JCO PO Article Insights: Statistical Considerations for Biomarker-Driven Oncology Clinical Trials

JCO PO author Dr. Amar U. Kishan, Professor, Executive Vice Chair, and Chief of Genitourinary Oncology Service in the Department of Radiation Oncology at the University of California, Los Angeles, shares insights into his JCO PO article, “Transcriptomic Profiling of Primary Prostate Cancers and Nonlocalized Disease on Prostate-Specific Membrane Antigen Positron Emission Tomography/Computed Tomography: A Multicenter Retrospective Study.”  Host Dr. Rafeh Naqash and Dr. Kishan discuss the relationship between Decipher genomic classifier scores and prostate-specific membrane antigen (PSMA) PET/CT-based metastatic spread. 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 articles. I'm your host, Dr. Rafeh Naqash, Assistant Professor at the OU Health Stephenson Cancer Center at the University of Oklahoma. Today we are joined by Dr. Amar Kishan, Executive Vice Chair of the Department of Radiation Oncology at the David Geffen School of Medicine at UCLA and UCLA Jonsson Comprehensive Cancer Center, and also the corresponding and senior author of the JCO Precision Oncology article entitled, “Transcriptomic Profiling of Primary Prostate Cancers and Non Localized Disease on Prostate-Specific Membrane Antigen (PSMA) Positron Emission Tomography/Computed Tomography: A Multicenter Retrospective Study.” Dr. Kishan, welcome to our podcast and thank you for joining us today. Dr. Amar Kishan: Thank you so much for that kind introduction and the invitation to be here today. Dr. Rafeh Naqash: Well, it seems to me that there's a theme that people in the GU space, investigators in the GU space, are very interested in trying to understand risk predictors for prostate cancer. We had somebody, I believe from Huntsman Cancer Center a few months back on a previous podcast, where they were trying to do risk prediction modeling as well. Could you tell us why that's something that the GU community is very interested in? What's the background? Is it because there's no risk prediction approaches currently? And would this somehow influence management in the near future? Dr. Amar Kishan: Yeah, that's a great question. So, I think this goes back to the point that we're in the era of precision medicine now, and many cancers have these molecular stratification scores and all that. Prostate cancer has lagged a little bit behind in that regard, despite the fact that it's such a common cancer that affects so many people across the country and across the world. So, we do have risk stratification schemes for prostate cancer. These are based off clinical and pathologic variables, like the level of PSA, the size of the tumor on digital rectal examination, now, we're incorporating MRI imaging as well, and then what the cancer looks like under the microscope, the Gleason score. And now there have been revisions to the Gleason score, but it's really kind of the architecture, what the biopsy looks like. And this was kind of developed many, many years ago by Donald Gleason, a pathologist at the VA. What we're not necessarily taking into account routinely is kind of the biology of the cancer per se. You know, what are the molecular drivers? How could that influence ultimate outcome? And that's very important because we have these risk groups, low risk, very low risk, favorable intermediate risk, unfavorable intermediate risk, high risk, very high risk. But within each of those groups, based on the clinical kind of pathological characteristics, there's a huge heterogeneity in outpatients too, and our treatments are effective, but they can be morbid. Putting someone on hormone therapy for an extended period of time has a lot of side effects. Dose escalating radiotherapy or doing surgery and then radiation afterwards, these are big things that have a big impact on the patient, and I think we really need better risk stratification tools to understand who needs intensification and who we can de-escalate treatment for. Dr. Rafeh Naqash: I think those are absolutely valid points, perhaps not just for prostate cancer, more so for all cancers that we currently treat, especially in the current day and age, where we have a tendency to add more and more therapies, combination therapies for patients, and as you mentioned, risk stratification to help identify high risk versus low risk, where you can de intensify treatment, is of high value from a patient standpoint as well as from a financial toxicity standpoint. So then, going to this next part of the approach that you used, and from what I understand in this paper, you had the radiological aspect, which is the PSMA PET, which we'll talk about. Then you had the genomic aspect, where you did some genomic risk-based stratification. Then you had the transcriptomic score based on the Decipher score. So, could you go into some of the details, first, for the PSMA PET, when is it used? What is the utilization? What is it based on, the science behind the PSMA PET? And then we can talk about some of the other genomic transcriptomic predictors that you use in this study. Dr. Amar Kishan: Sure. Absolutely. So, a PSMA PET is an advanced molecular imaging tool. PSMA stands for prostate specific membrane antigen. It's a membrane protein that is expressed on the surface of prostate cancer cells. It is expressed elsewhere in the body as well. The utilization of this for imaging has been a revolution in the staging of prostate cancer, both upfront and in the recurrent setting. We basically had fairly recent approval for PSMA PET being used more routinely in upfront staging and recurrent staging in 2022. Essentially, what this is it gives us an ability to detect whether prostate cancer has spread at a time of diagnosis or try to localize the recurrence. Now, no imaging test is perfect, of course, and a PET has a resolution of about 3 mm. There are questions about the sensitivity of the PET. You get it on a patient with high-risk disease, the PET is negative; you do surgery, there are positive lymph nodes. That can happen, but it's far superior to the tools that we have had before. For instance, beforehand, all we would have is a contrast enhanced CT, bone scan, and MRI. And the sensitivity of those is far below that of a PSMA PET. And that has actually been shown in a randomized trial called the ProPSMA trial out of Australia, where they compared conventional upfront imaging versus PSMA upfront imaging with a crossover design, and there was better detection of disease with the PSMA PET. So that's been a revolution in how we stage prostate cancer. But I'm sure many of your listeners and others are aware of the concerns. When you get a new test and you're detecting disease that's extra prostatic, for instance, are you seeing truly significant new disease that we do need to change our management for, or are we just seeing stuff that wasn't there before that actually wouldn't impact anything? And what I mean by that is, let's say you're seeing things that would never have made a difference to the patient, but now you're saying they have metastatic disease. You're changing their entire treatment paradigm, all kinds of things like that. There's implications to this that hasn't been fully fleshed out. But very recently, like we're talking in July of 2024, essentially, there was a Lancet Oncology paper that looked at the long-term prognosis of patients who had extra prostatic disease on PSMA PET, judged by something called a PROMISE score, kind of gives a quantification on the volume of disease, the brightness of disease, and they correlated that with long term outcomes. And that was really the first time that we have long term follow up data that this extra prostatic disease on PSMA PET actually is prognostically important. So, we're getting there. I mean, now that it's approved and, in some sense, the cat is out of the bag, patients are coming in asking for a PSMA PET, etc. I'm sure everyone has experienced that, but I think we now do have good evidence that it actually is prognostically important as well. Dr. Rafeh Naqash: Thank you for that explanation. And again, to put this into context for things that I've seen and that might also help the listeners in other tumors, so, for example, melanoma surveillance tends to be or while on treatment, patients tend to have more PET scans than what you see, maybe in individuals with lung cancer, where you get a baseline PET and then you have follow up CT scan based imaging is that something that you guys have shifted from in the prostate cancer space with the approval for PSMA PET, where follow up imaging, whether patient is on treatment or surveillance imaging, is PSMA PET based? Dr. Amar Kishan: Yeah, that's a good question. I think there's actually less robust data to support it as a means of treatment response. But in terms of evaluating a recurrence, then, yes, that has become kind of a standard tool. It's very complicated because all of the metrics that we have for, say, a treatment failing are based on conventionally detected metastases or something that shows up on a CT or bone scan. So, again, that question arises if someone is on systemic therapy and then you see something on a PSMA PET, are you going to abandon the therapy that you're on? It technically would be earlier than you would otherwise have done that, or what are you going to do? So, that hasn't been fully fleshed out, but it is used in that circumstance. So, I'd say less for treatment monitoring and more for evaluation of suspected recurrence. Dr. Rafeh Naqash: Understood. And I'm guessing, as a futuristic approach, somebody out there may perhaps do a trial using PSMA PET based imaging to decide whether treatment change needs to be made or does not need to be made. Dr. Amar Kishan: Yeah. It is being incorporated into trials as we speak, I think. Dr. Rafeh Naqash: Now, going to the second part of this paper is the Decipher score. Could you explain what the score is, what its components are, how it's calculated? Is it DNA, is it RNA, is it both combined? Is it tissue based; is it blood based? Dr. Amar Kishan: Yeah. So, the Decipher is also an approved test now, was approved in 2018. What it is, essentially, and how it's derived is based on the idea originally that patients might have a recurrence after surgery for prostate cancer. And it's just a PSA recurrence. It's this way. It's literally what we call a biochemical recurrence. That patient might not have any problems, whereas other patients with a recurrence might go on to develop metastatic disease. And we didn't have a good way of determining which patient is which. Get back to that prognostic problem that we have. So, some investigators, they looked at men that had radical prostatectomy from 1987 to 2001 at the Mayo Clinic that had archived tissue. They looked at FFPE, or basically paraffin embedded tissue. They extracted the RNA and then did a microarray analysis and looked at transcriptomic signatures and wanted to see, could this discern the patients who had mets, who had clinically significant recurrences from those that didn't? And out of that exercise came the Decipher Genomic Classifier, which basically is based on 22 genes. These are involved with cell proliferation, etc., but it's an RNA-based, tissue-based assay. So, if you wanted to order a Decipher on somebody, you would need to use a biopsy or prostatectomy specimen to do so. Essentially, that the samples, they would take the highest grade, highest Gleason grade specimen, send it to their lab. Their main lab is in California. The company is called Veracyte. And then they will do this RNA express analysis with a microarray and then return a score. The score is 0 to 1. Basically, 0 is the lowest, one is the highest, and it is a way of prognosticating the risk of metastasis. Originally, when you get a Decipher report, it actually will tell you the 5 and 10-year risks of distant metastasis, and we'll quantify that. Dr. Rafeh Naqash: And you said this is approved or has been approved in 2018. So, is this insurance reimbursable at this point? Dr. Amar Kishan: Most insurances do, not all, and the criteria for getting it can vary, so we can talk about it, but it was initially developed in this post-op setting. On the basis of a significant amount of validation studies, it has been moved to being used in the upfront setting as well. So, if you look at some of the ongoing NRG trials, for instance, they are stratifying patients based off the upfront Decipher score. And this is based off of validation studies that have been conducted looking at past RTOG trials and other trials. That said, sometimes it is not approved by commercial insurances in the upfront setting, because that wasn't where it was initially validated and derived. But honestly, here in 2024, that's very uncommon. It's much more common that it's approved. Dr. Rafeh Naqash: Understood. And in your practice, or the medical oncologist practice at your institution or other institutions, is this something that is commonly used for some sort of treatment decision making that you've seen? Dr. Amar Kishan: Yeah. So, as a radiation oncologist, I do think it's a useful test, because my approach is, if we're talking about adding hormone therapy, for instance, which is oftentimes dominating the conversation, we know that it offers a relative benefit to a lot of patients. We've published on this; others have published on it. Let's say it reduces the chance of metastasis by about 40%. 10-year risk of metastasis has a ratio of 0.6. So, 40% reduction. But if your risk of metastasis is 2%, that benefit is not that much in absolute terms. And we don't historically have a great way of saying, what is your absolute risk of metastasis? And I think Decipher is one tool that does tell us that - it literally gives it on the report. Now, is that a holy grail? Is it 100% accurate? Nothing is 100% accurate. But it does give us some quantification. Then I can go back to the patient and say, yes, you will get a benefit from adding hormone therapy, but you're talking about going from 2% to 1%, and so they can decide if that's worth it to them. Conversely, it could be a situation where they really don't want hormone therapy, but it comes back that their risk of metastasis is 20%, and then there's actually a big absolute benefit. So that's how I use it as a radiation oncologist, and we would use it upfront. Now surgeons, and if I was consulting on a post operative patient, maybe it plays more of a role. And do we need to do post operative radiotherapy on this patient, or do we need to add hormone therapy in the postoperative situation? From the medical oncology perspective, there are emerging data that may be useful in the choice of systemic therapy for metastatic disease, but that is a little bit earlier in the investigational stage, I would say. So, when I'm working with medical oncologists, it's often still in this localized setting, and typically, do we add hormone therapy or not, and that type of thing. Dr. Rafeh Naqash: Understood. And from a reporting standpoint, so the Decipher score, I'm guessing it's some sort of a report that comes back to the ordering physician and you basically see the score, it gives you a potential recurrence free survival percentage or a metastasis percentage of what is your risk for having metastasis in the next five years - is that how they generally do it? Because I've personally never seen one, so I'm just curious. Dr. Amar Kishan: Yeah, essentially, it comes back with a score, a numerical score, again, from 0 to 1, and it will basically give you the five-year risk of distant metastasis. The ten-year risk of distant metastasis. You can request an extended report that provides additional, not as well supported signatures that are out there, like ADT response signature, etc. But those maybe may have been published, but are not clinically validated as much, but the actual Decipher report, which goes to patients too, just has this kind of 5,10-year risk of distant metastasis. They have some estimations on prostate cancer specific mortality as well. Dr. Rafeh Naqash: Sure. Now, the third part of this project, and correct me if I'm wrong, the grid database of the 265 genomic signature score. From what I understood, this is a different component than the Decipher score. Is that a fair statement? Dr. Amar Kishan: Yeah. No, that's exactly correct. And that was an exploratory part of this analysis, to be honest. Basically, I think our main focus in the paper was those advances that we've talked about PSMA and Decipher, those happened concurrently. People started developing PSMA PET, people started developing Decipher. And so, what we wanted to understand was, if you have a patient that has extra prosthetic disease on PSMA PET, are those biologically more aggressive cancers, is their Decipher score going to be higher? What can we learn about the biology of this? And we were the first, to my knowledge, where we actually had a large data set of patients that actually received PSMA PETs and Decipher. And that's kind of the gist of the paper. We have patients in the upfront setting, patients in the post radical prostatectomy setting, and we're essentially showing that there is this correlation. In the upfront setting, the odds of extra prosthetic disease are higher for higher Decipher scores, which is kind of maybe validating that this biology is capturing something that's akin to this ability to spread. And in the post-op setting, because we have time to failure, technically, we can calculate a hazard ratio rather than odds ratio. So, we have a hazard ratio that's significantly associated with an