arm where less androgen deprivation therapy is being given. So, I think it's a really promising area to see, and I think what has been shown is that this tool has been validated really across the disease continuum. And so, I think there are opportunities to do that in multiple clinical scenarios. Dr. Rafeh Naqash: Then moving on to the technological advancements, very fascinating how we've kind of evolved over the last 10 years perhaps, from DNA based biomarkers to RNA expression and now H&E. And when you look at cost savings, if you were to think of H&E as a simpler, easier methodology, perhaps, with the limitations that centers need to digitalize their slides, probably will have more cost savings. But in your experience, as you've tried to navigate this H&E aspect of trying to either develop the model or validate the model, what are some of the logistics that you've experienced can be a challenge? As we evolve in this biomarker space, how can centers try to tackle those challenges early on in terms of digitalizing data, whether it's simple data or slides for that matter? Dr. Timothy Showalter: I think there's two main areas to cover. One, I think that the push towards digitalization is going to be, I think, really driven by increasing availability and access to augmentative technologies like this multimodal AI technology where it's really adding some sort of a clinical insight beyond what is going to be generated through routine human diagnostic pathology. I think that when you can get these sorts of algorithms for patient care and have them so readily accessible with a fast turnaround time, I think that's really going to drive the field forward. Right now, in the United States, the latest data I've seen is that less than 10% of pathology labs have gone digital. So, we're still at an early stage in that. I hope that this test and similar ones are part of that push to go more digital. The other, I think, more interesting challenge that's a technical challenge but isn't about necessarily how you collect the data, but it certainly creates data volume challenges, is how do you deal with image robustness and sort of translating these tools into routine real-world settings. And as you can imagine, there's a lot of variation for staining protocols, intensity scanner variations, all these things that can affect the reliability of your test. And at least for this research group that I'm a part of that has developed this multimodal AI tool can tell you that the development is sophisticated, but very data and energy intensive in terms of how to deal with making a tool that can be consistent across a whole range of image parameters. And so that presents its own challenges for dealing with a large amount of compute time and AI cycles to make robust algorithms like that. And practically speaking, I think moving into other diseases and making this widely available, the size of data required and the amount of cloud compute time will be a real challenge. Dr. Rafeh Naqash: Thank you for summarizing. I can say that definitely, you know, this is maybe a small step in prostate cancer biomarker research, but perhaps a big step in the overall landscape of biomarker research in general. So definitely very interesting. Now, moving on to the next part of the discussion is more about you as a researcher, as an individual, your career path, if you can summarize that for us. And more interestingly, this intersection between being part of industry as well as academia for perhaps some of the listeners, trainees who might be thinking about what path they want to choose. Dr. Timothy Showalter: Sure. So, as you may know, I'm a professor at the University of Virginia and I climbed the academic ladder and had a full research grant program and thought I'd be in academia forever. And my story is that along the way, I kind of by accident ended up founding a medical device company that was called Advaray and that was related to NCI SBIR funding. And I found myself as a company founder and ultimately in that process, I started to learn about the opportunity to make an impact by being an innovator within the industry space. And that was really the starting point for me. About four years ago, soon after Felix Feng co-founded Artera, he called me and told me that he needed me to join the company. For those who were lucky to know Felix well, at that very moment, it was inevitable that I was going to join Artera and be a part of this. He was just so persuasive. So, I will say, you know, from my experience of being sort of in between the academic and industry area, it's been a really great opportunity for me to enter a space where there's another way of making an impact within cancer care. I've gotten to work with top notch collaborators, work on great science, and be part of a team that's growing a company that can make technology like this available. Dr. Rafeh Naqash: Thank you so much, Tim, for sharing some of those thoughts and insights. We really appreciate you discussing this very interesting work with us and also appreciate you submitting this to JCO Precision Oncology and hopefully we'll see more of this as this space evolves and maybe perhaps bigger more better validation studies in the context of this test. Thank you for listening to JCO Precision Oncology Conversations. Don't forget to give us a rating or review and be sure to subscribe so you never miss an episode. You can find all ASCO shows at asco.org/podcast. 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