Good morning, everyone. I'm Jeff Drazen, and this is the panel on decoding cancer. So when I was 16, my father was diagnosed with gastric cancer. He was dead within a year. The doctor said there was nothing that could be done. That was 1963. In 1984, I was junior faculty at the Brigham Hospital. And I had a patient with lung cancer. That was my specialty, was pulmonary disease. And when we diagnosed his cancer, there was surgery and some chemotherapy. But it did very little for him. Then within the past year, I've had a patient who was in his 40s. It never smoked cigarettes and developed lung cancer. And he thought he was going to die within a month. But it turned out that his particular tumor was a responsive tumor. And now two years later, he's doing remarkably well. And part of the reason for this success is that we as a community have begun to decode cancer. It's no longer a monolithic thing. It's no longer a simple death sentence for everyone. In this morning's panel, we're going to be talking about the progress that's been made. And in the past 10 years, the progress has been tremendous. And so what we'll do now is we'll introduce our four panelists just briefly. And then we'll get into the meat of it, how we've begun to decode cancer. So first to my left, Textu Chao. Good morning, ladies and gentlemen. I'm Shiloh Chao from Chinese Academy of Medical Sciences. So pleased to be here. I studied and worked in Shanghai for 30 years. Actually, I'm the immunologist. Two million area, I worked. One is the innate response and inflammation. Another one is about the cancer immunotherapy. As the immunologist, I'm so pleased to see the movie demonstrated by Francis. How the T-cell can recognize the cancer cell and then cure it. And so we have to understand what's the. Just a brief introduction yourself. Yeah. So now the major task of my now is being the president of Chinese Academy of Medical Sciences. So trying to work with the medical communities in China in the world to benefit the people. Thank you. Catrine Bosley. Catrine Bosley. I'm the CEO of Editas Medicine. And I've been in the biotechnology industry for about 25 years. I studied science as an undergraduate, but I've been in companies ever since really working to translate new science into medicines. And in cancer, I've done a lot of work, but a number of other therapeutic areas as well. Lydia Sohn. Hi, I'm Lydia Sohn. I'm at UC Berkeley, the mechanical engineering department. My background is in physics. And I've made a translation over into medicine and biology. It's a very exciting time for us all, I think. In Francis Collins. I'm Francis Collins. I'm the director of the National Institutes of Health in the United States. I started out as a chemist, changed my mind, went to medical school, got interested in genetics. Had the privilege of leading the Human Genome Project, which produced the first complete sequence of the human genome in 2003. And now as the person who in the US oversees the government's investments in biomedical research, I find that cancer is one of the areas that is of the greatest excitement and the greatest rapid movement scientifically. So it's a thrill to be part of this panel with these other distinguished folks. I'm going to ask the technical people if they could turn off the background movies here. And Francis, start off. How do we decode cancer? Well, let me just do a quick little setting of the stage of why this is such an exciting time in cancer and what we have learned about it. So if we can have the PowerPoint, I'm just going to walk you through very briefly. This is not going to be a lecture. Don't panic. What it is that leads us to say that cancer is a disease of DNA. So can I have the PowerPoint up on the screen on the side, please? Basically, we have learned as a process over the last 30 years that what you see here in this microscope slide, which are cancer cells growing, which is about the only thing that we could have said in the past about cancer, is that you could look at it under the microscope and it looked abnormal. And the cells were invading where they weren't supposed to. What's really driving that? Well, it happens because of mutations, misspellings in DNA. Here you see DNA spilling out of the nucleus of a cell. And if you zeroed in on it, of course, it is this amazing information molecule of all living things. It has a simple language. There's four letters in its alphabet, A, C, G, and T. But if there's a mistake in that DNA in a place that causes a cell to grow when it really shouldn't have, then you could have cancer as a result. Very important to keep in mind, though, that takes usually more than one glitch in a cell to cause it to go from being normal to being malignant. It's a multi-step process. So most malignancies have multiple mutations, invulnerable places, each of which is giving that cell an advantage over its neighbors and ultimately the potential of spreading outside of the organ where it started. So as we now really try to do what we can to take apart cancer and figure out better strategies for treatment, we're able to use this kind of information to really see what are the drivers at the basic molecular level of the malignancies that happen in people. And what we're learning is that it really doesn't matter so much what organ system your cancer arose in. What matters is what are the mutations that are specific for that cancer. Because we have now an increasingly long list of drugs that specifically target some of those mutations. Jeff talked about his patient with lung cancer. I'm guessing that patient who's now lived for two years had an ALC mutation or maybe an EGFR mutation, which is one of the ones that would be driving that in a lung cancer for which we have a targeted therapy. And so when you are in that situation and you know you are, this is moving away from one-size-fits-all chemotherapy to a specific, smart kind of bomb that goes straight to the heart of the problem. We will talk, I'm sure, about whether that is sufficient or whether you can get remissions out of that, but you often don't get cures. The other thing I quickly want to touch on is this revolution that's happening in cancer immunotherapy. Because your immune system's pretty good at finding abnormal cells and getting rid of them. Some people say, we're probably getting cancer every day, but we don't know it because the immune system cleans up those cells before they have a chance to grow very far. But cancers have a diabolical ability to be able to suppress the immune system and cause it to go to sleep. And we have new therapies that are now making it possible to release the brakes and let the immune system do what it needs to. And I just wanted to show you a rather cool video of what that looks like when a T cell, which is part of the immune system that's particularly aggressive at going after a cancer cell, gets activated. So can we run the video, please? That's a T cell, all lit up and red. And you can see how busy it is. This is migrating around in a laboratory culture dish so you can watch it. And it's searching its environment. It's moving constantly. It's got all these ruffles. Now it's found a cancer cell. And it's really getting excited. It's lighting up its membrane with all of those ruffles and trying to figure out how can it pull together its armamentarium to actually do that cancer cell in. And what it has going for it, see those red globules though in there? Those are granules which are capable if they get released into the cancer cell to