 I'd like to briefly describe some of the research we've been doing in my lab, looking for novel therapeutic targets within the RCC kinome, if I could figure out how to go forward. There we go. No disclosures. So kinases, I think, as you all know, are enzymes that catalyze the phosphorylation of various substrates, including proteins, lipids, as well as nucleotides. Obviously, the protein kinome is the best characterized in mammals. Kidney cancer has obviously been defined by therapeutic successes targeting such kinases as the VEGF receptor tyrosine kinases, as well as the intercellular serine-3-in-kinase MTOR. Here's a handful of now FDA-approved drugs, which have obviously done a very good job targeting these. But that leaves about 600 other protein kinases that are targetable, and so we sought to explore what about the rest. We don't like to leave anybody out in my lab, so. So we undertook a SI kinome screen, which is a high-3-put screen using three 84-well plates. I won't be labored at the point here, but basically, siRNAs are seeded into three 84-well plates. They are mixed with transfectionary agent, as well as cell lines of interest in reverse transfection, and then allowed to incubate for approximately 96 hours, and then read by cell-tidered glow. And then the percent activity, or essentially the percent lethality, is adjusted for positive negative controls, which are ubiquitin B and GAPDH. So here are the results of our two cell lines that we screen, the 7860 cell line and the RCC4 cell line, both of which are VHL null. And essentially, these are waterfall plots with the most lethal hits being towards the left, and the least lethal hits being towards the right. And I've highlighted the four Janus kinase family members, Jack 1, Jack 2, Jack 3, and TYK2. And you can see that both TYK2 and Jack 2 were relatively highly lethal in both cell lines that we screened. We wanted to validate this, and through independent siRNA sequences, validated that both Jack 2 and TYK2 in the RCC4 and 786 cell lines were highly lethal. We went searching through the literature and noticed that Ryan Corcoran and MGH had published a paper looking at targeting the Jacks that pathway in pancreatic adenocarcinoma. This is a figure from his paper that actually shows data from Cyril Benes' large panel of cell lines in which he's treated over 500 cell lines of various organ sites with various numbers of both targeted kinase inhibitors as well as chemotherapeutic agents. And these cell lines here are ranked from most sensitive on the left to the least sensitive on the right. And you can see that kidney actually surprisingly was thought to be highly sensitive to the Jack inhibitor AZ960. So again, I hypothesized that the Janus kinase family might be activated in renal cell carcinoma. We compared the levels of phosphorylated TYK2 and phosphorylated Jack 2 to the immortalized renal proximal tubular epithelial cell cell line RP-TECH. And as you can see here, both in 786 cells as well as RCC4 cells, there were elevated levels primarily of TYK2 but as well as phospho Jack 2. We also looked through literature and found that there were gene signatures associated with TYK2 activation. And we took two large data sets of clear cell renal cell carcinoma primary tumors and we looked by gene set enrichment analysis for GSEA from Richmond of the TYK2 signature in tumors versus normal. And in both cases we saw that there was a high enrichment of the TYK2 activated signature in clear cell renal cell carcinoma tumors versus normal. This is better visualized here and this is more or less to give you a reference for how enriched they are relative to normal. And we essentially made a compilation score of the TYK2 signature and we ranked them from highest to lowest, highest being on the left and lowest being on the right. And you can see on the top tract in Duke versus Carolina blue that all the Carolina blue samples which are the normal samples from TCGA tended to be clustered on the right hand side suggesting that the normal samples were not highly activated in TYK2. However we obviously thought this was a bit disingenuous to think that all renal cell carcinomas have activation of TYK2 and if we clustered the TCGA tumors using the TYK2 gene signature we saw was there was a clear subset of tumors that likely had relatively high levels of TYK2 activation whereas some of the other tumors may not and therefore we conclude that there is clearly heterogeneity in TYK2 activation within renal cell carcinoma. TYK2 module the gene signature appear to be prognostic so if we rank ordered the tumors from highest activation to lowest activation and bisected them at the median level we could see that there was a tisly significant survival difference in these TCGA tumors with those with a high TYK2 signature doing worse. But then the quick big question obviously is is TYK2 functions irrelevant. So we first began to explore that by knocking down TYK2 or JAK2 via SiRNAs and you can see in both 7860 cell lines as well as RCC4 cell lines there was significant cell growth inhibition in vitro. Primarily TYK2 seem to be doing a little bit better job. We made stable cell lines expressing SHRNAs against TYK2 as well as JAK2 and again we saw that both TYK2 and JAK2 knocked down cells had higher growth inhibition than the nonspecific controls. So there are actually a reasonable plethora of Janus kinase inhibitors out there thankfully to the hematologic malignancies community which have developed them around the fact that JAK2 is highly mutated in myelopliphrid disorders. We had both a preclinical compound in late stage phase 2 trials TG-101348 as well as the FDA approved INC-18424 also known as JAKA-FIA-RUX-LATINIM. We actually calculated the AG-C50s of these two compounds to renal cell carcinoma cell lines and we treated the cell lines for 30 minutes or 24 hours and we were surprised to see that while TG was able to abolish phosphorylation of JAK2 and TYK2 at 24 hours, sorry, INC really wasn't able to or did not really down-regulate signaling at that time point. When we tested the efficacy of these drugs in vitro, we saw that the TG compound as expected based on the data I just showed did a better job at inhibiting growth on plastic relative to the INC or JAKA-FIA compound. And again, if we treated 7.860 xenografts with TG or INC, we saw that TG did a better job as expected at inhibiting