You're at the Thyroid, Neoplasia, and Cancer Oral Abstract Session. We have some very exciting oral abstracts for you today. I think you're going to enjoy them. During this session, there's going to be a Q&A period at the end. And so there's two options for you. You can either scan the QR code, ask your questions, and Dr. Peters and I will review them, and if time, ask them. Or you can also come up to the microphone in the old-fashioned way, ask your questions, and we can have an interactive discussion. This is a hybrid meeting, so there may be some virtual questions that are coming in as well. So we hope that you enjoy this session. Dr. Peters and I look forward to the upcoming talks, and I'll turn it over to Dr. Peters. Thank you. Thank you very much, Dr. Hamart. Good morning, everyone. It's a great pleasure to introduce the first speaker, which is Dr. Shana Was-Imam from the University of Toledo, who's going to share with us his presentation, also on behalf of the other coworkers, entitled Decoding Cancer Immunoediting of Tumor Microenvironment Provides Immunogenomic Marker for Thyroid Cancer Screening. Please go ahead. This is next slide, but if you can use this as a pointer. I think the guy is coming. Would you show the first slide, please? I think so. Yeah, it is. It is. Yeah. Good morning, everyone. Thanks for allowing me to present this work, entitled Decoding Cancer Immunoediting of Tumor Microenvironment Provides Immunogenomic Marker for Thyroid Cancer Screening. No conflict of interest, patent pending, University of Toledo, Ohio. As we know, thyroid cancer is predicted to become the fourth most common cancer by 2030. Almost near around 600,000 FNA performed annually, and almost one-fifth of them comes under the feature of ATP of undetermined significance, or follicular lesion of undetermined significance. Our primary goal is to identify or characterize the follicular lesion of undetermined significance, because most of the surgery made as a diagnostic thyroidectomy, and that leads to the 70% of the surgical procedures are unnecessary. That means out of that, 15% to 30% only renders having the malignancy. This table shows the thyroid cancer diagnostics available in the United States, their sensitivity, as well as specificity. Recently, Lancet published a report where it's really alarming for the endocrinologist, as well as endocrine surgeon. It states that a majority of the endocrine surgeon of the patients are over-diagnosed. Majority of the thyroid cancer have been over-diagnosed, and you can see the numbers there, it's too high. And this compels us to work on, or to understand, dire need to develop diagnostic marker which have a high specificity and high sensitivity. Not only that, this over-diagnosis leads to the thyroidectomy, as well have the complications. So keeping this view in mind, we designed our work, and these are the objectives, stratifying the risk of cancer in different thyroid autoimmune conditions, developing an immunogenomic marker for early detection of thyroid cancer. Previously, we have shown that thyroid cancer is really surrounded by reactive immune cells, and these reactive immune cells have immunoregulatory capacity. That means they regulate the immune responses in and around the tumor microenvironment, and facilitate the development of the tumor growth. And this been reported in so many literatures. And you can see this thyroid cancer, the uniqueness is, you can see, oh yeah, sorry. The uniqueness of the thyroid cancer, there is an intersection of the cancer, as well as the immune microenvironment in an area. And that is, we believe those are the players who decided the fate of the cancer. We have established a proof of principle, as in our previous publication, we have shown that a population of the T-cells, which is highly proliferative in natures, and we named as a double negative T-cells, are present in the very high number in the setting of thyroid cancer. Not only that, we also looking into the risk of the cancer in different autoimmune disease, thyroid autoimmune diseases like Graves and Hashimoto thyroiditis. As we mentioned previously, we have shown that the double negative T-cells, as you can see in the margin, double negative T-cells, these are the CD3 positive, CD4 negative and CD8 negative, and that's have a regulatory functions, and not only that, these DNT cells are 20 times more abundant than the classical T-reg cells. Not only that, these DNT cells have a role in regulating the proliferation of the effector T-cells, CD4 and CD8 T-cells, and that's how contribute to the tumor tolerance. I'm just briefly illustrate the, this illustrate briefly describe the mechanism of how this double negative T-cells regulate the immune microenvironment in thyroid cancer. The tumor antigen being presented to the antigen presenting cells, antigen presenting cells chop the protein and pick the cancer peptide, and this cancer peptide are presented to the T-cells, CD4 and CD8 T-cells. As well as same time, this the same peptides will be present, the DNT cells also activated themselves with the same peptide, the mechanism known as trigocytosis. In literal terms, we can say is a stealing, so stealing of the peptide, and that's how the DNT cells activate themselves. Once they are, they both are DNT cells and CD4 and CD8 T-cells activated with the same peptides, and they induces apoptosis to the CD4 and CD8 T-cells. Not only that, when the double negative cells, they are also producing very profuse amount of the granzyme and perforin. That's how induces apoptosis to the B-cells and the NK-cells, and these NK-cells in the, recently in 2019, we have explained how the low NK-cells or no NK-cells leads to the differentiation of resident monocytes to the M2-microphages, and that's how facilitate the pro-tumorous microenvironment and induce a tolerance to the cancer. We are also, it's need to, it's need to understand the mechanism of this, that's how we need to understand the transcriptome of the tumor microenvironment as well as to know the secretome of these environments. Now here is the schematic diagram. We have shown the fine needle guided, the ultrasound guided fine needle respiration to quantify the tumor-associated DNT cell for screening of the thyroid cancer, and here is most important, the biopsy is made at the junction of the cancer as well as the immune cells. So in the similar way, these double negative T-cells where predominate population in the thyroid cancer, FNA samples, and you can see here these populations are almost equal to the CD8 T-cells populations and where are in case of thyroid autoimmunity, this population is very low. The same we have, not only that, the comparative proliferative cycle of the DNT cells in thyroid cancers is revealed here. These DNT cells have a high proliferative cycles up to the P5. Most important is that DNT cells, that means they check the proliferation of the CD8 T-cells. Like I say, most affected populations are the CD8 T-cell population where CD4 is also affected, but it's not, but the proliferative cycle is comparatively less than the DNT. We did the, as the DNT cells have a role in cancer progression and as we are considering as a risk for the cancer, we recruited the patient and we analyzed the risk rate of the cancer with the proportion of the DNT cells. And these DNT cells, these DNT cells are proportionally, have a very high sensitivity, 96.6% and a specificity of 100% with the NS-CAL-292. So thyroid cancer diagnostic, we can say here, then the the table can see here, the highest specificity with the available tests are maximum is 82% while the DNT cell-based present diagnostic test have a sensitivity of 96.6% and