JCO PO Article Insights: Analytical Validation of Tumor-Informed ctDNA Assays for MRD

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.

In this JCO Precision Oncology Article Insights episode, host Dr. Carolyn Lineen summaries the article, "Concordance of Oncotype DX Breast Recurrence Score Assay Results Between Paired Core Needle Biopsy and Surgical Excision Specimens in Hormone Receptor Positive, HER2-Negative Early-Stage Breast Cancer," by Nassar et al. TRANSCRIPT Carolyn Lineen: Hello and welcome to JCO Precision Oncology Article Insights. I'm your host, Carolyn Lineen, from St. James's Hospital, Dublin, and today we will be discussing the JCO Precision Oncology article titled "Concordance of Oncotype DX Breast Recurrence Score Assay Results Between Paired Core Needle Biopsy and Surgical Excision Specimens in Hormone Receptor Positive, HER2-Negative Early-Stage Breast Cancer" by Dr. Aziza Nassar and colleagues. The Oncotype DX Breast Recurrence Score assay is a 21-gene expression test that provides both prognostic information regarding distant recurrence risk and predictive information regarding the benefit of adjuvant chemotherapy in hormone receptor-positive, HER2-negative early-stage breast cancer. The recurrence score ranges from 0 to 100, with higher scores indicating a greater risk of recurrence and a potentially higher likelihood of benefit from chemotherapy. Traditionally, genomic testing is performed on surgical excision specimens following tumor resection. However, this approach can potentially delay access to biological risk stratification, which may be important when early treatment planning or neoadjuvant therapy is being considered. The primary objective of this study was to evaluate the level of concordance between recurrence scores derived from paired core needle biopsy specimens and surgical excision specimens obtained from the same untreated primary breast tumors. Investigators specifically evaluated both continuous recurrence score agreement and categorical risk classification concordance. The study included 134 patients with paired biopsy and surgical specimens. The median patient age was 62 years, with a wide age range from 33 to 99 years. Approximately 17% of patients were aged 50 years or younger, while 83% were older than 50 years. All patients had hormone receptor-positive, HER2-negative early-stage breast cancer and had not received prior systemic treatment before either specimen collection. Each patient contributed two tumor samples: a core needle biopsy specimen obtained at initial diagnosis and a surgical excision specimen obtained during definitive tumor resection. Both samples underwent Oncotype DX testing, allowing direct within-patient comparison. The investigators reported mean recurrence scores of 15.6 for core needle biopsy specimens and 16.6 for surgical excision specimens. Although this absolute mean difference between specimen types did reach statistical significance with a P value of 0.003, the authors note that this numerical difference was small at one recurrence score unit and may not therefore be clinically meaningful. Additionally, categorical recurrence score results did not differ significantly. The primary measure of agreement between recurrence scores was the Lin's concordance correlation coefficient. The study demonstrated a Lin concordance correlation coefficient of 0.86 with a 95% confidence interval ranging from 0.80 to 0.90, indicating strong agreement between biopsy and surgical specimens. Additionally, categorical agreement was assessed using Cohen's kappa statistic. The study reported a kappa value of 0.64 with a 95% confidence interval from 0.44 to 0.83, indicating substantial agreement between specimen types. Comparing this study to previously published evidence, the authors referenced prior smaller studies examining concordance between paired tissue samples. For example, earlier research evaluating 50 patients demonstrated correlation coefficients of approximately 0.8 and categorical concordance rates ranging from 72% to 78%, depending on the classification cut points used. Compared with earlier studies, the present study provides stronger evidence supporting consistency between biopsy and surgical testing. These findings have several important implications for clinical practice. First, early availability of recurrence score results may enhance multidisciplinary care planning. Obtaining genomic risk data at the time of diagnosis allows tumor boards to integrate molecular risk stratification into initial treatment discussions rather than waiting for postoperative results. Second, biopsy-based testing