tumor growth in vivo. So now we had some evidence that JAK inhibition or Janus-Kynecine inhibition may have some therapeutic relevance in renal cell carcinoma. We wanted to know whether or not we could actually combine Janus-Kynecine inhibition with any currently FDA approved therapies. We chose to focus on mTOR primarily because we believe that VEGF, right or wrong, that VEGF receptor inhibition is primarily working through an anti-angiogenic effect and therefore not a cell autonomous effect. So we first sought to see whether or not treatment with allosteric mTOR inhibitors such as rapamycin might induce any type of kinase feedback, as has been shown for other inhibitors such as MAC inhibitors, PI3 kinase inhibitors, AKT, et cetera. What we saw was that in a time-dependent manner cells treated with rapamycin appeared to induce phosphotylic A2 as well as phospho-JAK2. Stat1 is known to be a direct target, phosphorylation target of TYK2. We saw that in cells expressing a non-specific SHRNA that rapamycin-induced levels of phospho-stat1. To some degree, we could block this rapamycin-induced up-regulation of phospho-stat1 by treating with knockdown of TYK2 but not of JAK2, suggesting that TYK2 is inducing this phosphorylation mark. And then we looked in vitro as well whether or not the combination of mTOR inhibition plus Janus kinase inhibition would be of any value. And we saw that relative to control as well as any of the single agents that the combination of rapamycin plus Janus kinase inhibition with TG was better. So what signaling pathways does TYK2 regulate? I just showed you some data of which we have more that it regulates stat1 signaling. We went about this in a relatively unbiased manner by using phosphokinase arrays from R&D systems. And here we either expose these membranes which have 43 different phosphotiracine proteins spotted in duplicate to either lysates that were derived from 7.860 cells expressing a non-specific hairpin on top. In the middle is 7.860 cells expressing knockdown of TYK2, and the bottom is of JAK2. And to be honest, there weren't dramatic alterations in phosphorylation status of these proteins. But we did note that there was a block of phosphoproteins here that appeared to be significantly dampened in the SH-TYK2 cells. We densitometry calculated this, and it appeared that this was the stark family kinase of proteins, and by densitometry our hypothesis had held up. We looked at this on the cellular level as well. And we saw that in both 7.860 cells as well as RCC4 cells, knockdown of TYK2 very specifically decreased phosphorylation of the stark family kinases, whereas knockdown of JAK2 did not affect the stark family kinases at all. And as well we used a Luminex Beteray assay, which is able to differentiate the stark family of kinases. And of the four that were readily detected, there were significant decreased levels of the stark family kinases in the TYK2 SRNA cells over the control or JAK2 cells. So now that we've connected TYK2 to both Sark as well as STAT1, we wanted to begin to globally assess the kinomic landscape of renal cell carcinoma. And to our knowledge, there wasn't a very good way to do this globally prior to the advent of some homegrown technology by Dr. Gary Johnson at UNC. And Gary Johnson has used this approach to essentially look at the dynamic reprogramming of the kinome in the setting of MEK inhibition and specifically in triple negative breast cancer. And his lab had really shown that in the setting of MEK inhibition that PI3 kinase m-torn inhibition was also up-regulated and able to be targeted. So how does he do this? We've abbreviated it by calling it MibMS. Mib stands for multiplex inhibitor beads. And essentially there are a number of kinase inhibitors that can be covalently bound to Cepharose beads. These are layered through a Cepharose column. Tumors are prepared and their lysates are run through the column. The point here being that activated kinases are captured within the column. They can then be eluded and run by mass spectrometry, which is the MS portion of MibMS. And one can do this in fourplex thanks to the utility of eye track. And then obviously there's a number of issues with normalization, cross runs, et cetera. So we've gone about that by making a very large pool of both normal kidney as well as tumors that are run each time as a standard. This is a very small slide just showing that we do believe that the assay overall is relatively reliable and that if we run either normal or tumors through this in replicate, we can see that the overall R value is quite high. So not to tease you, but we don't have a lot of data. This is from the first 30 tumors. This is on a log 10 scale. We do see that there is obviously up and down regulation of the Kynome as expected. We were obviously most interested in SARC given that TYK2 is regulating SARC. And we see that three of the SARC family kinase members tend to be relatively dynamic and also highly expressed, including HCK, LCK, and Lynn. So in summary, I think what we've shown you is that in clear cell, renal cell carcinoma, we see clear, we believe clear activation of the TYK2 Janus Kynase family member. We think there's activation of JAK2 but have yet to go down that pathway to figure out what JAK2 is actually doing. TYK2 appears to be up regulating STAT1, which we know is involved in survival from past studies. Whether or not that's true in renal cell carcinoma, we have yet to determine. And finally TYK2 also up regulates the SARC family of kinases, which we know is a critical mediator of invasion and potentially metastases, again, which we need to show is operative here. We see that the Rappelogs appear to up regulate TYK2 and JAK2, whether this is a sort of a direct effect of Kynome reprogramming in the classic sense or it's a reflection of increased secretion of various cytokines or chemokines, I think we have yet to determine. And then finally, we're hopeful with MIV and MESS, we'll begin to get a better overall picture of the Kynomic landscape of renal cell carcinoma, in addition to identifying other tractable targets. Just like to thank the members of my lab in particular, Bhavani Krishnan, who's done a very good job carrying this project out. Gary Johnson has been a great collaborator at UNC with his group, Ross Levine at Moroslone Kettering, and then Takeshi Shimura here at Loyola. Thank you.