basically rupture its membrane. And you can see those granules more clearly here. They even line up appropriately when they get close to a cancer cell and get ready to blast it. Now I'm going to show you what happens when we let this whole thing happen. The T cells are in green. The cancer cells in red. You see that bright flash? That was when the T cell ruptured the cancer cells membrane and the dye that we're using slipped inside the cell and gave you a big bright flash. There goes another one. These are really fun to watch. This is like a video game except this is serious stuff. This is about life and death. And this is happening all the time, probably, to prevent cancers in each of us. But if it gets out of control, we need to unleash those green T cells to do this. And that's what some of the new immunotherapies are all about. One of those, in fact, was the result of the Lasker Award, the US Nobel Prize, being awarded just a couple of days ago to James Allison. Well, I could let this run for a while, but I think you get the idea of what's happening here. It's almost like 4th of July fireworks where those T cells are showing those cancer cells what for. So between the therapies that are being developed in terms of targeted drugs that go after specific cancer mutations and the immune therapy, we're in an exciting place. But we need to scale this up. And one of the goals of the President's Precision Medicine Initiative in the US is, in fact, focused specifically on cancer. And starting in the next few months, we're going to see what we could do to really push this much harder than has previously been possible. Thank you, Francis. So Lydia, we've sort of seen the Star Wars video. Those T cells, they were, gee, you got it. That's amazing. So how can you help us with that? What I do in the lab and many of my colleagues is we're building new tools to help monitor, to help detect cancer. And one of the focus in my own research is to look at circulating tumor cells. Those cancer cells shed from the primary tumor and circulate in the bloodstream. And I think what's interesting, it goes to how individualized everyone's cancer is, the uniqueness and the fact that we now know that some people, our EGFR, have the mutation that actually is my mom who has that lung cancer form. And the question is really, since there's uniqueness in cancer patients, there's also uniqueness in the circulating tumor cells that are in the individual body. And I think it's quite fascinating at some level. So we have, in the US, one FDA-approved system, Cell Search. And that's focused solely on one type of circulating tumor cell that's expressed one particular type of protein, EPCAM. And now we know that these circulating tumor cells, they're heterogeneous. They have a heterogeneous population. And it's a question now of which cells are the ones that might lead to that metastacy in the body? And can we actually capture those cells to give it to, for instance, my colleague, Amy Her, at UC Berkeley, where she can actually lyse the cells and start to look at the proteins and looking heterogeneity. But we still need to be able to try to isolate these cells and try to at least give a first pass in saying you have a whole range of different cells expressing different markers, whether they're a stem cell like or they're showing EMT and everything. And that's something that we're focused on right now in the lab. And I think that helps overall this whole idea that everyone's unique. They're going to have different subpopulations. What do those subpopulations mean for that person's cancer? How does it change during the course of therapy and so forth? And to be able to track that, I think, is powerful on the clinical side. But it also could be powerful towards studying cancer, developing new drugs and so forth. Great. So, Katrina, Francis told us that cancer results from spelling mistakes. I would be in big trouble. So is there a way we can correct these mistakes? Well, if I may have the slides one more time, there's an additional slide to give you a picture of the tool that is currently really capturing the imagination and really tremendous amount of effort within the scientific community called CRISPR-Cas9. So this is a tool to do what's called genome editing. The idea that you could go in and in that sequence of DNA where you have a mistake be able to fix it. Very simple idea, a little bit more complex in practice. But the concept is to be able to, if you have a mistake in that sequence, it could be a small mistake or a large mistake, can you go in and either delete it or correct it, paste in the corrective DNA. Now, in the world of genetic diseases like cystic fibrosis or certain forms of retinal disease, you would want to work directly in the patient's cells where the disease is occurring. In something like cancer, as you mentioned, this cancer cells are very heterogeneous. They're not all the same as one another. And so figuring out which exact mutations, which mistakes in the DNA you want to correct, that does make directly applying this CRISPR approach to cancer is challenging. However, what people are doing right now is putting together what Dr. Collins mentioned with the T cell attacking the cancer cell. And I'm sure something you're very deeply involved with. The idea to, how can we better train T cells to do that job? So there's been some spectacular work that's 20 years to be an overnight success. This is what it takes. But this idea of engineering the immune cells of the body, the T cells of the body, to go find the cancer cells. There has been amazing progress in that fairly recently such that now a lot more folks have come together to say, OK, how do we improve on that? How do we make that more successful? So it works in more patients. So it works in more different kinds of cancers. And then so that you can have more easy to use versions of it for patients. And that's where, right now, putting this CRISPR technology together with this engineered T cell technology. For those of you who read this literature, it's the CAR T or the Camaric Antigen Receptor T cells, putting those two things together so that you're using CRISPR to really engineer much more advanced versions of this T cell. So I think you're putting together two of the most exciting technologies in biological research right now. But that is absolutely the direction that makes scientific sense to put these two together and take cancer immunotherapy to the next level by using CRISPR. So you can use it to create the commando T cells, which are separate from the kind of run-of-the-mill soldier. Exactly, yes. We want the advanced, the Army Rangers, the very specialized. They're ninja warriors. Ninja warriors, these cells, exactly. And partly because as many of you may know, some cancers are tougher than others. Some cancers have responded well to the various traditional kinds of medicines. And some are just very, very, very tough. And so finding ways and also patients may do well for a while. And then the medicines stop working and the cancer comes back. So finding ways to create these very durable, long-lasting remissions is one of the things that makes people very excited about this CAR-T approach is while it doesn't work for everybody in that way, seeing patients have that very, very long, durable remission tells us, OK, this version of the T cell was the right answer for these patients. How do we figure out the next version that will work in more patients? And that's where we're wanting to push this kind of approach. So it's the precision personalized medicine that Francis talked about at that interface? Absolutely, absolutely a piece of it. Because in the version of this technology that's being used today, what you do is the patient, you take cells from their body, you work on them outside of the body to essentially change them and train them to be able to go after the tumor. And then you give them back to the patient. So it is a very, very personalized therapy in that regard.  