increased risk of spread for patients with higher Decipher. The grid portion, which is the genomic resource information database, was more of an exploratory part where I mentioned the Decipher score is based off this microarray, they're looking at 1.4 million transcripts. Only 22 are part of the Decipher, but you can request the rest of the signature data as well. And so, we wanted to look at other pathways, other signatures that have been published, like looking at DNA repair, neuroendocrine pathway, just to see if we could see any correlations there that's not necessarily as clinically actionable. These are more exploratory. But again, we were trying to just look at whether patients who had non localized disease on their PSMA PET, whether their primary had more aggressive biology. We did see that. So that's kind of loosely speaking things like PTEN loss, androgen receptor, DNA repair, metabolism, neuroendocrine signaling, which are thought to be portenders of aggressive disease. Those pathways were upregulated at the RNA level in patients who had non-localized disease. And that's kind of the take home from that. But I wouldn't say any of that is clinically actionable at this point. It's more kind of defining biology. Dr. Rafeh Naqash: Some of the interesting correlations that you make here, at least in the figures that we see, you're looking at different local occurrences, nodal metastases, M1A and M1B disease. And one thing that I'm a little curious about is the Decipher score seems to be lower in pelvic nodal metastasis, that is, PSMA PET positive versus local recurrence, which has a slightly higher Decipher score. Is that just because of a sample size difference, or is there a biologically different explanation for that? Dr. Amar Kishan: Yeah, that's a good point. I would assume that's probably because of a sample size in this case, and it's a little bit complicated. It wasn't statistically different. And it was 0.76 on average for patients with local recurrence and 0.7 for patients with a pelvic nodal metastasis. Well, what I think is interesting is we can maybe think that in this post-op setting the time to failure could have been long in some of these cases. So, it is conceivable that an isolated nodal recurrence 10 years after the surgery, for instance, is not as aggressive a cancer as a local recurrence in a short time after the surgery. And that's not taken into account when you're just looking at median scores like we are in this fox and whiskers plot. But overall, I think what it's suggesting is that there are patients who have more indolent disease. That's actually pretty widespread there. There are pretty indolent cases that have these nodal metastases. So just because you have a nodal metastasis doesn't mean it's an incredibly aggressive cancer, biologically. Dr. Rafeh Naqash: Now, the exploratory component, as you mentioned, is the grid part where you do look at TP53, which is a cell cycle gene, and higher TP53 associated with worse recurrences, from what I understand. Do you see that just from a cell cycle standpoint? Because from what I, again, see in the paper, there's a couple of other cell cycle related signatures that you're using. Is that just a surrogate for potential Gleason score? Have you guys done any correlations where higher Gleason score is associated with maybe higher cell cycle checkpoint, pathway related alterations and replication stress and DNA damage and perhaps more aggressive cancers? Dr. Amar Kishan: Yeah, that's a great question. We haven't done that in this paper, but it has been published before that there is this correlation loosely between grade and some of these parameters - so repair, metabolism, androgen receptor signaling. However, it's a very great point that you bring up, which is that it's pretty heterogeneous and that's why we need something like this as opposed to Gleason score. So, you can have Gleason 10 cancer. I mean, that would be pretty uncommon. But within the Gleason 9, at least, which we have published on and looked at, there's a heterogeneity. There are some that are biologically not that aggressive. And the converse Gleason 7, you can have some that are actually biologically aggressive. That's why it may be useful to move away from just the pathological architecture and get a little bit more into some of these pathways. Dr. Rafeh Naqash: What's the next step here? I know this perhaps isn't ready for primetime. How would you try to emphasize the message in a way that makes it interesting and clinically applicable for your colleagues in the GU community? Dr. Amar Kishan: Yeah. I think for me, what I would try to emphasize here and what I think is the main takeaway is this is kind of a validation that having extra prostatic disease on PSMA PET is likely suggestive of a more aggressive disease biology. And I think what this stresses to me is the importance of getting a PSMA PET, particularly in patients with high-risk prostate cancer. This isn't always happening. And I think if we see things on a PSMA PET, we really need to consider systemic therapy intensification. And what do I mean by that as a practical point? You have a high-risk prostate cancer patient. You get a PSMA PET, you see an isolated pelvic lymph node. If we believe the results of the study, that's a more aggressive biology likely. Whether we have the Decipher or whether we have genomic signatures, which we may or may not have, maybe that patient should get treated with something like an androgen receptor signaling inhibitor in addition to ADT, more akin to a clinically node positive case. So, intensify the systemic therapy, more aggressive disease. That's how I would incorporate it practically into my practice, that really what we're seeing on the PSMA PET is real. It's a reflection of biology that's aggressive. It's not just some Will Rogers effect where you're upstaging stuff needlessly. I think this is telling us some true biology. So that's kind of what my takeaway would be. I think future areas of investigation would be, honestly, to try to have a better idea of what's going on in these metastases. So, if you could design a study potentially, where your biopsy some of these and actually do sequencing and understand a little bit more of that. And so, we're looking into stuff like that. But my takeaway for like the everyday clinician would be to try to get a PSMA PET, if you can, and to intensify therapy on the basis of that, or at least consider it, discuss it in a multidisciplinary setting. Dr. Rafeh Naqash: And I'm guessing somebody out there, perhaps even you, are thinking or planning on doing a ctDNA MRD based correlation here, since that's up and coming in this space. Dr. Amar Kishan: That is up and coming, I think one of the challenges in prostate cancer is the amount of ctDNA can be low. But yes, you're right, that's certainly things that a lot of us are looking at, too. Dr. Rafeh Naqash: Excellent. Well, thank you for the science discussion, Dr. Kishan, could you tell us a little bit about yourself, your career trajectory, where you started, what you're doing, and perhaps some advice for early career junior investigators, trainees, things that might have worked for you, that could also work for them as they are progressing in their careers. Dr. Amar Kishan: Sure. So, yeah, I'm a radiation oncologist at UCLA. I run the prostate cancer radiation program. Clinically. I'm also heavily involved in our research enterprise, so I kind of oversee the clinical and translational research aspect. That's what I do currently. So, I did my residency in radiation oncology at UCLA. Just on a personal note, my wife is from LA, her parents live in LA. We really wanted to stay in LA, so I was fortunate to be able to join the faculty here. I always liked GU oncology, so that was kind of a natural thing for me to kind of go into this position here and try to build the GU program. I've been very fortunate to have great collaborators. My message to students and trainees is to try to reach outside your department for mentorship as well. It's important to have people inside your department who can mentor you. But as a radiation oncologist, I work so closely with urology, so closely with medical oncology that I'm very fortunate to have individuals in those departments who have a vested interest in me and my success as well. I like working with them. It's important to be a team player. If they need help, you help them. If you need help, you ask for help from them. So, I think that's the single biggest thing that I would say to any trainee is don't be intimidated. Please reach outside of your department. Lots of people are willing to help and provide mentorship, and it's helpful to have that perspective. We are in a very multidisciplinary environment and era of practicing medicine. Dr. Rafeh Naqash: Well, thank you again for those personal insights and especially for submitting your work to JCO PO. And we hope to see more of this work perhaps in the subsequent sessions for JCO PO, and maybe we'll bring you back again. And at that point, the Decipher and the PSMA PET scan will have more data, more implementation in the clinically relevant real-world setting. Dr. Amar Kishan: Thank you very much. And if I could just give one quick shout out. The first author of this work, which I presented, was Dr. John Nikitas, who is a trainee that works with me here at UCLA a PGY5 resident. So, I do want to give credit to him as well. Dr. Rafeh Naqash: And John, if you're listening to this hopefully, it's always great to get a shout out from your mentor. Thank you both again for putting in the work and effort to submit this manuscript. 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.    Disclosures  Dr. Kishan Honoraria Company: Varian Medical Systems, Boston Scientific,  Janssen Oncology  Consulting or Advisory Role Company: Janssen, Boston Scientific, Lantheus  Research Funding Company: Janssen , Point Biopharma

In this JCO Precision Oncology Article Insights episode, Mitchell Elliot summarizes an editorial: “A Targeted Methylation–Based Multicancer Early Detection Blood Test Preferentially Detects High-Grade Prostate Cancer While Minimizing Overdiagnosis of Indolent Disease” by Dr. Brandon A. Mahal, et al. published on August 29, 2024.  TRANSCRIPT Mitchell Elliott: Hello and welcome to JCO Precision Oncology Article Insights. My name is Mitchell Elliott, a JCO Editorial Fellow. Today, I'll be discussing the article, “A Targeted Methylation–Based Multicancer Early Detection Blood Test Preferentially Detects High-Grade Prostate Cancer While Minimizing Overdiagnosis of Indolent Disease,” by Mahal et al. Cancer overdiagnosis, particularly of low-risk conditions that are unlikely to cause harm, is a common issue in screening tests. In prostate cancer screening, overdiagnosis affects 23% to 42% of cases, often due to the prevalence of low-grade cancers and the low specificity of the prostate specific antigen or PSA tests. Data from previous studies have highlighted that men with low grade prostate cancer often die with prostate cancer and not of prostate cancer. Over diagnosis can lead to unnecessary treatments, increased patient anxiety, side effects, and excessive healthcare costs. Multicancer early detection, or MCED tests offer a new approach by detecting multiple cancer types from a single blood sample with low false positive rates, typically less than 2%, and they also have the ability to predict the cancer type from this one test. The GRAIL Galleri test, based on methylation patterns of circulating tumor DNA, showed high accuracy detecting over 50 cancer types, including prostate cancer, in the circulating cell free genome atlas or CCGA in PATHFINDER studies. This type of MCED test paradigm is being developed for use alongside traditional screening methods in adults over the age of 50. This study evaluated this particular MCED test ability to detect both indolent and aggressive prostate cancer, aiming to assess its potential to contribute to over diagnosis. This cohort was part of the circulating cell free genome atlas or CCGA study, a multicenter case control study with three phases to validate this particular MCED test. The CCGA enrolled 15,254 participants, of which 8,584 had cancer and 6,670 did not. Enrollment was carried out in 142 North American sites between 2016 and 2019. Eligibility for cancer cases required a confirmed diagnosis or high suspicion with planned biopsy or surgery within six weeks of enrollment. This study evaluated 420 recently diagnosed men with prostate cancer from substudy 3, the independent clinical validation arm. The PATHFINDER study was a prospective cohort study of 6,662 adults over the age of 50 enrolled from seven US health networks between December 2019 and December 2020. Participants underwent testing with the GRAIL Galleri test, with results shared with physicians and participants. The test indicated the presence or absence of a cancer signal and predicted the cancer signal of origin if detected. This study's prostate cancer cohort included 18 men diagnosed through MCED testing or PSA screening, excluding two with recurrent disease. PSA testing was not collected in this particular study. Detectability by the Gleason group, clinical stage, association of detection status with tumor methylation fraction, and overall survival were assessed in these studies. The results are broken down by each substudy evaluated. Substudy three of the CCGA enrolled a clinically relevant patient population. The median age of the men enrolled were 65. Ethnic diversity was not represented, however, in this cohort, with only 15% of participants reporting as non-white, non-Hispanic. It is important to note that only 8.4% of patients included in the study self-identified as black non-Hispanic, a particular group of participants with a higher incidence in more aggressive prostate cancer. The overall MCED test sensitivity for prostate cancer detection was low in 11.2% or 47 out of 420 patients included in this cohort. The cancer signal of origin prediction accuracy was 91.5% with 43 of 47 patients having prostate cancer predicted. The test did not detect any low-grade tumors. It detected 3 of 157 favorable or intermediate grade tumors as well as 4 of 78 unfavorable intermediate grade tumors, and finally 36 of 113 high grade tumors, typically, Gleason score 4 and 5. Detection increase was staged with only 3.2% or 3 of 95 of stage one disease detected with the MCED test, while 14.9% or 7 of 47 with stage 3 and 81.5% 22 out of 27 patients with stage four disease. Compared with expected overall survival estimated from the United States SEER database, non-detected cancer cases had roughly three times better overall survival with a hazard ratio of 0.263 with a 95% interval of 0.1 to 0.5 with a p value of less than 0.05, and detected case that had similar survival, the hazard ratio of 0.672 with a 95% interval crossing one and a p value of 0.2 when adjusted for age, Gleason grade, and clinical stage. This suggests that patients identified to be ctDNA positive at diagnosis have an overall worse outcome than those who are ctDNA negative, a consistent phenomenon with previous studies using the same or different tumor informed and diagnostic ctDNA assays. Next, the authors evaluated the outcomes in the PATHFINDER cohort of 18 participants. The characteristics of patients enrolled were similar to the previous cohort. Only one case was detected, which was between Gleason group 3 and 5, and had either stage 3 or stage 4 disease not defined in the manuscript. Because only a single case of prostate cancer was identified in PATHFINDER via this test, cancer signal of origin, predicted accuracy, tumor methylation fraction, and survival outcomes were not calculated. In summary, this test preferentially detected high grade and advanced stage prostate cancers, identifying 93% of Gleason grade 3 to 5 and 67% of stages 3 and 4 cases, while notably did not detect Gleason grade 1, having only 1.9% of Gleason grade 2 detected and 4.2% of stage 1 and stage 2 cancers overall. Importantly, around one third of the detected cases in substudy three of the CCGA, involved non metastatic disease, including stage 1 to stage 3 were Gleason grade 3 to 5, which are potentially curable. Prostate cancers that were not detected via this test had better survival rates after adjusting for age, grade and stage in the SEER database. This suggested that MCED testing is unlikely to contribute to the overdiagnosis of indolent prostate cancers. Additionally, a positive cancer signal with a predicted prostate origin strongly indicates the presence of aggressive disease, warranting immediate diagnostic investigation. One limitation of the study is the lack of representative inclusion of patients from diverse ethnic backgrounds. Overdiagnosis of prostate cancer due to PSA levels disproportionately affects black men, and the generalizability of these findings in the study is limited by the fact that over 85% of the study cohort was self-reported as white non-Hispanic. Further data is required to understand the biology of cancer in this community and limit the bias of molecular screening tests so they are effective regardless of ethnicity.   Thank you for listening to JCO Precision Oncology Article Insights. This was a summary on “A Targeted Methylation–Based Multicancer Early Detection Blood Test Preferentially Detects High-Grade Prostate Cancer While Minimizing Overdiagnosis of Indolent Disease.” Please follow and subscribe on your favorite streaming platforms. For more podcasts from ASCO, visit www.asco.org/podcasts.   The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.      