a specificity of 100%. That means the present criteria of 9.14% cutoff at the 100% specificity highlights the test ability towards predicting benign nodules and identify the test as a rule-of-test. That means unnecessary 70% thyrodoctomy rate for benign lesions is not ideal. Hence, the rule-of-test will directly influence the cost of the effectiveness of the patient satisfaction. So these are the schematic representation of a screening of the FNA sample for thyroid cancer and the outcome of the project. Outcome of the projects are generation of an immune scores using cellular and the cytokines profile, adaptation of a screening method on the PCR platform by identifying differentially expression gene and to adapt onto the PCR platform for the robust screening. Then prognostic model and nomograms with the help of bioinformatician and machine learning engineer, a predictive model will be designed involving clinical parameters. So in conclusion, our study proposed a cutoff of 9.14% based on quantification of DNT cells as an immunogenomic marker for early diagnosis of thyroid cancer with 100% specificity. We propose that instead of linear evaluation, a prediction model can be designed involving clinical parameters, differentially expressed gene, diagnostic immune scores, cytokines and transcriptomic profile. Further, the model can be validated and a diagnostic nomogram could be constructed. This analysis provide not just a diagnostic marker but a predictive tool for severity, improvement of cancer in thyroid cancer active surveillance patients. Thank you. Thank you very much. I see that there's a question from the audience. Maybe while we're waiting until that, you could already explain a little bit more about the cases and the controls because it wasn't really clear to me from the presentation. In the abstract, you mentioned 46 FNAs, which is relatively small compared to the other studies that you mentioned. But could you mention what cases and what controls were out of those 46? Yeah, right now in the presentation, we do have like 127 samples and with these like 46 are positive for... Sorry, 96 are positive for thyroid cancer and like... Sorry. Yeah. Can I go back to the... Because there I can explain this. Yeah. So here is the low risk rate because those are the Hashimoto patients, low risk rate and is the high risk rate. We identify the low and high risk rate on the basis of the final confirmatory diagnosis post-surgical. So we are screening first taking the FNA, then we are following those patients and confirmatory diagnosis will be made first and then we are putting the statistics. And on that basis, we found that the cut-off to DNT cell 9.14% have a sensitivity of 96.6% and a specificity of 100%. Thank you. We only have time for very short questions and very short answers, please. Yeah. Okay. Just by way of disclosure, I'm Josh Klopper. I'm the Medical Director for Verisight. I'm obligated to tell you that the GSC is not an Affymetrix chip. It is RNA-seq whole transcriptome processing. So just for that platform. My question is, have you tested this on indeterminate thyroid modules? Yes, we do. So how does the performance look? All I see here is cancer versus I think benign or in Hashi. How does it perform in indeterminate cytology? Yeah. The paper has just been published five days back. I can give you the paper. We have explained each and every exclusion, inclusion criteria and everything is there. Thank you. Melissa Luckner from UCLA. I like that you're using immunology to think about diagnostics. The question I have for you is, with the double negative T cell population, how does it compare in terms of its expected cytokine or gene expression profile related to gamma delta versus alpha beta T cells or NK T cells which might also be double negative? And how do you compare the two? Yeah. Thank you. Very good questions. Actually, DNT cells are alpha beta T cell. Joanna Kubo-Gryzińska, NIH. I have a question regarding your patient's population. My understanding from the presentation was that you included patients with autoimmune thyroid disorders, so meaning Hashimoto's thyroiditis, Graves' disease patients, and you plan to incorporate clinical data as well. So my question to you is, have you incorporated TSH values, thyroid hormone values? There's growing evidence of growth simulatory effects of thyroid hormones, TSH data from the past. So did you see any signal over there? Have you considered that? Thank you for asking this question. Definitely, we have taken into consideration all the patient parameters. We have the data in the publication in the supplemental figures. We have incorporated and we have included all the patient information, and the results are based on the confirmatory diagnosis from the academic pathologist, post-surgically. Thank you very much. Thank you. I'd like to introduce the second speaker, which is Dr. Tilak Kano from Ohio State University. Dr. Kano will also, on behalf of the other co-authors, present the data regarding the study entitled The ERKON1-4 Metastasis Progression Suppressor Gene is Hypermethylated at Intron 1 and Downregulated in Papillary Thyroid Carcinoma. Okay. Okay. Can you start the next one, or do we need to do that from here? Sure. That is another one. Not this one. It's wrong. Last one. Last one. Down. Yeah. Thank you. Thank you. I would like to thank the committee meeting organizer for the opportunity to give me to present our work on the regulation of ERKON1-4 in thyroid cancer. Oh, my God. I went last. Sorry. Next. Metastasis Progression Suppressor. Progressive metastasis is the approximate cause of cancer-related mortality for patients with cancer. Identifying drivers and gatekeepers of late-stage progression is crucial. We previously identified the regulator of calcium, ERKON1-4, as a functional downregulated MPS in thyroid cancer, and ERKON1-4 loss increases the metastasis through the transcription factor in NOV3. The mechanism of ERKON1-4 loss in the thyroid cancer and whether reversible are not known. The ERKON1-4 promoter and intron one contains CG-rich regions reported to be hypermethylated in other cancer, other tissue. Hypothesis. ERKON1-4 expression levels are downregulated by methylation of regulatory regions and can be reversed in the thyroid cancer cells. ERKON1-4 is hypermethylation in association with reduced expression in thyroid cancer. Shown here is the gene structure of ERKON1-4. Three positive CG-rich regions are noted in the right. One in the proximal promoter named Region 1, and two intron named Region 2 and 3. Materials and method. We screened human thyroid cancer cell line and identified a representative panel of five with low base ERKON level. And we analyzed ERKON1-4 protein and mRNA levels by Western and QRPCR before and after demethylation treatment with decitabine at a time point by initial time course experiment. And we used two methods to identify demethylation, DNA methylation. One was quantitative MB2D214 bead capture assay, and another one was qualitative methylation specific PCR. As shown in the red arrows, methylation specific PCR identify hypermethylation of intron one in all cell lines. There was no evidence of hypermethylation of CGDs regions of the proximal promoter in any of the other cell line. Therefore, we focused further studies in intron one CGDs regions. We next assessed methylation of intron one by qualitatively before and after decitabine treatment using MB2D214 bead capture assay. Here results from the most methylated region two of intron one showing that reduction of methylation following demethylation with decitabine after 72 hours. We next performed QRDPCR to determine if treatment with a