So how can the immune system help us more? What can we do to take it to the next level? So we have so much at the tour now to engineer immune system and empower their capacity to care the cancer cell. Just mentioned, we can have the CRISPR-9 technology to relieve the suppressive status of the T cell from the cancer patients. As we know, there is an immune suppressive status in the cancer patient, not only in the tumor microenvironment. So the T cell, freshly isolated from cancer patients, cannot cure the cancer efficiently. So we have to re-indicate them in vitro, expand them to enough members, then adopt a transfer to the cancer patients. So this way we can amplify the specific anti-tumor immune response against cancer in vivo. So I think we can re-indicate the T cells in vitro. I think this is one approach. I think another approach is to identify the tumor antigens expressed by the tumor tissue. So this is the target. This determines the specificity of immunotherapy. So by identifying the tumor antigens by the genomics, so we can prepare the therapeutic antibody against the cancer. So this is another approach. I think surprise and surprise or regulating and regulator is the smart strategy of our immunologist to fight cancer. As we know, the immune system want to recognize cancer cells and kill them. However, cancer cells are very smart. They can indicate the immune system to be favorable of their growth, their metastasis. So cancer, not cancer cells, I think the cancer tissue, can release so much kind of factors, indicates the immune system to be suppressive. So they cannot recognize the cell. So another approach, I think, we can use the combination therapy to relieve the suppression by the in combination with chemo therapy, radiation therapy, and something like that. So we should use the competitive strategy to fight cancer, I want to say. And as to the precision oncology, so we should have the precision research first, identify the biomarkers, how to predict the population of the patients who are responsive to the immunotherapy you want to use. So last year, we identified one markers of the liver cancer. Only a few preparation of the cancer patients as a liver cancer are responsive to interferon therapy, adjuvant therapy. So why? Why most of them are not responsive? Why some of only a few of them are responsive? Finally, we identified the one protein rig I. So at the high level of this protein, the patients are responsive to the interferon therapy. So through this way, next time, if you want to use alpha interferon therapy, we should detect or scanning the rig I level from the tissue. Then if the rig I level is relatively high, we can use the interferon therapy. If it's very low, we cannot use the interferon therapy. So the precision oncology, one of the strategies is to identify the markers to predict the responsiveness of the patient to the therapy you want to use. And also, we identify the target for the drug design, I think next topic maybe. So the big change that's occurred is that we've begun to understand, or actually a pretty good understanding, how cancer cells go from quiescent normal cells to ones that are kind of getting aggressive. And they're sort of sneaky about it because they realize that the body's got its own immune surveillance, and they put it to sleep so that they don't get picked off by the immune system.  Are they smart, or are they just changing all the time? And it's Darwin at work. When you change a way that helps you survive, that there's a fire out there, and one of the genetic changes makes you immune to fire, then you're fine. So is this a sarcastic process, one that's kind of just random, or is the cell smart enough to know what's going on out there and to try to beat it back in an organized way? Yes, if you're worse about this. So during the interaction of the cancer and the host, host want to recognize another part. So I think adapting to the killing by the immune system is one of the strategy of the cancer. So they want to lose some tumor antigen, just as you told us. So they want to change themselves to adapt to the survival environment. So this is the very smart, this is just the Darwin's rule. But at the same time, the cancer is actively indicating the immune system. They really so much feathers to suppress the immune system. So adapting themself to the change themself to escape the immunological surveillance, it's one strategy. But at the same time, they also indicate to the system to be favorable for their survival. So I think this is another very smart strategy. Yeah, your question is very appropriate, Jeff, because I do think cancer is a pretty good model of evolution except happening in the individual level over a measurable period of time as opposed to evolution over hundreds of millions of years. So yeah, cancer cells are going to survive if by some random process they develop some attribute that allows them to escape the immune system and to keep growing. And particularly if they're able to leave their original home and spread to some other part of the body, then they've got a real advantage. There's lots of them out there. This has a real consequence for when we try to design drug therapies for cancer. There are this really wonderful growing list of targeted therapies like the Tarsiva against EGFR that you mentioned with your patient or Crizzotinib, which works against lung cancer where you have an alkymutation and a long list of others. Melanoma, all the drugs that target the oncogene called BRAF, gave wonderfully exciting results. You'd give the drug to somebody with metastatic melanoma. The tumors would melt away. People would go back to work. But then about nine months later, it was back again. So what's that about? Well, it's really a matter of mathematics. By the time you've been diagnosed with metastatic malignant melanoma, there are more than 100 million cells, cancer cells, in your body. The mutation rate for each letter in the DNA code is about one in 100 million. So somewhere in that group of cells are some that have already, just by random chance, developed a mutation that's going to make them resistant to your drug therapy. So you give the drug therapy. It looks like everything melted away. But those resistant cells keep on growing. And pretty soon they recreate the entire scene. So what's the answer? The answer has got to be that you hit them not with one drug, but you hit with two. Because the chances that you're going to have so many cells that two drugs have, by chance, a resistant cell in there somewhere is much lower. Three would be even better. You may be recognizing a resonant theme here with how we figured out how to treat HIV-AIDS. Remember HIV-AIDS? And originally we started with one drug, AZT, got people in pretty good responses, but it came roaring back because the virus was resistant. Same problem of mathematics. Now we treat HIV-AIDS with three drugs and we keep people in remission for life. We need to move our cancer therapy in that same direction, figure out how to use combinations. But you know what? The