Podcasts about ffpe

JCO PO authors Dr. Philippe Bedard (Staff Medical Oncologist at Princess Margaret Cancer Centre and Professor of Medicine at University of Toronto) and Dr. Alberto Hernando Calvo (Medical Oncologist at Vall d´Hebron University Hospital) share insights into their JCO PO article, “Combined Transcriptome and Circulating Tumor DNA Longitudinal Biomarker Analysis Associates With Clinical Outcomes in Advanced Solid Tumors Treated With Pembrolizumab,” one of the top downloaded articles of 2024. Host Dr. Rafeh Naqash and Drs. Bedard and Hernando Calvo discuss how combined transcriptome and ctDNA longitudinal analysis associates with pembrolizumab outcomes. TRANSCRIPT Dr. Rafeh Naqash: Hello and welcome to JCO Precision Oncology Conversations where we bring you engaging conversations with authors of clinically relevant and highly significant JCO PO articles. I'm your host, Dr. Rafeh Naqash, podcast editor for JCO Precision Oncology and Assistant Professor at the OU Health Stephenson Cancer Center at the University of Oklahoma.  Today we are excited to be joined by Dr. Philippe Bedard, Staff Medical Oncologist at the Princess Margaret Cancer Center and Professor of Medicine at the University of Toronto, as well as by Dr. Alberto Hernando-Calvo, Medical Oncologist at the Vall d'Hebron University Hospital, both authors of the JCO Precision Oncology article titled, “Combined Transcriptome and Circulating Tumor DNA Longitudinal Biomarker Analysis Associates With Clinical Outcomes in Advanced Solid Tumors Treated With Pembrolizumab.”  Thank you for joining us today. Phil and Alberto. Dr. Alberto Hernando-Calvo: Thank you. Dr. Philippe Bedard: Great to be with you. Thanks for having us.  Dr. Rafeh Naqash: One of the reasons we do this podcast, as some of the listeners who listen to this podcast regularly may know, is to bring in novel approaches and try to understand how the field is moving towards a space where we are understanding biomarkers better. So your manuscript that was published in JCO Precision Oncology fulfills many of those criteria. And interestingly enough, I was at a conference at the Society for Immunotherapy of Cancer last month earlier in November and a lot of excitement at SITC was revolving around novel transcriptomic biomarkers, proteomic biomarkers or imaging based biomarkers. So could you tell us a little bit about why you started looking at biomarkers? This is an extremely competitive field. Why did you think that looking at the transcriptome is somewhat different from or more interesting from tumor mutational burden PDL-1 than other biomarkers that we currently use? And that question is for you Alberto to start off.  Dr. Alberto Hernando-Calvo: So I think gene expression profiles may have a predictive performance as compared to already existing biomarkers and this was one of the points that we describe in our manuscript. The gene expression signature that we developed back in 2019 at Vall d'Hebron Institute of Oncology was initially developed based on over 45 different tumor types and tested in over 1000 patients treated with antiPD-1 and anti PDL-1. And back then and in this manuscript, we proved that for instance the gene expression signature VIGex that we developed has a potential complementary role to other predictive biomarkers. In this case, we observe this predictive power with ctDNA dynamics and we then see a correlation with other existing biomarkers such as tumor mutational burden. So I don't think we need to use one or the other, but rather they may have additive predictive power. So we need to better individualize predictive biomarkers based on tumor types and select the best combination possible to improve the performance.  Dr. Rafeh Naqash: I completely agree that one size does not fit all, especially in the landscape of immunotherapy. From your perspective, when you developed the original signature, how did you choose what genes to look at? I looked at the manuscript, on the methodology side, some of the signatures are pro-inflammatory STING interferon gamma based, so how did you try to identify that these are the 7 to 10 or whatever number of signatures on the transcriptome side? And then why did you try to combine it with ctDNA based changes?  Dr. Alberto Hernando-Calvo: Back in our initial manuscript, published in Med from Cell Press, we developed the VIGex gene expression signature, as I mentioned, with taking into consideration over 1000 tumor samples from FFPE that we can consider real world samples because they are from real patients coming from the clinic notes as part of real investigational protocol doing or performing biopsies on patients. We did observe after doing a VIGex research and doing different tests, we eventually collected these 12 different genes. Because there is a combination of both genes involved in the interferon gamma pathway, we have genes associated with Tregs as well as T cell memory cells. So it's not only looking at genes that are associated with T cell activation or CD8+ T cell infiltration, but also looking at genes that may be overactivated, overexpressed, an immunosuppressive tumor microenvironment. So it was both selecting genes, the minimum number of genes to do it more scalable and having the minimum dataset of genes and including in the signature genes that are already at targets for immune sequent inhibitors or are being tested in immunotherapy combinations.  Dr. Rafeh Naqash: Thank you. And Phil, for the sake of our listeners, could you elaborate upon this aspect of using ctDNA? So this was tumor-informed ctDNA from what I understood in the manuscript. You guys basically try to use it to understand changes in the ctDNA with treatment and then try to combine it with the transcriptome signature. How did the idea come up initially and how did you plan on combining this with an RNA-based signature? Because I have seen manuscripts and other data where people are either using one or the other, but not necessarily both together. So how did you guys come up with that idea? Dr. Philippe Bedard: Well, we thought that this was a great opportunity to look at the combination of the transcriptome as well as the ctDNA dynamics because we had run an investigator-initiated phase 2 clinical trial called INSPIRE at our institution at Princess Margaret from 2016 to 2018, where patients across five different tumor groups received single agent pembrolizumab. And we really did a deep dive on these patients where there were tumor biopsies before and while on treatment. We did exome sequencing, we did RNA sequencing to capture the transcriptome. And in a prior analysis, we had partnered with Natera to look at their Signatera assay, which is a bespoke ctDNA assay, to look at ctDNA dynamics using this test and the association with response outcomes as well as survival outcomes. So we thought that this was a really unique data set to try and address the question of whether or not there was complementarity in terms of looking at the transcriptome and transcriptome signatures of IO benefit together with the ctDNA dynamics. Dr. Rafeh Naqash: From a patient treatment standpoint, it sounded like you mostly tried to include individuals who were treated with pembrolizumab. Did this not include individuals who were treated with chemoimmunotherapy or chemotherapy with pembrolizumab? Just pembrolizumab alone? And if that's the case, some of the tumor types there included, from what I remember, ovarian cancer and some other unusual cancers that don't necessarily have approvals for single agent pembrolizumab, but perhaps in the TMB-high setting. So can you elaborate on the patient selection there for the study?  Dr. Philippe Bedard: Yeah, that's a great question. So at the time that the study was designed in 2015, this was really the early days of immune checkpoint inhibitor therapy, so we didn't have the approvals that we have now in specific tumor types for immunotherapy and chemotherapy combinations. So when the study was designed as an investigator initiated clinical trial, the idea was really to capture patients across different tumor types - so head and neck squamous cell carcinoma, malignant melanoma, ovarian cancer, triple negative breast cancer, and a kind of mixed histology solid tumor cohort, where we knew that there were some patients who were going to be immunotherapy responsive, where there was already approvals or evidence of single agent activity, and others where the responses were more anecdotal, to try and understand in a phase 2 clinical trial with kind of a deep dive, which patients benefited from treatment and which didn't. Dr. Rafeh Naqash: Interesting approach. Going to the results, Alberto, could you help us understand some of the important findings from these data? Because there's different sections of how you tried to look at the response rates, the survival, looking at the immune deconvolution, if you could explain that. Dr. Alberto Hernando-Calvo: So the first thing that we tried was to further confirm the external validation of this immune gene expression signature, VIGex in the INSPIRE asset. So what we observed at VIGex-Hot, the category defined by VIGex-Hot tumor microenvironment, was associated with better progression free survival. After including that in a multivariable analysis adjusted by other biomarkers such as TMB, PDL-1 or tumor type, this was also confirmed for overall survival. So then the next step was to really try to hypothesize if the addition of ctDNA dynamics, taking into consideration the ctDNA quantification at baseline as compared to cycle three, if those dynamics could further improve the predictive performance of VIGex categories taken in the baseline samples. What we did observe was that, for instance, VIGex-Hot tumors in baseline tumor samples that were having a ctDNA decrease, as I mentioned before on cycle three assessment as compared to baseline, were having both better progression free survival and better prognosis overall. Another important finding was the evaluation of response rate across tumor types considering both biomarkers. I would say the most important finding is that when we were considering a cold tumor microenvironment in baseline samples before pembrolizumab initiation plus an increase in ctDNA values, what we observed is that those patients were having a 0% response rate. So this may help as a future strategy either for intensification of immunotherapy regimens in a more individualized way or for an early stop to immunotherapy and try to avoid financial toxicities as well as toxicities for our patients. Dr. Rafeh Naqash: From the data that you showed, it seems that there was a strong correlation, as you sort of mentioned, between individuals that had ctDNA clearance and baseline immune pro-inflammatory signatures. So do you really need the transcriptome signature or could the ctDNA just serve as an easy quick surrogate? Because from a cost standpoint, doing whole transcriptome sequencing or more RNA sequencing or tissue standpoint, where tissue is often limited, can become a big issue. So do you think that validation of this may perhaps more revolve around using ctDNA as an easier metric or surrogate? Or am I overestimating the utility of ctDNA? Dr. Philippe Bedard: I think it's a really good question. In our data set which was relatively small, there were 10 patients who had ctDNA clearance, meaning ctDNA that was positive at baseline was not detected. And so 9 out of those 10 patients, as you alluded to, were VIGex-Hot. So the question is a good one, could you do the same with just ctDNA clearance alone, particularly in identifying these patients who really do well, who have long term disease control on immunotherapy? I think it's a tough question to answer because the