JCO PO author Dr. Alok A. Khorana, MD, FASCO, Professor of Medicine, Cleveland Clinic and Case Comprehensive Cancer Center, shares insights into the JCO PO article, “Molecular Differences With Therapeutic Implications in Early-Onset Compared With Average-Onset Biliary Tract Cancers.” Host Dr. Rafeh Naqash and Dr. Khorana discuss how multiomic analysis shows higher FGFR2 fusions and immunotherapy marker variations in early-onset biliary cancer. 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 POarticles. I'm your host, Dr. Rafeh Naqash, Podcast Editor for JCO Precision Oncology and Assistant Professor at the OU Health Stephenson Cancer Center at the University of Oklahoma.  Today, we are joined by Dr. Alok A. Khorana, Professor of Medicine at the Cleveland Clinic and Case Comprehensive Cancer Center, and also the Senior Author of the JCO Precision Oncology article titled, “Molecular Differences With Therapeutic Implications in Early-Onset Compared With Average-Onset Biliary Tract Cancers.”  At the time of this recording, our guest disclosures will be linked in the transcript.  Dr. Khorana, it's an absolute pleasure to have you here today, and welcome to the podcast. Dr. Alok A. Khorana: Thank you. It's an absolute pleasure to be here and thank you for highlighting this article. Dr. Rafeh Naqash: Absolutely. We're going to talk about science, obviously, and a few other things. So to start off, for the sake of our audience, which comprises academicians and community oncologists as well as trainees, can you tell us a little bit about biliary tract cancers, what we have learned over the last decade or so, where the standard of treatment currently lies. And then we can dive into the article that you published. Dr. Alok A. Khorana: As many of you who treat GI cancers know, biliary tract cancers for a long period of time were sort of the orphan cancer in the GI cancer world. They're not nearly as common as, say, pancreatic cancer, and certainly not as common as colorectal cancer. They're sort of also, in this weird ‘no man's land’ between well known sort of adjuvant therapy trials in pancreatic cancer or colorectal cancer, but because they're not as high in volume, there weren't really large trials done in this population. What's really changed in the past decade, especially, has been the slow but sure realization that biliary tract cancers are in fact a target rich cancer, almost similar to what you would see with lung cancer, and that's only a slight exaggeration. And in some studies, as many as up to 40% of patients with biliary tract cancers can have something that's targetable. And that's really revolutionized the way we think of biliary tract cancers. It also separated this field from pancreatic cancer where formerly the two used to be lumped together, and even within biliary tract cancers, we are now slowly realizing that there are differences between intrahepatic, extrahepatic and gallbladder cancers. Big change is really afoot in this field, particularly with the identification of mutation directed targets. Dr. Rafeh Naqash: Thank you for that explanation.  Now, another question I have is, although I don't see any GI cancers, but I have good colleagues of mine at our cancer center who see a lot of GI pancreatic/biliary cancers, and one of the things that comes up in our molecular tumor board often is how certain cancers of unknown primary end up being identified or categorized as biliary tract cancers based on NGS. And again, the uptake for these NGS is perhaps isn't optimal in the field yet, but in your practice, how do you approach situations like that? Do you use NGS in certain cases where the tissue of origin or the patterns of the mutations indicate that this might be biliary tract cancer and then treat the patient accordingly?  Dr. Alok A. Khorana: Yeah, that's true. And that's certainly how I approach things, and I would say even in my own personal practice, that has been a change. I was a little bit skeptical about the benefit of sort of tissue of origin type of testing in carcinoma of unknown, primarily, especially if you can sort of narrow it down to one or other area of the GI tract. But with the identification of sort of targeted subpopulations, especially of biliary tract cancer, I think it's become imperative. And I know we're going to get into the paper, but if you want to learn nothing else from this 20, 25 minute podcast, one lesson I just want to make sure everybody gets is that any patient with biliary tract cancer should have NGS done as soon as possible. Dr. Rafeh Naqash: Thank you for highlighting that important aspect.  Now, going to the topic at hand, what was the driving factor? I've heard a lot about colorectal cancers, early onset versus later onset. What was the reason that you looked at biliary tract cancers? Is that something that you've seen on a rise as far as early onset biliary tract cancers is concerned?  Dr. Alok A. Khorana: Yeah. So we got into this subject also from starting out at colorectal cancer. And as you know, and I'm sure most of your audience knows, there's been a lot of literature out there over the past five, six, seven years suggesting and then documenting and then sort of proving and reproving that colorectal cancer is on the rise, and especially in people younger than age 50. And even in that population, it's on the rise in two different subpopulations, people in their 20s and 30s and then people in their 40s that are close to the screening colonoscopy rates. That's been investigated heavily. We still don't fully understand why that's happening, but it's not restricted to the United States. It's a worldwide phenomenon. You can see it in the United States, in North America. You can see it in western Europe, but you can also see it in many Asian countries with specific sort of subpopulations. For instance, in some countries, men are more likely to have early onset cancers.   And then a newer finding that sort of emerged over the past couple of years is that this early onset increase in cancers is not just restricted to colorectal cancer, although that's the one that sticks out the most, but in fact, is widespread across a bunch of different types of cancers. In my own research program, we had gotten into a sort of better understanding of early onset colorectal cancer a couple of years ago, driven primarily by the sort of patients that I saw in my practice. And it's just, as you know, when you have a couple of those heartbreaking cases and they're just impossible to forget, and it sort of just drives your attention, and then you want to do something to help them. And if you can't help them personally, then you want to do something that can change the field so that more of these patients are not coming in your clinic next year or the year after.  So a couple years ago, at the Cleveland Clinic where I practice, we created a center for young onset cancers, and at the time it was primarily focused on colorectal cancer. But as we are getting into colorectal cancer, we realize that beyond colorectal cancer, we are also starting to see more younger people with other cancers, including pancreas cancer, including gastric cancer, and including bile duct cancers. And we realized that because so much attention was being focused on colorectal, that maybe we should also be paying a little bit of attention to what was happening in this space. I want to, for your listeners, point out that the problem in bile duct cancers is not to the same degree as you see in colorectal cancer. Just a couple numbers to sort of, to set this in perspective: about 5%, 7% of bile duct cancers are young onset - it's not a huge proportion - 90%+ percent of patients are not young onset. But the impact on society, the impacts on those providing care, is obviously substantial for younger patients. And it is true that even though the proportion of patients is not that high, the incidence is rising.   And there's a very nice study done a couple of years ago and published that looked at what the cancers are that are rising at the highest rates. And bile duct cancer and gallbladder cancers were listed amongst the two with the highest rate, so about an 8% rate per year of increase. And so that's really what drove our interest was, as we're seeing early onset bile duct cancers, it's rising year by year, and what is this disease? Is it the same as you see in sort of the average patient with bile duct cancer? Is it different? How do we characterize it? How do we understand it? What are some of the causes precipitating it? And so that's what led us to sort of one of the investigations that we've documented in this paper.  Dr. Rafeh Naqash: Excellent.   So, talking about this paper, again, can you describe the kind of data that you use to understand the molecular differences and also look at potential immune signatures, etc., differences between the groups? Dr. Alok A. Khorana: Yeah. So the objective in this paper was to look at genomic differences between early onset and usual onset, or average onset biliary tract cancers. And this sort of followed the paradigm that's already been established for early onset colorectal cancer, where you take a bunch of people with early onset disease, a bunch of patients with average onset or usual onset disease, and then look at the profiling of the tumors. And we've done this for genomics, we've done this for microbiomics, we've done it for metabolomics. And the lessons we've learned in colorectal cancer is that, in many ways, the profiles are actually quite substantially different. And you can almost think of them as diseases of the same organ, but caused by different processes, and therefore leading to different genotypes and phenotypes and microbiomes. We had absorbed that lesson from colorectal cancer, and we wanted to replicate it in this type of cancer.  But as we discussed earlier, this is a relatively rare cancer, not that many cases per year. For colorectal, we could do a single institution or two institution studies. But for this, we realized we needed to reach out to a source of data that would have access to large national data sets. We were happy to collaborate with Caris Life Sciences. Caris, many of you might know, is a provider of genomics data, like many other companies, and they house this data, and they had the age categorization of patients less than 50, more than 50. And so we collaborated with investigators at Caris to look at all the specimens that had come in of bile duct cancers, identified some that were young onset and some that were older onset. It was roughly about 450 patients with the early onset or young onset, and about 5000 patients with usual onset cases. And then we looked at the genomics profiling of these patients. We looked at NGS, whole exome sequencing, whole transcriptome sequencing, and some immunohistochemistry for usual, like PDL-1 and MSI High and things like that. And the purpose was to say, are there differences in molecular profiling of the younger patient versus the older patient? And the short answer is yes, we did find substantial differences, and very crucial for providers treating these patients is that we found a much higher prevalence of FGFR2 fusion. And that's important because, as I'm sure you've heard, there's a ton of new drugs coming out that are targeting specifically FGFR fusion in this and other populations. And hence my statement at the outset saying you’ve got to get NGS on everybody, because especially younger patients seem to have higher rates of some of these mutations.  Dr. Rafeh Naqash: Excellent. You also looked at the transcriptome, and from what I recollect, you identified that later onset tumors had perhaps more immune favorable tumor microenvironment than the early onset. But on the contrary, you did find that FGFR2 early onset had better survival. So how do you connect the two? Is there an FGFR link, or is there an immune signature link within the FGFR cohort for early onset that could explain the differences? Dr. Alok A. Khorana: Yeah, that's a great question. So, to kind of summarize a couple of these things you talked about. So, one is we looked at these genomic alterations, and, yes, FGFR2 fusion was much more prevalent. It's close to 16% of young onset patients, as opposed to roughly 6% of average onset patients. So almost a threefold increase in FGFR fusion. And because there's so many drugs that are targeting FGFR fusion, and because the population included a period of time when these drugs had already been approved, we think some of the benefit or the improvement in median survival associated with being younger is likely driven by having more FGFR fusion and therefore having more drugs available to treat FGFR fusion related tract cancer with corresponding increase and increase in survival. And that was part of it. There was one other alteration, NIPBL fusion, that's been sort of known to be associated with a certain subtype of cholangiocarcinoma, but it doesn't really have a drug that targets it, so it's not sort of very useful from a clinical perspective.   The other two things you talked about, so transcriptome and immuno oncology markers, we found a couple different results on this. So one is that we found in younger people, angiogenesis was enriched, and why this is so we don't quite have a good answer for that. The other was inflammatory responses. So there's a couple of gamma interferon pathways and a couple other types of pathways that you can sort of do pathway analysis, and we found that those were enriched in the older patients or the average onset patients. But the benefit for immunotherapy was similar across the two groups. So even though we saw these differences in signaling in terms of which pathways are upregulated or downregulated, it didn't seem to translate into the current generation of immune checkpoint inhibitors that we're using in terms of benefit for patients. But we did see those differences.  Dr. Rafeh Naqash: I completely agree, Doctor Khorana. As you mentioned, that one size fits all approach does not necessarily work towards a better, optimal, personalized treatment stratification. So, as we do more and more sequencing and testing for individuals, whether it's early onset cancers or later onset cancers, figuring out what is enriched and which subtype, I think, makes the most sense.   Now, going to the FGFR2 story, as you and most listeners probably already know, FGFR is an approved target, and there are a band of FGFR inhibitors, and there's some interest towards developing specific FGFR2, 3 fusion inhibitors. What has your experience with FGFR inhibitors in the clinic been so far? And what are you personally excited about from an FGFR standpoint, in the drug development space for GI cancers?  Dr. Alok A. Khorana: Yeah, I think the whole FGFR fusion story sort of actually deserves more excitement than it's gotten, and it may be because, as I mentioned earlier, biliary tract cancers are a relatively low volume type of cancer. But the results that we are seeing in the clinic are very impressive. And the results that we are anticipating, based on some ongoing phase two and phase three trials, appear to be even more impressive for the very specific inhibitors that are about to hopefully come out soon.   Also, the possibility of using successive lines of FGFR inhibitors - if one fails, you try a second one; if the second one fails, you try a third one because the mechanisms are subtly different - I think it will take a little while to figure out the exact sequencing and also the sort of the rates of response in people who might previously have been exposed to an FGFR inhibitor. So that data may not be readily available, because right now most patients are going in for longer trials. But having that type of possibility, I think, kind of reminds me of the excitement around CML back when imatinib suddenly became not the only drug and a bunch of other drugs came out, and it's kind of like that. I think again, it's not a very common cancer, but it's really wonderful to see so many options and more options along the way for our patients. Dr. Rafeh Naqash: Thank you. Now, going to your personal story, which is the second part of this conversation, which I think personally, for me, is always very exciting when I try to ask people about their personal journeys. For the sake of the listeners, I can say that when I was a trainee, I used to hear about Dr. Khorana’s course, I always thought that Dr. Alok Khorana was a hematologist. My friends corrected me a few years back and said that you’re a GI oncologist. Can you tell us about your love for GI oncology and the intersection with hematology thrombosis, which you have had a successful career in also? Can you explain how that came about a little bit? Dr. Alok A. Khorana: Yeah, sure. So it is a common, I guess I shouldn't say misperception, but it's certainly a common perception that I'm a hematologist. But I'll sort of state for the record that I never boarded in hematology. I did do a combined hem-onc fellowship, but only boarded in oncology. So I'm actually not even boarded in hematology. My interest in thrombosis came about- it's one of those things that sort of happen when you're starting out in your career, and things align together in ways that you don't sort of fully understand at the time. And then suddenly, 10 years later, you have sort of a career in this.   But it actually came about because of the intersection of, at the time, angiogenesis and coagulation. And this is the late ‘90s, early two ‘00s, there was a lot of buzz around the fact that many of the factors that are important for coagulation are also pro angiogenic and many factors that are coagulation inhibitors. These are naturally occurring molecules in your body, and can be anticoagulant and anti angiogenic. A great example of this is tissue factor, which is, as you'll remember from the coagulation pathways, the number one molecule that starts off the whole process. But less widely appreciated is the fact that nearly every malignancy expresses tissue factor on its cell surface. This includes breast cancer, it includes leukemia cells, it includes pancreatic cancer. In some cancers, like pancreatic cancer, we've even shown that you can detect it in the blood circulation. And so for me, as a GI oncologist who was seeing a lot of patients get blood clots, it was particularly fascinating to sort of see this intersection and try and understand what is this interaction between the coagulation and angiogenic cascades that's so vital for cancers. Why is coagulation always upregulated in cancer patients? Not all of them get blood clots, but subclinical activation of coagulation always exists. So I would say I was fascinated by it as an intellectual question and really approached it from an oncology perspective and not a hematology perspective.   But then as I got deeper into it, I realized not everybody's getting blood clots, and how can I better predict which patients will get blood clots. And so I had both a hematology mentor, Charlie Francis, and an oncology mentor, Gary Lyman. And using sort of both their expertise, I drafted a K23 career development award specifically to identify predictors of blood clots in cancer patients. And that's the multivariate model that later became known as the Khorana Score. So again, I approach it from an oncology perspective, not a hematology perspective, but really a fascinating and still, I would say an understudied subject is why are cancer patients having so many clotting problems? And what does it say about the way cancer develops biologically that requires activation of the coagulation system across all of these different cancers? And I think we still don't fully understand the breadth of that. Dr. Rafeh Naqash: Very intriguing how you connected two and two and made it a unique success story. And I completely agree with you on the tissue factor. Now there's ADCs antibody drug conjugates that target tissue factor, both a prude as well as upcoming.   Now, the second part of my question is on your personal journey, and I know you've talked about it on social media previously, at least I've seen it on social media, about your interactions with your uncle, Dr. Har Gobind Khorana, who was a Nobel Prize winner in medicine and physiology for his work on DNA. Could you tell us about how that perhaps shaped some of your personal journey and then how you continued, and then also some personal advice for junior faculty trainees as they proceed towards a successful career of their own? Dr. Alok A. Khorana: Yeah, thank you for bringing that up. So very briefly, this is about my uncle. He's actually my great uncle. So he's my grandfather's youngest brother. And I grew up in India in the ‘70s and ‘80s, and at the time, I ran away from this association as fast as I could, because growing up in India in the 70s and ‘80s, it was a socialist economy. There wasn't a lot going on. There was certainly none of the IT industry and all of everything that you see right now. And so there were very few icons, and my great uncle was definitely one of those few icons. As soon as you mentioned your last name, that would sort of be the first question people would ask. But he did serve as a role model, I think, both to my father, who was also a physician scientist and a professor of medicine, and then to myself in sort of making me realize, one, that you can't really separate medicine from science. I think those are really integrated, and we want to ask questions and answer questions in a scientific manner. He chose to do it in a basic science world. My father did it in a clinical science world, and I have done it in a clinical and a translational science world. Again, sort of using science as the underpinning for sort of understanding diseases, I think, is key. And so that was certainly a massive inspiration to me.  