decitabine resulted in the increase of ARCN1-4 mRNA levels in all five cell lines. ARCN1-4 mRNA levels was significantly increased after 48 hours of treatment. Next, we performed western blot following the decitabine treatment to determine if protein level of ARCN1-4 also rescued, and we saw the western blot result show it was increased, and we did quantification of multiple experiment, and we saw this one after 72 hours. Next, we assessed the quantitative level of intron one methylation at region two and region three with 18 pairs of normal and papillary thyroid cancer samples. Paired analysis showed a statically significant increase in methylation in both side, but the amount of methylation is consistent of the increase were greater for region two in of intron one in the left. Next, and finally, we analyzed ARCN1-4 mRNA levels on the left and NOV3 levels in the right with paired sample, and in this also result demonstrate reduction of ARCN1-4 and consistent with the methylation data increase NOV3, consistent with our prior functional and inverse association population data. Conclusion, ARCN1-4 is hypermethylated in intron one in thyroid cancer cell lines. ARCN1-4 hypermethylation is reversed by decitabine and RNA protein levels increase. ARCN1-4 is hypermethylated at intron one in PTC versus normal tissue, and ARCN1-4 gene expression is downregulated in PTC patient tumor samples in association with NOV3 upregulation. And ARCN1-4 metastasis progression suppressor is downregulated in thyroid cancer cell lines and papillary thyroid cancer by intron one hypermethylation, and ARCN1-4 loss can be reversed by demethylating agent decitabine. Thank you for your attention, and I look forward to have questions. Thank you very much, very exciting data. While people are still thinking of questions, maybe I could start, and I was wondering, so you clearly show this effect of the hypermethylation, and by affecting it, you kind of reverse the suppression. Do you think it's specific for this gene, or did you have a chance to also look at other genes where perhaps the same regulatory aspects may be involved? It has been shown in other cell types, but we did, in our preliminary study, we haven't not identified, so maybe phosphorylation, that method we have to do, we are going to do that one. Thank you. Did you have a chance to take a look at this ARCN1 hypermethylation in tumors with evidence of metastasizing to the lymph nodes versus indolent tumors which have not metastasized? My understanding was that the comparison was between tumor and normal. But do we know? Peer samples. No, peer sample, maybe. Sure. So, we've not looked at hypermethylation in distant events yet, but we've already shown in published in the relationship of lower marking on the prognosis of metastasis. Okay. So that's the next step. Thank you. Thank you. And what about hypermethylation with respect to pre-existing genetic alteration, like PRAF or any other alteration? Did you see any relationship? Because I'm trying to understand the mechanism by, no. No. So, thank you very much. If there are no further questions. Thank you. And we move to the next speaker, which is Dr. Zanton Vang from the NIH, who will present data on integrins as potential molecular targets in thyroid cancer imaging and therapy. Dr. Vang. Sorry, but actually there's a modification. Oh. Okay. Okay, thank you. So, it will be Dr. Shilpa Thakur presenting on Dr. Vang's behalf. Okay. Good afternoon, everyone. And I would like to thank organizers for giving me this opportunity to present my research work here. And I, well, my name is Shilpa Thakur, and I work at NIH with Dr. Joanna Klobogorzinska. And the title of my research is Integrins as Potential Molecular Targets in Thyroid Cancer Imaging and Therapy. Okay. So, I will start with a brief introduction about integrins. Integrins are these, sorry, integrins are the cell surface transmembrane proteins which binds to extracellular matrix, other transmembrane proteins, and soluble ligands. They present as heterodimers and consist of alpha and beta chains which are non-covalently attached. Upon binding to their ligand, they initiate a series of signaling and structural changes. And the downstream signaling pathways include focal adhesion kinase and PI3-AKT pathways, which play a role in various processes such as survival, proliferation, differentiation, and others. Integrins family consists of 18 alpha chains and eight beta chains, which together form 24 types of heterodimers. And these heterodimers actually differ from each other in terms of their ligand preferences. In this presentation, I'm gonna focus particularly on alpha-V-beta-3 heterodimer. And this heterodimer actually binds to arginine-glycine-aspartate motif, also known as RGD motif, present on its natural ligands. Upon binding to this motif, it initiates signaling changes. The reason why I'm focusing on alpha-V-beta-3 heterodimer because it tends to overexpress in tumor tissues and it also has role in tumor neovasculature and promotes angiogenesis. So because it binds to this RGD motif, a various radiolabeled RGD peptides has been synthesized by combining the RGD peptide to the radionuclide with the help of a biofunctional coupler and a linker. Depending on whether it binds to a diagnostic radionuclide such as gallium or 64-copper or lutetium, it can be used for both diagnosis as well as for therapeutic purposes. These radiotracers have been used both clinically as well as clinically for diagnosis and imaging in tumors that are overexpressing this alpha-V-beta-3 heterodimers. So our lab particularly focused in thyroid cancer, so we were interested to look at alpha-V-beta-3 mRNA expression in thyroid cancer, and it overexpresses, as you can see, based on this Human Protein Atlas database. So provided that there is an initial evidence that alpha-V-beta-3 overexpresses in thyroid cancer and the fact that it can be targeted using radiolabeled RGD peptides, the goal of our study was to establish the utility of alpha-V-beta-3 integrin as a molecular target for the imaging and therapy of thyroid cancer. It's not moving. Okay, there. So the most common thyroid, sorry, it moves ahead. Oh, sorry, what happened? Okay. Okay. Yeah, that's the one, okay, thank you. So the most common type of thyroid cancer is papillary thyroid cancer, and it has been molecularly characterized into BRAF-like or RAS-like, depending on the transcriptional signature of 71 genes. So this 71 gene signature has been used to calculate this BRAF-RAS score, also known as BRS, and it ranges from minus one to plus one. With BRAFs, like tumors, have a negative BRS score, and RAS-like tumors have a positive BRS score. In our study, we wanted to study the correlation of alpha-V-beta-3 expression with the BRS score and see whether it is overexpressed in BRAF tumors or RAS tumors. With that in mind, we analyzed the correlation of alpha-V-beta-3 mRNA expression and correlated it with BRS using this TCGA data set consisting of 496 papillary thyroid cancer tissue samples. Upon performing this correlation, we found that alpha-V-beta-3 are moderate to low, so moderate to low negative correlation with the BRS score, suggesting that the BRAF-like tumors with a negative BRS score has high alpha-V-beta-3 expression. So next, we wanted to test the same thing in the tumor tissues and perform the protein analysis. So with that, we did immunohistochemistry, and for that, we used human tissue microarray consisting of normal thyroid as well as various thyroid cancer tissue samples, and upon performing this analysis, we found that papillary thyroid cancer tissue samples has the highest alpha-V integrin expression as well as