field is also changing in terms of sensitivity of detection of ctDNA tests. So we know now that there are newer generations of tests which can detect even at logs down in terms of allele variants in the circulation. So I think we need more data to address the question. I think it is important as to what is the best test, what is the endpoint that we should be using from a drug development point of view in terms of really trying to push and understand which treatment regimens are the most effective and have early readouts in terms of activity. Because we all recognize in the clinic that radiographic response doesn't tell the whole story, especially early radiographic assessments using RECIST or other criteria that we apply in clinical trials. Dr. Rafeh Naqash: From a clinical trial standpoint, we often talk about validation of these studies. You may have heard of other tests where, for example, the NCI iMatch, which is incorporating transcriptome sequencing based approach to stratify patients as an integral biomarker for treatment stratification. Is that something that you guys are thinking of using, this approach where individuals who are signature highly inflamed perhaps get lesser therapies or there's a de-intensification of some sort similar to what people are trying to do with ctDNA-based approaches? Dr. Philippe Bedard: I think that's a great question. I think it makes a lot of sense. And certainly, with the new wave antibody drug conjugates in terms of identifying patients who have expression of targets for antibody drug conjugates, that's very attractive as an approach because we don't necessarily have IHC markers for all of the different targets of antibody drug conjugates. We don't necessarily have IHC markers to completely understand different contributions to the tumor microenvironment and whether or not tumors are inflamed. But it's also a challenging approach too because RNA-seq currently is not a routine clinical test. Sometimes there are issues, particularly in patients who have stored specimens that are formalin-fixed and paraffin-embedded in terms of the quality of the RNA for RNA sequencing. And it's not always feasible to get pre-treatment biopsies and turn them around in an approach. So I think it is an attractive approach for clinical trials, but it's a hypothesis that needs to be tested. It's not something that is ready for clinical prime time today in 2024. Dr. Rafeh Naqash: One of the other interesting observations that I came across in your manuscript was that tumor mutational burden, interestingly, did not correlate with signature high tumors. What is the explanation for that? Because generally you would expect a TMB high to perhaps also have an immune gene high signature. Could it have something to do with the tumor types because there was a heterogeneous mixture of tumor type? Or I'm not sure. What else could you possibly think of that you didn't see those correlations or just sample size limitations? Dr. Alberto Hernando-Calvo: Yes. So our findings are consistent with prior data suggesting for instance T cell inflamed gene expression profile was also not correlated with tumor mutational burden and both biomarkers in a prior publication. So to have additive predictive performance for identifying patients most likely to benefit from anti PD-1 regimen, so we somehow were expecting this observation, the fact that both biomarkers are not very correlated. Dr. Rafeh Naqash: So given the proof of concept findings from your study, Phil, what is the next interesting step that you guys are thinking of to expand this? Would you think that a nivolumab-ipilimumab treated cohort would have similar findings? Or is this a treatment specific single agent immunotherapy specific correlation that you found versus something else that you may find in a nivo-ipi cohort or a doublet immune checkpoint cohort?  Dr. Philippe Bedard: The findings are really hypothesis generating. They require additional validation. And you're quite right, there may be nuances in terms of specific tumor types, combinations with other immunotherapy or combinations with chemotherapy or other agents. So I think it would be great if there are other data sets that are collecting this type of information that have ctDNA dynamics and also have transcriptome and potentially exome or genome analysis to look at these types of questions because the field is moving quickly and we really need more data sets in order to understand some of the nuances and greater numbers to validate the signals that we see. Dr. Rafeh Naqash: And one thing, as you said, the field is definitely moving very quickly. I was meeting with a company an hour back and they have an imaging-based approach using fresh tissue to look at pharmacodynamic biomarkers. And I used to work in the NCI with a group that was very interested and they developed an immuno-oncology pharmacodynamic panel that has been used and published in a few clinical trials where they did phosphorylation status. So the final theme that comes out of most of these research based studies that are being done is that one size does not fit all. But the question that comes to my mind is how many things do you necessarily need to combine to get to a predictive biomarker that is useful, that is patient centric, and that perhaps is able to identify the right therapy for the right patient. What is your take on that, Phil?  Dr. Philippe Bedard: Yeah, that's a great question too. The challenge is it depends on the context in terms of what degree of positive predictive value do you need as well as the negative predictive value to drive clinical decisions. So I think in certain situations where you don't have other approved treatment options and with a therapy that is potentially low toxicity and low financial toxicity, then I think the bar is very high in terms of being able to really confidently identify that patients aren't going to benefit. I think the nuance and the challenge becomes when you move into earlier lines of therapy, or when you talk about combinations of agents, or trying to understand within the context of other available options, particularly with treatments that have significant side effect profiles as well as financial risks, then it becomes a much more nuanced question and you really need comparative studies to understand how it fits versus the existing treatment paradigm. So I'm not really answering your question with a specific number because I think it's hard to give you a number. Some of that we also need input from patients in terms of what kind of level of validation do you need and what kind of level of discrimination do you need in order to drive decisions that are meaningful for them. Dr. Rafeh Naqash: Definitely early days, as you pointed out. More and more work in this field will hopefully lead us in the direction that we all want to go in.  Now, going to a different aspect of this podcast, which is trying to understand the trajectories for both of you, Phil and Alberto. And as you mentioned, this project seemed to have started in 2015. So I'm guessing there's a history there between Princess Margaret and Vall d'Hebron. Could you highlight that a little bit? And then perhaps, Alberto, after that you could tell us a little bit about your career when you worked at Princess Margaret as a fellow and then now back at Vall d'Hebron. Phil, you as well. Dr. Philippe Bedard: So absolutely. We have a long history of collaborating with Vall d'Hebron in Barcelona. It's really a great cancer institution with a lot of like minded individuals. We have a formal partnership and we have a lot of informal links in terms of scientists and clinicians who we work with and who we collaborate with on early phase clinical trials, as well as through different investigator networks and other translational projects. So this was really how this collaboration came about and we were fortunate to have Alberto, who came to work with us for two years and brought this great idea of looking at this signature they had developed at Vall d'Hebron in their phase one group and applying it to a data set that we had through the INSPIRE clinical trial.  Dr. Rafeh Naqash: Sounds like a very successful academia-academic collaboration, which is very nice to see. So, Alberto, could you tell us a little bit about your career trajectory and how you ended up at Princess Margaret and then back at Vall d'Hebron and what you do currently? Dr. Alberto Hernando-Calvo: Yes. So I did my oncology residency at Vall d'Hebron in Barcelona, Spain. Then I decided to further specialize in early drug development as well as head and neck cancer oncology. So I decided to pursue a clinical research fellowship under the supervision of Phil Bedard, among others. And so we decided to further validate the signature that we had developed both in the cancer genomic lab at Vall d'Hebron Institute of Oncology and the phase one unit at Vall d'Hebron, and apply the signature that have been originally tested in patients receiving anti PD-1 or anti PDL-1 combinations in early phase clinical trials. In the phase 2 clinical trial of INSPIRE, where we also had ctDNA dynamics and allowed us to test both biomarkers and see that additive predictive power when we were using both. That was one of my research topics under the mentorship of Dr. Bedard and my fellowship at Princess Margaret. And this was one of the manuscripts describing all the findings of this collaboration between Vall d'Hebron and Princess Margaret Cancer Center. Dr. Rafeh Naqash: And then, Phil, if you could highlight some of the things that you've done over the course of your career and perhaps some advice for early career junior investigators and trainees.  Dr. Philippe Bedard: I finished my oncology, medical oncology training at the University of Toronto in 2008. And then I did a breast cancer fellowship in Brussels at Breast International Group. At the time, I was really intrigued because it was really kind of the early days of microarray and RNA signatures in terms of expressing signatures were being used as part of a clinical trial that BIG was running called the MINDACT Study. And so when I finished my fellowship, I came back to Princess Margaret, started on staff. I've been here now for 15 years. I was fortunate to work with the phase 1 group and kind of my career has sort of morphed in terms of early drug development as well as genomics. I've been involved with the American Association for Cancer Research project GENIE, where I'm the current chair. This is really an international data sharing project with panel based sequencing, which both Princess Margaret and Vall d'Hebron have contributed to. And I've been fortunate to work with a number of really talented early career investigators like Alberto, who spend time with us in our drug development program and launched transitional research projects that leverage some existing data sets at their own institutions and also bring together with different research groups at our institution to lead to publications like this one. Dr. Rafeh Naqash: Thank you so much. This was very exciting. Phil and Albert, thanks for joining us today and thank you for allowing us to discuss your interesting manuscript and hopefully we'll see more of this biomarker work from you guys in the near future, perhaps published in JCO Precision Oncology.   And thank you for listening to JCO Precision Oncology Conversations. Don't forget to give us a rating or review and be sure to subscribe so you never miss an episode. You can find all ASCO shows at asco.org/podcasts.     The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions.  Guests on this podcast express their own opinions, experience and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement.

