 Thank you very much. I'd like to thank the planning committee for the opportunity to present on behalf of the thyroid group our work today. So today we're going to talk about the view of the data from 30,000 feet. But before I do that, I felt obligated to give a little background. So I was thrilled when the TCGA announced that we're going to do thyroid. Thyroid cancer can sort of get shortchanged in the big scheme of cancer. I think one of the reasons that they did is because thyroid cancer is clearly on the rise. However, the mortality of thyroid cancer is not that high. It's actually over the same period has actually trended down flat and now is rising up. But clearly it's one of the few cancer types that is actually increasing in incidence. So I am a professor of pathology, so I have to show some histology. No, just kidding. This is important because the papillary carcinoma, which is what our project's on, has three main types and it'll come through in the data. So I really wanted to spend just a minute to express this. So papillary carcinoma gets its name from the tumor on the left here, which is a tumor that has finger-like projections or papillae. But not all papillary carcinomas are actually papillary in terms of their architecture. There's a group here that we recognize that are called the follicular variant. Not to be confused with follicular carcinoma, but the follicular variant of papillary carcinoma. And then there's a third main type, the tall cell variant, in which the cells are more columnar than cuboidal. And so we recognize these three variants, and it's kind of important. We know from lots of papers that these have different genetic profiles and different gene expression profiles, and that will also come out in our data set. These are the common genetic defects in thyroid cancer. Now we're just looking at papillary carcinoma. This whole chart shows the whole spectrum of thyroid cancer, but it's worth looking at. This one on here is post-Ternobal, so radiation-induced cancers. So ret rearrangements are common in papillary carcinoma, even more common in radiation-induced areas. BRAF mutation, very high rate of V600E mutations. Some small rate of BRAF rearrangements, which we'll see. NTRK rearrangements. RAS mutations are quite interesting. So notice it goes from zero to 21%. So depending on the cohort of papillary carcinoma, you'll get different numbers. But we definitely know that the follicular variant is enriched for RAS mutations, just as follicular carcinoma. Pax-8P-pargamma rearrangements are thought to be present mostly in follicular carcinoma, but there's been a few recent studies that show that they can also occur in some papillary carcinomas, again, the follicular variant. And then beta-catenin and P53 mutations are sort of things that occur down here when tumors show histologic progression to poorly differentiated and undifferentiated carcinoma. So that's the genetic landscape. There's a big issue for a big opportunity, a big issue for the TCGA. So if you genotype thyroid cancers, differentiated thyroid cancers, you only find one of these driver mutations in about three-fourths of the cases. So we don't know what those other mutations are. So this project is all teed up to try to find those other mutations. And this is important not just for understanding the cancer biology, but there are already cancer diagnostic tests on the market based on genotype. So if we can expand the genotypic universe of papillary thyroid cancer, those tests will get better. So again, this is the first look at the data. We did a data freeze about just less than a month ago. Much of what I'll show you today was generated by the FireHose platform. We're really just getting started, and Gaddy wanted me to stress that much of this has not been validated. Here's the sample counts. We're pretty far along in the project, and the remaining cases are sort of in the pipeline. So we're thinking we might just wait until we full it out to the full 500, but we're still discussing that. Here's some of the clinical data. Thyroid cancer occurs in a younger population. The mean age is 46. You know, I'm sort of envious when I saw those survival plots. That's really not so easy in thyroid cancer. There's not a lot of deaths. To do a good outcome study in thyroid cancer, you sort of need 15 years of follow-up. And so we're not going to have too many Cap and Meyer plots anytime soon. You can see we've had one death so far. Like in all endocrine diseases, way more common in females, almost three to one. And we have a good breakdown of the different histologic types. So here's some of the data. So again, I want to stress that papillary carcinoma is a differentiated tumor. And overall, it has a low mutation rate. So here's the mutations per sample. It's generally uniform across here, but you can see there's a few samples that are jumping up and showing that they have a much higher mutation rate. The sequencing coverage is outstanding. And then down here, we can see the rate is quite low. Please, someone showed that plot earlier. I don't know if anyone looked. I looked for thyroid. It was definitely on the left end of that plot away from the head and the excrements cancer. So it's a low mutation rate. Not surprising because it is such a well differentiated tumor. So this is a great slide that integrates a lot of the data. And I'll spend a little time going through this. This shows the common mutations with BRAF here, representing 57% of our cohort. We have some RAS genes. And notice the BRAF and the RAS genes and the fusions down here are all mutually exclusive, which we've known in thyroid