highest alpha-V-beta-3 integrin expression. So next, we tested this in our thyroid cancer cell lines, and this included both BRAS-like as well as BRAF-like thyroid cancer cell lines. Upon doing the expression analysis at the protein level, we found that the thyroid cancer cell lines, BRAF-like thyroid cancer cell lines specifically has higher alpha-V-beta-3 expression, and we found a strong negative correlation between their protein expression and BRS score, suggesting that BRAF-like cell lines are associated with high alpha-V-beta-3 protein expression. So given that, now we have established that there's a subset of thyroid tissues which overexpresses alpha-V-beta-3. The next thing that we came into mind that these patients, the patients which overexpresses alpha-V-beta-3 could be a good candidates to receive RGD-based therapy or imaging. With that in mind, so in support of our hypothesis, there was this study published in 2020 by Parihar et al. And in this study, they actually studied the uptake of this gallium-labeled dota-RGD peptide in radioiodine refractory thyroid cancer patient, and they found that this uptake was very specific to the metastatic lesions. Also, in addition to this, they tested the uptake of this, used this therapeutic radionuclide-consisting RGD peptide for the treatment of one patient which also was radioiodine refractory, and they found that treating this patient with this lutetium-labeled RGD peptide resulted in reduction in metastatic lesion-reward burden. So this study was actually kind of support our hypothesis. But we feel that addition of this Evans blue moiety to the RGD peptide could enhance the therapeutic efficacy of these RGD peptides. And the reason for that belief is that this Evans blue moiety, it binds to human serum albumin, and with its binding, it increases the retention time within the blood, and over time, there's more tumor-specific uptake. And this peptide, this EB-conjugated RGD peptide has been synthesized by our collaborators at NIBIB, and they have the patent for it. So in our studies, we plan to use this EB-labeled RGD in our preclinical thyroid cancer models. Oh, also, one more thing, they also tested this EB-labeled RGD peptide in a preclinical model, mouse model, where this preclinical mouse model was made using non-small cell cancer patient-derived xenografts, and they also tested the therapeutic efficacy of unconjugated RGD with the conjugated RGD, and they found that when they used the EB-labeled RGD, the tumor shrinks over time, and it disappears at 24 days without any signs of reoccurrence. However, the mice treated with unconjugated RGD, their tumors kept on growing. So the survival of the mice was very high in cases where mice were treated with EB-labeled RGD. So since the preclinical, the previous preclinical study was done in non-small cell cancer patient-derived xenografts, we had to establish our own model and test this in thyroid cancer model. So for this, we are planning to use OQ-2 cell lines, which is characterized by high alpha-B beta-3 expression, and we have established both metastatic and subcutaneous model that we are going to use further to test the therapeutic and diagnostic efficacy of RGD peptides. In addition, we'll also be using FTC as a low alpha-B beta-3 model. So one important aspect is, before going to testing, is to make sure that this tumor lesion or the metastatic lesions, they retain the alpha-B beta-3 expression, which we see in the in vitro studies. So for that in mind, we looked at their alpha-B and alpha-B beta-3 heterodimer expression in the OQ-2 metastatic lesion, and we found that the alpha-B expression remains preserved, and we also tested the heterodimer expression, which is also still there. So this suggests that this model could go forward to test the diagnostic and therapeutic efficacy of RGD peptides. So this is what we have done so far. This study is very initial phase, and there's a lot to do. So we plan to test further the diagnostic and as well as the therapeutic efficacy of RGD-labeled RGD peptides in our thyroid cancer models. And in addition to this, we will also be testing the therapeutic efficacy of lenbetanib and compare it with the therapeutic efficacy of radiotracer. The lenbetanib is like the standard care of therapy for a patient who does not respond to standard therapy, which is radioiodine therapy. So we want to compare the therapeutic efficacies of the both, and in addition, both the compounds, they tend to inhibit the angiogenesis and affect human vasculature. So I think the synergistic effects could be more beneficial for the treatment purposes. So this is what we have done so far, and so the conclusion, based on our initial studies, is that BRAF-like papillary thyroid cancer is associated with high expression of alpha-V beta-3 integrin. The alpha-V beta-3 integrin could potentially serve as a molecular target for imaging and therapy with radio-labeled RGD analogs in a subset of thyroid cancer patients. Appropriate preclinical models to test the therapeutic utility of radio-labeled RGD analogs in vivo have been established. Lastly, I'll say thank you for your attention, and any questions are very welcome. Thank you. Thank you. Thank you very much. Very exciting data. Thank you. Dr. Ringel. Thanks, that was a great presentation, and I'm sure you're, and I just have a couple quick questions for you. So one is you're probably aware, because one of your co-authors was first author on this, that we've looked at this and demonstrated that integrins really don't go up in the central part of the tumors of aggressive thyroid cancers. Their step up is in the periphery, right? And that we published before. So I was curious to see what the depth of your cell-killing effect would be for your integrin label, whether that would actually get to the central part of the tumors or would be, or has a limited depth of activity. And then the second question is, of course, the TCGA dataset is all really intra-thyroidal, low-grade papillary thyroid cancer with only 11 cases with distant metastases. So have you really had a chance to look carefully to see whether this is really a BRAF-associated or whether this is really an aggressive metastatic-associated thing? And it may be better the second, but I was curious to see whether you really had a chance to tease that out yet. So two questions, the depth, because integrins in general are not upregulated in the center, and then the mets versus the genomics. Okay, yeah, those are very great questions. And this, we haven't yet tested because that's the next step. We have the only very preliminary studies. So that's very, that will be very interesting to see what happens in the center of it. But based on that preclinical studies, we are relying more so on this EB-conjugated RGD peptide. The reason being that it's more tumor-specific binding and accumulation within the tumor tissues. So maybe we will see a good effect in the center, but if the alpha-b-beta-3 is not there in the center, then that could be very challenging for us. But we don't have that answer yet because that's the next step. Interesting to see, yeah. Your mouse model is diffuse, but the human tumors are less. So it might be worthwhile to try to see whether you can recreate that. And Vasily will know that for sure. Yes, true. You know, another thing that I missed, that this, you know, our radioliberal RGD peptides, they also target tumor vasculature. So maybe that will more be additive effect that we'll see over there. So, and another question, I'm sorry, I forgot. No, the TCGA data association with BRAF is intrathyroidal early-stage tumors. I was wondering whether you had a chance to look at