may support decision making regarding treatment sequencing. Earlier genomic information may help guide selection of neoadjuvant therapy or inform early decisions about adjuvant chemotherapy necessity. Third, early testing may reduce delays in treatment initiation. Separate research evaluating presurgical Oncotype DX testing has demonstrated potential reductions in time to initiation of adjuvant therapy by approximately 8 days, suggesting potential improvements in care efficiency. Additionally, biopsy-based testing demonstrates strong technical feasibility. Studies examining real-world implementation have reported test success rates as high as 99.1% when performed on core biopsy specimens. Despite the encouraging results, certain limitations must be considered. Core needle biopsy samples evaluate only a portion of the tumor, and intratumoral heterogeneity could theoretically influence recurrence score results in selected cases. Preanalytical factors, including tissue fixation and sample handling, may also affect RNA integrity and assay performance. Standardization of specimen processing protocols will be essential if biopsy-based testing becomes routine. Furthermore, although analytical concordance is strong, prospective outcome studies demonstrating equivalent long-term clinical outcomes based on biopsy-directed treatment decisions would further strengthen the evidence base. In conclusion, this study demonstrates strong concordance between Oncotype DX Breast Recurrence Scores derived from core needle biopsy specimens and surgical excision specimens in patients with hormone receptor-positive, HER2-negative early-stage breast cancer. With a concordance correlation coefficient of 0.86 and overall categorical agreement exceeding 90%, the findings support the clinical feasibility of performing genomic testing at the time of diagnostic biopsy. If validated through additional prospective studies, this approach may enable earlier risk stratification and improve multidisciplinary treatment planning. 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.

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.  

In this JCO Precision Oncology Article Insights episode, host Dr. Jiasen He summaries the article, "Longitudinal Evaluation of Circulating Tumor DNA as a Prognostic Biomarker to Detect Molecular Residual Disease in Germ Cell Tumors," by Hassoun et al. TRANSCRIPT Jiasen He: Hello, and welcome to the JCO Precision Oncology Article Insights. I'm your host, Jiasen He, and today, we'll be discussing the JCO Precision Oncology article, "Longitudinal Evaluation of Circulating Tumor DNA as a Prognostic Biomarker to Detect Molecular Residual Disease in Germ Cell Tumors," by Dr. Rebecca Hassoun and colleagues. Traditionally, treatment response for solid tumors has relied on imaging, which focuses on visible anatomic changes in the tumor. However, imaging does not always reflect molecular or cellular changes and cannot detect microscopic disease, which is clinically important and often linked to relapse. Liquid biopsy, on the other hand, is minimally invasive and can be used for cancer monitoring by analyzing circulating biomarkers in biofluids such as blood. One type of liquid biopsy is circulating tumor DNA, or ctDNA, which measures small fragments of DNA released by tumor cells into the bloodstream. ctDNA can allow precise monitoring of tumor-specific mutations and be a powerful tool for assessing treatment responses. ctDNA has already been applied in clinical settings for cancers such as non-small cell lung cancer and breast cancer, etcetera. However, there is still limited data on the use of ctDNA for germ cell tumors. Germ cell tumors are the most common malignancy affecting men aged 15 to 35 years. Accurate risk stratification and disease monitoring is key to risk-adapted therapy, maximizing the chance of cure while minimizing side effects. One unique tool we use currently for diagnosis, staging, and monitoring is serum tumor markers, such as AFP, beta-hCG, and LDH. However, these markers have limitations, including false elevation in certain clinical scenarios, and studies have shown that they can be normal in up to 40 percent of patients with germ cell tumor. This creates an unmet need for other sensitive and specific biomarkers to improve patient care. In this paper, the authors investigated the use of ctDNA in a cohort of patients with germ cell tumor at various disease time points. They compared ctDNA results with traditional serum tumor markers to evaluate whether ctDNA can predict relapse and survival outcomes. This multi-institutional retrospective study included