Method for FFPE Organ-Chip -Lindsay Parmelee HTL(ASCP) 1,2,3, Stephanie Pei Tung Yiu PhD 1,2,3,4, Chi Ngai Chan PhD 1,2,3, Sizun Jiang PhD 1,2,31 Center for Virology and Vaccine Research 2 Beth Israel Deaconess Medical Center 3 Harvard Medical School 4 Wyss Institute Organoids are currently being developed for applications in biomedicine such as drug development and disease research. With many organoid models emerging on the market there is growing need to develop methods to adapt organoids to the established work flows and assays that are the foundations of modern research.  A method was developed for processing, embedding, and sectioning Organ-Chips for FFPE workflows. Organ-Chips were treated with Histogel and trimmed to fit standard sized cassettes. Followed by processing and embedding as usual before proceeding to the microtome. The resulting slides have successfully been stained with hematoxylin and eosin and immunohistochemistry, as well as shown promising results for use on multiplexing platforms. Although the process is laborious and requires continued refinement the slides should be sufficient for highplex proteomics and transcriptomics methods and can be used in addition to FFPE tissues for research into immunology, oncology, and virology.

Research Requires Flexibility: Protease-Free Permeabilization Expands FISH Tissue Applications.-Andrelie Branicky, Shared Laboratory Resources, Lerner Research Institute, Cleveland Clinic, Cleveland, OH Fluorescence in situ hybridization (FISH) visualizes the presence of a specific DNA or RNA sequence in a tissue sample or cell. This method, particularly the mRNA version, detects gene expression when protein might not be present or IHC is impossible. FISH combined with immunohistochemistry enables spatial transcriptomics, which provides significantly more information about the tissue microenvironment. Formalin-fixed paraffin-embedded (FFPE) tissues are the standard for tissue preservation in the clinical world. Most commercial mRNA probe and amplification systems are built around the model of FFPE tissue that can withstand harsh protease permeabilization. In the research world, tissues are fixed in different fixatives for varying times; all at the discretion of the investigator instead of an organization like the CLIA.  Given the wide range of tissue preparations, the HCR automated FISH-ISH protease-free program provides the flexibility to combine  FISH and fluorescent immunohistochemistry on tissue fixed in a variety of ways such as: 10% NBF, Histochoice (a glyoxal-based fixative), and methanol/acetic acid, with only minor changes to the basic protocol. Additionally, the lack of harsh protease pre-treatment maintains tissue integrity and morphology for staining and imaging. 

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

Designing a successful PCR assay is all about selecting the right primers to deliver the sensitivity and selectivity for which PCR is known for. But anyone that's designed an assay themselves will know that doing so successfully is a lot harder it sounds. We're joined by two PCR assay design pros for this episode. Kimi Soohoo Ong, and Dr. Rounak Feigelman, both from Thermo Fisher Scientific, shine a light on the many factors that must be considered to design a winning PCR assay. From the level of fragmentation of nucleic acids in the sample, to what other species' genomes that may be present in the sample, to what the sample matrix may contain, to the PCR master mix being used, if multiplexing is required, to what assay controls will be, and more!  These two practiced bioinformaticians cover these challenges and then tell us how their team overcomes challenges to develop winning assays for both qPCR and dPCR applications. Our conversation uncovers the level of skill and artistry that goes into this craft. As always, you get to learn a bit more about our guests' backgrounds and career paths in the Cassie's Career Corner portion of the interview. They share how they both chose a bioinformatics path over wet lab work, while also acknowledging how important the wet lab work is to what they do. They also share some great advice and resources for anyone looking to explore a career in bioinformatics. Visit the Absolute Gene-ius page to learn more about the guests, the hosts, and the Applied Biosystems QuantStudio Absolute Q Digital PCR System. 