the step-up that might occur in distant metastatic lesions. No, not yet, but that will be interesting to see as well. Thank you so much for wonderful questions Room for one more question Hi, wonderful dog. I do only one question. What mouse model you have used thyroid cancer mice model you have used So we are using two different model. One is metastatic mice model and this is like immune compromised mice So these models we have already established and know that we work very well And another model will be nude mice model. So there will be you will be creating subcutaneous You know graft models, you know, and we have established that we just haven't tested or you know, readily able traces on those mortars So these are the solid tumor or diffuse tumor like so the subcube will be the solid tumor which will be formed here and the other will be the metastatic lesions that will be spread like in the lungs and Maybe sometimes, you know, we see lesion in the liver as well. So So what the status of the lymph node in and if it is lymph nodes we haven't tested that but Maybe I'm not sure Okay, thank you, thanks, thank you So we've had some terrific talks so far we have three more coming up and so the next one I would like to introduce is Dr. Purvis She's from CHOP in Philadelphia And so she's going to be representing her group and she's going to talk about novel murine models of BRAF V600E Driven papillary thyroid cancer Welcome, Dr. Purvis It's a good afternoon, it's great to be able to talk to you today about my project And so we're just going to jump right into my project here So thyroid cancer incidence has been increasing over the last several decades in both Pediatric and adult populations. If you look at the graph on the far right You can see that the majority of this increase is due to Papillary thyroid cancer and this is the most common diagnosed thyroid cancer Initially this increase was solely thought to be due to increased surveillance Particularly in the pediatric population as you can see on the graph on the right. In 2006 when the ATA first published formal guidelines for pediatric specific tumors, there was a steep increase in diagnosis however due to increase in size of lesions and Increased metastatic disease at diagnosis. It's believed that this isn't truly just due to increased surveillance Additionally, features of pediatric versus adult onset thyroid cancer can be quite different Pediatrics are far more likely to exhibit larger tumors at the time of diagnosis and they're more likely to exhibit extra thyroid invasion Additionally, pediatrics more often present with Not only lymph node metastasis, but distant metastasis and up to two-thirds of children that have distant metastasis will never achieve remission. And for children that are Refractory to radioactive iodine treatment, there is currently no approved systemic therapy So Despite the fact that pediatric and adult onset thyroid cancer share very common I mean Oncogenic drivers such as RAS, BRAF, and RET are in tract fusion The prevalence or the distribution of these in an adult population versus a pediatric population is different So in the table that you can see here the blue bars represent a TCGA study for adult onset and the orange bars represent a pediatric study that we did at CHOP looking at the prevalence of oncogenic drivers and BRAF is the most common mutation in adults and it's the second most common mutation in pediatrics So BRAF V600E is the most common BRAF mutation within that and Despite pediatric and adult PTC sharing this common mutation It has various different risk factors involved. So in an adult setting this mutation is associated with the highest risk for lymph node metastasis While in a pediatric setting this mutation is also associated with lymph node metastasis. It does not infer the highest risk for this and then in an adult population this mutation has also been associated with decreased response to radioactive iodine and a higher disease specific mortality Neither of these two trends are observed in pediatrics and the reason for this is not understood So under normal conditions So, excuse me Activation of the AKT pathway and the MAP kinase pathway are very commonly observed in thyroid cancer under normal physiological conditions Receptor tyrosine kinase would be activated by a growth factor which would then activate RAS. RAS can then activate both the AKT pathway and the BRAF pathway ultimately leading to downstream signaling that promote migration proliferation and survival And the PI3 kinase pathway obviously can be negatively regulated by p10. So for our mouse model we employ a Single copy of the endogenous allele of BRAF V600E so in the absence of our TPO Kraber-Combinase this mini gene here expresses a Normal wild-type copy of BRAF V600, sorry of BRAF. However in the presence of TPO recombinase this mini gene is excised and it leads to a expression of one copy of BRAF V600E which of course Leaves the kinase constitutively active and continues to signal down the MAP kinase pathway Repeat for this model. We also wanted to Have activation of the AKT pathway and also to model Cowden's disease And so we knock out one copy of the p10 One copy of p10 and so as you can see on the right here exons four and five are Flanked by LOXP sites in the presence of our TPO CRE. These are excised leading that allele non-functional therefore Essentially knocking out one copy of p10 So these mice go on to Develop thyroid cancer at a hundred percent penetrance by five weeks of age and then from those tumors I've gone to our derived cell lines and These are on a pure congenic background of 129 and so The first cell line that we'll be talking about will refer to from now on as WD2 So this cell line just to review has one copy of BRAF V600E and one Copy of p10 is inactivated. This arose from a male mouse That was four weeks old and you can look at the H&E here and see that this tumor was well differentiated And has classic papillary features The other cell line that we'll be talking about is PD1 and this Arose from a mouse that had the exact same mutations one copy of BRAF V600E and one copy of p10 Knocked out and this arose from a female mouse That was 32 weeks old at the time that it was collected and you can see looking at the cystology here This tumor has progressed to a more poorly differentiated state And if you look at the panel here, these are different differential interference contrast images to be able to see The morphology and size of the cells and you can see that while there are definitely some similarities between the two there is also different heterogeneity not only between each other but within showing that While they do they are from the same tumor. There is heterogeneity in these populations So the next thing I wanted to do was to characterize the cell growth patterns of these cell lines and so on The left here you can see a growth curve and the first two days the cells are in a lag phase and then they go into exponential growth and What is significant here is the fact that PD1 is significantly more proliferative than WD2 Please note the break in the axis here Next we wanted to look at the activation of the MAP kinase and the AKT pathway And so to do this we serum solve the cells Overnight, which is those lanes are represented here by the minus signs and then the plus signs represent the cells that have been serum starved Overnight and then given an FBS stimulus for 10 minutes before collection to signal through the pathway so first Excuse me At first we'll compare the basal rates after starvation. And what is a most note here is the fact that At the phospho AKT levels for PD1 at basal are significantly