And then after I immigrated to the US in the late ‘90s, I met him on a regular basis. He was certainly very inspirational in his successes, and I realized the breadth of what he had done, which I did not realize in my youth growing up. But this is a person who came to the US. This was before Asian immigration was even legal. So he got here and they had to pass a special bill in Congress to let him be a citizen that was based on the sort of work that he had done in Canada and in the UK before he came here. And then he sets up shop in the University of Wisconsin in Madison and hires tons of these postdocs and essentially converted his lab into this massive factory, trying to figure out the genetic code. Really just the type of dedication that that needs and the amount of work that that needs and the ability to do that in a setting far removed from where he grew up, I think it's just really quite mind boggling.  And then he didn't stop there. He got the Nobel for that, but I have these letters that he wrote after he got the Nobel Prize, and he was just completely obsessed with the possibility that getting the Nobel would make him sort of lose his mojo and he wouldn't be as focused on the next aspects of science. And he was just really dedicated to synthesizing DNA in the lab, so creating artificial DNA, which he ended up doing. And the offshoot of that work, so not just the genetic code, but PCR essentially was developed by his lab before it became sort of what we now know as PCR. And then ditches all of that in the ‘80s and ‘90s and moves to understanding the retina and just focuses on retinal disorders. And then signal transduction, essentially trying to figure out when a single photon of light hits your eye, what happens biologically. It's a completely different field. And just took that on and spent the next 20,30 years of his life doing that. So the ability to sort of change fields, I thought that was very inspirational as well, that you don't have to just stick to one question. You can get into one question, answer it as much as possible, and then find something else that's really interesting to you and that really grabs your attention, and then stick with that for the next couple of decades. So lots to learn there. Dr. Rafeh Naqash: Thank you. Thank you. And then, based on some of your personal lessons, what's your advice for junior faculty and trainees as you've progressed in your career?  Dr. Alok A. Khorana: I think, number one, and I can't emphasize this enough, and sometimes it actually causes a little bit of anxiety, but it is finding the right mentor. And for me, certainly that was key, because my mentor, who was Charlie Francis, was not an oncologist who was a hematologist, but was like me, sort of supported this idea of trying to understand, hey, why does coagulation interact with cancer? And so he approached it from a hematology perspective, I approached it from a cancer perspective, but he sort of gave me the freedom to ask those questions in his lab and then later on in the clinical setting and clinical translational setting, and then got me access to other people who are experts in the field and introducing you and then getting you on committees and making sure you sort of get into clinical trials and so on. And so having a mentor who sort of supports you but doesn't stifle you, and that's really key because you don't want to just ask the question that the mentor is interested in. And as a mentor now, I don't want to have my mentee ask the question that I'm interested in, but also a question that the mentee is interested in. And so there's a little bit of a chemistry there that's not always replicable, and it can go wrong in sort of five different ways, but when it goes right, it's really vital. And I mentioned it causes anxiety because, of course, not every day is great with your mentor or with your mentee, but over a period of time, has this person done sort of their best to get your career off to a start? And have you served that mentor well by doing the things that are– there's responsibilities on both sides, on both on the mentor and on the mentee. And if you can find that relationship where there's a little bit of chemistry there and both of you are effectively discharging both your responsibilities and satisfying your intellectual curiosity, I think that can't be beat, honestly. To me, sort of number one is that and everything else follows from that. So, the networking, making sure your time is sort of allocated appropriately, fighting with sort of the higher ups to make sure that you're not having to do too much, things that are sort of away from your research interests, all of that sort of flows from having the right person. Dr. Rafeh Naqash: Couldn't agree with you more, Dr. Khorana, thank you so much. It was an absolute pleasure. Thank you for sharing with us the science, the personal as well as the professional journey that you had. And hopefully, when you have the next Khorana Score, Khorana score 2.0, JCO Precision Oncology will become the home for that paper and we'll try to have you again maybe in the near future.  Thank you for listening to JCO Precision Oncology Conversations. Don't forget to give us a rating or review and be sure to subscribe so you never miss an episode. You can find all ASCO shows at asco.org/podcast. Thank you so much.   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. Khorana  - Honoraria Company: Pfizer, Bayer,  Anthos, Sanofi, BMS, WebMD/MedscapeConsulting or Advisory Role Company: Janssen, Bayer, Anthos, Pfizer, Sanofi, BMS Research Funding Company: Anthos, Bristol-Myers,  Squibb Travel, Accommodations, Expenses Company: Janssen, Bayer, Bristol-Myers Squibb 

In this JCO Precision Oncology Article Insights episode, Miki Horiguchi summarizes an editorial: “Expanding the Reach of Personalized Medicine in Cancer Care: Current Progress and Future Directions of JCO Precision Oncology” by Dr. Yushu Shi et al. published on May 30, 2024. TRANSCRIPT Hello and welcome to JCO Precision Oncology Article Insights. I’m your host Miki Horiguchi, an ASCO Journals Editorial Fellow. Today, I will be providing a summary of the article titled “Expanding the Reach of Personalized Medicine in Cancer Care: Current Progress and Future Directions of JCO Precision Oncology”. This is an editorial by Dr. Yushu Shi and colleagues that investigated trends in publication, peer review, and global influence of JCO precision oncology. Before getting into the editorial, I would like to briefly introduce to precision oncology and the JCO Precision Oncology journal as a leading platform for research in this field. Precision oncology is a personalized medicine approach that leverages advances in genomics and molecular profiling of tumors, biomarker-driven decisions, and targeted therapies to enhance clinical care for patients with various cancer types. Since there are many aspects to consider, such as biologic, clinical, and statistical aspects, advances in precision oncology also come with numerous challenges. These include identifying targetable mutations and addressing tumor heterogeneity and drug resistance. Other challenges are developing new study designs and statistical analysis methods to evaluate new approaches, as well as developing methods to manage large and complex datasets.  Since the American Society of Clinical Oncology introduced the journal JCO Precision Oncology (or JCO PO) in 2016, it has played an important role as a dedicated platform for publishing high-quality research and promoting discussions on those challenges. JCO PO is a peer-reviewed, online-only, article-based journal publishing articles across multiple categories. These include original reports, case reports, review articles, commentaries, correspondence, editorials, special articles, and molecular tumor board case discussions. The journal’s contribution to the advancement of the field is reflected in the journals’ impact factor, which was 4.6 in 2022 and 5.3 in 2023.  In the editorial, Dr. Shi and colleagues first investigated the publication trends from 2017 to 2022, highlighting cancer types, article types, the number of citations, and topics of papers published in JCO PO that have had broad impact. The papers accepted at JCO PO covered a broad range of research topics, including genomics-driven tumor treatments, molecularly selected targeted therapy, translational oncology, cancer biomarkers, gene expression and profiling, biostatistics and clinical trial methodology, epidemiology, and cancer prevention and control. The most common cancer types are thoracic, GI, and breast cancers. Original reports were more likely to be cited than case reports. The average number of annual citations for original reports was 4.33, while it was 1.39 for case reports. The authors listed the 10 most cited papers published in JCO PO in a table. The most cited paper was an original report titled “Landscape of Microsatellite Instability Across 39 Cancer Types” by Bonneville and colleagues. The paper has been cited more than 600 times since it was published in 2017.   Next, the authors conducted an analysis to see trends in peer-review. When manuscripts are submitted to JCO PO, they go through a rigorous peer-review process. Reviewers evaluate them based on five key metrics: importance of the study, originality, quality of writing, relevance to clinical practice, and scientific strength. Each metric is rated on a scale from 1 to 5, with higher scores indicating better performance. Dr. Shi and colleagues compared the rating scores between accepted and rejected manuscripts of original reports and case reports. They found that the median score of accepted manuscripts was above 3.5 for all metrics. The findings highlight that no single metric determines acceptance, underscoring the importance of excelling in all five areas when developing manuscripts. Finally, the authors looked at trends in global influence in JCO PO. Counting the country where the corresponding author’s institution is located, Dr. Shi and colleagues found that JCO PO has accepted manuscripts from 36 countries, indicating a steady increase in its global reach. The United States accounts for about 71% of the total contributors. The other top contributors include France, Canada, Italy, Australia, the Netherlands, Germany, Japan, the United Kingdom and China. Notably, global collaborations among authors have significantly increased, with the proportion of papers from multiple countries more than doubling from 12.5% in 2016 to 26.5% in 2022. These facts reflect JCO PO’s ongoing commitment to engaging with the international precision oncology community and encouraging global research submissions. At the end of the editorial, the authors provided some guidance for future authors. Across original reports and case reports, successful submissions to JCO PO typically have a translational focus. They provided a mechanistic understanding of tumor biology and utilized cancer genomics to inform clinical decision making. The authors also highlighted several underrepresented but growing areas of interest at JCO PO. These include pediatric oncology, sarcomas, ethics, trial methodology, informatics, computational approaches, and statistical methods related to precision oncology. Furthermore, the increasing significance of germline genetics, pharmacogenetics, molecular diagnostics, and molecular epidemiology in precision oncology has been recognized and valued by JCO PO. JCO PO also has special series issues. The special series feature timely research topics, such as Equity in Precision Medicine, Statistical Methods for Precision Oncology, and Next Generation Sequencing. Through these special series, JCO PO continues to lead the advancement of the application of precision oncology across a diverse patient population. The authors also provided points to consider when submitting case reports. For successful case report submissions, especially n-of-1 reports that showcase novel findings with potential clinical impact, it is crucial to include robust data to support the clinical observations, investigate underlying mechanisms, and ensure proper protection of patients’ identity and autonomy. An n-of-1 report alone is often insufficient for publication. Successful case reports typically extend beyond a single patient, examining the phenomenon in multiple patients and providing mechanistic validation, either in vitro or through preclinical models. Thank you for listening to JCO Precision Oncology Article Insights and please tune in for the next topic. 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.  

JCO PO author Dr. Jonathan D. Tward, M.D., Ph.D., FASTRO, at the HCI Genitourinary Cancers Center and the Huntsman Cancer Institute at the University of Utah, shares insights into his JCO PO article, “Using the Cell-Cycle Risk Score to Predict the Benefit of Androgen-Deprivation Therapy Added to Radiation Therapy in Patients With Newly Diagnosed Prostate Cancer.” Host Dr. Rafeh Naqash and Dr. Tward discuss how the cell-cycle risk score predicts the benefit of androgen-deprivation therapy in prostate cancer treatment. TRANSCRIPT Dr. Abdul 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, Assistant Professor at the OU Health Stephenson Cancer center. Today, we are excited to be joined by Dr. Jonathan Tward, Leader at the HCI Genitourinary Cancer Center, and Vincent P. and Janet Mancini Presidential Endowed Chair in Genitourinary malignancies at the Huntsman Cancer Institute at the University of Utah. Dr. Tward is also the lead author of the JCO Precision Oncology article titled “Using the Cell-Cycle Risk Score to Predict the Benefit of Androgen-Deprivation Therapy Added to Radiation Therapy in Patients With Newly Diagnosed Prostate Cancer.”  At the time of this recording, our guest's disclosures will be linked in the transcript.  Doctor Tward, welcome to the podcast and thank you for joining us today. Dr. Jonathan Tward: Thank you so much, Dr. Naqash. I'm excited to share this important research with your audience.  Dr. Abdul Rafeh Naqash: Awesome. For the sake of simplicity, we'll refer to each other using our first names, if that's okay with you.  Dr. Jonathan Tward: That's great.  Dr. Abdul Rafeh Naqash: Okay. So, Jonathan, this complex but very interesting topic revolves around a lot of different subtopics as I understand it. There is genomics, there are implications for treatment, there is machine learning and computational data science research. So, to start off why you started this project or why you did this research, could you, for the sake of our audience, try to help us understand what androgen deprivation therapy is? When is it used in prostate cancer? When is it used in combination with radiation therapy? And that would probably give us a decent background of why you were trying to do what you actually did in this research. Dr. Jonathan Tward: Yes, thank you very much. So, men who are diagnosed with localized prostate cancer, which is the majority of prostate cancer diagnosis, are faced with a lot of treatment decisions. And those decisions range all the way from, “Should I just go on active surveillance with the idea that it might be safe to treat later?” to “Should I consider surgery or radiation?” And then there's various forms of radiation. Now, as a radiation oncologist, one of the things that I have to consider when I meet a patient with localized prostate cancer who is pondering receiving radiation therapy, is whether or not we want to intensify treatment by doing more than just radiation alone. And androgen deprivation therapy, very specifically also thought of as chemical castration, what that really is is some kind of therapy where you are trying to reduce a man's testosterone levels to nearly zero. And the rationale for using androgen deprivation therapy in prostate cancer and in this case, specifically localized prostate cancer, is that one can think of testosterone almost as the food and growth signal for prostate cancer. There have been numerous prospective randomized trials that have been performed in the past that have clearly demonstrated that adding androgen deprivation therapy to certain contexts of patients with localized prostate cancer receiving radiation improves the outcome, including risk of metastasis and overall survival.  The problem is, we don't want to just intensify therapy for everybody who walks through our doors with localized prostate cancer. Some men have lower risk disease, and some men have higher risk disease. And conventionally, the way we make this decision is by looking at things like NCCN risk groups, which kind of lump patients into a few different boxes, generally speaking, called low risk, intermediate risk, and high risk. And if you think of those risk groups, the patients with the contemporary standard of who to add ADT to are men who are considered high risk localized, or men who are considered unfavorable intermediate risk localized. That being said, I think there's a recognition that we're overtreating some unfavorable intermediate risk men and undertreating them, and the same could be said of high-risk disease. So, I think we're always looking for better tools that make it a little bit more personalized, rather than lumping men into just one of several boxes. Dr. Abdul Rafeh Naqash: Sure. And this sort of reminds me of the oncotype DX, in a way, trying to connect people with ER/PR, breast cancer, and where chemotherapy, plus anti-estrogen and progesterone therapy may be applicable. So, I think you were trying to do something similar in this research, and as far as I remember, please correct me if I'm wrong, this is knowledge that I remember from my board exams, we classify this high risk, intermediate risk, and low risk based on the Gleason score. Is that correct? Is that still true, or has this changed? Dr. Jonathan Tward: It's still true. Conventional risk stratification, which is still used, literally only looks at a few parameters. You mentioned one, which is the Gleason score, which is really a human subjective judgment by a pathologist about how deranged cells look under a microscope. That's one parameter. The second parameter is the PSA value at the time of diagnosis. And the third parameter is the cT stage, which is really based on the digital rectal exam. Now, when you ponder that the entirety of our risk classification system is based on two subjective and one objective pieces of information, meaning what a Gleason score looks like, what the T stage is based on human interpretation, and then the only objective piece of data, PSA, it's rather rudimentary way of classifying men. I mean, it's done us well since the late ‘90s, when that particular classification system was derived. But it strikes me as odd that we should take all newly diagnosed localized prostate cancer patients and say you fit into one of three boxes, when we know there's so much more complexity to people and so many different treatment options and choices out there, which we're trying to match to the patient to ensure that we right size the treatment for them. Dr. Abdul Rafeh Naqash: Understood. Now, as we go into the precision medicine component of this research, there's genomics research in metastatic cancers. But is there any genomics research in early-stage prostate cancer where there have been differences that have been identified between the intermediate low risk, high risk? Is that something that has been explored to date? Dr. Jonathan Tward: Well, there are certainly somatic mutations that track with certain aggressive features. But I think when I think about the spirit of your question, within the localized prostate cancer space, there's been several molecular signatures that have been developed and, in fact, been commercialized that have been shown quite clearly that if you have a certain array of gene expressions, let's say, that that can correlate with metastasis or risk of recurrence or death. And the work that we're talking about today is one that actually uses one of the commercially available biomarkers, commercially it's known as Prolaris. But very specifically, in the work that I think we're discussing today, what we're looking at is cell cycle progression genes. And these are genes that maybe, to simplify it, are sort of hallmarks of how quickly cells are turning over. And what's interesting about looking at cell cycle progression is it's not certainly particular to prostate cancer. I mean, you could make an argument that cell cycle progression genes are probably relevant measures in any cancers, but there's been much work done over the past 15 to 20 years that have clearly validated that this particular cell cycle progression gene signature, which is now commercially available, clearly correlates with risk of progression, risk of metastasis in localized prostate cancer patients, whether they're receiving surgery or radiation. But what we've done is we've built upon this molecular work and added clinical risk features and added results of prospective randomized trials to use this test to personalize the precise risk reduction of what would happen to a man who is pondering adding ADT to radiation therapy. So, it's a very powerful precision tool.  