patients with stage I, II, and III germ cell tumors, primarily testicular cancer, who had at least one ctDNA test result. ctDNA was evaluated longitudinally at different time points, including pre-orchiectomy, during the molecular residual disease, or MRD, window, defined as 1 to 12 weeks post-orchiectomy but before primary therapy, and during the surveillance window, defined as more than 12 weeks post-orchiectomy or follow retroperitoneal lymph node dissection or post-chemotherapy. ctDNA analysis was performed using a tumor-informed 16 multiplex PCR next-generation sequencing assay. A total of 324 plasma samples were analyzed from 74 patients in this cohort. The majority had stage I disease, around 40 percent, and nonseminomatous histology, around 70 percent. 15 patients were evaluated in the pre-orchiectomy window, and only one patient tested negative for ctDNA. This patient had stage I disease. The authors further assessed ctDNA positivity in both the MRD window and surveillance window, evaluating its association with event-free survival. They found that ctDNA outperformed serum tumor markers in both settings. ctDNA positivity was associated with significantly worse event-free survival compared with ctDNA-negative patients. Among the 14 patients with stage II to III disease who had ctDNA assessed in both the MRD window and surveillance window, nine patients consistently had a negative ctDNA or converted from positive to negative over time. In contrast, five patients demonstrated persistent ctDNA positivity, and all of these patients subsequently relapsed. Among the 38 patients who had both ctDNA and serum tumor marker tests during the MRD window, nine patients showed discordant biomarker results. Of these, 6 patients were ctDNA-negative but serum tumor marker-positive, and one of them experienced recurrence. Three patients were ctDNA-positive but serum tumor marker-negative, and one of these patients also recurred. During the surveillance window, 46 patients had both biomarkers available, and 10 showed discordant results. Three patients were ctDNA-negative but serum tumor marker-positive, and none of them recurred. In contrast, all seven patients who were ctDNA-positive but serum tumor marker-negative experienced recurrence. This intriguing data strongly support the potential role of ctDNA in patients with stage I, II, and III germ cell tumors. However, as the authors noted, the retrospective nature of the study presents limitations, as treatment approaches, imaging schedules, and the timing of testing were not standardized, and ctDNA testing varies among participating institutions. Larger prospective trials with standardized protocols and long-term follow-up will be essential to validate these findings and determine how ctDNA can be reliably integrated into clinical practice. 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.

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

In this JCO Precision Oncology Article Insights episode, host Dr. Harold Nathan Tan summarizes "Palbociclib in Patients With Head and Neck Cancer and Other Tumors With CDKN2A Alterations: Results From the Targeted Agent and Profiling Utilization Registry Study" by Worden et al.  TRANSCRIPT Harold Nathan Tan: Welcome to JCO Precision Oncology Article Insights, where we explore research that is reshaping our understanding of cancer therapeutics. I'm your host, Harold Nathan Tan, and today's episode centers on the TAPUR study, an analysis that confronts a long-standing assumption in molecular oncology: namely, whether CDKN2A alterations create a therapeutic vulnerability that can be exploited by CDK4/6 inhibition with palbociclib. CDKN2A is one of the most frequently altered tumor suppressors across solid tumors. Its importance lies in its production of two proteins, p16 and p14, which serve as guardians of cell cycle progression. p16 directly inhibits CDK4 and CDK6, preventing phosphorylation of the RB protein and therefore blocking entry into S phase, whereas p14 stabilizes p53 by counteracting MDM2, enabling cells to pause or die in response to oncogenic stress. When CDKN2A is lost or mutated, these dual checkpoints collapse. CDK4/6 activity becomes unchecked, RB remains phosphorylated and inactive, and p53-mediated surveillance is blunted from a mechanistic standpoint. This creates a possible dependency on CDK4/6 signaling that could, in principle, be therapeutically reversed by palbociclib. The TAPUR study is a prospective phase 2 basket study designed to evaluate whether FDA-approved targeted agents can meaningfully benefit patients with advanced treatment-refractory cancers