cancer, the thinking being that having more than one of these doesn't add any biological advantage. The histologic data is up here. And so it's hard to see, so I'll explain it. So the BRAF tumors are enriched for the classical type and the tall cell type, which is consistent with the literature. The RAS mutant tumors are almost all the follicular variants. Again, this is consistent with what we've known. The tumors with the fusions are mixed between classical type and follicular type. And then these so-called wild type tumors where we don't know the driver mutation have really a smattering of histologic types. So immediately we're seeing a very strong correlation between genotype and histologic type. And so that gives me a lot of confidence that this is a quality data set. We could see the fusions, as I mentioned briefly, are here. RET fusions are the most common, but we're also picking up some Pax-8-P Pargamma, NTRK, and a few BRAF fusions down here. And again, mutually exclusive with BRAF-RAS. I want to bring your attention to this point right here, which is this initiation factor. And it's also mutually exclusive with these other common mutations and the fusion. So that's telling me, suggesting to us that this is a biologically significant mutation, even though we've not validated that. And then the copy number changes are shown here. Notice across the BRAF cohort, there's not a lot of copy number changes. Across the follicular variant or the NRAS cohort, there's not a lot. But notice there's a band right here that represents chromosome 22. So there's an enrichment for loss of chromosome 22 in these RAS mutant tumors. The tumors with fusions are also pretty quiet. And then the remaining 20%, the so-called wild type tumors, can be divided into two groups, those with more changes and those that are pretty silent. So the first thing I want to do as a pathologist is I want to go back and look at these tumors over here that don't have a lot of changes and just review their pathology. Because truth is, endocrine pathologists, we fight over diagnoses a lot. So we need to look at that. There's also messenger RNA differences that we know, some genes here, and then microRNA, which I'll show a little bit more. So this tells a very compelling story, this one slide, that integrates much of the data and shows that this is a quality data set. Yes, we've replicated some things that we've known. But the integration of all the data in this setting, I don't think anybody has come close to doing. So this is that new potentially novel mutation, this X-linked translation initiation factor. It's very interesting, there's no known role in thyroid cancer. And in fact, we could find just one other synonymous mutation in the cosmic database. So this will take validation, but it's certainly an interesting finding. Fusions, I showed some fusion data. Truth is, we're still going through this. There's much work to be done on fusions. This was some data from an earlier analysis that showed this fusion right here, which is in the business called RET-PTC1, which is the most common version. And then we have some more novel things, this ETv6, NTRK3, which, in speaking with Jim Fagan, he's validated this in an independent cohort from the Ukraine, both in radiation and non-radiation cases. So we think this is a real finding. And then Pax-8-Pepar-gamma, as we'd expect in a few cases. Onto the methylation work, the methylation profiling identifies four classes of tumors that generally correlate again with histologic type and mutational status. So we can see there's two groups over here on the left that are mostly the classical type and the tall cell type. And they are enriched with BRAF mutations. And on this side, which is more similar to the normals, we have an abundance of the follicular variants and tumors with RAS mutations. So the methylation work is integrating nicely into the same compelling story. A few interesting molecules, Mir21, which you heard a little bit about this morning, and Mir146B, both been worked on in thyroid cancer. But not at the methylation level, and here we show inverse expression between methylation and expression. So these are interesting leads for us to work on. And then as a thyroidologist, we always like to look at thyroid-specific genes. Not because they tell us that much about the cancer biology, but more they give us thoughts about progression and possibly loss of radioactive iodine treatment. And so that's a big issue in our field when tumors become a little less differentiated and no longer respond to radioactive iodine. So here we can show one gene, thyroid peroxidase, that actually shows a differential methylation profile based on the different types, classical, follicular, and tall cell. And we're from my group and others, we know that TPL goes down in BRAF mutant tumors compared to the follicular variant. And sure enough, methylation is playing a role here. Again, inversely expressed between methylation and expression. So that's a potentially interesting story. And we need to look at other genes in the thyroid like the sodium simporters, sodium iodine simporters and others. MicroRNAs, we can use various tools to cluster these. Here's a cluster driven by Mir21. So we can get four types or seven types. And notice the four types is actually showing some, again, correlation to histologic type, which we know reflects genotype. So I think the microRNAs will fit in nicely. This needs some work, though. If you look at the British Columbia software versus fire hose, you can generate different clustering algorithms and then actually compare them head to head and start