Dr. Abdul Rafeh Naqash: Sounds very interesting. When you go deeper into this platform, is this genomic testing platform, does it incorporate RNA transcriptome or is it DNA, or is it a composite of both? Dr. Jonathan Tward: There are various molecular tests that are out there. In this particular case, these are mRNA expression levels of cell cycle progression genes, and they are kind of calibrated against some normal housekeeping genes, which is how the test is run. Dr. Abdul Rafeh Naqash: Understood. So, from what I understand in the discussion, you very appropriately said, in fact in your first paragraph, the goal here is to match patient level precision medicine approaches and reconcile them with population level therapeutic options. It's a very catchy statement. Can you help explain for our audience how you tried to do that? And this goes back to the question that you were trying to understand, where to use combination therapy in a localized prostate cancer based on risk stratification and deriving that risk stratification from the cell cycle score and then arriving to certain thresholds. So could you go through that in simple terms to help us understand how you tried to do it and what was the outcome and what are the implications of that? Dr. Jonathan Tward: Sure, there's a lot to unpack there, but I'll do my best to simplify it. So, we'll start with the basic question that faces a patient and their radiation oncologist, which is, if they're going to receive radiation, should you add hormone therapy? And if hormone therapy was completely nontoxic, you'd say, “Sure, just add it to everybody if there's a benefit.” But the problem is, of course, hormone therapy is associated with all kinds of unpleasant side effects and additional risks, so we don't want to utilize it unless we're sure that the benefit is clear. When you think about the way most of oncology decides whether or not adding an intervention should be done in a particular patient context, it's actually been derived originally from prospectively randomized trials, which usually assigned a hazard ratio or some kind of known relative reduction to doing ‘thing B’ versus ‘thing A’ or ‘thing B’ in addition to ‘thing A’. But what's curious about always looking at hazard ratios and saying that those are the reasons why you should do additional things, discounts a really important fact, which is the baseline risk of something bad happening has to be accounted for first before you decide whether or not it a relative risk reduction matters. So to state more clearly, if I knew a prostate cancer patient sitting in front of me only had a 2% risk of developing metastasis within 10 years, if I just did radiation alone, if I then say adding hormone therapy might cut that in half from 2% to 1%, a patient might say, “You know what? I'm not sure I want to accept the toxicity of many months of hormone therapy to cut my risk of metastasis from 2% to 1%.” But if you had a patient where that risk was 20% risk of metastasis with radiation alone, and you told them I can cut that risk down to 10% or 12%, then that's something they would seriously consider.   And so what this work really does is precisely that. It gives us a tool where, using the molecular signature of the cell cycle progression genes, which afford a patient a certain risk of metastasis, and also taking into account clinical risk factors that we know are prognostic, Gleason score, PSA, their age, how many cores of the biopsy were possible. We use all this information, and I'll use a strange term, multiplex it into a robust risk model that will prognosticate extremely clearly what that patient's precise risk of metastasis will be within the next 10 years, and this is the key point, if they receive radiation alone.   So, think of this work in two phases. Phase one is calibrate the risk in a patient if they get radiation alone, by using both molecular and clinical prognosticators. But then take the power of numerous randomized trials, which have clearly set the hazard ratio reduction for adding the hormone therapy, and then using mathematical principles, applying that hazard ratio risk reduction to the absolute risk. And then what you ultimately do is, at a very individual level, have a patient sitting in front of you where you can say, “Mr. Jones, I've run this test on you, and I can tell you definitively that if you receive radiation therapy for your localized prostate cancer, the risk of metastasis will be 12%. But if you add, let's say, six months of hormone therapy, that could be reduced to 7%, and the absolute risk reduction might only be 5%.” And if you think about that number in a number needed to treat mentality, then you could say, “Listen, I have to give 20 men identical to you, hormone therapy for one to benefit. Is that worth it to you?”   And what it really does is it empowers the patient. Rather than following a guideline that says, “Effectively, thou shalt do this for this risk group,” you really want to engage the patient in the conversation about the risk benefit of what you're going to do. And I think it's uncommon in oncology for physicians to be able to very precisely tell a patient sitting in front of them, if you do ‘thing A’, this is the risk, something bad happen. If you do ‘thing B’, this is how the risk reduces. And I think now we really get into shared decision making, rather than a, “Trust me, I'm a doctor,” paternalistic situation. Dr. Abdul Rafeh Naqash: That's a very interesting approach. Again, you're basically personalizing the personalized medicine approach, refining it further, and involving the patient in discussions, which helps them understand why something would make sense. And some of this, as you might already know, people have tried to do in some other tumor types, hasn't necessarily led to significant clinical decision-making changes. But I think the way the field is evolving, especially this research that you published on and others are working towards, will hopefully result in more personalized approaches for individual decision making for these patients.   Now, I do understand that simplicity sometimes results in more uptake of some information versus when sometimes things get more complex. So, in your assessment, when you came up with these results, you looked at the genomic score, you took the randomized clinical trial data, you did the absolute risk reduction. From what I understood in the manuscript, it does look like you did come up with a threshold of what would appropriately risk stratify individuals, meaning individuals that are at a higher risk if they cross that threshold, versus individuals that are at a lower risk if they cross that threshold. Is that a fair statement or is this a continuum? So there is no binary, but this is over a scale that this assessment can be made. Dr. Jonathan Tward: So, there are elements of your summary that are fair, but this is a continuum which allows any individual to accept whatever risk reduction they want. That being said, there is no standard in oncology for what percent risk should you intensify a treatment for? And when you poll physicians and doctors as to how much reduction in death or how much reduction in metastasis, doctors and patients are all over the map at what they consider to be a threshold. But we designed these thresholds actually from prior work, based on surveying both patients themselves, as well as experts who were on cooperative trial group steering committees, and ask them, essentially, “At what level of risk reduction would you want to intensify treatment?” And what's interesting is most people who are asked that question are willing to do more treatment intensity for an important outcome like metastasis if the absolute risk reduction of that event happening is 5%. So as a general principle, that's how it was set.  These thresholds in the current paper we're discussing actually weren't defined in this current work. They were defined in prior works, where we had clearly shown in retrospective data sets that they could discriminate very well who does or doesn't benefit from hormone therapy. What's, I think, novel about this paper, even though we had previously validated those thresholds, is that now that we're using the randomized trial data, it's extremely robust in our risk estimates, and we can say that it's truly a predictive biomarker. Because it's one thing to prognosticate an outcome, but predict a difference in treatment A versus treatment B usually requires randomized trial data so that you get the highest level of evidence and the confidence that it works. Dr. Abdul Rafeh Naqash: So the next steps for this very, very provocative research, is it something prospective validation or are you going to try to utilize maybe proper group trial data or other pharma trial data, individual patient data to risk stratify these individuals and validate?  Dr. Jonathan Tward: So these thresholds, for example, that you refer to are very well validated. There's multiple prior studies, well over at this point, 1500 patients where there's validation. And yes, we have reached out to cooperative groups to do some additional validation. That being said, this work is already ready for prime time and being used. In fact, this test is the commercially available Prolaris test. The results gleaned from this work are published on the score report that a patient and a physician receives. So the reality is that this is already existing as a clinical tool in the community. And the NCCN guidelines also support the use of this and other tests to move from a stratification to personalized medicine. So it's not like this is so much in the experimental realm as it is effectively a complete tool that is being used today. And effectively, it's available for any patient or physician diagnosed with localized prostate cancer to immediately order on biopsy tissue. Dr. Abdul Rafeh Naqash: One naive question, Jonathan, I wanted to ask is most prostate cancers tend to be prostatic adenocarcinoma. So if it's a neuroendocrine localized prostate cancer, does the same risk assessment apply? Because neuroendocrine tumors in general seem to be higher replication stress or higher tendency to metastasis. Does it change from your perspective, from the genomic assessment standpoint, the CCR score standpoint? Dr. Jonathan Tward: That's a very interesting question, because what I will tell you is that there are probably a lot of, well, I wouldn't say a lot, but there are some neuroendocrine cancers mixed in with the adenocarcinomas that no one identified as neuroendocrine, which in a way were baked into the cake of the risk signature. Even though that is so, I dont think we’ve independently looked very specifically at known neuroendocrine cancers and compared them to the adenocarcinomas. What I would actually argue though, is that if you have a neuroendocrine cancer sitting in front of you, the point about whether or not you're adding ADT is relatively moot because neuroendocrine cancers may or may not respond to ADT, and you have to start considering chemotherapeutic-like decisions.   So the question, which is very interesting and academic, is that I would presume the cell cycle progression score should be elevated, although I don't know that in a neuroendocrine cancer, this tool doesn't appear to be useful at this moment for neuroendocrine cancers because we're not making decisions about chemo. That's an interesting and provocative question, and now you make me want to study that. So potentially, the next paper would be neuroendocrine cancers, whether or not it might prognosticate using a topicide or something else like this. But we would have to rely on prospective trial data as well to see whether or not we could use it the same way.  Dr. Abdul Rafeh Naqash: Hopefully, if you do work on it, then you can submit the manuscript again to JCO PO for us to talk again. Dr. Jonathan Tward: Yeah, and you'll be on the author bar.  Dr. Abdul Rafeh Naqash: Appreciate the inclusion. So thank you so much, Jonathan, for talking to us about the science. And a few quick minutes about yourself. Can you tell us a little bit about your career trajectory, how you ended up doing what you're doing, and maybe some lessons learned and some advice for early career junior investigators that would be helpful for them?  Dr. Jonathan Tward: Yes, that's a happy memory. When I was a young undergrad, I was fortunate to do some volunteer work in a radiation oncology department and had mentors there who guided me into considering a career in medicine and specifically a career as a physician scientist. So I'll start with the best advice is to get mentors early on and throughout your career who are really interested in your career development and who are accomplished that can kind of help you along. But I went to medical school with an open mind and continued to love oncology. I think it has some of the most complex questions that are unanswered. It is very high stakes oncology. There's still a lot of death and disability and consequences of our therapies. And I just love the idea of working in an environment, both clinically and as a researcher, to try to solve some of those questions like, how do I improve outcomes? How do I make therapy less toxic?  And radiation oncology for me, was a nice fit in genitourinary cancer, I guess, specifically because mid GU cancer realm patients are presented with a menu of treatment options. It's kind of interesting. It's a little bit unlike other cancers. But I had fantastic mentors throughout both my medical school as well as residency program who really helped guide me and encourage me along the way. And so without spending too much time, I would say go out of your way to find people who are successful at what they do, are interested in making you better, and really sit at their knee and listen to them when they are trying to guide you because they really have your best interests in mind. And I think as a mentor and a mentee, what makes me most proud is watching people I've trained go out and succeed. I mean, the reward of being a mentor is watching your mentees succeed.  Dr. Abdul Rafeh Naqash: Thank you. Appreciate all those words of wisdom, Jonathan, and excited to see all the subsequent steps and results from the research that you're doing. Thank you again for joining us today and providing a very simple summary of a very complex topic which I think our audience and perhaps some of the trainees listening to this podcast will appreciate. We really appreciate your time.  Dr. Jonathan Tward: Thank you so much, Rafeh.  Dr. Abdul Rafeh Naqash: 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/podcast.     The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.   Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity or therapy should not be construed as an ASCO endorsement.     Dr. Tward Diclosures:   HonorariaCompany name: Bayer Consulting or Advisory RoleCompany name: Myriad Genetics, Blue Earth Diagnostics, Janssen Scientific Affairs, Merck, Bayer, Boston Scientific, Myovant Sciences, Myriad Genetics, Lantheus Medical Imaging Research FundingCompany name: Bayer, Myriad Genetics Travel, Accommodations, ExpensesCompany name: Myriad Genetics, Bayer

In this JCO Precision Oncology Article Insights episode, Miki Horiguchi summarizes two articles: “Biomarker-Driven Oncology Trial Design and Subgroup Characterization: Challenges and Potential Solutions” by Wang, et al. published on June 7, 2024, and “Biomarkers in Oncology: Complexities in Biomarker-Driven Studies and Statistical Analysis” by Uno, et al. published on July 22, 2024. TRANSCRIPT Miki Horiguchi: Hello and welcome to JCO Precision Oncology Article Insights. I'm your host, Miki Horiguchi, an ASCO Journal Editorial Fellow. Today, I'll be providing summaries for two articles.   The first article is a review article titled, “Biomarker-Driven Oncology Trial Design and Subgroup Characterization: Challenges and Potential Solutions,” by Dr. Jian Wang and colleagues. Biomarker driven clinical trials represent a key component of precision medicine, focusing on tailoring treatments to patients based on specific biomarkers. By identifying and targeting therapies to patients who are most likely to benefit, these trials aim to improve treatment outcomes and reduce adverse events.  The article highlights several important points to optimize biomarker driven clinical trials. The authors first reviewed US FDA approvals in biomarker defined subgroups and conducted an in-depth analysis of key regulatory considerations. They developed an innovative decision tree to guide designing biomarker based clinical trials. In addition, they clarified the statistical challenges, including ones found in the all-comers study design. The authors found that most of the US FDA approvals are being restricted to the biomarker positive subgroup, indicating that observed treatment benefits in the overall population are heavily influenced by the biomarker positive patients. This raises concerns as the treatment effect in the biomarker negative subgroup may be smaller but still clinically meaningful. Additionally, achieving adequate statistical power for the biomarker negative subgroup is often not feasible. These factors could limit access to the treatment for biomarker negative patients who might benefit from it. To address these challenges, the authors introduced various statistical methods and conducted numerical studies to compare the performance of several of these methods. They found that a promising approach is a Bayesian Dynamic Borrowing Method that leverages evidence from the biomarker positive subgroup to evaluate the treatment effect in the biomarker negative subgroup. The authors emphasize that any statistical method used for subgroup analysis must be prespecified. Proactive engagement with regulatory authorities and alignment with the guidelines before finalizing study designs and analysis plans are also essential.  The second article is an editorial which accompanies the first article, "Biomarkers in Oncology: Complexities in Biomarker-Driven Studies and Statistical Analysis” by Dr. Hajime Uno and Dr. Miki Horiguchi. In this editorial, the authors introduced additional statistical considerations that can further enhance informed decision making based on the results of biomarker driven oncology clinical trials. Specifically, the authors raised three key points to consider.   Number one is controlling the type 1 error rate. The qualitative assessment of a new treatment involves a statistical test, while regulatory decisions consider the totality of evidence rather than evidence based solely on P values. Statistical tests play a crucial role in determining treatment benefits in each of the three analysis populations, that is, the biomarker positive, the biomarker negative, and the all-comers population. The type 1 error rate of a statistical test is the probability of rejecting the null hypothesis when it is actually true. The threshold for the type 1 error rate is conventionally at 0.05. The threshold value can vary depending on the situation, but maintaining the type 1 error rate at the nominal level is essential to ensure the reliability of the conclusions drawn from a statistical test. Any inflation or deflation of the type 1 error rate from the nominal level can lead to significant issues in regulatory decision making.  Number two is choosing robust and interpretable quantitative summaries of treatment effect. Statistical tests provide a binary outcome aiding regulatory decisions like drug approval. However, quantifying the magnitude of the treatment effect is more informative for clinicians and patients when assessing the risk benefit balance of the treatment. Therefore, the choice of a summary measure to quantify the between group difference is also important. Dr. Wang and colleagues use the Cox Hazard ratio in their study, which is the most common summary measure in oncology trials. Yet this measure relies on several assumptions. Specifically, when it is applied to biomarker driven trials, the proportional hazards assumption must hold in both biomarker positive and biomarker negative subgroups.   In addition, when a stratified Cox analysis is used to integrate the hazard ratio of the two subgroups to derive the hazard ratio for the all-comers population, there is an underlying assumption that the hazard ratios from the biomarker positive and biomarker negative subgroups are the same. These assumptions do not usually hold in practice, and violations of these assumptions can compromise the interpretability of the estimated between group difference and its generalizability to future patient populations. It has also been discussed widely in both statistical and clinical journals that the hazard ratio is difficult to interpret because of the lack of absolute hazards from the treatment and control groups. To address these limitations, Doctors Uno and Horiguchi suggested using alternative summary measures, including restricted mean survival time and average hazard with survival rate, which do not share these limitations and offer more robust and interpretable results than the conventional hazards ratio approach.   Number three is using coherent statistical analysis models for the three analysis populations. In the first article, Dr. Wang and colleagues introduced a Bayesian Dynamic Borrowing approach. The primary analysis of their approach borrowed information from the biomarker positive subgroup only when analyzing the biomarker negative subgroup. They did not perform the borrowing when they analyzed the biomarker positive subgroup. The accompanying editorial highlights the potential bias introduced by this asymmetric approach. Specifically, suppose the treatment effect in the biomaker positive subgroup is pronounced, but that in the biomarker negative subgroup is weaker. In this case, their asymmetric approach produces a more favorable result for the biomarker positive subgroup compared to the symmetric approach, where each subgroup follows the information from the other subgroup. Providing a convincing rationale for using an asymmetric approach or conducting a sensitivity analysis with a coherent approach for both subgroups would be required.  To conclude, biomarker driven oncology trials are diverse and complex, requiring a tailored approach to statistical analysis that considers the unique characteristics of each trial. The Bayesian approach represents one useful analytic approach, but might not be a universal solution for all biomarker driven studies. Further discussions among stakeholders, such as those from regulatory authorities, clinicians, and biostatisticians will stimulate further research on the optimal design and analysis methods for biomarker driven clinical trials in precision oncology.  Thank you for listening to JCO Precision Oncology Article Insights and please tune in for the next topic. 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.      