combination, if I had cancer, might be a different set of three drugs than for you, even though you might have cancer in the same organ that looked the same under the microscope, but you had a different list of molecular drivers than I did. And you wanna be able to personalize or precision-orient that therapy. The challenge is, how do you run trials like that? Where everybody's on a different combination and then figure out whether it worked or not. The FDA is, you know, their hairs on fire, trying to figure out exactly how they would decide whether to approve something. They're getting there and they have some pretty good ideas about it. That's the direction I think we have to go, is to go from monotherapy to multiple approaches, maybe including both a targeted drug and an immunotherapy. There's no reason to do one or the other. Why don't you do both? That's, I think, our challenge for the next half decade is to figure out how to put all of those tools in place and go after some of those most recalcitrant cancers like pancreatic or brain tumors, which we don't do very well with. We ought to be able to win those battles. I think the other thing that I might add to that is that there's a dimension of diagnosis to this, which really, the concept of personalized medicine, it goes directly to that. So for a given patient, how do you know what their exact kind of tumor is? The reason that we can actually approach it now in a DNA sequence-driven way is because of what Dr. Cullins and all his colleagues did in terms of doing that first sequence of the human genome. Now, the first sequence took a lot. Only 13 years and $400 million. The first one was expensive. But because the first one was done, we can all now send a cheek swab to 23andMe and get it done. Or more particularly, if you have cancer, you can get a very high quality, rapidly done, pretty inexpensive sequence of your tumor. In fact, so in the United States, there are advertisements on television for this cancer treatment healthcare company. And they talk about, in their advertisement, we sequence your tumor. Now, I don't say that because I'm trying to make an advertisement for them, but I think it speaks to the degree with which the concept of cancer as a disease of DNA has really fully taken hold in the medical community. And that's a spectacular shift conceptually, I think for physicians, because we didn't used to think of it as a DNA disease. We used to think of it as many different things before we kind of understood the real underpinnings. And now have the tools to address it at that level as well. So I think that equally important to what drugs are we making, is the ability to actually diagnose and leverage the human genome project as a critical part of that to be able to apply this concept for real patients today. If I might add, for someone like me who's more of an engineering applied person, it's up to us to try to help all of you develop the more sensitive techniques to detect the cells that have changed as early as possible so that we could hand it over to you, hand it over to your institute so that you could start seeing what are the mutations because things will happen quickly. And the question is, do we right now have the tests that can be sensitive to detect these changing cells to be able, in the body from which then? And so that's something that is an objective for people writing. And that's really important also when you're trying to decide whether you're on the right track. So you are giving that first blast of drugs to somebody who has a cancer and you think you've chosen the right drugs. If you have the ability to see what's happening to circulating tumor cells, you're in a much better position to know without having to wait for a couple, three months to see if the scans change, you get a more immediate idea. And likewise, when you're trying to find out, okay, somebody looks like they're in a complete remission. Are they really? Are they, is it starting to come back? Because if so, you ought to jump right on it.  And having the kind of thing that you do to do that very early detection, circulating tumor cells is a real advance. So one of my mentors in my youth used to say that one man's noise is another man's signal. So you study individual cells, Lydia. What's the variance, right? You've heard that not all these cancer cells are alike, that there's one of them that's hanging out and if you kill all its brothers and that one happens to be immune to what you're using to kill its brothers, it's gonna survive. So do we have the capacity to determine what the variance is when a patient rolls in with the tumor, or do we have to wait for the process of selection to tell us what's going on? Can we be smart enough to pick it out in advance? So as Francis suggests, we have drug A, maybe even have drugs B and C, but we have many choices for B and C.  Well, that's a loaded question. I think right now the state of the art in engineering and clinical diagnostics is such that we're just now understanding that there's a whole bunch of different cells and which one is it? I don't think we know right now. I understand that it's definitely not, for instance, the epithelial cells, those are transitioning in going through a process of transition to EMT or a stem cell like, but even then, I think it's still out there. And I thought what was best said to a student of mine had said, if you think about it, there's one to 10 cells and 10 mils of blood. That's what everyone anticipates as a CTC range. But then you have how many liters of blood in your whole body? But then there's only one or two metastatic tumors initially at start. So it's like one or two cells or a clump of cells. So how do you know which one it is? And I don't know and I ask all of you, how can we know that? There's a lot about the microenvironment and everything and that would help inform someone like me to be able to help figure out what's the best way to pinpoint and isolate these cells. So I think hopefully I've answered that question. So how did those tumors, the cells express something on their surface that we could monitor immunologically? The immunology is a great way to find a needle in a haystack. Can we employ that technology to help in this battle? So there are two strategies to, early diagnosis of cancer. I think when from the blood sample, we can detect the protein and the microRNA in the blood to show the progress of the cancer and what's the types of the cancer, the patients. And I think another very important approach, now we are utilizing is bicepine. So we can get the very small tissue to know, through the gene detection to see if there are any pre-cancer type. So I think by the standing of the small tissue, we can know the cancer status, a pre-cancer or advanced cancer. I think two ways we can use to distinguish the normal cell and the cancer cell. So we've seen that this thing we've called cancers, really many things. And you've been in the business of developing therapies. And sort of the therapeutic development nightmare is that I don't want one drug, I want 100 million drugs. Is there a way to kind of fine tune this? Is there a way that we can develop a therapeutic approach that would be applied rather than a specific drug and that would have many different outcomes? How can we beat the cancer at its own game? So it's a great question because I think what we want to, we want to be careful to still be objective and rigorous in the data that we develop. And I think that the regulatory authorities, the FDA, the EMA, Cossetia, et cetera, care very deeply about that too. So one of the challenges in developing drugs, particularly in such a serious disease as cancer is balancing that real urgency and need of the patient with the need to be objective and not be anecdotal. The plural of anecdote is not data, right? And so we really do need to find a balance there. Certainly in any drug development and most importantly in cancer, you always want to work looking at your new therapy on top of or on a background of other therapies. That's usually how you start. One of the interesting challenges here is, so think about how are most cancers traditionally treated. Traditional chemotherapy, which has to do with interfering with dividing cells.   