harboring specific genomic alterations. In this analysis, patients were eligible for palbociclib if their tumors carried CDKN2A loss or mutation and retained RB activity. Two cohorts were examined: one consisting of head and neck cancers, and another composed of a broad spectrum of tumor types that collectively shared the CDK2 alteration. The results from the head and neck cancer cohort are particularly intriguing. Among the 28 available patients, the study observed a disease control rate of 40%, surpassing the predefined threshold for a positive signal. Although the objective response rate was low at only 4% with one partial response, the durability of disease stabilization was clinically meaningful. However, the most important insight comes from examining which head and neck tumors benefited. The strongest and most durable disease control occurred in non-squamous malignancies, particularly salivary gland tumors such as adenocarcinoma, adenoid cystic carcinoma, and poorly differentiated parotid tumors, as well as in esthesioneuroblastoma. In contrast, classic head and neck squamous cell carcinoma rarely demonstrated sustained benefit. When progression-free survival was analyzed, non-squamous tumors achieved a median PFS of approximately 20 weeks compared to just eight weeks in squamous tumors. This divergence reflects deep biological differences. Many non-squamous head and neck cancers preserve an intact RB axis and rely on CDK4/6-driven cell cycle control as a core proliferative mechanism. By contrast, squamous tumors tend to accumulate a dense array of co-alterations that weaken or circumvent CDK4/6 dependency. Many squamous tumors also harbor disruptive TP53 mutations, removing essential checkpoint control and allowing the cell to bypass the growth-arresting effects of palbociclib. In other words, even though CDKN2A loss is present, CDK4/6 is no longer the dominant node controlling proliferation in these cancers, and the tumor simply finds other ways to drive cell cycle entry. One of the most thought-provoking findings from the TAPUR study involves esthesioneuroblastoma. Three patients with this rare tumor achieved durable disease control despite the lack of standardized systemic treatment options for this malignancy. Genomic analyses have shown that while esthesioneuroblastoma often carries TP53 or IDH2 mutations, a meaningful subset exhibits alterations in CDKN2A or related cell cycle regulators. The consistency of this disease stabilization observed in TAPUR may reflect a lineage-specific reliance on CDK4/6 signaling, opening the door for future exploration of CDK4/6 inhibitors in this orphan disease. In the histology-pooled cohort, which included 40 available patients across 18 tumor types, palbociclib did not achieve the disease control threshold required to declare activity, with only a disease control rate of 13% and an ORR of 5%. While a few isolated responses occurred, for instance in thymic carcinoma and B-cell lymphoma, the overall disease control rate was 13%, which failed to rise above what might be expected from the natural history of advanced refractory cancers. This outcome reinforces the principle that CDKN2A loss is not a universal predictor of CDK4/6 dependency. Many of the tumors represented in this cohort, such as pancreatic cancer, melanoma, and gastrointestinal malignancies, are well known to evolve multiple compensatory mechanisms that circumvent CDK4/6 as a critical proliferative node. The safety profile of palbociclib was consistent with its known hematologic toxicities. High rates of neutropenia, leukopenia, and thrombocytopenia were observed, along with one treatment-related death due to respiratory failure. In a setting where activity is limited to specific subgroups, these toxicities underscore the importance of careful patient selection and raise the bar for demonstrating clinically meaningful benefit, particularly in heavily pretreated populations. So what do these findings tell us about the broader landscape of precision oncology? First, they remind us that a mutation's functional role is dependent on the cellular and lineage context in which it occurs. CDKN2A loss may accelerate proliferation in many tumors, but the mechanism of that acceleration varies widely, and the degree to which a tumor relies on CDK4/6 signaling is anything but uniform. Second, the findings suggest that palbociclib monotherapy may hold meaningful and durable benefit in the subset of non-squamous head and neck cancers, particularly salivary gland malignancies and esthesioneuroblastoma. Third and perhaps most importantly, the results reinforce a growing consensus