In this JCO Precision Oncology Article Insights episode, Fergus Keane provides a summary on "Multi-Institutional Study Evaluating the Role of Circulating Tumor DNA in the Management of Appendiceal Cancers" by Belmont, et al published on May 9th, 2024. TRANSCRIPT  Fergus Keane: Hello and welcome to JCO Precision Oncology Article Insights. I'm your host, Fergus Keane, an ASCO editorial fellow. Today I will be providing a summary of the article entitled, "Multi-Institutional Study Evaluating the Role of Circulating Tumor DNA in the Management of Appendiceal Cancers" by Dr. Erika Belmont and colleagues.  While appendiceal cancers represent an uncommon diagnosis, the incidence has been rising, with now over 3000 new cases per year diagnosed in the United States. The management of appendiceal cancers includes surgical resection for localized tumors and cytoreductive surgery with hyperthermic intraperitoneal chemotherapy, also known as HIPEC, for select patients with peritoneal metastasis. For patients with higher grade appendiceal cancers, systemic therapy is often included in the treatment paradigm. However, little data pertaining to the optimal treatment regimens exists.  Despite best practice, disease recurrence within three years of surgery will be observed in about 70% of cases of appendiceal cancers. The current conventional methods for surveillance for both detection of recurrence as well as for assessment of response to systemic therapy are using cross sectional imaging and serum tumor markers. These methods are limited and there is a recognition that more accurate biomarkers are required. Circulating tumor DNA, also known as liquid biopsies, refer to shed tumor DNA identified in the plasma. Several ctDNA assays exist, including tumor agnostic assays and tumor informed assays, the latter of which assess presence of personalized tumor derived mutations. The utility of circulating tumor DNA has been studied across several different cancer types and in several different disease settings, for instance in lung cancer and colorectal cancer. However, it has not been well demonstrated to date in appendiceal cancers.  This study aimed to investigate the role of the Signatera ctDNA assay in patients with appendiceal cancer. Specifically, the authors aimed to evaluate factors associated with circulating tumor DNA detection and the association between ctDNA and recurrence free survival after surgery. Their hypothesis was twofold, firstly, that circulating tumor DNA detection would be reduced in patients who received recent systemic therapy, and secondly, that circulating tumor DNA detection after cytoreductive surgery and HIPEC would be associated with a shorter recurrence free survival across all appendiceal cancer grades. The study design was a retrospective review of patients with appendiceal cancers treated at MD Anderson Cancer Center in Texas and the University of Chicago who underwent circulating tumor DNA testing between January 2019 and December 2022. Clinical, pathologic and treatment related information was collected for all patients. Regarding patient treatment, all patients received treatment as per the consensus recommendations at both cancer centers. Diagnostic evaluation was with CT or MRI imaging and serum tumor markers. Diagnostic laparoscopy was performed to evaluate for the presence of peritoneal metastases. The patient treatment plans were determined via MDT tumor board discussions and cytoreductive surgery, and HIPEC was offered with curative intent to eligible patients.  Systemic therapy with 5-FU based doublet or triplet therapy with or without VEGF inhibitors was offered to patients with grade two or three tumors and with a good performance status. HIPEC protocols involved the use of mitomycin C. Postoperative surveillance involved cross sectional imaging and tumor marker evaluation every three months for two years and thereafter every six months if the patients remain disease-free. Circulating tumor DNA testing was offered at the discretion of the treating physician, typically every three months after surgery. The Signatera assay is a personalized, multiplexed, PCR based next generation sequencing platform. Three major analyses were performed. Number one, the frequency of any time ctDNA detection was evaluated in patients with ctDNA assays drawn at the time of radiographic or laparoscopically identifiable disease. Number two, the correlation between preoperative ctDNA levels and intraoperative peritoneal cancer index was evaluated in patients with peritoneal metastases. The third analysis involves the association between circulating tumor DNA presence drawn within one year of optimal resection.  A total of 402 plasma samples were obtained from 94 patients from the two centers. Most patients had grade 2 or 3 appendiceal cancers and 85% underwent surgery. Most patients had peritoneal metastases. 50 patients had circulating tumor DNA assessment in the presence of stage 4 disease, included in this, 13 patients were tested preoperatively, 26 patients who developed recurrence after surgery were included, and 11 patients who did not undergo surgery. In total, circulating tumor DNA was detected in 66% of these patients. The detection frequency was 57.1% in patients with grade 1, 62.5% in patients with grade 2, and 70.4% in patients with grade 3 disease, but this variability did not meet statistical significance. Lower circulating tumor DNA detection was observed in patients who received systemic therapy within six weeks before ctDNA assessment at 43.8% versus 76.5%, and multivariate analysis confirmed this association, demonstrating that recent systemic therapy was associated with an odds ratio of 0.22 versus less recent systemic therapy.  17 patients underwent circulating tumor DNA testing before cytoreductive surgery, and HIPEC and circulating tumor DNA was detected in 23.5% of these cases. No correlation was observed between ctDNA detection and intraoperative PCI index in these patients. Among the 50 patients with ctDNA testing within one year of optimal resection, survival estimates were generated for 36 patients who underwent cytoreductive surgery and HIPEC for grade 2 and 3 appendiceal cancers. The median follow up was 19.6 months. Circulating tumor DNA detection after cytoreductive surgery was associated with a shorter median recurrence free survival of 11.3 months versus not detected in those without ctDNA detection. On multivariate analysis, this was confirmed. The median time interval between surgery and ctDNA detection was 31 weeks. In this cohort of 36 patients, 44.4% or 16 patients developed disease recurrence. During the surveillance period, ctDNA was elevated in 93.8% of these patients, demonstrating a higher sensitivity than CEA, CA 19-9 or CA 125 tumor markers. Only one patient with disease recurrence had negative ctDNA at that time. Among these 16 patients with disease recurrence, one patient with a positive ctDNA test had their first sample drawn after diagnosis of disease recurrence, and one patient who had extensive adjuvant systemic therapy developed ctDNA negative recurrence. In the remaining 14 patients, circulating tumor DNA detection preceded the diagnosis of recurrence on imaging by a median of 11 weeks.   In summary, this study is a large, retrospective report of tumor-informed circulating tumor DNA testing in patients with appendiceal cancers. This study is one of the first to elucidate the factors associated with circulating tumor DNA detection in this disease and a potential role for circulating tumor DNA as an adjunct tool in the surveillance of patients with this malignancy.  Again, I'm Fergus Keane, a JCO Precision Oncology Editorial Fellow. Thank you for listening to the JCO Precision Oncology Article Insight. Please tune in for the next topic. Don't forget to give us a rating or review, and be sure to subscribe so that you never miss an episode. You can find all ASCO shows at www.asco.org/podcasts.    The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.  Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.      

JCO PO author Dr. Samuel J. Klempner shares insights into his JCO PO article, “PD-L1 Immunohistochemistry in Gastric Cancer: Comparison of Combined Positive Score and Tumor Area Positivity across 28-8, 22C3, and SP263 assays”. Host Dr. Rafeh Naqash and Dr. Klempner discuss assessing the analytical comparability of three commercially available PD-L1 assays and two scoring algorithms used to assess PD-L1 status in gastric cancer samples. TRANSCRIPT  Dr. Abdul 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. Abdul Rafeh Naqash, Social Media Editor for JCO Precision Oncology and Assistant Professor at the OU Health Stephenson Cancer Center. Today we are excited to be joined by Dr. Samuel J. Klempner, Director of Gastro Esophageal Medical Oncology and Assistant Professor at Harvard Medical School Mass Gen Cancer Center and author of the JCO Precision Oncology article, “PD-L1 Immunohistochemistry in Gastric Cancer: Comparison of Combined Positive Score and Tumor Area Positivity Across 28-8, 22C3, and SP263 Assays.” At the time of this recording, our guest disclosures will be linked in the transcript. Dr. Klempner, welcome to our podcast and thanks for joining us today.  Dr. Samuel J. Klempner: Happy to be here. Thanks for having me. Dr. Abdul Rafeh Naqash: For the sake of this podcast, we'll be using our first names. So, Sam, it was great to see you at ASCO recently, where I believe you presented these data as an abstract as well. Dr. Samuel J. Klempner: Yes, we had a poster presentation for this paper, which was published in parallel with the meeting. Dr. Abdul Rafeh Naqash: Congratulations, and I'm very happy that you chose JCO PO as the destination for these data. So we're going to be talking about a lot of different things today in the context of gastric cancer, which I know you treat very often in your clinic. So could you tell us what the treatment landscape for advanced gastric cancer currently is? Because that goes into the context of why I believe you and your colleagues went ahead with this project.  Dr. Samuel J. Klempner: Yeah, happy to. As you know, unfortunately, half or more of our patients, by the time they come to medical attention for a gastric or GE junction or esophageal adenocarcinomas, unfortunately have advanced disease, often metastatic at presentation. So we have this large population of patients with advanced disease, and over the last couple years, we've actually made some substantial advances in the management and survival of this population. This has been mainly driven by biomarker selection, whether it be adding immunotherapy on top of HER2 therapy, whether it be testing for claudin and seeing the results with claudin directed therapies. And perhaps the vast majority of patients are potentially eligible for immune checkpoint inhibitors. We've seen several phase three trials, perhaps highlighted by CheckMate 649, KEYNOTE 859, rationale studies confirming that there are populations of patients who derive significant survival advantages from the addition of anti PD-1 on top of chemotherapy. So the landscape has really evolved into a biomarker directed world, which is exactly what we hope, because ultimately, the goal is, of course, to match patients with the best drugs at the right time. And that's really the background of where this analytical effort came from.  Dr. Abdul Rafeh Naqash: Thank you for giving us that overview. Going to the second part, which, as you mentioned in your initial overview about the role of immunotherapy, and as we all know, immunotherapy has changed the treatment landscape for a lot of different tumor types. And as clinicians, we often see or ask, what is the PD-L1 positivity for, let's say, lung cancer, which is what I treat, and gastric cancer, which is what you treat. Some of the nuances that we don't necessarily go into when we're looking at those reports is the combined positivity score, the tumor proportion score, or the tumor area positivity. Could you give us an understanding, for the sake of our audience or for the sake of our trainees who might be listening to this podcast, what the CPS, or what the TAP  mean and where they are used in the treatment landscape for biomarker selection in the context of gastric cancer? And how do you approach the different cutoffs for CPS when you're treating an individual in the standard of care setting for gastric cancer? Dr. Samuel J. Klempner: For sure, happy to. So I think eventually it all comes back to patients. When we're sitting in a clinic room with the patient, we want to be able to have features about the tumor that's going to tell us if a therapy is more or less likely to work, maybe if there's a prognostic implication so we have predictive and prognostic biomarkers. And PD-L1 expression does not appear to be particularly prognostic, but it does appear to be predictive of benefit from immune checkpoint inhibitors. Therefore, all of the phase 3 trials that we've seen in some way have linked the biomarker expression to outcomes, whether it's the primary endpoint, whether it's post hoc retrospective analyses, etc. What we've seen is that all of these phase 3 trials have largely used different antibodies to define PD-L1 strata within the trial. So whether that's 22C3,  whether it's 28-8, whether it's 263, those are the predominant antibody clones used to examine PD-L1 expression in tumor samples. And it's been pretty clear across these large phase 3 trials that there is a trend with increasing PD-L1 expression and increasing magnitude of benefit. We see this in the improved hazard ratios in the CPS greater than five or greater than ten versus less than one, etcetera.  However, the scoring systems have varied. There is TPS tumor positivity, which only accounts for tumor cells. There is combined positive score, which accounts for tumor cells and mononuclear infiltrates and involves counting cells. And then perhaps the most recent one is the tumor area positivity, which is essentially a non counting method to look broadly at the area of the sample that is expressing PD-L1. It was on this background that we said, is there analytical concordance among the main antibodies? Our work does not address whether there is difference in clinical outcomes between testing 28-8 and 22C3 and SP263. It is simply a pure analytical comparison of the three antibodies. Is a CPS 5, when you call it by 28-8, somewhat agreeable to a TPS or a TAP greater than five with the same antibody and with a different antibody. So we felt that this was kind of a question that hadn't really been fully addressed in the field and may help contextualize results for clinicians and ultimately cross trial comparisons.  Dr. Abdul Rafeh Naqash: Thank you for that explanation. And you bring forth a very important question. And I remember this example of a patient with lung cancer who had tissue NGS done, and they had a limited gene panel with PD-L1 testing sent that showed a PD-L1 of close to 15 or 20%, and then another NGS panel with a different antibody, suggesting that they had a PD-L1 of close to 60-70%, which significantly changes the overall approach for treatment in the context of blood cancer. Is that something that you experience in gastric cancer also, in terms of variability for CPS, determining what treatment combinations you might be able to put an individual patient on? Dr. Samuel J. Klempner: It's rare that we have samples at any institution tested in multiple methods, but these types of papers and others had looked at some stuff similar and prior to our publication, but we know that there is both spatial heterogeneity. So if you test a tumor versus metastasis, you may have different PD-L1 scoring even in regions of large samples, like surgical resections, there will be some intra tumor heterogeneity in regions of expression. And then we also know that sometimes after therapy, for example, post radiation, there's some data that at the time of surgery, the PD-L1 expression may be higher than what the presurgical sample was. So there's a lot of variables that are factored in. But one thing that wasn't really well known is, across the standard antibodies, how well is the inter assay comparison? There had been some work from a group in Singapore, a very nice paper suggesting that at the higher cut points, the agreement was pretty good across the assays, CPS greater than 5 and greater than 10, and maybe slightly less so at the lower. They had used a different method, which was not really what is standard, and they had used multiplex immunofluorescence or IHC. This is not a validated method for PD-L1 scoring. So that was an open question, sort of. Although they laid a very important piece of data down, we wanted to use the most standard assays and essentially do a very similar analysis, but using the standard scoring criteria. Dr. Abdul Rafeh Naqash: Very interesting. So, could you walk us through the approach of how you looked at this question, what kind of samples you used and what kind of testing algorithms you implemented to look at the cross validation of these three different antibodies? Dr. Samuel J. Klempner: The antibodies were chosen primarily because those are the standard ones that either have companion diagnostics or have been used most commonly in phase 3 trials. So 22C3 has most commonly been linked to pembrolizumab, 28-8 to nivolumab, and 263 used with Roche and Genentech trials primarily. And so we selected the antibodies based on the common use. We selected the scoring systems of CPS and TAP, again based on the most commonly used and validated scoring algorithms in gastric cancer. And then, although most patients in clinic and metastatic disease present with biopsy samples from the primary tumor, there may be some limitations in biopsy samples in terms of small amount of material and ability to reliably count 100 cells, etc., for CPS. So we actually use surgically resected samples from a commercial biobank, 100 samples, and essentially 28-8 was really the reference. And we picked samples that, using 28-8 CPS PD-L1 expression represented the entire spectrum, meaning we had CPS less than 1, we had greater than 1 and less than 5, greater than 5 and less than 10, and greater than 10, so that we could compare across these different strata, because those are the most common strata that have been used in clinical trials and linked to magnitude of benefit. Dr. Abdul Rafeh Naqash: And something that, interestingly, I see here when we go to some of the results, and I'm pretty sure you'll talk about the concordance, is the correlation coefficient seems to increase as the percentage positivity increases for a certain antibody. Could you try to help us understand why that might be the case? Is it because it's easier for the pathologist to look at the slide when there is a certain level of positivity that crosses a certain threshold? Or could there be some other factors that are not well understood. Dr. Samuel J. Klempner: Yeah, it's a totally good question, and I think it's something that's seen in other IHC biomarkers as well. If you look at HER2, you'll see some similar trends. The agreement at IHC 3+ is pretty good and greater than it is at lower cut points. And having talked to multiple pathologists, and I'm not a pathologist, we had three pathologists scoring all of these samples, and essentially, it's what you might expect. It is just easier when there's a lot of the marker. It is easier to judge the high extremes of the strata. So the agreement at greater than 10 is quite good, and this has already been shown by others. It's just an easier thing to score for anyone. The agreement is better across all of the assays at higher cut points, whether it's TAP greater than 10% or CPS greater than 10%. And you can see that pretty clearly in our data, and it's also been shown in other data sets looking at roughly similar questions in other tumor types.  