You know this far better than I do. But those are the original approaches in terms of what we call traditional chemotherapy or traditional cancer drugs because you were hitting every dividing cell in the body because cancer is dividing that rapidly. Now, there are a lot of good drugs like that. We still use those a lot because they actually can help patients quite a lot, but they do have a lot of serious side effects and they often aren't sufficiently efficacious. We also use radiation therapy, so literally x-rays, usually focused on a particular part of the body. But again, you're trying to kill cells and that has a lot of side effects too. So these sorts of therapies, they have helped patients tremendously. They do have a lot of side effects. Ideally, you'd like to have a targeted therapy and do it in place of. Not have to go through those very difficult therapies. So I think it's partly how do you do the combinations? That is absolutely one of the challenges. But also, if a person has been newly diagnosed with a cancer, there are traditional therapies, let's say, let's say lung cancer would have you, there are traditional therapies available, and then there's something new. Do you try that early on or do you try it in the patients that are most advanced where all the other therapies have failed? There's an ethical aspect to that, but then there's also, there's an ethical scientific aspect of if your therapy is gonna probably work best if you get early on, can you do that trial? How do you do that trial? Is that something that's feasible to ask somebody to agree to do if there are traditionally approved therapies available? So I think there's a couple different dimensions to this. I don't have an overarching answer for you. In my experience, you need to look at each type of cancer you want to address. What is the hypothesis you have for what you're trying to develop? See if there is a scientifically legitimate and ethical way to do an objective trial so that you get a clear readout. I don't think we can escape from the need to do those real experiments in patients. So I'm gonna pick up on one phrase that you used and ask your three co-panelists. You said the specific type of tumor that you have. And we've thought of the specific type of tumor like you have lung cancer, but I have a patient with EGFR mutant lung cancer and there'll probably be seven or eight different kinds of that. So we're gonna take a lot of patients and subdivide, take something we've called lung cancer instead of calling it one thing. It's really 50 diseases or 100 diseases. And as a biotechnologist, you might want to attack the most frequently occurring of those. So how do we begin to give labels to these different kinds of cancers so that the treatments can be designed to hit them? So I think our taxonomy for cancer is undergoing a significant revolution and it should because I think that the organ in which the cancer arose is gonna be a lot less important than what's happening in those cancer cells that's driving their malignant behavior. We are just starting at NIH a trial called the MATCH trial and they're aimed to enroll 3,000 patients and they're enrolled on the basis of what DNA changes are found in their tumor.  What matters is what were the DNA mutations that were identified.  And ideally we try to do combinations in this and 20 drug companies have actually agreed to take part which is a big step forward. Drug companies traditionally have not been too excited about having their novel therapy given to a patient who's also getting a novel therapy from another company because suppose there's a toxicity, how do you figure out which is which? They've generally preferred just to have one drug at a time but as we've been talking about that may not be the way to cure people. So we're gonna have to have this new dynamic of companies being willing to share the risks and they have agreed to do so in this trial. So over the course of the next two or three years thousands of people will be enrolled in this. It's a very different mindset than what we've traditionally done but I think it is the way to kind of get past our old ideas about what matters and focus on what really does matter which is what's driving that malignancy, what tools do we have to go after it, can we in fact do better than we have with the old ways and attack this in a purely rational strategy. I suspect there gonna be some pretty significant exhilarating moments and I suspect there also gonna be some real failures and a really important part of this is to figure out when it doesn't work, why didn't it work? If you had this tumor and it had these characteristics and you had these drugs and man it should have been just the right thing and the cancer just keeps growing anyway. Why was that? If you could figure that out, learn from that then the next time you could do better. That's a big part of our challenge right now. And that's going to sort of take a paradigm shift in research when you recruit patients with lung cancer into clinical trials they're desperate, right? They know that 10 years ago they were going to have a very short, pretty terrible life and yet my patient was able to do things that he wanted to do that he hadn't thought of doing because he didn't realize the time was short and in pretty good health. So we've talked now for almost 40 minutes among ourselves. It's time to bring you all in, our audience. So I'd like to get a show of hands. How many of you know somebody that's had cancer? And do they talk about it this way?  I need to think about what my life is going to be ending soon, what I need to do to make it better. Have you seen among your friends or even yourselves and your family members a change in the past three or four years when you hear that somebody has cancer? Tell us your stories and ask the panel how we can help you understand them.  