JCO PO author Dr. Brandon Huffman shares insights into his JCO PO article, “Analysis of Circulating Tumor DNA to Predict Risk of Recurrence in Patients With Esophageal and Gastric Cancers” and discusses the article's findings of ctDNA levels in the preoperative, postoperative, and surveillance settings in patients with EGC. Host Dr. Rafeh Naqash and Dr. Huffman discuss ctDNA assessments, treatment paradigms and interventions, and tumor-informed assays. 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, social media editor for JCO Precision Oncology, and I'm also an Assistant Professor in Medical Oncology at the OU Stephenson Cancer Center. Today, I am excited to be joined by Dr. Brandon Huffman. Dr. Huffman is a gastrointestinal medical oncologist, and he's also an instructor in medicine at the Dana-Farber Cancer Institute at the Harvard Medical School. He's the lead author on today's JCO Precision article, "Analysis of Circulating Tumor DNA to Predict Risk of Recurrence in Patients with Esophageal and Gastric Cancers."   Our guest's disclosures will be linked in the transcript.   Dr. Huffman, welcome to our podcast and thanks for joining us today. Dr. Brandon Huffman: Of course. Thanks for having me. Dr. Abdul Rafeh Naqash: For the sake of this discussion, we'll refer to each other using our first names. So, Brandon, exciting to have you today. We're going to talk about this very interesting topic on circulating tumor DNA and how your team used the ctDNA assessment in patients with esophageal and gastric cancers. For the sake of the listeners, could we start by asking you what are the current treatment paradigms for early-stage esophagogastric cancers? Since you practice this on a daily basis, what is the current approach, briefly, which will play into how this study looked at ctDNA in the context of early-stage esophagogastric cancers? Dr. Brandon Huffman: Yes, definitely. Thanks first for having me. Thanks for highlighting our work, and I'm really excited to talk with you about our manuscript and research today. To answer your question about how to treat localized esophagogastric cancer, it's a little bit more specific depending on where in the esophagus, GE junction or stomach where the tumors arise. For instance, we treat esophageal and upper gastroesophageal junction cancers with, often, chemoradiation, neoadjuvantly, and that is followed by surgery. And if there's a pathologic incomplete response, then many patients will get Adjuvant Nivolumab, a PD-one inhibitor, whereas the lower the tumor is in the upper GI tract, most often, perioperative chemotherapy is used for the lower GEJ and gastric cancers. Dr. Abdul Rafeh Naqash: Thank you so much. And I know, I think to some extent, if I remember correctly, immunotherapy has been incorporated into this paradigm. Is that a fair assessment? Dr. Brandon Huffman: That's exactly right. So, excitingly, we treat patients with neoadjuvant chemo or chemoradiation, and surgery is really the crux of the treatment paradigm for esophagogastric cancers in general. However, recently the CheckMate 577 clinical trial for the use of adjuvant Navolumab showed an improvement in disease-free survival in patients who had an incomplete path response. They used one year of Nivolumab compared to placebo. So it has recently become a standard of care where I practice, and I feel like a common practice around the country. Dr. Abdul Rafeh Naqash: Thank you so much. Now, going to the premise of this paper where you and your team basically looked at circulating tumor DNA as a prognostic marker in these patients that had early-stage esophagogastric cancers, was there a specific reason why you wanted to look at the early stage? What was the rationale for evaluating this biomarker in this patient population? Dr. Brandon Huffman: So, esophageal and gastric cancers affect a large number of patients every year. And unfortunately, despite our best efforts with curative intent therapy, over 50% recur within three years. So we know that there are pre surgical risk factors such as a larger bulky primary tumor or lymph node-positive disease that increase the risk for progression or recurrence after surgery. And we know, in addition, in other GI malignancies and other malignancies such as colorectal cancer, for instance, that the presence of circulating tumor DNA after surgical resection of localized tumors is associated with an increased risk of recurrence. So this has actually led to clinical trials investigating whether or not ctDNA can be integrated into the decision-making for adjuvant colorectal cancer treatment, such as ongoing trials such as the BESPOKE trial, COBRA, DYNAMIC trials that have recently been reported. The use of ctDNA is being used in other malignancies. And to give you a little bit of background, this project started when I was seeing patients with Dr. Sam Klempner at Mass General during my fellowship, where I was in the combined Dana-Farber/Mass General program. And he and others had begun collecting serial plasma samples on every patient we saw with esophagus, gastroesophageal junction and gastric cancers to assess for the presence or absence of ctDNA. And we used the tumor-informed ctDNA assay from Signatera, which, for those who aren't familiar, this is a ctDNA platform where a panel is built from the results of whole exome sequencing on the patient's FFPE tumor. The panel includes 16 patient-specific somatic single nucleotide variants for each patient, and it's new for each patient. Once that panel is built, the cell free DNA is tested from a plasma sample. And if there are two or more of the tumor-specific variants present, then they're considered ctDNA positive. So some of those colorectal cancer trials that I mentioned before are using this assay, and we wanted to investigate whether or not this high-risk population could be further assessed for risk of recurrence. Dr. Abdul Rafeh Naqash: Excellent. Thank you so much. And I know that a lot of these ctDNA based assessments have made inroads into the GI malignancy space, lesser in the other tumor types. I think we are all trying to catch up to what you guys are doing in the early-stage colon cancer space or the early-stage esophagogastric cancer space. So it's definitely very a interesting avenue to assess minimal residual or molecular residual disease. Now, going back to the methodology, I found it very interesting, and I think it's very important for listeners especially to understand the context of ctDNA assessments because I think a majority of oncologists are used to the liquid biopsy aspect. But this is not necessarily the liquid biopsy. It's somewhat different. So what I've understood, and I'd like to ask you to explain in the context of tumor-informed and tumor uninformed assays, what are the assays that are available, and how do they differ in terms of serial monitoring? And why is this ctDNA-based assessment somewhat different or more patient-customizable than our regular liquid biopsy assays, which are also blood based but not tumor-informed? Dr. Brandon Huffman: That is the question of the hour. And many different research projects are ongoing to try and identify which one is better, if one is better. I know that there are some commercial assays, for instance, that are not tumor-informed. They take a blood sample and then test for cell free DNA. The risk behind that is it's testing for common genetic mutations from a next-generation sequencing panel platform. And it may also detect CHIP variants or clonal hematopoiesis of indeterminate potential variants that aren't related to the underlying solid tumor malignancy. So a tumor-informed assay, for instance, such as the one that we used in this study, uses the patient's tumor and sequences it with whole exome sequencing and identifies very specific variants within the tumor that are only present within the tumor because they compare it also with a normal blood sample from the patient at the same time. And so they pick tumor-informed specific variants that then they test for on their assay. And that increases the sensitivity of the ctDNA assay so that you can really try to understand, is this cell free DNA that we are detecting related to the tumor or can we ignore it potentially? I don't know if we can necessarily ignore it in all honesty because it could affect- there's a lot of ongoing work that is looking at the risk of CHIP. But overall, this is specific for the primary tumor that we were investigating. Dr. Abdul Rafeh Naqash: I definitely agree with you there. I think the important point, as you mentioned, is that using the whole exome approach, in the blood and the tumor, you're able to eliminate the CHIP variants or the germline variants that may not be contributing. And that way you're able to specifically look at certain genetic alterations that eventually, I think using PCR-based approaches, you identify the same and quantify the same in the blood serially. And that's how this tumor-informed assay is somewhat unique and different. Now, going to the crux of this study, could you tell us a little about the patient population? I think you stratified patients. You had a pre-operative cohort, you had an MRD cohort, you had a surveillance cohort, and you had a cohort where you assessed ctDNA positivity at any time point. So, several different cohorts, and you assess recurrence-free survival in those cohorts. Could you tell us a little bit more about how you evaluated these cohorts? What were the selection criteria, and how many patient samples did you have for these different cohorts? Dr. Brandon Huffman: Absolutely. So, we aimed to determine the feasibility of testing ctDNA in patients with gastroesophageal cancer. And so, there were several clinicians from over 70 institutions across the United States who began prospectively collecting serial plasma samples for the presence or absence of the tumor-informed ctDNA. And they included patients from stages one through stage four, gastroesophageal cancer specifically, they included patients who were stages one through four with gastroesophageal cancer. They were collected at the discretion of the ordering clinicians and then incorporated into their routine clinical care as they saw fit. Within this dataset, we have a subset, a large number of patients that is unique to this dataset, specifically in that we have clinical outcomes, treatment, and follow-up data for the patients that were reported on the main findings in the paper. So, overall, we collected and analyzed over 900 plasma samples in almost 300 patients with gastroesophageal cancer, esophageal, gastroesophageal junction and gastric cancers. And in many of the analyses, we lumped them all together. But then we also wanted to separate it out because, as I mentioned before, the treatment paradigm does differ amongst a more proximal esophageal tumor compared to a distal gastric cancer. So, we focused a majority of our analyses on the detection of ctDNA and localized disease, which included 212 patients with stages one through three gastroesophageal cancer. And I would say we had three major findings. Most of the patients who were tested beforehand, which was a small subset, as I mentioned, this was pragmatic at the discretion of the ordering clinician, but most of the patients who were tested beforehand had positive preoperative ctDNA present. Of the patients who were tested for postoperative ctDNA at any time point, and then specifically within the different subsets of populations that we talked about, postoperative ctDNA was associated with at least a tenfold increased risk of recurrence in all subsets. And ctDNA detection postoperatively was independently associated with recurrence when controlling for age, sex, tumor location, and microsatellite status. So, a few of the populations that we wanted to test for, one in particular was the molecular residual disease, or MRD window. We labeled this MRD window as the time from surgical resection until 16 weeks. So, if patients were ctDNA positive within that window, we counted that in the primary outcome. And the reason that we chose the MRD window, in addition to this time point of 16 weeks - I should say that the 16 weeks is without any therapy postoperatively, so they have not been treated with any chemo or immunotherapy in this window. We thought that this MRD window was an interesting research topic because the CheckMate 577 Adjuvant Nivolumab clinical trial identified that 16 weeks was