higher than those of WD2 And despite the fact that they both originally have only one copy of p10 Inactivated and then moving on to look at them into response to a growth stimulus What's of note here is that the phospho ERK for PD1 in response to FBS is significantly higher than that of WD2 So this indicates that there is increased signaling through both pathways For PD1 one into in response to a growth stimulus and the other independent So since these cell lines both originally had the exact same initial mutations We were very curious as to why PD1 had such higher activation in phospho AKT even at basal and so we went to look at protein expression of p10 and through Mechanisms that we do not know at this time PD1 has lost complete protein expression of p10 And so this of course explains why there is increased signaling through the phospho AKT pathway even at basal rest So Next to be able to actually evaluate the role of age of onset at for disease progression We need to establish age equivalence in mice for humans This is a common technique that has really been adopted by a lot of labs recently Including one paper from melanoma that was just recently published this month in nature And so for our studies the age equivalence that we will be using So a mouse age of four to five weeks at age of injection is equivalent to a pediatric prepubertal onset of disease and a mouse age of 20 to 22 weeks at Injection is equivalent to adult onset disease so now with these cell lines and these age equivalents established what I am able to do is to Inject these cells into a fully immune competent mouse And so I can use a cohort of pediatric and a cohort of adult for each cell line and then evaluate Penetrance and progression for these two cell lines in a fully competent immune competent host over ten weeks and so what we observed was that there was differential penetrance and progression for both cell lines in Pediatric and an adult host so we first focus to the graph on the left You can see that WD2 was not penetrant and a pediatric host. No tumors were formed or observed over ten weeks however in an adult host It was penetrant at a rate of 20% and these tumors were observed and Progressed relatively quickly and had to be collected before day 40 of this experiment Now if we move on to PD-1 Unsurprisingly due to its increased differentiation status and Increased growth is far more penetrant So it has a hundred percent penetrance in a pediatric host and a ninety percent penetrance observed in an adult One other thing of note is that in an adult host these tumors Is onset and progress much faster with the first animals having to be collected around day 20 Whereas in a pediatric host we get closer to day 40 So additionally building off of the fact that PD-1 is so much more penetrant and advances much faster It's not moving PD-1 sub-q tumors are also capable of micro and macro long metastasis And so this is observed in both pediatric and adult populations at an approximate 20% and on the right here you can see a macro long metastasis with the paired histology and that is in a Pediatric host and the bottom picture is in a adult host So in summary Well differentiated and poorly differentiated cell lines exhibit different growth rates and activation of the MAP kinase and the AKT pathways Despite having the same initial genotypes well differentiated and poorly differentiated cell lines exhibit differential penetrance and disease progression in pediatric and adult hosts and We believe that these new models will allow us to evaluate the role of age of onset of disease in regards to development and progression of peploid thyroid cancer And with that I would like to acknowledge my lab particularly my mentor dr. E.B. Franco as well as our postdoc Victoria and our fellow Allison who also helped contribute to this work and I would also like to acknowledge our clinical team and our collaborators and with that I'll take any questions Great fantastic presentation and so we're opening up to the audience for any questions, but just a quick one for you So this sounds like an exciting new model. So I guess two parts like one. What is your next steps? What are you gonna look at with this model? And then two is this just mimicking sort of prepubertal Thyroid cancer as well. Like I noticed you mentioned that it was prepubertal mice and I do imagine that the thyroid cancer It's a continuum and cancer in an 18 year old may be different than cancer than an 8 year old. Yes, so there is So thyroid cancer occurs in pediatrics both pre-pubertal and post-pubertal Pre-pubertal it's more Equal as far as gender prevalence and post-pubertal In pediatric and then also on into the adult host adult age It's much more heavily weighted towards women. So there's definitely some sort of Non-understood hormonal role there and then once you get out to a geriatric population This is what goes back to 5050 It could be adopted for either currently for this specific study We chose this focus on prepubertal, but it definitely could be used for post-pubertal with minor adjustments Hi, Brian Haugen, Colorado. Very nice work and nice presentation Um, I may have missed it but in in the model of pediatric versus adult What was the age of injection? How old were they when you injected them so for the pediatrics, they're four to five weeks old first post-birth so post weaning but pre-sexual maturity and Then for adults, it's 20 to 22 weeks of age and how young can you inject them? You could do it as young as three weeks for sure. I'm you could probably inject younger, but there's definitely between mothers and Rejection and things like that There's a risk for Skimming the study that way because they get it to help me out a little is four to five weeks in my mind It'd be more like kind of an older teenager, right? Not a not a really a young kid in a mouse time, but I don't know. Is that right? It's kind of debated in the field a lot of people so generally speaking Sex differences as far as like sexual maturity is different whether it's male or female male can be as early Depending on your strain six weeks to eight weeks and a female more to eight to ten weeks And so we chose four to five weeks so it's before both of those time points But of course those hormones and they would reach sexual maturity in the middle of the study Which of course is a normal progression that you would see in a pediatric patient that had pre pubertal Diagnosis, they would eventually progress into puberty. Great. Thank you. Okay, great. Thank you so much So our next speaker is dr. Kumari from the NIH and They're going to talk about mTOR signaling is associated with regulation of mitochondrial respiration in thyroid cancer Welcome, dr. Kumari. Thank you so much Hello everyone, my name is Sonam Kumari I work at the National Institutes of Health at Bethesda and the topic of my presentation is mTOR signaling is associated with regulation of mitochondrial respiration in thyroid cancer Starting with the background thyroid cancers are divided into BRAF like and RAS like tumors based on their molecular signature and oncogene driven signaling pathways are involved in the regulation of thyroid cancer metabolism including glycolysis and oxidative phosphorylation So as I mentioned earlier the clustering of human thyroid cancers are done into BRAF like and RAS like based on the molecular signature and you can see in figure a that BRAF like tumors are clustered based on the The MAP kinase signaling is more prevalent in the BRAF like and in the RAS like tumors Both MAP kinase and PI3AKT pathways are involved and in figure B you can see that in the BRAF like tumors there is increased MAP kinase signaling