Now I can't, yes please. Then tell us who you are. Hi, my name is Piro Skarnagia, I work for LSE. First of all, thank you. You all saved lives with your work. Thank you so much. The story is that I think the perception has changed my one of how cancer can work and how medicine and science can help us through the past years. I think there's much more hope and in family more discussion, not only of what's happening, what happened in the past. We didn't know in the family that there was cancer, that was a forbidden subject. I think there's much more openness which is critical if I understand the new genetic dominance of this treatment. Can I have a question? What is the role of the environment? We have heard in the past so much about carcinogens, exposure to sun and all that. So in this new framework where gene is the driver and then the mispelling of the gene, what's the role of the environment? It's causing the change in the genes causing the mispelling, what is the role? How should we think about it now? I'm glad you brought it up because I was getting a little worried that we were getting very deterministic here about the DNA role. Like most conditions, cancer is a mix of genetic predisposition and environmental exposure and just random changes. We shouldn't forget the random change part because every time you have to copy the entire genome of a cell, it's possible to make a mistake. And so some parts of cancer probably are simply on that basis. But we certainly know some very dramatic examples of environmental influences on cancer, smoking. It just amazes me that we are still at a point where whatever country you look at, there are a lot of people still smoking cigarettes when we have such compelling evidence of the connection of that to lung cancer and to the kind of lung cancer that's really very hard to detect early and very hard to treat. Sun exposure. We're seeing a lot more melanoma these days in the southwest of the U.S. where there's a lot of sun. Well, it's very clear that that's not just a random chance. It is in fact ultraviolet light which can damage DNA. And if it damages in a way that actually causes that cell to grow, most DNA damage is harmful to the cell. But once in a while, you hit the place that actually activates an oncogene or knocks away a tumor suppressor and then the cell starts growing. So we know a lot about a couple of those things. We know radiation is certainly a risk for cancer. I mean, look at all the follow-ups in people who got exposures, whether it was in the atomic bomb blasts or other things. But there's still a sense that there's other stuff out there. And a great deal of effort going into that. We have environmental scientists constantly on the prowl to try to identify other kinds of exposures that may be contributing to cancer. And usually there's a big controversy about whether they've found something or not, whether it's in the air or the water. We obviously need very large studies, epidemiology studies to begin to identify those connections. And I think lots of research enterprises are aiming to do just that. But I should have mentioned also viruses.  Certainly liver cancer from hepatitis virus or cervical cancer from HPV, which is now pretty much a preventable disease with a vaccine. You should think about all those things as well. Those are caused by a environmental exposure. It happens to be a virus and not something in the air or the water. So I don't think it would be appropriate for us to have this session about cancer without talking about prevention because we've really been talking about treating people who have the disease. And a lot of the prevention is trying to be sure you avoid the environmental exposures that we know are bad for you. And also trying to identify what kind of screening tests are available for people at higher than average risk in order to pick up cancer while it's still as small as possible and as treatable as possible. We have a big controversy about whether mammograms are actually doing what we wanted them to right now or there's some debate about whether mammograms are finding things as often as you would like or whether we're causing an awful lot of anxieties and follow-up procedures and people have a positive mammogram which turned out to be a false positive. But it's the idea of trying to do that early detection. So yeah, I'm sorry, the long answer but environments critical, prevention's really important to think about we don't want to have people taking all these targeted therapeutics or immunotherapies. We don't want them to get cancer at all. If they fall through the safety net and get it we want to be ready but mostly we want to keep them from getting cancer in the first place. Other questions, yes. Because I don't speak English, so I speak Chinese. I would like to raise my question. I'm from China Business News. My question is for this lady. Lady, you mentioned about, you mentioned a very important information because different patients have different DNA so the cost is very, very expensive. 300 million, I'm not sure whether maybe it's not the correct information. For each person the treatment of that cancer is 300 million. We learned that for the rescue and the cleanup of those firefighters who have suffered the cancers during the blast event in Tianjin. So if it is so expensive, how could they afford that? Thank you. Let me try to rephrase the question to make sure that we have it correct. There are many potential targets and the 300 million refers to the number of letters in the alphabet. Actually, I think he's talking about the original cost of the first genome that was mentioned. Right, and that cost has now was dropped way down to maybe a couple thousand dollars and at the rate it's going to be less than the airfare flying from Boston to Beijing. In fact, it is already, it depends on what class of service you're in. So we think that it's possible to identify the tumors but let me, the rephrasing the question is for each of these firefighters exposed in Tianjin, will every one of them have a different mutation or are there in fact some soft spots or hard spots depending on your perspective where we can know to look to see whether somebody's at risk. So they've had an environmental exposure. Is there a way to check whether it's individual circulating tumor cells or to know whether one of their checkpoints has been modified by their environmental exposure.  So this question about the expensive of the genome sequencing individually and how much for the personalized medicine for each person. I think this question maybe raised by the reporter. So I think now the expense of the whole genome sequencing is reduced remarkably and very cheap. I think now it's time to practically use this technology to benefit general people. And also we can use this technology for the population study to go to the big data and then provides the data for the policy makers to improve the, I think the quality of life for the prevention, not only for the treatment, but just now we talked so much about the treatment of cancer patients. But now we should, maybe by the sequencing we can also benefit the people, have curiosity of their sensitivity to be the cancer patients. Maybe we can provide them informations for them to take measures for prevention of the cancer. Yeah, with low price, I think. The other thing I might add with regard to your question is in developing drugs, we don't think about the market as this country, that country. We think about it as patients wherever they may be who have the type of disease that we're trying to address. And if you think about the medical community, the big international medical conferences, the big cancer conferences, for example, physicians from all over the world are there because they really are seeking to understand the application of the insight, the genetic insight, the treatment insight across wherever they might be treating patients. So this is why in every country you have the academic medical centers that are really at the forefront of knowledge, and those physicians are all going to the same conferences with one another and exchanging the most advanced insights. So for example, the firefighters that you referred to are part of, I'll call it a global community of patients and the experts that will seek to treat them will be working off of insights from patients in the US and patients in Brazil and everything else. So I think that the medical community at