the window in which patients could be enrolled up until that timepoint to receive adjuvant nivolumab. So, we're thinking from a future project standpoint, a future clinical trial, perhaps, that if we have identified that patients who are ctDNA positive within this timepoint window, is there an increased risk for recurrence? Because if there is, then perhaps nivolumab intervention will decrease that risk or something that is escalated further. And that's a question that we don't have the answer for, a question that our data can't answer adequately. But it's an interesting one that I see the future questions that can be answered from these data. Dr. Abdul Rafeh Naqash: Thank you so much. And I agree with you there that this is a very intriguing approach of finding out whether treatment escalation has to be done based on ctDNA positivity, but also, conversely, treatment de-escalation, which there is a lot of emphasis being laid on, especially in the early phase trial in lung cancer, especially in the early setting when targeted therapies or immunotherapies are approved for one to three years, depending on what kind of therapy you're looking at. In those individuals that perhaps have negative ctDNA after one year, maybe therapy de-escalation would be a reasonable approach. So, definitely more interesting clinical trial ideas in this space focusing on ctDNA assessments. Now, one of the questions that comes to my mind is, when you use ctDNA-based assessments, initially, the patient gets biopsied, and it usually takes four to six weeks for ctDNA-based assessments to come back--I'm talking about tumor-informed assay results to come back, in my personal experience. So, could that potentially, or in your practice, how do you mitigate those delays? If you're trying to schedule a patient for surgery, for example, does that cause any delays in any care because you're trying to get the assessment done, or does your workflow proceed as planned and then you get the results and then subsequently you perhaps make a decision based on their ctDNA assessment? Dr. Brandon Huffman: At the present time, we are trying to gather more data to understand what we should do with the results that we're receiving. And I think the starting point of collecting serially to just understand the process is helpful. One of the questions we wanted to know that we weren't able to answer with this dataset was: is there lead time? In many cases, ctDNA detection can occur even a year prior to radiographic recurrence. In our case, because this was a pragmatic, clinically at the discretion of the investigators when they decided to test patients for ctDNA, there is heterogeneity among those who are ctDNA positive, and when they get their radiographic imaging, maybe they were moved up. I know in our practice with Dr. Klempner, when I was seeing these patients with him, it was a flag for us to order scans earlier in a patient that we might not have historically ordered so that we could then see, is there something intervenable? Maybe there was a positive lymph node on PET imaging that we could radiate or that wasn't included in the neoadjuvant radiation, for instance. So, we could not predict the lead time from positivity to radiographic recurrence, but I think that that's the hope is that we detected micrometastatic disease, my hope is that we can intervene in the future. But these data aren't able to quite answer that question perfectly. Dr. Abdul Rafeh Naqash: Sure. And there's definitely caveats to doing this in a pragmatic manner based on investigator assessments. Now, another question I was thinking of is, when you do do these ctDNA based assessments, and since these are tumor-informed, meaning you biopsy the tumor initially, you identify certain single nucleotide variants and those are the ones that you basically barcode and do PCR assessments using blood. We've learned time and again that tumors can change based on the kind of therapy that you give the patient. So, if your tumor is seeing FOLFOX nivolumab, or all the other novel therapies that you guys give in the setting, is there a chance that the tumor changes over time and you may not be able to capture those newer single-nucleotide variants that are coming up? It's just a provocative question, but I wanted to see what your thoughts are on that. Dr. Brandon Huffman: It's a great question. I don't entirely know the answer. I'll just be forthright about that. I do think that when designing these assays, they try to choose the more clonal rather than subclonal variants. And so the hope is that, despite the heterogeneity that we know occurs in esophagogastric cancers, we can eliminate that possibility. But you're right, there's no perfect way of knowing that. Dr. Abdul Rafeh Naqash: I really appreciate you using that word subclonal versus clonal. I think that perhaps makes a difference there. But again, more to do in this field to understand how the tumor evolves and whether it's the clonal mutation, subclonal mutation that needs to be followed. But definitely a lot of interesting work in this space that's ongoing, and, like you mentioned, there are ongoing trials, and both in the neoadjuvant adjuvant space, this field is definitely moving fast in the right direction. I briefly want you to highlight that one patient case study example that you had. And this was a patient with oligometastatic disease recurrence where you used the ctDNA assessment. And I do some of this in my daily practice, and I really found it useful to have this sort of a patient case example that elaborates in the bigger picture of how this kind of assessment works in a real-life scenario. So it's not just data, it's a patient's trajectory over the course of time where the treating physician was able to use this assay. Could you tell us a little bit more about this individual example here? Dr. Brandon Huffman: Yeah, absolutely. So this was a 56-year-old man that we saw in clinic with stage three esophageal adenocarcinoma, and was treated with the standard neoadjuvant cross chemoradiation, had an R0 resection with residual disease with a significant treatment effect. And there were lymph nodes that were positive on surgical resection with 39 lymph nodes removed. The patient recovered well and was followed with the standard of care radiographic and clinical surveillance. We also were looking for ctDNA, and what we noted was that there were, often you find these undulating pulmonary nodules that come and go, and they may or may not be infectious, and maybe there's one that's sub-centimeter that slowly grows, and what we found was that at about five months post-surgery, there was a positive ctDNA MRD, and we repeated it at short interval and noted a rising value, which this assay will give you a quantitative value. Once we did that, we ordered imaging and saw a nine-millimeter pulmonary nodule and ultimately biopsied it. It was there in the right upper lobe, and it was positive for metastatic adenocarcinoma. So we treated the patient with the standard FOLFOX plus Nivolumab and actually did SBRT, stereotactic body radiotherapy, to the lung metastasis. And his ctDNA became undetectable. So because FOLFOX is toxic, we transitioned to a maintenance of Nivolumab and he was on maintenance therapy for several months and had no radiographic evidence of disease and remained ctDNA negative for twelve months. So we biopsied the right upper lobe lung lesion. It was positive for metastatic adenocarcinoma, and then after a multidisciplinary discussion, we treated him with SBRT and then FOLFOX and Nivolumab and then dropped down to Nivolumab maintenance once his ctDNA was undetectable. That highlights the fact that this was an isolated recurrence, which we continued to monitor, and then he had another site of disease a few months later, and we did SBRT to that area while he maintained on just Nivolumab, and the ctDNA came down as well.   So I think, although it doesn't prove anything necessarily, other than demonstrating there is a correlation with the newly diagnosed metastatic disease, it does note that you can use this in dynamic ways, and if it really helps patients live longer, although this is anecdotal--who knows? If we hadn't done SBRT to that area, it was 9 mm. We could have waited until it grew, but then maybe some subclonal, more aggressive metastasis could have really put this patient in a much tougher situation. So it's an interesting case example, and there are several others that we could have put in here that are pretty similar. Dr. Abdul Rafeh Naqash: Thank you so much for highlighting that case. I couldn't agree more that there is a certain aspect to the ctDNA assessment, where in individuals like the example that you've highlighted here, this can provide lead time potentially and help with earlier management of perhaps more like oligometastatic disease rather than diffuse disease burden. And in that context, one of the questions that I was going to ask you, based on your data, was there any correlation of tumor burden preoperatively and ctDNA positivity after surgery that you guys were able to identify or thinking of identifying? Dr. Brandon Huffman: Unfortunately, with our data set, we weren't able to look at that assessment of comparing the overall tumor burden to the quantitative value. But it's an interesting one because we know that in other malignancies, for instance, if there is a correlation of overall disease burden, it also depends on the tumor type, but we also know that perhaps patients will respond differently to chemo or immunotherapy if they have a lower tumor burden, if they have a lower ctDNA value, potentially. I think that's an interesting question for a future project. Dr. Abdul Rafeh Naqash: Thank you so much, Brandon. We do like to talk a little bit about the person behind the work. So tell us a little bit more about yourself, your training, your interests, and some little advice for other early-career investigators who might be looking into a similar space and hopefully get inspired by the kind of work that you've done or are planning to do. Dr. Brandon Huffman: Sure. So, as I mentioned, when I started this project, I was in fellowship. I was seeing patients with Dr. Sam Klempner at Mass General, where I saw patients with him for a year, and as part of my clinical training in the Dana-Farber/Mass General HemOnc Fellowship. Since that time, I have graduated fellowship. I'm a GI Medical Oncologist at Dana-Farber Cancer Institute, and in the GI division, I see patients with all GI malignancies, and I focus on the development of clinical trials in upper GI malignancies, along with investigating the use of circulating tumor DNA as a biomarker, hopefully, we can understand whether it's a predictive biomarker that we can intervene upon in the future. I think the greatest advice that I received and that I will give to all future trainees; I'm not sure that I'm qualified to tell this to all the junior investigators, but here it is: Find yourself a mentor who really cares and invests in you and your ideas. I have that with Sam, and this project was an incredible part of my development as a junior investigator. I've asked really interesting questions. There are more questions that can be answered from this data set, and I'm excited for the opportunity. Dr. Abdul Rafeh Naqash: Thank you so much, Brandon. Thanks for taking the time to speak with us today and thank you for choosing JCO Precision Oncology as a destination for your work. Hopefully, we'll see more of this subsequently in the years to come. Thank you for listening to JCO Precision Oncology Conversations. Don't forget to give us a rating, a review, and be sure to subscribe so you never miss an episode. You can find all ASCO shows at asco.org/podcasts  The purpose of this podcast is to educate and to inform. This is not a substitute for professional medical care and is not intended for use in the diagnosis or treatment of individual conditions. Guests on this podcast express their own opinions, experience, and conclusions. Guest statements on the podcast do not express the opinions of ASCO. The mention of any product, service, organization, activity, or therapy should not be construed as an ASCO endorsement. Guest Bio Dr. Brandon Huffman, MD, is a gastrointestinal medical oncologist and Instructor in Medicine at Dana-Farber Cancer Institute and Harvard Medical School.  Guest Disclosures Brandon M. Huffman Stock and Other Ownership Interests: Doximity