to make some sense of how much you believe them. This is kind of interesting. So this is the British Columbia software versus fire hose. Four groups versus three. And you can see some cohorts line up nicely here and other cohorts get sort of scattered into others. So we have some work to do to try to figure out what's the most meaningful way to look at the microRNA data in a global sense. But clearly there's some useful data in there. And then cancer regulome, Lisa Ipe was kind enough to prepare some slides for us in which they look at all the factors, all the measurements throughout the data set. And we just started with something simple, like histologic type. And she was able to show that there's many, many, many associations shown here. And sure enough, some of the more interesting ones is mere 21, which I just showed you, what had differential methylation expression, and here's BRAF. So these are all potential leads and we'll certainly be using some of these software tools, which are at our disposal. So in conclusion, I would argue that we're making good progress. I think we're progressing as planned. I think the cohort is outstanding and truly representative of the disease. I make this point because that's not true for every paper in the literature. People cherry pick cases and what they're publishing is not representative of the broader disease. So I really do think this cohort is accomplishing that. We have a low overall mutation rate with few copy number changes, but we have a few tumors that have increased copy number changes, which we'll spend more time working on. And we've uncovered and reproduced strong associations between the tumor morphology, its genotype, its gene expression profile, copy number changes, and methylation status. And we've uncovered many interesting novel leads, mutations, and gene expression patterns to keep us busy for quite some time. So there's much to do. We still have to decide whether we're going to fill out the whole cohort and publish where we're at now. But I do think we're on track for our first paper in the middle of next year. As with all the projects, there's many, many people to thank, and I would hate to go through these individually because I'm sure I've left some people out, but clearly I'd like to thank Gaddy Getz, who I've not met yet. So Gaddy, if you're here, come up and introduce yourself. But thank you very much. Oh, there you are. Tom, thank you very much. You think that the fact that so many of them have BRAF mutations would suggest that the BRAF inhibitors might be a therapeutic approach for them? Well, I wish maybe Jim Fagan can answer that. He's more in tune to the clinical trials. There's certainly many clinical trials ongoing. Steve Sherman at MD Anderson is working on that, but I've not heard, it's not distilled down into like this home run where people are ready to give up radioactive iodine. I know Matt. Sure, so just a couple questions and then a comment. My first question is about the relationship between thyroid carcinoma and lung adenocarcinoma, because I think there are a number of similarities. First, the major, as you very well know, the major marker in one of the leading amplified genes in lung adenocarcinoma was the thyroid transcription factor one gene, suggesting potentially some common etiology. And, you know- There's also retry arrangements, too, that are common. There's retry arrangements, BRAF and RAS mutations. And I'm wondering if you've started to look at commonalities between the diseases or have thoughts about how to do so. Certainly that would be a good comparison, but there's some things that jump out, there's very few EGFR mutations in thyroid. So I think the similarity is there, but I don't know how strongly it'll hold up. And I think my second thing is more of a comment, which is I think if the rest of the cancer community could do as well as the thyroid cancer community has done, we probably wouldn't need TCGA or a National Cancer Institute. So we were very struck by the survival data. Yes, yes, well, that's not to belittle thyroid cancer. Most of the deaths though are actually in those poorly differentiated and anti-plastics. If I showed those survival plots, the survival plot for anti-plastic is measured in six months. So thyroid cancer represents the whole spectrum and I'm hoping that we're gonna get to a more aggressive thyroid cancer project, which will then nicely integrate right into this. Because we have many cases that have both papillary carcinoma sitting right next to anti-plastic carcinoma. It'd be nice to profile both of those in parallel. Thank you, Matt. Could I ask one last question? Yeah. Thyroid cancer is one of the most interesting ones with respect to heritability and familial syndromes and sibling risk. And it's been in the past discussed that the outcome may be related to whether the early onset family driven cases versus the more sporadic later ones. When you look at the data set you've put together, are you able to in any way parse out or do you have information on the heritability in terms of family related cases or the like? So we have to separate obviously medullary thyroid carcinoma, which has a much stronger familial association than sort of follicular cell thyroid cancers. I know the group at Ohio State has worked on this. There's some germline mutations of, I believe, TTF1 that make you susceptible to papillary. So there are familial cases of familial papillary carcinoma, but it's not nearly as strong as medullary. That's something that I think we'll get around to looking at, but it's not something that's gonna jump out at us right away. Thank you.