that the future of CDK4/6 inhibition in solid tumors lies not in monotherapy, but in rational combination strategies. CDK4/6 inhibitors have been shown to synergize with EGFR inhibitors, PIK3CA, and mTOR inhibitors, MEK inhibition, and even immune checkpoint blockade. These combinations aim to dismantle the compensatory pathways that allow tumors to escape CDK4/6 blockade and may unlock therapeutic potential in tumors that show limited sensitivity to monotherapy. Ultimately, the TAPUR findings challenge the notion that CDKN2A is a straightforward predictive biomarker. Instead, the study reveals CDKN2A as a biomarker whose meaning is modulated by tumor lineage, co-mutation status, and the broader regulatory circuit governing proliferation. Precision oncology must therefore move beyond single-gene interpretation towards integrated frameworks that situate genomic alterations within their biologic ecosystems. In some head and neck cancer subtypes, particularly non-squamous malignancies, that ecosystem appears amenable to CDK4/6 inhibition, and that insight, not the simplistic gene-to-drug match, represents the true value of the TAPUR analysis. Thank you for joining me for this episode of JCO Precision Oncology Article Insights. I'm Harold Nathan Tan, and I look forward to exploring more research that continues to refine how we understand and strategically exploit the vulnerabilities of cancer. 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. 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    

In this JCO Precision Oncology Article Insights episode, Natalie DelRocco summarizes "Genomic Risk Classifiers in Localized Prostate Cancer: Precise but Not Standardized" by Góes et al. published on September 10, 2025. TRANSCRIPT Natalie DelRocco: Hello and welcome to JCO Precision Oncology Article Insights. I'm your host, Natalie DelRocco, and today we will be discussing the editorial "Genomic Risk Classifiers in Localized Prostate Cancer: Precise but Not Standardized." This editorial by Góes, Li, and Chehrazi-Raffle, and Janopaul-Naylor et al. describes genomic risk classifiers, or GRCs, for patients with localized prostate cancer. Like any risk prediction model, GRCs are intended to help identify groups of patients that may benefit from less intense or more intense anticancer therapy. Risk prediction tools can be difficult to bring into clinical practice; they require a lot of validation. And as the authors describe, GRCs in localized prostate cancer are no exception. The authors of this editorial contextualize an article by Janopaul-Naylor et al., which attempts to retrospectively explore the clinical use of three available GRCs for localized prostate cancer: Decipher, Oncotype DX, and Prolaris. Each of these three GRCs is being used in clinical practice currently. In the original article, all three GRCs were associated with less intense therapy being prescribed in practice. However, the editorial authors note that this is likely selection bias due to the observational nature of the study design. It is conceivable that GRCs were more likely ordered to make decisions for patients who were already thought to be good candidates for less intensive therapy. Another weakness of the retrospective study design is that patient level covariates known to be associated with clinical prognosis in localized prostate cancer, such as staging, Gleason score, prostate specific antigen, were unavailable. The authors note that sampling bias may also be an issue. Uninsured patients are not included in the original article, and therefore may impede the ability to make conclusions about the association of GRC use with income level. The editorial authors highlight important study findings as well as these limitations, such as the heterogeneity of interventions following GRC result return. The Prolaris GRC was found to be associated with more surgical interventions, while the Decipher GRC was associated with more androgen deprivation therapy plus radiation. Additionally, patients with active surveillance were more likely to have a GRC in general ordered. While these conclusions are very interesting, the editorial authors note that further exploration and validation, given the retrospective study design and limitations outlined, are needed to fully understand the impact of GRCs in the practice of treating localized prostate cancer. Thank you for listening to JCO Precision Oncology Article Insights. Don't forget to give us a rating or a review and be sure to subscribe so that you never miss an episode. You can find all ASCO shows atasco.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.