Do we own our own body parts? What can we do with them? Can we sell them and control what others do with them? People often say, "it's my body", but the law is much more complex. This lecture explains the law on body part ownership, tracing it from the early legal cases through the body-snatching years of the Victorian period, to the present day. Should we use the law of property to regulate human tissue?A lecture by Imogen GooldThe transcript and downloadable versions of the lecture are available from the Gresham College website:https://www.gresham.ac.uk/lectures-and-events/body-lawGresham College has been giving free public lectures since 1597. This tradition continues today with all of our five or so public lectures a week being made available for free download from our website. There are currently over 2,000 lectures free to access or download from the website.Website: http://www.gresham.ac.ukTwitter: http://twitter.com/GreshamCollegeFacebook: https://www.facebook.com/greshamcollegeInstagram: http://www.instagram.com/greshamcollege

DNA Today's host Kira Dineen is also the host of the PhenoTips Speaker Series. This monthly live webinar focuses on relevant genetics topics by featuring discussions with thought leaders and experts in genomic medicine. In this podcast episode we are sharing an installment of the PhenoTips Speaker Series, “The Future of Cancer Genetics”.Thanks to advancements in genome sequencing, physicians are equipped with improved knowledge on the causes of cancer, as well as alternative treatment options for specific cancers. Despite this growing wealth of cancer genomics data, experts remain unclear on how to translate cancer genetics knowledge into realizing precision medicine. To prepare practitioners for the future of cancer genetics, PhenoTips invited Dr. Banu Arun and Dr. Mark Robson to share their insights.Dr. Arun is a Professor in the Department of Breast Medical Oncology, Co-Medical Director of the Clinical Cancer Genetic Program, and Section Chief of Breast Genetics, Prevention, and Screening at the University of Texas MD Anderson Cancer Center. Hailed by Forbes as one of the top 30 Breast Medical Oncologists in the United States, she has received the FASCO award recognition in 2020 from the American Society of Clinical Oncology (ASCO) and the ASCO-American Cancer Society 2021 Award. Dr. Arun has more than 200 peer-reviewed publications with research focusing on identifying risk biomarkers for breast cancer, and characterizing risk factors in high-risk women with hereditary gene mutations as well as assessing their breast cancer biology. In addition she has reviewed for prestigious journals, such as BMJ, JCO, Cancer, Cancer Prevention and Epidemiology, and served in several committees including her current position as the Co-Chair for the SWOG Prevention and Epidemiology Committee.Dr. Robson is the Chief of the Breast Medicine Service in the Department of Medicine at Memorial Hospital, New York, Attending Physician on Breast Medicine and Clinical Genetic Services, and a Member of the Memorial Sloan Kettering Cancer Center. He is an associate editor for the Journal of the National Cancer Institute and a Fellow of the American Society of Clinical Oncology (ASCO), as well as a past chair of the ASCO Ethics Committee. His clinical research is on the optimal application of germline information to the management of cancer patients. He has been a lead investigator for trials of PARP inhibitors in patients with BRCA mutation–associated breast cancer and is currently developing new models for the acquisition of germline information, including "mainstreaming" through test ordering by primary oncology providers and broad genomic screening in the context of somatic mutational profiling. In addition, he is investigating the use of polygenic risk scores in facilitating decision-making among women with or without an inherited predisposition.In this webinar moderated by Kira Dineen, Dr. Arun and Dr. Robson will illuminate the future of cancer genetics by discussing:The latest technological advancements in cancer genetics.Barriers in the specialty and methods to overcome them.Strategies to prepare practitioners for the future of cancer genetic care.Hope to see you live for the next installment of Phenotips Speaker Series on January 18th about ending the diagnostic odyssey! PhenoTips' Chief Operating Officer and VP of Scientific & Medical Affairs, Dr. Pawel Buczkowicz, will be speaking with Dr. Ana Cohen, Clinical/Research Assistant Director of the Molecular Genetics Laboratory at Children's Mercy's Center for Pediatric Genomic Medicine. Register here for the live event on January 18th at 11am-12pmEST. Stay tuned for the next new episode of DNA Today on January 21st, 2022 with Allelica's Giordano Bottà to discuss polygenic risk scores! New episodes are released on Fridays. In the meantime, you can binge over 165 other episodes on Apple Podcasts, Spotify, streaming on the website, or any other podcast player by searching, “DNA Today”. Episodes since 2021 are also recorded with video which you can watch on our YouTube channel. DNA Today is hosted and produced by Kira Dineen. Our social media lead is Corinne Merlino. Our video lead is Amanda Andreoli. See what else we are up to on Twitter, Instagram, Facebook, YouTube and our website, DNApodcast.com. Questions/inquiries can be sent to info@DNApodcast.com.Do you want to connect with other people who have the same genetic variant as you? You should check out “Connect My Variant”, it's an online resource that allows you to do just that. “Connect My Variant” also provides different avenues of informing your family of possible inherited risk of disease. This includes helping find where your variant came from and finding distant cousins that may also be at risk. The University of Washington has supported the “Connect My Variant” project in an effort to help patients and families understand where their unique genetic variants come from. Check out it at ConnectMyVariant.com. (SPONSORED)Did you know that most cancer samples cannot be subjected to some of the most common cytogenetic analyses due to their storage in formalin and other intractable storage conditions? Don't let difficult sample types and convoluted assay cascades get in the way of your research! Phase Genomics has developed a brand new Next Generation Cytogenomics platform to advance discovery in reproductive genetics and precision oncology. A single assay has the ability to do comprehensive testing for chromosomal abnormalities in fresh, frozen, AND even paraffin-embedded FFPE samples. Learn more about Phase Genomics' incredible new platform in cytogenomics by visiting PhaseGenomics.com. You can also hear our in depth interview with them on episode 169 of DNA Today which will be released on January 28th. (SPONSORED). PerkinElmer Genomics is a global leader in genetic testing focusing on rare diseases, inherited disorders, newborn screening, and hereditary cancer. Testing services support the full continuum of care from preconception and prenatal to neonatal, pediatric, and adult. Testing options include sequencing for targeted genes, multiple genes, the whole exome or genome, and copy number variations. Using a simple saliva or blood sample, PerkinElmer Genomics answers complex genetic questions that can proactively inform patient care and end the diagnostic odyssey for families. Learn more at PerkinElmerGenomics.com. (SPONSORED)Are you a genetic counselor or genetic counseling student? Join me in participating in a research study surrounding education on gender-affirming care in genetic counseling. This study is from the University of Michigan Genetic Counseling Program. It requires a pre and post test survey along with an online 2-3 hour educational tool. I just got access to the modules and am looking forward to learning this week! And here's a bonus: you are entered to win one of 10 $50 gift cards! Complete the survey here . (SPONSORED).

And you thought you could only resolve cellular heterogeneity in fresh frozen tissue. Time to bring out the FFPE blocks!

In this episode of the Epigenetics Podcast, we caught up with Dr. Keji Zhao from the National Heart, Lung, and Blood Institute at the National Institutes of Health in Bethesda, MD, to talk about his work on the genome-wide investigation of epigenetic marks and nucleosome positioning. Dr. Keji Zhao pioneered in the development of cutting-edge techniques in the field of epigenetics. Current methods at that time relied on DNA microarrays, however, Dr. Zhao wanted a more comprehensive and unbiased approach that would avoid the shortfalls of these array-based methods. Hence, he set out to develop new sequencing-based methods like ChIP-Seq and MNase-Seq with accompanying computational methods to analyze the huge amount of sequencing data that would be generated. Using the above-mentioned techniques, Dr. Zhao was able to show that histone deacetylases (HDACs) and histone acetyltransferases (HATs) were found at inactive and active genes, respectively, as previously thought. Surprisingly, he was also able to show that HDACs were also located at active genes. Furthermore, both, HATs and HDACs can be found at low levels at silenced genes. In this episode we discuss the story behind how Dr. Keji Zhao was one of the pioneers of the chromatin immunoprecipitation technology, how he discovered the genomic locations of HATs and HDACs, and in the end he shares some tips and tricks on how to get the best results in ChIP-Seq assays.   References Artem Barski, Suresh Cuddapah, … Keji Zhao (2007) High-resolution profiling of histone methylations in the human genome (Cell) DOI: 10.1016/j.cell.2007.05.009 Dustin E. Schones, Kairong Cui, … Keji Zhao (2008) Dynamic regulation of nucleosome positioning in the human genome (Cell) DOI: 10.1016/j.cell.2008.02.022 Zhibin Wang, Chongzhi Zang, … Keji Zhao (2009) Genome-wide mapping of HATs and HDACs reveals distinct functions in active and inactive genes (Cell) DOI: 10.1016/j.cell.2009.06.049 Wenfei Jin, Qingsong Tang, … Keji Zhao (2015) Genome-wide detection of DNase I hypersensitive sites in single cells and FFPE tissue samples (Nature) DOI: 10.1038/nature15740 Binbin Lai, Weiwu Gao, … Keji Zhao (2018) Principles of nucleosome organization revealed by single-cell micrococcal nuclease sequencing (Nature) DOI: 10.1038/s41586-018-0567-3 Related Episodes In Vivo Nucleosome Structure and Dynamics (Srinivas Ramachandran) Development of Site-Specific ChIP Technologies (Hodaka Fujii) Multiple Challenges in ChIP (Adam Blattler)   Contact Active Motif on Twitter Epigenetics Podcast on Twitter Active Motif on LinkedIn Active Motif on Facebook Email: podcast@activemotif.com