as evident by the increased red color in the ERG signature whereas in the RAS like tumors both MAP kinase signaling and PI3AKT pathways are involved and one important thing to note here is that mTOR signaling is upregulated in the RAS like tumors Next the BRAF RAS code has been developed to quantify if the gene expression profile is Similar to the BRAF mutant profile or the RAS mutant profile and this is based on the quantification of gene Expression based on standardized and the centered around the mean 71 gene signatures With the BRAF like ranging from minus 1 to 0 and the RAS like from 0 to plus 1 If you see the figure on the left There is a clear distinction between the BRAF and the RAS mutant profiles in the thyroid cancer samples Whereas the figure on the right shows the different BRS code for the different thyroid cancer cell lines So coming to the objectives of the study as there is inadequate information on the role of oxfos activation and regulation in thyroid cancer the purpose of the study was to determine association between major oncogene driven signaling pathways and mitochondrial respiration in thyroid cancer So Starting with the methods for this study We analyzed the RNA sequence data of 496 human thyroid cancer tissue samples from the cancer genome atlas for BRAF like cell lines and two RAS like cell lines for the BRAF like cell lines the BRS code range from minus 0.36 to minus 0.72 and the BRS code for the RAS like cell lines range from 0.32 to 0.21 We used an important method for our study which is called the Seahorse mitostress assay and This is a plate based live cell assay in which we we can see the oxygen consumption rate Also known as OCR over time and for this assay We use three different compounds. The first compound is oligomycin which inhibits ATP synthase and it leads to a reduction in the OCR rate You can see it leads to reduction in the OCR rate the second injection is FCCP which is an uncomplicated agent and it inhibits the mitochondrial membrane potential and It leads to increase in OCR and the final injection is a combination of rotenone and antimycin A which is a complex one and complex three inhibitor and it leads to shutdown of OCR and We optimize this assay based on the cell number, the concentration of the different compounds and normalize based on protein content. Coming to the results, we observed that the RAS-like tumors are associated with a higher expression of Oxford's markers as evident by low to moderate positive correlation between BRS and the different Oxford's markers, the components of the respiratory chain as shown in this figure such as cytochrome BC complex, succinate dehydrogenase B and ATP synthase as well as the other components. Next we wanted to check for the activation of the different oncogene drivers such as phosphor AKT, phosphor mTOR, AMPK and ERK. If you see the figure on the left of the western blot, you can see that there was increased expression of phosphor AKT in the RAS-like cell line FTC133 and we observed differential expression of phosphor AMPK in the different thyroid cancer cell lines in which TPC1 had the lowest expression. We also observed increased expression of phosphor ERK in one of the BRAF-like cell line which was BCPAP and if you look at the expression of phosphor mTOR in the different thyroid cancer cell lines, you can observe that there was increased expression of phosphor mTOR in the RAS-like cell lines which suggested activation of mTOR signaling pathway. Next we wanted to see what is the correlation between the thyroid cancer metabolism and the mTOR signaling pathway. So if you see the figure, the first one, there was increased positive correlation between mTOR and the BRS core and figure B shows that there was increased correlation between basal OCR and the phosphor mTOR and figure C shows that there was increased positive correlation between maximum OCR and phosphor mTOR and the last one shows that there was a trend of correlation between ATP production rate and phosphor mTOR. So because we saw increased expression of phosphor mTOR in the RAS-like cell lines, the next step was we hypothesized that the phosphor mTOR inhibition in the RAS-like cell lines might lead to less oxphors, so for that we used an mTOR inhibitor which is rapamycin for our study and in the first figure you can see that there was decreased proliferation rate in all the examined cell lines after treatment with rapamycin and rapamycin also decreased the expression of the downstream target of mTOR which is P70S6 kinase. Next we also tested the effect of rapamycin on the oxphors rate through seahorse analysis and we observed that there was a decreased oxphors rate after treatment with rapamycin in the cell lines which had high phosphor mTOR expression, while if you see the figure on the right there was no significant difference in the BRAF-like cell lines. So the next step was to also knock down mTOR in the cell lines which showed high expression of phosphor mTOR which was FTC133 and here we performed the knockdown through CRISPR gas technique and we selected the clone which showed significant down regulation of mTOR after knocking down in FTC133 and as you can see here in the seahorse mitostress assay we saw significant down regulation of oxidant consumption rate in the cell line which had low mTOR expression and the bottom figure shows the quantification of the seahorse mitostress assay. So we also checked for the expression of, we used another mTOR activator which is a leucine and here also we observed that there was increased proliferation of the cells, the different thyroid cancer cell lines after leucine treatment and there was increased expression of the downstream target of mTOR which is P70S6 kinase in the cell lines which had more mTOR expression and in the seahorse analysis you can see that there was increased oxidant consumption rate after treatment with leucine in the cell lines which had more mTOR expression, sorry we saw that activation of mTOR through leucine led to increased basal OCR and maximum OCR in the cell lines which had low baseline mTOR activation while the cell lines which had high mTOR activation did not show any significant difference. So coming to the conclusions of this study, mTOR signaling is associated with the regulation of mitochondrial respiration as its inhibition decreases oxfose rate while its activation leads to increased mitochondrial respiration and the change in mitochondrial respiration might be one of the mechanisms of thyroid cancer growth regulation caused by medications targeting mTOR signaling. So I'd like to thank my supervisor Dr. Johanna Klubo and our research team and Metabolic Diseases Branch at NIDDK and thank you all for listening to my talk and I'll be happy to take any questions if you have. Thank you, it looks like we already have a question so I'll open up to audience. Thank you very much, very beautiful presentation. Thank you. I have a question about the tumor cell metabolism. So as you probably also well know, the cancer cells depend, if you look at the metabolic balance, energy balance, they depend much more on aerobic glycolysis. So can you say something about this? How was this in your experiments? Because we have shown also that for instance patients who have PTEN deficiency and have an activation of mTOR in their cells, in their tumors as well, they also produce high amounts of lactate. Could you perhaps speculate on this? Okay, so there is a newly identified phenomenon which is called the reverse Warburg effect or the metabolic coupling. So in that case, the lactate which is produced by the cell that is utilized for growth, so instead of glycolysis, the lactate is used