this cutting edge research level tends to be quite international. And I think just as we don't anymore think of tumors quite as much as a breast tumor or a prostate tumor, we give it a genetic basis. I think the same thing with regard to what is the genetic makeup of the person and where do they come from. What we really care about is the genetic signature of the tumor and that's the group that we put together to try to treat those patients. Thank you, I'm Vijay. I run a tumor profiling company in India for the last two years to do next-gen sequencing. Not a week goes by that I don't get calls from just my own social network that someone has been diagnosed and they want to know what we can do to help. So I think this is getting really universal now. I have a very specific question about transfer of knowledge from precision medicine into medical practice. And in particular, we find it very difficult to get treating oncologists to use this information at first line therapy, right? Even foundation medicine and carous and so on in the US today are really treating at second line, third line, sometimes really when therapy has failed and only then genomic signatures are being looked at. How do we get this into first line? So Catherine was referring to this as the dilemma and it's not just because oncologists are slow to pick up on new opportunities. It's because for many of these therapies we don't know yet sufficiently how they're going to work. And yet for many cancers we have a standard approach. It may not be that great, but it is what is offered to people with that diagnosis. I think you can kind of see the path that's been followed with targeted therapies that got started a little earlier and you can see where we need to go here, so I mean look at Herceptin, the very first sort of targeted cancer therapy based upon a molecular understanding of breast cancer and coming up with a way to make a monoclonal antibody. Initially that was tried on people who'd already failed chemotherapy, now it's first line. Look at Gleevec for chronic myelogenous leukemia. Initially seemed like this is gonna be a pretty risky strategy trying to block a kinase. Gosh, it really seemed to work quite well in the first 30 patients and now it's first line therapy and it's amazingly successful. So we have to kind of go through those stages and to get there you wanna be sure that you have the data to base it upon.  Hurry up already, let's get the data. Which means that we worldwide really need to mount these trials on a scale as quickly as possible so that we can begin to learn what works and what doesn't.  But it's our obligation, I think, as patients, as providers, as researchers to be pushing this envelope. Now that we have a pathway, we have a strategy, we have a framework, we should not be waiting around to find out how to apply. This has to be brief. Thank you very much for a very impressive panel. My question is actually maybe to go back to the original video that Professor Collins has shown as can the panel envision designing or generating superimmune cells or superimmune T cells that can recognize all the antigens that we have so far in our data? So am I too optimistic or thank you? Well, in a way, that's what people are trying to do right now. I have a very good friend who has brain cancer, glial blastoma multiforme, the most aggressive form. She was diagnosed four years ago.  So she was enrolled in a clinical trial at NIH and it was what you heard about earlier, taking out her T cells, putting into them an appropriate cassette to train them to go after that abnormal protein in her brain tumor that otherwise shouldn't be there and then giving those back and doing that repeatedly. And it's pretty unheard of for somebody to be four years out from that disease because the five year survival is about a year and on the average. And here she is way out there on the tail. Now I can't, that's an anecdote. Be careful here cause this has only been done a few times. I think what you're getting at is could we apply that in a general way and every kind of cancer know what the target should be, train the T cells to go after that. We're not there yet cause finding those sort of wonderful Achilles heel examples for every cancer doesn't come so easy. I will say, we touched on this, that the other immune therapy approach that doesn't require you to know that is the one that basically takes the breaks off of the immune system in a general way. So when Jim Allison gets the Alaska Award in a couple of weeks, it will be for figuring out that if you make a monoclonal antibody against something called CTLA-4, you unleash those T cells not just for one target but for all targets and you give a chance for a cancer that was run and wild to get tackled. And of course there might be a side effect from that. Oh yeah. Your immune system can be attacking yourself. So in the few minutes we have left, I think that in the past decade, the word cancer has evolved from a monolithic death sentence to a question of what type and is this something that we have worked out a way to deal with? I think it's important to think back to 1948 when Sidney Farber published his first paper on the treatment of childhood leukemia. He got remissions at that time and there were people who said it was terrible to treat these children because their disease always came back. But we have two elements here. We have scientists that wanna cure people and we have patients that wanna be cured. And putting them together to decode their disease and to kill it selectively and permanently if possible is the goal that we're making progress toward. And I think that you've heard the mechanisms. We use the immune system.  We can identify the specific mutations in a person's individual cancer and we know what makes it susceptible to specific drugs so the tumor can't grow. We've made great progress and we have these two groups of people, scientists desperate to help people and patients desperate for help and that combination is gonna lead to progress. So come back to Dalyan in a decade and we'll have wiped this one off the map. We hope. Thanks for your attention. Thank you. Thank you.


The CPI numbers will be posted on Tuesday, February 14, 2023. The month-over-month January CPI number is estimated to be 0.5%. The year-over-year CPI number for January is estimated to be 6.2%. The Federal Reserve Banks have been raising interest rates to fight inflation. The Fed's inflation target is 2% year-over-year. The 6.2% year-over-year number for January, if true, is far from the Fed target. That means the Fed will have to continue to increase interest rates to curb inflation. To make matters worse, the Bureau of Labor Statistics has revised the month-to-month CPI number for December from negative 0.1% to positive 0.1%, and the November month-to-month CPI number has been revised from 0.1% to 0.2%. If the 0.5% month-to-month January CPI number were true, it will have a very bearish effect on the stock market.