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

In this episode of JCO PO Article Insights, host Dr. Jiasen He summarizes the article, "Somatic Mutation Profiles of Colorectal Cancer by Birth Cohort" by Gilad, et al published October 11, 2025. 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, "Somatic Mutation Profiles of Colorectal Cancer by Birth Cohort," by Dr. Gilad and colleagues. Early-onset colorectal cancer is defined as colorectal cancer diagnosed before the age of 50. Several reports have suggested that early-onset colorectal cancer has unique characteristics. Compared with late-onset colorectal cancer, early-onset colorectal cancer cases are more commonly found in the distal colon or rectum, tend to be diagnosed at more advanced stages, and may display unfavorable histologic features. Although the overall incidence of colorectal cancer has declined in recent decades, the incidence of early-onset colorectal cancer continues to rise. This increase appears to be driven by birth cohort effects. The reasons behind this rise remain unclear but are likely multifactorial, involving changes in demographics, diet, lifestyle, environmental exposures, and genetic predisposition. At the same time, studies have shown conflicting results regarding whether there are differences in the mutation profiles between early-onset and late-onset colorectal cancer. Therefore, it is crucial to explore whether colorectal cancer somatic mutational landscape differs across birth cohorts, as this could provide important insight into generational shifts in colorectal cancer incidence. To address this question, the authors conducted a retrospective study to characterize the mutation spectrum of colorectal cancer across different birth cohorts. Consecutive colorectal cancer patients who underwent somatic next-generation sequencing at the University of Chicago pathology laboratory between 2015 and 2022 were retrospectively identified. Tumors were tested for 154 to 168 genes and categorized as either microsatellite stable or high according to established thresholds. Patients with hereditary cancer syndromes or inflammatory bowel disease were excluded. Participants were then grouped into birth cohorts by decades, as well as into two major groups: those born before 1960 and after 1960. Genes that were identified in at least 5% of the sample were selected and grouped into 10 canonical cancer signaling pathways. These genes and pathways were then included in the analysis to explore their association with colorectal cancer across different birth cohorts and age groups. A total of 369 patients were included in the study, with a median birth year of 1955 and a median age at colorectal cancer diagnosis of 62.9 years. 5.4% were identified as having microsatellite-high tumors. The median tumor mutational burden was 5 mutations per megabase for microsatellite-stable tumors and 57.7 mutations per megabase for microsatellite-high tumors. Patients with microsatellite-high tumors tended to have earlier birth years and were diagnosed at an older age. However, after adjusting for potential confounders, neither birth year nor age remained statistically significant. Similarly, after controlling for confounders, no significant associations were observed between birth year or age and mutation burden. In this cohort, APC, TP53, and KRAS were the most frequently mutated genes. No statistically significant differences in the prevalence of gene mutations were observed across birth cohorts. Correspondingly, the most affected signaling pathways were the Wnt, TP53, and (RTK)/RAS pathways. Similar to the gene-level finding, no significant differences in the prevalence of these pathways were identified among birth cohorts. When examining patients born before and after 1960, the authors found that the older birth cohorts were diagnosed at an older age and had higher tumor mutational burden. However, no significant differences were observed in any of the genes or pathways analyzed. Among microsatellite-stable tumors, 18.3% were classified as early-onset colorectal cancer, while 81.1% were late-onset colorectal cancer. Consistent with previous reports, early-onset colorectal cancers in this cohort were more likely to be left-sided and more common among more recent birth cohorts. However, no significant differences were identified in any of the examined genes or pathways when comparing early-onset to late-onset colorectal cancer. In this cohort, a higher prevalence of early-onset colorectal cancer was observed among more recent birth cohorts, consistent with previous reports. Still, no distinct mutational signature was identified between the early and late birth cohorts. The authors proposed that the lack of distinct mutational profile by age or birth cohort may be due to the limited number of key molecular pathways driving colorectal cancer. Although environmental exposures likely differ across generations, the downstream effects may have converged on similar biological mechanisms, leading to comparable somatic mutations across cohorts. Alternately, they proposed that the observed birth cohort differences in colorectal incidence may be driven by distinct mutation signatures, epigenetic alterations, or changes in the immune microenvironment rather than variations in canonical gene mutations. As the authors noted, given the retrospective nature of this study, its modest sample size, and the predominance of advanced-stage tumors, larger prospective studies are needed to validate these findings. In summary, this study found no significant differences in the mutational landscape of colorectal cancer across birth cohorts or age groups. The authors proposed that the generational shift in colorectal cancer incidence is unlikely to be driven by changes in the underlying tumor genomics. However, larger prospective studies are needed to validate these findings. Thank you for tuning in to JCO Precision Oncology Article Insights. Do not 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. 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