Dr. Abdul Rafeh Naqash: Going to the interesting results that you have in this paper, could you highlight for us some of the important findings that you had and put them into context of what their clinical implications may be? Dr. Samuel J. Klempner: Yeah, I think I'll start with the clinical implications so that what clinicians, and we're both clinicians, what we want to know is, if I have a report that says the CPS is greater than 1 and it's done with a 22C3 test, is that also likely to be greater than one if it had been done with a 28-8 test or scored with a different algorithm - CPS versus TAP? So, essentially, some degree of confidence on the interchangeability between the assays themselves, that is really the clinical implication. And so, to accomplish this, we set out to basically do the comparisons you'd have to do to convince yourself that that is true. So you take samples against a reference range, in this case, across the PD-L1 strata, you pick a reference test, in this case, 28-8, you have one pathologist be the start, and then you compare other pathologists against each other and that person, and you look. And in the pathology literature, they have strata of agreement which tend to go from poor, moderate, good to excellent. And these are sort of accepted standards in the pathology world about inter reader agreement. So between one pathologist and another, and things that are moderate or good are considered essentially acceptable at interchangeable levels.  And so, as you suggested, at the higher cut points, the agreement is very good. The clinical interpretation of that is that if you get a TAP greater than 10% scored on a 22C3 antibody on a Dako staining system, you can feel relatively confident that that would also be called a TAP or a CPS greater than 10 by a 28-8 antibody, suggesting there is good agreement between the two antibodies at that cut point. As you move down, there is a little bit less agreement, and that is consistent with what's been shown before. But in our data set, the agreement was still pretty good across all three of the antibody clones, even at the lower cut point, so greater than 1% for TAP or CPS greater than 1. And that provides, I think, some reassurance to clinicians that whatever test their own pathology lab is using, if it's one of these three assays, they can provide some degree of confidence that what they're seeing would be similar to what they were seeing if it had been done with another test. Dr. Abdul Rafeh Naqash: I think that that is very important, because even though we do want broad testing in general for metastatic tumors, as you probably will agree with, but there's a lot of practices still that institutions tend to do their own testing with limited gene panels or even IHCs. So I think to put that in the context of your study, as you said, if you have a certain antibody that is positive, as you've shown, then that also likely means that with another antibody that your institution may not test for, it's likely the tumor sample is likely going to be positive at a similar level.  So I think you also used digital pathology as part of this project, even though that may not be the most important aspect. As we move slowly and steadily towards artificial intelligence and machine learning, could you tell us how you incorporated the digital assessments and how you utilize them to correlate with the pathologist assessment and the futuristic perspective of how we could eventually try to incorporate digital pathology assessments for this kind of staining approach, which might limit interobserver operability differences as well as time constraints? Dr. Samuel J. Klempner: I hope I can do this part justice, because, again, I'm not a pathologist. But the digital imaging analysis was really essentially used as a quality check and verification tool in our own paper. Our intent was not to establish DIA directly as a superior methodology to TAP or CPS, but simply to provide ourselves some degree of confidence in the staining pattern and distribution across the three assays, and whether or not this would generate significant differences in what the PD-L1 score would have been called. And so, the bottom line is, the digital imaging analysis suggested there were very minor differences across the three assays in terms of, like, percent cell positivity, which is one of the main readouts, and the mean difference was actually quite small. So we felt that the digital imaging analysis, which was really considered somewhat exploratory in our own work, supported what we saw with the pathology comparators read in traditional methods. I think it sets somewhat of an initial pilot data benchmark to say that maybe we can think about moving tools like digital imaging analyses forward in terms of PD-L1 scoring approaches in the future. But it does not provide adequate data to say that we can do this now or we have enough samples and enough comparisons to say that, “Hey, for sure, digital imaging is equivalent to pathology reading.” I think that we're getting there and our data supports that that may ultimately be the conclusion, but for us it was really essentially an orthogonal support and sanity check for our traditional approach, which is, of course, a pathologist based scoring. So supportive and suggestive, but not definitively conclusive. Dr. Abdul Rafeh Naqash: Definitely early days for visual pathology assessments, but I think that it's a very rapidly evolving field, and hopefully we'll see more of this in the next few years, as well as incorporating some assessments into clinical trials.  Now, shifting away from your honorary pathologist role as part of this project to your actual role as a clinician investigator/clinician scientist, could you tell us your career trajectory, how you started, how you've self paced yourself, and how you've tried to mentor certain different individuals in your current role? Dr. Samuel J. Klempner: Yeah, I remember my grandfather and other people telling me, just try to leave it a little bit better than you found it. And so that's, I think, a guiding principle. I hope that at the end of my own career, I can leave oncology a little bit better than when I started. I think the best way to do that is to mentor and train the next generation who are going to drive these practices. I started, like many others, personally touched by cancer in my family, which started me on a journey towards oncology, was somewhat frustrated by the lack of options available to my mom, and then became deeply interested in the science and how come we knew so little about cancer, so spent a fair amount of time in labs, and had a really formative experience with Lew Cantley looking at PI3 kinase resistance and signal transduction, and wanted to learn to speak the language and interact with people driving the lab based work. And that's been something I've tried to keep as central to my career as someone who has a very strong translational interest.  And so I try to think of ways that I think we can learn from every single patient and every subgroup. I mean, for example, in our own work here, it's very unclear if there's a biology linked to the different PD-L1 strata. So for example, does a PD-L1 CPS greater than 10 tumor have a very high interferon gene signature? Or are there features of the T cells that are different between a CPS 10 or higher versus a less than 1? So PD-L1 is a biomarker, but is it really telling us about biology? And so these are the types of questions that I try to stimulate in all the residents and fellows and hopefully it will drive translational projects. But I think just having the conversations and asking the questions and talking to people. I mean, I love the ASCO Career Lounge and always try to do that when possible. I know you do the same. I think staying curious is really the thing that I try to remain in life and also in my career and have fun and enjoy with your colleagues. And I think that will make us all better researchers and ultimately translate to better outcomes for our patients, which is, of course, why we all do this. Dr. Abdul Rafeh Naqash: Wonderfully said Sam, thank you so much. Thanks again for choosing JCO PO as the final destination for your work. Hopefully we see more of the similar work that you do in your field in JCO PO. And thank you for talking to us about your journey as well.  Dr. Samuel J. Klempner: Yes, thanks for having me. I'll talk to you sometime soon.  Dr. Abdul 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. Klempner Stock and Ownership Interests TP Therapeutics Nuvalent, Inc Honoraria Merck Serono Consulting or Advisory Role Atellas Pharma Bristol-Myers Squibb Merck Daiichi Sankyo/UCB Japan Sanofi/Aventis Mersana Exact Sciences Novartis SERVIER AstraZeneca Amgen I-Mab iho Oncology    

In this JCO Precision Oncology Article Insights episode, Mitchell Elliot provides a summary on "Serial Postoperative Circulating Tumor DNA Assessment Has Strong Prognostic Value During Long-Term Follow-Up in Patients With Breast Cancer" by Shaw, et al published on May 1st, 2024. TRANSCRIPT The guest on this podcast episode has no disclosures to declare.  Mitchell Elliott: Hello and welcome to the JCO Precision Oncology Article Insights. I'm your host, Mitchell Elliott, an ASCO Journal editorial fellow. Today I will be providing a summary of the article titled, “Serial Postoperative Circulating Tumor DNA Assessment Has Strong Prognostic Value During Long Term Follow up in Patients with Breast Cancer,” by Dr. Jacqueline Shaw and colleagues.  Circulating tumor DNA is shed readily into the peripheral blood by tumors. ctDNA makes up a small fraction of the total cell free DNA in the peripheral blood and can be detected using highly sensitive assays. ctDNA assays can be tumor-informed where blood samples are tested for the presence of tumor specific mutations, which are selected by sequencing the primary tumor, so the panels are patient specific. Tumor agnostic assays also exist which are typically looking for the presence of cancer driver mutations or cancer derived methylation signals, which are not patient specific but rather cancer specific. Several retrospective analyses of clinical trials and cohorts have demonstrated that the identification of ctDNA in patients in follow-up can predict relapse in breast cancer, lung cancer, and colon cancer. Personalized tumor informed assays have demonstrated high technical specificity, but to date there is no gold standard assay identified and no direct comparison between all of the available assays. While the literature to date has demonstrated that identification of ctDNA prior to clinical relapse is possible, no study has demonstrated that it improves patient outcomes.  In this specific study, the authors evaluated the Signatera assay, a tumor informed assay based on whole exome sequencing, enabling the design of personalized panels for up to 16 tumor specific variants detected via multiplex PCR next generation sequencing. This was evaluated in the exploratory breast lead interval study or EBLIS, which is a study based out of the United Kingdom. EBLIS is a multicenter prospective cohort study funded by Cancer Research UK and the National Institute of Health Research that opened for recruitment in 2012. This was a retrospective analysis so no results were directly shared with patients or physicians. Patients were eligible if they were 18 years or older, had histologically confirmed breast cancer and must have completed all surgery and chemotherapy within three years of entry into the study. They had to have an adjuvant online risk relapse at greater than 65% or mortality of greater than 50% at 10 years, which defines a very high risk subgroup for study enrollment.  The results of this study and the baseline patient characteristics reflected the predefined clinical risk. The majority received neoadjuvant or adjuvant chemotherapy. Most patients were diagnosed with invasive ductal carcinoma and were staged 2b to 3c. There were 156 patients identified from this cohort after 28 had insufficient DNA and 3 had unsuccessful whole exome sequencing, which are required for the assay generation. Of the 156 patients, there were 1136 plasma time points evaluated. Of the 1136 plasma time points, ctDNA was identified in 46, which represents approximately 4% of the total time points in this high risk cohort. 34 patients have experienced disease relapse, including 22 with hormone receptor positive HER2 negative disease, three with hormone receptor positive HER2 positive disease, seven with triple negative breast cancer, and two with hormone receptor negative HER2 positive disease. ctDNA was detected in 30 of the 34 patients who had a subsequent relapse with a patient specific sensitivity of 88.2%. Relapse was predicted with a lead time interval of up to 38 months with a median of around 10.5 months ranging from 0 to 38 months. 100% of relapses were detected through ctDNA in patients with hormone receptor positive HER2 positive disease, triple negative breast cancer and hormone receptor negative HER2 positive disease.  Patients with a positive ctDNA test had a poor recurrence free survival with a hazard ratio of 52.98 with a 95% confidence interval of 18.32 to 153.2 with a statistically significant p value. Patients also had a significantly reduced overall survival if ctDNA was detected in the adjuvant setting. Multivariate models incorporating clinical pathologic variables and ctDNA status were analyzed. In this, ctDNA status remained the most significant factor associated with recurrence free survival and overall survival. Interestingly, concurrent ctDNA analyses and CA 15-3 measurements were available for 100 patients. CA 15-3 status was defined as positive and negative at the cutoff value of 30 units per milliliter. A Fisher's exact test showed a borderline statistically significant correlation between ctDNA status and CA 15-3, with a p value of 0.053. Again, multivariate analyses indicated that ctDNA was independent of CA 15-3 in predicting recurrence free survival and overall survival. Interestingly, ctDNA was not detected in 4 patients who experienced subsequent disease relapse, even with consistent and frequent sampling. Furthermore, ctDNA was detected in 5 out of 122 patients who did not have a subsequent recurrence, all being hormone receptor positive HER2 negative. These patients also had mature follow up. It is unknown if there was a change in the adjuvant treatment associated with subsequent negative tests, and follow up continues.   In summary, the study reaffirms that personalized ctDNA assays have high technical sensitivity and specificity for the identification of patients at risk for disease relapse. The test is highly predictive of recurrence in patients with breast cancer, especially with triple negative subtype where all patients had ctDNA detected prior to clinical relapse. However, for patients with hormone receptor positive breast cancer, these results suggest that this test needs to be used with caution, as a small proportion of patients experience disease relapse with negative tests and others whose tests are positive have not yet relapsed. It is unknown if these patients with ctDNA detected have radiographically overt metastatic disease in the absence of clinical symptoms, as concurrent radiographic surveillance was not performed in the standard of care follow up. Prospective clinical trials are required to define a role for ctDNA surveillance in clinical care.  Again, I'm Mitchell Elliot, a JCO Precision Oncology editorial fellow. Thank you for listening to the JCO Precision Oncology Article Insight, and please tune in for the next topic. 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 www.asco.org/podcasts.  The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.  Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.      