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.10.21.349100v1?rss=1 Authors: Zhao, C., Jiang, T., Ju, J. H., Zhang, S., Tao, J., Fu, Y., Lococo, J., Dockter, J., Powlowski, T., Bilke, S. Abstract: Background: As knowledge of mechanisms that drive the development of cancer grows, there has been corresponding growth in therapies specific to a mechanism. While these therapies show improvements in patient outcomes, they can be expensive and are effective only for a subset of patients. These treatments drive interest in research focused on the assignment of cancer therapies based on aberrations in individual genes or biomarkers that assess the broader mutational landscape, including microsatellite instability (MSI) and tumor mutational burden (TMB). Methods: Here we describe the TruSight Oncology 500 (TSO500; Research Use Only) bioinformatics workflow. This tumor-only approach leverages the next-generation sequencing-based assay TSO500 to enable high fidelity determination of DNA variants across 523 cancer-relevant genes, as well as MSI status and TMB in formalin-fixed paraffin-embedded (FFPE) samples. Results: The TSO500 bioinformatic workflow integrates unique molecular identifier (UMI)-based error correction and a dual approach variant filtering strategy that combines statistical modeling of error rates and database annotations to achieve detection of variants with allele frequency approaching 5% with 99.9998% per base specificity and 99% sensitivity in FFPE samples representing a variety of tumor types. TMB determined using the tumor-only workflow of TSO500 correlated well with tumor-normal (N =170, adjusted R2=0.9945) and whole-exome sequencing (N=108, adjusted R2=0.933). Similarly, MSI status determined by TSO500 showed agreement (N=106, 98% agreement) with a MSI-PCR assay. Conclusion: TSO500 is an accurate tumor-only workflow that enables researchers to systematically characterize tumors and identify the next generation of clinical biomarkers. Copy rights belong to original authors. Visit the link for more info

Link to bioRxiv paper: http://biorxiv.org/cgi/content/short/2020.07.24.219758v1?rss=1 Authors: Gracia Villacampa, E., Larsson, L., Kvastad, L., Andersson, A., Carlson, J., Lundeberg, J. Abstract: Formalin-fixed paraffin embedding (FFPE) is the most widespread long-term tissue preservation approach. Here we present a procedure to perform genome-wide spatial analysis of mRNA in FFPE tissue sections. The procedure takes advantage of well-established, commercially available methods for imaging and spatial barcoding using slides spotted with barcoded oligo(dT) probes to capture the 3' end of mRNA molecules in tissue sections. First, we conducted expression profiling and cell type mapping in coronal sections from the mouse brain to demonstrate the method's capability to delineate anatomical regions from a molecular perspective. Second, we explored the spatial composition of transcriptomic signatures in ovarian carcinosarcoma samples using data driven analysis methods, exemplifying the method's potential to elucidate molecular mechanisms in heterogeneous clinical samples. Copy rights belong to original authors. Visit the link for more info

This podcast is part of the 2019 NSH Symposium/Convention Poster Podcast Series. To read the full abstract, visit the Block.   Authors: Carlos Genty, BS, HT(ASCP)QIHC, Critical X, Houston, Texas; Timothy McDonnell, MD, Ph.D., Critical X, Houston, Texas    

Mehdi Benkahla, Ph.D.I graduated from the Faculty of Sciences of Tunis, Tunisia in 2012 with a Master of Science degree in Microbiology. Then, I was awarded an Erasmus Mundus Ph.D. scholarship to study at the University of Lille, France from which I graduated with a Ph.D. in Virology. I joined the group of Prof. Matthias von Herrath at the La Jolla Institute for Immunology in July 2018.Talking points:Viruses and type 1 diabetes : T1D is an autoimmune disorder of unknown etiology. The disease pathogenesis is the result of a complex interaction between genetic, immune and environmental factors. Among the potential environmental factors, viral infections arise as critical triggers for type 1 diabetes development.Fixed tissues from nPOD, advantages and disadvantages : Tissues collected from organs donors can either be fixed in formalin and then embedded in paraffin (FFPE) or frozen.Islet organoids and live human pancreas slices (Current projects that we are preparing): Islet organoids : replicating the organ function, multicellular complexity, and three dimensional cellular organization in an in-vitro setting.Live human pancreas slices: Obtained from nPOD, these slices can be cultured for 2 weeks which provide a live readout of several aspects of beta cell function.----------------Welcome to the Pardon My Pancreas podcast!! This show is all about the REAL life with diabetes. Your two host are Matt Vande Vegte & Ali Abdulkareem. Both type 1 diabetics, both diabetes advocates, both diabetes content creators. Matt is the man behind the brand at FTF Warrior which is an tribe dedicated to helping people living with diabetes achieve a healthier life through online coaching while Ali is the creator of the Diabetes Daily Hustle from the Youtube vlogs and podcast show! This episode is sponsored by FTF Warrior. An online community for diabetics dedicated to helping people live a healthier life! https://www.ftfwarrior.comFollow Matt here:Instagram: https://www.instagram.com/ftfwarrior/Facebook: https://www.facebook.com/ftfwarrior/Youtube: https://www.youtube.com/channel/UCCCzwLc-MTNk9636tQyXuwQ---------------------------Follow Ali here:Instagram: https://www.instagram.com/ali.abdlkareem/Youtube: https://www.youtube.com/channel/UCOgPM9FFVTOX5gN_qnVHRNA---------------------------Disclaimer: While we share our experiences with diabetes, nothing we discuss should be taken as medical advice. Please consult your doctor or medical professional for your health and diabetes managementMusic: https://soundcloud.com/joakimkarud

This podcast is part of the 2017 NSH Symposium/Convention Poster Podcast Series.  The lead author of this poster is Courtney Anderson. For more information on the author and to view the abstract, visit The Block.

Full text - http://bit.ly/2pgqWjW Oncotarget | Interview with Dr. Kelber from the Department of Biology, California State University Northridge, Northridge, CA talking about their featured cover paper in Oncotarget Volume 8 Issue 4 "A novel method for RNA extraction from FFPE samples reveals significant differences in biomarker expression between orthotopic and subcutaneous pancreatic cancer patient-derived xenografts" Facebook - http://bit.ly/2xznxjV Twitter - http://bit.ly/2xzWvsu LinkedIn - http://bit.ly/2xzJ6kc Pintrest - http://bit.ly/2xzX8SS Reddit - http://bit.ly/2hoxI0N www.Oncotarget.com

In this webinar, you will learn: - How to perform isolated proteomics of microscopic regions of interest - How to use this technique with FFPE tissue - How proteomics can help you understand molecular mechanisms in disease We recently developed a technique that allows localized proteomics of microscopic regions of interest, such as specific cell types or neuropathological features of disease. This technique uses laser capture microdissection (LCM) to isolate regions/cells of interest followed by label-free quantitative mass spectrometry (LC-MS). Importantly, we optimized this technique to use formalin-fixed paraffin embedded (FFPE) tissue, so that archived human tissue specimens collected at autopsy could be used. This is a particular advantage of our methodology, as the vast majority of human tissue specimens are FFPE blocks, which are currently an underutilized, but exceptionally valuable resource for medical research. We have successfully used this technique to analyze the proteome of neuropathological features that define Alzheimer’s disease (amyloid plaques and neurofibrillary tangles), as well as specific populations of neurons that are vulnerable in AD. Going forward, the use of localized proteomics has the potential to greatly increase our understanding of the molecular mechanisms that underlie AD. More broadly, this technique could be used to analyze regions or cells of interest isolated from any FFPE tissue, and therefore could be widely used to examine disease pathogenesis across a broad spectrum of diseases.

Dr Ragin talks to ecancertv at the annual AACR congress, Washington DC, 6-10 April 2013, about disparities breast cancer biology by ancestry. European-American (EA) woman have a higher overall incidence of breast cancer than African American (AA) women, yet AA woman have poorer survival outcome, even after controlling for factors related to socioeconomic status. AA women are diagnosed at a younger age with aggressive breast tumours, more frequently ‘triple negative’ due to lack of estrogen and progesterone receptor (ER and PR) expression and negative for HER-2 amplification, as well as, high proliferative indices. These ‘triple negative’ breast cancers are most lethal since hormonal- or anti-HER2 therapy are not effective; therefore, fewer treatment options are available. Currently, the reason for racial disparities in breast cancer biology and early age of onset in AA women is largely unknown. Future analyses include screening a larger cohort of 1000 FFPE tumour DNAs to effectively compare differential methylation with age at onset, and a variety of tumour characteristics and risk factors. Funded by 1 R01 CA133264 to CBA, KD, and MJH, and by Cancer Center Support Grant CA16056 to RPCI.