as a nutrient for its growth and higher metabolism and it has to be done through oxfords. Great, thank you very much. So we have one more last presentation. So I'd like to invite Dr. Perez from the University of Campinas. She's going to represent her group and talk about the identification of micro RNAs critical to the lymph node metastatic process of thyroid cancer. Welcome. Thank you. Can I have my slides? The upper one. The third. Yeah, this one. So I'm Laura Sterian-Ward. I'm talking on behalf of Karina Perez and our co-authors group from the University of Campinas in Brazil. So we know that papillary thyroid carcinomas are the main responsible for the increased incidence of thyroid cancer that we have been witnessing the last decades, but most of PTC cases are indolent and have a favorable outcome. However, lymph node metastases are not uncommon and they have been associated with risk of tumor occurrence and bad outcome, especially in the elderly patients. The identifications of these lymph node metastatic prone patients is essential in the management of these patients that can vary from just an active surveillance to more aggressive and invasive therapies. Micro RNAs are small, stable molecules that have emerged as important tumor biomarkers since they participate in a series of biological processes and are important in the regulation and control of key genes in the metastatic process. So our aim in this study was to identify deregulated micro RNAs that could be related to lymph node metastases and hence the poor prognostic patients. We started with bioinformatic analysis using the gene expression omnibus database from NCBI and we looked for micro RNAs data sets that included normal and PTC cases with and without lymph node metastases. We also used another type of tumor, the medullary thyroid carcinoma data set with, again, tumor and normal tissues. And we identified in the PTC data set 25 deregulated micro RNAs. In the medullary thyroid cancer data set, there were 41 deregulated micro RNAs and 14 were commonly deregulated in both types of tumors. Out of these 14, there were three micro RNAs that were deregulated in the lymph node metastatic PTC patients but not in the PTC patients without lymph node metastases. These micro RNAs were, therefore, our focus in the next steps. So we validated this data in the TCGA database and, in fact, we saw that micro RNA 148A was downregulated in the primary tumor in relation to the healthy control and in the lymph node metastases. Also, this mirror was associated to more advanced cancers with more advanced tumor stages and with tumors with lymph node metastases but not with distant metastases. We were not able to find the data on mirror 199, neither 3P nor 5P. So we proceeded with the investigation of the predicted genes of these three micro RNAs using mirror walk database. And we identified nine predicted genes and, again, we validated these genes in the gene expression omnibus dataset from NCBI. They're trying to associate micro RNAs with mRNAs of the predicted genes. We were able to identify five predicted genes, SNN, PVRL1, FBX028, and IDGA3 gene in this database. So PVRL1, that's also called Nectin1 gene, in fact, was upregulated in PTCs with lymph node metastases. And the same occurred with IDGA3 gene and FBX028, whereas SNN was downregulated in PTC with lymph node metastases. Then the next step was to validate these bioinformatic data on a bench study. So what we did was to look for the influence of these micro RNAs on cell migration. And we used a wound healing assay employing two types of cells, TPC1 and BCPAP cells that we transfected with mimetics of these three micro RNAs. And here you can see our results in TPC1 cells transfected with the mimetic for micro RNA 199A5P. You can see in the bottom of the slide the 24 hours result comparing various concentrations of the mimetic with the mock assay. Here represented in a graphic form and also in percentages. There is a nice difference between the mock and the mimetics of these 199A5P micro RNA, as you can see in all concentrations. The same occurred with the BCPAP cell transfected cells. Here again represented in the graphic and the percentages of the reduction of the wound healing rate compared to the mock. MIR1948A5P also produced important results in TPC1 cells reducing wound healing rate compared to mock. And also the same occurred in BCPAP cells. As you can see in percentages and in the graph form. However, MIR19983P, you can see it in the bottom line, did not reduce the migration neither of TPC1 nor of BCPAP cells. So, in summary, we showed that MIR199A5P and MIR148A5P are important factors. They can influence cell migration. But we were not able to demonstrate this with MIR19983P. In fact, literature already reported MIR199A5P as an inhibitor of the progression of PTC cells. They found in this publication that this micro RNA was less expressed in cancer tissues in comparison to normal tissues, was less expressed in TPC1 cells. And the restoration of this micro RNA increased the number of migrating cells. The MIR19983P was also described in this paper as related to PTC aggressive cancers. But we were not able to replicate this data on our assay. Concerning MIR148, we are, as far as we know, the first to describe this micro RNA as important in papillary-tired cancers. But it was already described in pancreatic dutal adenocarcinomas and in aggressive gastric cancer cells. So, in conclusion, we demonstrated that both with bioinformatics and a bench assay that we are actually confirming with a Boyden-Chamber new assay that these two micro RNAs, MIR19985P and MIR148A5P, are important concerning cell migration. And they may become useful biomarkers of PTC patients prone to lymph node metastasis. Thank you very much for your attention. So, thank you very much. Clinically, this seems very important. My question for you is, do you see this being used in risk prediction models? And if so, do you know if it's independent from other known co-variants that correlate with lymph node metastasis or pathologic? Yeah, the idea is to use it in human patients. And we are currently undertaking a prospective study with circulating micro RNAs that will possibly become important biomarkers of lymph node-prone metastatic patients. That's the idea. Great, thank you. And we have a question from the audience. Hi, I have a question. Like you said that MIR19983P, MIR19985P, and MIR148A5P, does it have a role in migration? Does it have any role in adjustment of the immune responses? And that's how the migration has been made? I don't know. That's a nice point. Thank you. So, in your study design, you selected the three micro RNAs that were common between PTC and MTC. Yeah, MTC was a control for important micro RNAs that could be related to metastasis. So the advantage of that approach is that you will identify more kind of common mechanisms. Exactly. But the disadvantage is that you don't detect PTC-specific mechanisms. So I was wondering, is that a next step? Yeah, perhaps. I mean, we selected the three micro RNAs that were characteristics of PTC lymph node metastasis. So they must be important for these patients. Thank you very much. So if there are no further questions, thank you very much again. And I would like to thank also on behalf of my co-chair, thank all the speakers again for their excellent talks and for sticking to the time limit. And thank you for your attention.

thyroid neoplasia

thyroid cancer

immunogenomic marker

papillary thyroid carcinoma

integrins

molecular targets

thyroid cancer imaging

mTOR signaling

mitochondrial respiration

microRNAs

lymph node metastatic process

potential treatments