JCO PO author Dr. Jun Gong shares insights into his JCO PO articles, “Phase II Study of Erdafitinib in Patients with Tumors with FGFR Amplifications: Results from the NCI-MATCH ECOG-ACRIN Trial (EAY131) Sub-protocol K1" and “Phase II Study of Erdafitinib in Patients with Tumors with FGFR Mutations or Fusions: Results from the NCI-MATCH ECOG-ACRIN Trial (EAY131) Sub-protocol K2”. Host Dr. Rafeh Naqash and Dr. Gong discuss the limited activity of FGFR inhibition in solid tumors with FGFR amplifications and mutations or fusions in this NCI-MATCH phase II trial. TRANSCRIPT  Dr. Rafeh Naqash: Hello and welcome to JCO Precision Oncology Conversations, where we bring you engaging conversations of clinically relevant and highly significant JCO PO articles. I'm your host, Dr. Rafeh Naqash, Social Media Editor for JCO Precision Oncology and Assistant Professor at the Stevenson Cancer Center at the University of Oklahoma.  Today, we are excited to be joined by Dr. Jun Gong, Associate Professor in the Division of Medical Oncology at Cedars-Sinai Medical Center and lead author of the JCO Precision Oncology article entitled "Phase II Study of Erdafitinib in Patients with Tumors Harboring FGFR Amplifications: Results from the NCI-MATCH ECOG-ACRIN Trial EAY131 Subprotocol K1" and "Phase II Study of Erdafitinib in Patients with Tumors with FGFR Mutations or Fusions: Results from the NCI-MATCH ECOG-ACRIN Trial EAY131 Subprotocol K2."   Our guest's disclosures will be linked in the transcript.   Dr. Gong, welcome to our podcast and thank you for joining us.  Dr. Jun Gong: Thank you, Dr. Naqash and JCO Precision Oncology for having me. Dr. Rafeh Naqash: We are excited to be discussing some interesting aspects that you have led and published on from the NCI-MATCH trial. We were trying to understand from a background perspective, since this master protocol has been going on for quite some time, could you give us a little bit of background for the sake of our listeners on what the NCI-MATCH is and what were the specific objectives for these two subprotocols?  Dr. Jun Gong: Yes, of course, Dr. Naqash. So, as you may all know, the importance of targeted therapies in the current era of precision oncology. And on that backdrop, the NCI-MATCH was a national multicenter study designed essentially to look for signals of efficacy across various solid tumor and hematologic malignancy types, with a focus on specific mutations. The master protocol is unique in that there are several arms to the trial, each targeting a specific potential targetable alteration using available agents in cancer today. Dr. Rafeh Naqash: Excellent. Thank you for that background. I know this master protocol has been going on for quite some time with different subprotocols. I believe some of them are immunotherapy-based. Also, you've led two important subprotocols, which are the FGFR amplification and the FGFR mutation or fusion. There are some differences, from what I gather, in responses for the fusions versus the amplifications or mutations versus the amplifications. Could you first delve into the first paper of the fusions, and describe what were the tumor types? As you mentioned in the paper, some tumors were excluded. What was the reason for the exclusion of some of those tumor types? Why did you want to study the fusions and mutations versus the amplifications separately? What was the background for that? Could you highlight some of those points for us? Dr. Jun Gong: Firstly, as a kind of a more background, FGFR has been a recognizable target for a couple of tumor types. And if you look at the broad landscape of FGFR alterations, they occur in about 5%-10% of cancers, with the majority being FGFR amplifications actually, and mutations and rearrangements following second and third respectively in most commonly identified alterations. With that being said, FGFR mutations and rearrangements have already been established in a couple of tumor types. Actually, the first FDA approval for an oral FGFR inhibitor was erdafitinib, which was the agent used in both of these back-to-back trials. However, erdafitinib was first approved in urothelial carcinoma, and since then, there has been an explosion in oral FGFR inhibitors targeting fusions and mutations in other cancer types, such as cholangiocarcinoma.   More recently, there was even an FDA approval in a myeloid malignancy as well. So, we used erdafitinib, being that it was the first FDA-approved, orally available agent to target this alteration. We conducted the two back-to-back studies in recognition that although rearrangements and mutations have already been established in certain tumor types, we were more interested in looking at the more common FGFR alteration, that being amplifications. However, the efficacy in that was a little unknown, and so these two separate subprotocols were developed: K2, which was to look at FGFR mutations and fusions in tumor types, excluding urothelial carcinoma, to look if there was a signal of efficacy beyond currently FDA-approved indications, and amplification as a separate cohort. Dr. Rafeh Naqash: That's a very good explanation of why you concentrated on the tumor types in these protocols.  Now, going back to subprotocol K1, could you tell us what were some of the tumor types that you did include, and what was the sample size, and what was the hypothesis for the sample size as a meaningful level of activity that you wanted to see and would have potentially led to a bigger, broader trial? Dr. Jun Gong: So, subprotocol K1 was the arm investigating erdafitinib in those with FGFR amplifications, and these were predefined on the NCI-MATCH protocol, looking at FGFR 1, 2, 3, and 4 amplifications essentially. These were allowed to have local testing through a local CLIA-certified assay, but then they needed to be confirmed on a central assay, which is the NCI-MATCH Oncomine assay. These statistics are uniform for the NCI-MATCH trials, and the goal was at least 31 patients, with the hypothesis that if the response rate was 16% or more, this was considered a signal of activity. However, there was an additional protocol specific requirement in that if the sample size was fewer than 31 patients, then the primary efficacy population would be assessed against a null hypothesis overall response rate of 5%. Meaning that if there were less than 31 subjects, an overall response rate of greater than 5% would be defined as positive. Again, the NCI-MATCH was uniform. Secondary objectives included progression-free survival, overall survival, and safety and toxicity. With that being said, K1 originally began accrual. The NCI-MATCH actually launched in 2015, but in the subprotocol K1, 35 patients were initially enrolled in the study. If you go down the eligibility criteria, however, a lot of these patients dropped out due to a lack of central tumor confirmation and various reasons. Ultimately, 18 patients were included in the pre-specified primary efficacy cohort. Dr. Rafeh Naqash: Thank you. I did see for subprotocol K1, you mostly had stable disease in a couple of patients, no responses, and I think one individual with breast cancer had a prolonged stable disease.   Now, from an FGFR amplification standpoint, did you or were you able to correlate - again, this is not objective responses, it's not a partial response or a complete response - was there any correlation from the level of amplification to the duration of stable disease?  Dr. Jun Gong: That's actually the core of our discussion about why K1, despite a variety basket of solid tumor types, somewhere, preclinical data had suggested FGFR amplifications could be targeted, that K1 was ultimately a negative trial with a 0% response rate. We dive in that although we included as an eligibility criteria a copy number variation of seven as the threshold for amplification, we realized that if you look at some of the literature out there, that even in the FGFR 1 and 2 amplification cohorts, where these are the more common cohorts of amplified tumor types that have been targeted, you really needed a high level of amplification, more than 99% of tumor cells being amplified in the previous studies, to actually generate a response.  The thought was that we assumed that FGFR amplification would lead to protein expression and dependence on FGFR signaling, providing sensitivity to FGFR inhibition. However, we realized that there is a certain degree where a high level of amplification needs to happen, and it may not be for all FGFR amplifications. We looked into the literature that FGFR 1 and 2 were the more commonly studied FGFR amplifications. FGFR 1, if you actually look at the amplicon structure, it tends to amplify a lot of other genes because it's such a huge amplicon structure. But FGFR 2 is shorter and centered on just FGFR 2 with a few other genes co-amplified. So, actually in the literature, they've already been seeing that maybe FGFR 2 amplification tumors are more readily targetable based on the robustness of evidence, rather than FGFR 1. But across all of these, the higher the level of amplification, seems the more targetable. Dr. Rafeh Naqash: Those are interesting discussions around protein expression on the tumor that could imply therapeutic vulnerability. So I've always thought about it, whether trials like NCI-MATCH trials or ASCO TAPUR, for example, would be perhaps more informative if, on a secondary analysis standpoint, proteomics is something that could be done on the tumor tissue, because similar to NCI-MATCH, ASCO TAPUR has other sub protocols where some of these mutations or amplifications don't necessarily result in antitumor responses. But I think from a biology standpoint, as you mentioned, a certain amplification might correspond to RNA expression and that might correspond to protein expression, which is downstream. So looking at that would be something interesting. Have you planned for something like that on these tumor specimens? If you have biobanked any of those specimens. Dr. Jun Gong: I think that's a great future direction. And I know you, Dr. Naqash, being involved in so many cooperative trials, I think it is possible, but it really depends on good trial planning from the onset. When designing such massive trials like this, I think the more important thing is if your trials are negative, but they are informative for the field to go back and have these postdoc available biobanks that you said. And I think having it integrated firstly, is way more efficient than to have kind of an amendment kind of going through halfway or when the trial is started. That could be a little bit more logistically difficult.  Dr. Rafeh Naqash: I completely agree. And you mentioned corporate groups, I think we've been discussing, and I'm pretty sure you have also, there's a lot to be learned from clinical trials that are negative. We often, in the academic or non-academic setting, end up not publishing some of those negative results, pharma or corporate group based studies. And I think the resources, the specimens, and the negative results could correlate to some other novel findings if some of those exploratory analyses are done in the appropriate manner.   Now, going to the drug itself or the erdafitinib here, it's a pan-FGFR inhibitor. Is that something that you think is a limitation in the drug development space? I do early phase trials, and I'm pretty sure you do a lot of these basket early phase trials. Is that something that you feel is a limitation when you have a drug that targets different mutations or different protein changes of the same gene or different amplifications? Could that be a reason why something like this doesn't necessarily work because it doesn't have as much specificity against the isoform as one might need to inhibit the downstream kinase activation?  Dr. Jun Gong: That is also a great point. The NCI-MATCH sub protocol K1 and K2 used erdafitinib, which was the first FDA-approved FGFR inhibitor. But as many of the listeners and yourself may know, there have been newer iterations in next-generation development of the FGFR inhibitors. And it's very fascinating, the tyrosine kinase inhibitors, with each iteration, you seem to have a little more potency and the ability to bypass some of the resistance mutations, almost paralleling the lung cancer space, where we kind of follow that, and they've been kind of the pioneers in that space. And to your point, yes, we consider– the NCI-MATCH was developed nearly a decade ago, and the available agents at that time, would it have changed the findings if we used a kind of a newer generation or more potent FGFR inhibitor? It's possible, I think, especially in the K1 cohort with the amplifications. We even suggested in the discussion of the paper future directions, is that one way to kind of bypass the amplification issue is to use more potent and specific FGFR inhibitors. And so I think it's very possible that you highlight this point.  Dr. Rafeh Naqash: And for the sake of our listeners, Jun, especially trainees, could you highlight what are currently some of the FDA-approved FGFR inhibitors, and what tumor types are they currently approved in?  Dr. Jun Gong: The first one, as we have hinted, was in treatment of refractory, essentially urothelial carcinoma with FGFR mutations and rearrangements, mainly 2 and 3. And this is where oral erdafitinib was approved. And it's interesting, I kind of teach my fellows and our health staff that erdafitinib is interesting in that its FDA label insert requires a starting dose of about 8 milligrams daily, and it's a 28-day cycle. But during the first 14 days, we're really looking at the serum phosphate levels. If they are within a certain level, if they are within 5.5 to 7, for example, you continue the current dose. But if they are less than 5.5, the FDA label actually mandates that you increase it to 9 milligrams oral daily, continuously. This is biologically logical to me. FGFR is located to the renal tubules, and so this is a major phosphate kind of metabolism pathway here. And so you're using that as a surrogate, essentially, if the right dosing is achieved. And so that's unique.  And then the subsequent kind of FGFR inhibitors that came about, you had a couple in cholangiocarcinoma, where, unlike urothelial carcinoma, where it's about 30% of the time, you'll find the FGFR alterations of target. It's about half of that 15% in cholangiocarcinoma, and it's mainly intrahepatic cholangiocarcinoma in that sense. And here you have pemigatinib, which is one of the FGFR inhibitors approved for cholangiocarcinoma. And then you also had infragatinib, which is approved. But however, infigratinib eventually had their FDA label culled. It was withdrawn by the company, I think it was in 2022. And then more recently, you had even a more potent FGFR inhibitor in cholangio approved and futibatinib. It's interesting that with these more later generations of FGFR inhibitors, they do show a correlation with phosphate levels, but they don't have that specific kind of dosing early on in the first cycle, like erdafitinib. And so it's interesting to see that with the later generations, you're seeing more potency as well. Dr. Rafeh Naqash: Thank you for that overview, which I'm sure most of the trainees appreciate since this is an up and coming field in the space of precision medicine, especially FGFR. From a side-effect profile standpoint, you mentioned phosphate issues. Do you think that is a drug class effect here, or is that an FGFR receptor subtype effect, depending on which FGFR receptor, 1 or 2 or 3, that is being targeted?  Dr. Jun Gong: I do think this is a class effect that you'll see across a lot of the trials where phosphorus elevations or decreases are going to be probably your most common treatment-related adverse event. And I actually emphasize this is probably one of the most trickier side effects of this class, where we’re almost having to have to monitor the phosphorus levels pretty routinely, pretty closely. And you also have other class effects on the nails. There's some rare retinal ocular toxicities that's unique to the FGFR class as well. And so it's a very exciting class of compounds, but it does require some close monitoring of some unique class effects as you’ve hinted. Dr. Rafeh Naqash: Based on the results from your K1 sub protocol, are FGFR inhibitors still the approach within, let's say, within cholangio or urothelial with FGFR amplifications? Is that still something that has been established and seen from a clinical response standpoint? Dr. Jun Gong: The FDA approvals are really for mutations and fusions. So this K1 sub protocol, essentially, I think provides one answer that we've been all wondering about for the longest time, “Hey, could amplifications be targeted as well?” Unfortunately, we didn't include urothelial carcinomas in this study because of the FDA approval. But from a kind of a basket solid tumor perspective, I think this really dampens the enthusiasm. As of right now, it really is fusions and mutations that are targetable. Amplifications need further investigation before becoming established in solid tumors. Dr. Rafeh Naqash: Going to the discussion with the second K2 protocol, which is mutations and fusions, can you highlight again which tumor types there where you saw some clinical outcomes that you saw and any unique insights on certain mutations or protein changes that were a little more relevant than some others?  Dr. Jun Gong: Sure. So this is the parallel study to K1, in that now we are looking at fusions and mutations of FGFR1, 2, 3, and 4. And essentially, we, again, excluded those with urothelial carcinoma, given the FDA approval for erdafitinib in this trial. The trial actually opened then the FDA approvals for the FGFR inhibitors for cholangiocarcinoma happened. So this trial didn’t really exclude those with FGFR mutated or rearranged cholangiocarcinoma as well. If you look at the breakdown of the cohort in K2, you saw a good mix of breast cancers or a couple of gynecologic malignancies. There were a couple of head and neck cancers. There were several brain tumors as well. There was one lung cancer. There were four noted intrahepatic cholangiocarcinomas. Again, we could not exclude those due to the fact that the trial had opened and was accruing when the FGFR inhibitors approved for cholangiocarcinoma happened. Similar design, with a phase II, single-arm, open-label of erdafitinib, and again, the same statistical design was implemented in that if it’s higher than 31 patients, 16% overall response rate was a primary endpoint goal. If it was less than that, it was against the 5% overall response rate.   And here in K2, 35 patients were enrolled and 25 patients were ultimately included in the primary efficacy analysis. So because it was fewer than 31 in the primary efficacy cohort, it followed the NCI-MATCH to be specified with a primary endpoint goal of 5% or higher. And here, in a heavily pre-treated cohort of more than 50% of subjects who have received prior than 3 or higher lines of therapy, overall response rate essentially confirmed was 16% with the p value of 0.034, which met the positivity cutoff of 5%. However, an additional seven patients experienced stable disease as best confirmed response. And it’s important to note that four of these were grade IV glioblastomas with prolonged progression-free survival. So ultimately, this trial was positive in reading the endpoint that outside of urothelial carcinoma, could FGFR inhibition be pursued in other tumor types that had FGFR rearrangements or fusions? Dr. Rafeh Naqash: You mentioned glioblastoma, which is an area of huge unmet need. Do you think a trial like this as an upfront approach in glioblastoma, perhaps maybe after Temodar, could be a more meaningful way using the strongest, more precise therapy earlier on when there are certain mechanisms that inhibition of which would result in anti-tumor responses? Do you think doing this earlier on rather than second, third, fourth line would be more intriguing in some ways?  Dr. Jun Gong: I think you’ve hit upon several key points there. Firstly, just a high unmet need in glioblastomas, in general. And then to us, although it was a stable disease it was quite noticeable that four of these occurred in IDH1 and 2 wild-type brain tumors. We kind of discussed that in the discussion as well. And of these, we actually realized that in the pre-clinical and other published literatures space that for some reason, IDH1 and wild-type tended to have more FGFR alterations, while 0% were found in IDH1 and 2 mutant high grade gliomas. So I think there is something hypothesis generating coming out of this study as well even though there were stable disease. And that you may be selecting for– We may be able to have future studies to select for a specific niche of glioblastomas. And as to your point, Dr. Naqash, I think  if we can have a design trial looking for these specific molecular subsets, I think it’s wide open for trials of this nature in the first line, second line, or refractory space. Even piggybacking into cholangiocarcinoma, you see, they’re now looking at these in the neoadjuvant and adjuvant space as well. So I think we can identify the subset - it’s wide open out there. Dr. Rafeh Naqash: I completely agree. I remember my program director a few years back when immunotherapy was in the metastatic setting, it was very exciting. He gave a talk in which he said "Early, earlier, earliest," and the more early, the better it seems. So I'm guessing that it's probably something similar for precision medicine-based approaches like targeting FGFR perhaps earlier.   So what is next for some of these two studies, or these ideas that have come out of these two studies? Are you trying to develop something subsequently, or is NCI-MATCH looking at it from a certain perspective? Or what would you want to do as a next step, ideally if you had the funding and the pharma support? Dr. Jun Gong: That’s the million dollar question. So just from the broad strokes, I think what these two back to back papers and studies comment is that amplifications may not be the more targetable of FGFR subset, but there is avenue for improvement there and further investigation. FGFR fusions and mutations however seem to go along with what we know in some of the FDA approved types now. Now the next step is in the area of precision oncology is could we expand the label indications now to other subtypes with FGFR fusions and mutations. And this is I think following precedent. You and the audience may know that there are a lot of different tumor agnostic approvals now for both immunotherapy and other targeted therapy types. So I think the goal of this study was to provide momentum for, perhaps, advancements into a tumor agnostic indication for FGFR inhibitors.  And we do cite in the K2 manuscript the results of a phase II study that was also published around the time we were writing the study up. It was the phase II RAGNAR study. And that enrolled patients, again, with FGFR fusions and mutations. And that trial was positive, too. That one was a larger study of 217 subjects. We highlight some differences in study populations as to why maybe the difference in responders were detected. Both were positive studies. It was reassuring that the overall survival impulse studies were about the same. And again, I think they don’t compete. I rather think they complement each other in providing this body of evidence that  may meet- at one point, the FDA should be approached with this evidence for a tumor agnostic mutation so that more patients with this subset could be benefitting.  Dr. Rafeh Naqash: Excellent. Thank you so much, Jun.  Now, could you tell us briefly what your background is, where you’ve trained, and your interests, and how you balance clinical research with some of your personal interests?  Dr. Jun Gong: Sure. Thank you for that interest. I did my training in medical school in New York. I went to New York Medical College. And then I did my residency at Cedars-Sinai for medicine. And I went to City of Hope for fellowship where I was trained in GU by Dr. Monty Powell who maybe you folks are familiar with. And my GI training was with Dr. Fakih at City of Hope. And since then I returned back to Cedars-Sinai where I serve as a dual GI/GU focused medical oncologist. I do clinical trials in both and translational science, really focused on targeting tumor metabolism in both as well. My advice to the listeners and trainees and I tell my own fellows this, I think it’s very rare now unless you’re in phase I to do a dual focus. So I actually emphasized to my trainees that the more focused you can be, the better. Unless you are going into phase I, for example. With that, you can hone in, develop your craft. But then again, I have known several mentors who do multiple tumor types. But I think the more traditional mechanism is to focus as much as you can is my advice for the listeners.  Dr. Rafeh Naqash: Thank you again, Jun, for all those interesting scientific and personal insights. We appreciate you and working with JCO Precision Oncology for both of your manuscripts. This is the first time we have ever invited a lead author for two manuscripts at the same time. It's always good to be the first in something, and I learned a lot and hopefully, our audience would have learned a lot. Dr. Jun Gong: Thank you, Dr. Naqash, for having me. It was a pleasure speaking with you and the crew. Dr. Rafeh Naqash: Thank you.   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, experiences, 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.