A protocol for RNA isolation from FFPE brain tissue was introduced and optimized in the laboratory. It was demonstrated that both, RNA yield and the ratio of light absorption at 260 nm vs. 280 nm (OD 260/280) in FFPE tissue are comparable to frozen tissue (23). A total of 27 archival brain specimens of 11 MS donors obtained from different brain banks were screened for the ability to amplify the housekeeping gene PPIA as well as miRNA 181a and miR 124. Results were compared to amplification of the same transcripts in 9 frozen MS tissue samples of 9 MS patients. The ability to amplify PPIA in FFPE tissue specimens was very heterogeneously distributed and the loss of amplifiable transcript copies ranged from 45 fold to 200 000 fold as compared to frozen tissue. In some archival samples PPIA could not be detected at all. These specimens were considered not suitable for further qPCR analysis. In contrast, the amplification ofmiRNA 181a and miR 124 in FFPE tissue was tremendously stable with an average loss of amplifiability of 1.7 fold only (23). Among several factors which possibly have an influence on impaired transcript amplification in FFPE tissue, the effect of length of formalin fixation was investigated in more detail. It was shown that duration of formalin fixation had great impact on loss of subsequent amplification of coding transcripts (e. g. PPIA). Compared to frozen tissue, PPIA amplification was reduced by ~15 fold in samples which were formalin-fixed for a day-long period, which is in contrast to a reduction of PPIA amplification by ~200 fold in specimens which had been fixed for years (23). Here again, miRNA amplification was demonstrated to be remarkably stable in the same FFPE tissue samples (23). Based on the stable miRNA detection in FFPE tissue specimens, 18 FFPE tissue specimens (MS n=13, healthy donor n=5) were included in a study which compared the miRNA expression pattern in MS lesions to healthy brain tissue by qPCR analysis of 365 mature miRNAs (42). Furthermore, an experimental setup was established which allows for precise dissection of MS lesions from surrounding normal appearing white matter (NAWM). To this end, FFPE sections were obtained using a microtome, were flattened in a DEPC water bath and mounted on PEN membrane coated slides. RNA yield and amplification of PPIA were not altered by this approach. Parallel tissue sections were stained with Luxol Fast Blue (LFB) and served as a model to help with the precise dissection of MS lesions. This setup was applied to 5 FFPE tissue samples (MS lesion n=3, healthy donor n=2). RNA was isolated from the dissected tissue specimens to analyse differential expression of 84 extracellular matrix (ECM) related genes in MS lesions compared to healthy tissue using TaqMan® Low Density Array qPCR technology. This was compared to a data set derived from frozen tissue samples that had been processed in a similar way. Detection of gene regulation (MS/healthy) in FFPE tissue was found to be reliable and comparable to frozen tissue, provided that the selected genes were of sufficient abundance (23). The up-regulation of the extracellular matrix component decorin could be validated on protein level by immuno-histochemistry in the same FFPE MS lesions. This result was published as part of a study which investigated the expression of several extracellular matrix related genes in MS lesions with frozen tissue, e.g. collagens and the protein biglycan (61). Furthermore this study showed that fibrillar collagens, biglycan and decorin are part of the perivascular fibrosis. These molecules are expressed inproximity to tissue invading immune cells, therefore suggesting a possible disease modifying function (61). In summary, this work presents a detailed protocol for the use of autoptic FFPE tissue specimens to obtain gene expression profiles from dissected MS lesions (23). This protocol was implemented as part of a study which investigated alterations of ECM in MS lesions (61) and contributed to obtain the first miRNA profile in MS lesions (42).

Life Technologies has just released a free webinar. Ambion scientists Emily Zeringer and Marie Gonzalez present the background, methods and what to expect when extracting nucleic acids from FFPE tissue samples. Watch the FFPE webinar now.

Life Technologies has just released a free webinar. Ambion scientists Emily Zeringer and Marie Gonzalez present the background, methods and what to expect when extracting nucleic acids from FFPE tissue samples. Watch the FFPE webinar now.

Background: In order to define new prognostic subgroups in patients with glioblastoma a miRNA screen (> 1000 miRNAs) from paraffin tissues followed by a bio-mathematical analysis was performed. Methods: 35 glioblastoma patients treated between 7/2005 - 8/2008 at a single institution with surgery and postoperative radio(chemo) therapy were included in this retrospective analysis. For microarray analysis the febit biochip "Geniom (R) Biochip MPEA homo-sapiens" was used. Total RNA was isolated from FFPE tissue sections and 1100 different miRNAs were analyzed. Results: It was possible to define a distinct miRNA expression pattern allowing for a separation of distinct prognostic subgroups. The defined miRNA pattern was significantly associated with early death versus long-term survival (split at 450 days) (p = 0.01). The pattern and the prognostic power were both independent of the MGMT status. Conclusions: At present, this is the first dataset defining a prognostic role of miRNA expression patterns in patients with glioblastoma. Having defined such a pattern, a prospective validation of this observation is required.

Thyroid cancer derived from follicular epithelial cells is the most common endocrine malignancy in man. An increased incidence of predominantly papillary thyroid carcinomas (PTC) was found in children exposed to radiation after the Chernobyl nuclear accident in 1986. Therefore, in this study, the goal was to establish a mouse model of thyroid carcinogenesis, based on a standardized histological classification scheme for the murine thyroid tumors, and complemented by molecular genetic analyses. In previous studies, radioiodine (I131, 111 kBq) was injected into iodine deficient fed mothers of various mouse strains (F1-hybrids and backcrosses of C57/BL6, C3H, BALB/c, and JF1). The first injection was applied during gestation and the second during lactation. The necropsy tissue was submitted for the analysis in this study. A set of 365 thyroid glands (203 irradiated and 162 control mice) was histological examined following the current WHO classification of human thyroid tumors (2004) for comparative purposes. The irradiated mice showed 24 % of cases with simple hyperplasia (SH), 20 % with nodular hyperplasia (NH), 7 % with follicular thyroid adenoma (FTA), and 5 % with follicular thyroid carcinoma (FTC) whereas in the control group only 3 % SH, 3 % of NH, 1 % of FTA, and 1 % of FTC were observed. Interestingly, no PTC was diagnosed in the mice, which is the most frequent irradiation-related type of thyroid cancer in human. Therefore, the histological type of the radiation-associated thyroid tumors in mice differs from that in human. However, some cases of murine FTC presented PTC-like biological behavior. In addition to the significant increase of hyperplasias in irradiated mice, most of the FTC (82 %) arose amongst a background of hyperplastic nodules. Therefore, a progression from NH to FTC, based on genetic instability, cannot be ruled out. The following molecular methods were used: PCR- (polymerase chain reaction-) based loss of heterozygosity (LOH), comparative genomic hybridization (CGH), and fluorescence-in-situ-hybridization (FISH). Since the CGH-study in mice using formalin-fixed paraffin-embedded tissue (FFPE) is not yet established, an important part of the study was dedicated to evaluate this methodology. The LOH-study was performed with thyroid gland tissue from 40 mice (seven normal thyroid glands, 12 SH, 10 NH, 10 FTA, and one FTC) using 36 microsatellites for nine different loci. With the exception of an LOH with a single microsatellite on chromosome 14 in 40 % of NH, LOH was found in 75 % of the irradiated male mice with H6F1-background on chromosomes 4, 5, 6, 11, 14, and / or 19. This suggests the existence of a mouse strain specific genetic predisposition, which influence on the genetic stability. One of the FTA (an atypical FTA) was highly suspicious for a deletion of the tumorsuppressorgene Rb1 (supported by intragenic FISH-analysis), which could play an important role in the thyroid carcinogenesis. For the CGH-study, thyroid tissue derived from 21 different mice (F2-hybrids) was analyzed (two normal thyroid glands, one SH, 12 NH, two FTA, and eight FTC). In 46 % of the hyperplasias, small chromosomal gains and losses located on different chromosomes were observed; suggesting that there exists a genetic instability, which may lead eventually to malignant progression. Regional polyploidies on chromosomes 4 and 5 were demonstrated in one of the FTAs, which could be a hint for the location of oncogenes. Taken together, in FTA development there is a broad spectrum of genetic alteration, and by inference mechanisms. In contrast, the FTC exhibited a significant increase of specific aneuploidies, mainly deletions of the chromosomes 4 (88 %), 9 (50 %), and 14 (38 %). Identical alterations of chromosomes 4 and 9 were also observed in the one case of an FTC from a non-irradiated mouse. These data indicate that irradiation, most probably, increases the frequency of genetic changes, but does not change the type of genetic alterations, which play a crucial role in thyroid carcinogenesis in mice. A better understanding of molecular genetics involved in thyroid tumorigenesis in standardized mouse models may give insight into the pathogenesis of the various tumor types. Together with the results from human pathology and in vitro studies, this may lead to a better knowledge about the molecular pathways with diagnostic, prognostic, and therapeutic relevance. The results of this study demonstrate a morphological and genetical difference between human (PTC) and murine (FTC) radiation-associated thyroid tumors, but a strong similarity to the human follicular tumors. Therefore, this mouse model serves as a good model of carcinogenetic mechanisms, tumor induction, and progression in the human follicular tumors FTA and FTC, resulting from the cooperative effect of radioiodine exposition and iodine deficiency.