Okay Got sound and vision, okay, I can't see what you guys are doing. That means I can't read what you guys are saying Let the color Sorry, it's hard to hear as well I'm just taking these alcohol wipes, which is 70% isopropyl alcohol And I'm just giving it a little bit of relief to lighten the color just slightly So it's just a tad dark Jeff is that maker space making more boards and Store I'm actually working on a preform geo board Don't know what's gonna work, but I hope it does And I hope it's going that you guys like Let's see if this is gonna put some like the grayish she blue color Purple Swabby things came from Jen and she got them off of Amazon when this is When this feed is done, I will get online and add them to the Amazon link down in the description box So you guys can find them as well I think one reason why I'm having problems with alcohol right in this area is that I've been working at for a little while And so it may be a little bit warm So the alcohol is gonna dry faster I think that could be what goes on right here It could also be that this alcohol that I'm dipping into is Just too contaminated with other colors and their chemicals Yeah, that's what I was thinking that it takes are transparent and I want to create like a multi-layer Surface for them that makes it kind of easier for people That aren't comfortable with free forms or have problems with it I think that would help a lot of people I guess is what I'm getting at A lot of people that want to do free forms There's Plenty of people out there that have no desire whatsoever to ever do I think Crystal's in the middle of this for sure I'm not sure which kind yet We'll see All right, this would be a good test. I just got black ink on the middle of my blue Let's get a fresh one Blue area here No, some of the blue came off Maybe that's not how you're supposed to use this stuff that maybe Scrubbing it is not okay I didn't read any of the instructions first However, that does make an interesting look Almost like a bark right here now Well, I'm holiday intimidate you. Hi, Kerry So I guess we're not supposed to scrub the solution Water soluble I'm gonna have to look it up a little bit because They'd probably be really expensive Angie If at first you don't succeed read the instructions, that's my whole life model So I'm gonna have to figure out what I did wrong with that, but I'll do that later I'll read later So I do want to add some more gold lines through piece And I also have some gold leaf here as well to embellish a little bit So let's go ahead and do another line of this color This is the I can't even begin to know how to say this word to lose with this because I prefer gs to be At least for my work I was rigid and uniform And supplied over the layer solution to stay where they are Any things that are over the solution are under the solution to stay where they are So because this is what there's a little bit of bleed out, which I actually really like for Dio You can see like it's I don't like if you have a red lipstick and it kind of gets outside of your lip line a little bit They're awesome Keep going over these areas because the alcohol picks up the color And just redeposites it a little bit. So it gives it extra definition Just applying this alcohol ink directly to The end of this brush Because if I put a whole bunch out There's really high odds that it's just gonna evaporate before I get it all used and I don't want to waste any So that's what I'm gonna do. What I love about alcohol ink is that you can reactivate them just by adding alcohol So there's no real like scary finality to it Like for example with airbrush You have to be really careful where you put any airbrush paint because It'll be really hard to blend that out Whereas with these I'm trying to completely spoon wherever it goes or you can just Put some alcohol on it and change it I'm not looking at the feed right now I'm just dotting on some alcohol for it to like self level out and blend on its own I like what it does better than what I make it do Those are my bets you guys I'm not sure Doris is here Oh, here she is For some reason I thought she stepped out So that looks fun.  They're in order right now. I think I'm sure working because that's all we all do But it's fun work. I get it. No worries. So now I want to add gold lime through here I'm trying to decide if I want to keep the Keep some white. What do you guys think? Keep the white? Trash of white I'm just dabbing some alcohol into where I have the gold I'm shaping it just slightly to have those ridges What it is about alcohol is gold, but it does not want to do it. It's probably the most temperamental Of white alcohol is probably the most temperamental But y'all know what I mean. I'm going to smit Gold leaf to this that I'm putting on right now I'm just going to give it a little thump thump extra And the ones that I'm using are actually gold like colored metal leaf. This isn't true gold leaf But you can use true gold leaf, but since this is a 100 test I didn't want to risk it I'm not going to add this quite yet. I'm going to wait till I I'm going to wait till this is done and then use this stuff Adhesive for metal and gold leaf So What did you guys think? Add white or no white? This is rich gold. Maybe I'll just save it and do Like use a paint pen or a scarlet Okay So I need More colors. I know the whites and me just I don't know what the deal is. I don't know why it's so difficult I'm blanking out Oh nervous.  Okay. Y'all remind me before I do this. Don't use blending solution or don't use alcohol Because it does not stay on the bottle Put it through this layer because this I've masked off and the gold It's stubborn and it's not going anywhere anyways I'm sure that's way more than I needed to use I can never remember when to use blending solution and when to not In my head, it's all the same, but it's so not the same Oh, this has some blue on it. So that's going to add a little bit of color. No Oh, that was alcohol. All right. You gotta wipe that part off No worries. No harm no foul I just made another clean brush Y'all I can't win today All right Some of the gold is coming up a bit, but that is perfectly fine with me That'll get a little bit more of a blend This part a little bit more visually interesting. No difference Except for that part what we're gonna do is Drop the color into it That's fun using this little I have no idea what to call it to fill in the white areas in between this green almost looks like we need Work resin and alcohol together. No, Jen would know the name Put two uniform and perfect So I'm gonna put in between dots to break that up a little bit As far as that is staying in This area instead of growing outward It's what I would have wanted if I put a chosen so I will say that the keel tea colors seem to push out more Whereas the um, what was that I just did Ranger kind of just sinks and sits where you put it I'm gonna do a little bit more of the white in here and then call this Good to go for now When I do geodes, I like to give some of the areas. I don't know if that's even I just want it to be different I definitely do that so all I'm doing is growing out like the keel tea one as well A lot of darker colors. Let's try the pearls Okay, this is a pearl mix today from Ranger. What's up? Notice scotia? It's barely four degrees. That sounds horrible. Let me show you guys where we're at. That was too doomed in, sorry Celsius that's even worse Wait, yeah, that's even worse Okay, solution blending solution blending solution It's actually really pearly I didn't seal in this ring and so I'm hoping it introduces itself a little bit down into the To help that, I'm just I'm just messing with it on that. So much that it ruins the line between the two I do want to bring in some of that color. I will show you when it's dry I wonder why they made alcohol ink so that you can't add alcohol to it. That just doesn't make sense to me So I'll probably do the pearl again in this line because it looks a lot better than just white. Awesome, Scarlett Okay, I should probably do a thin line of gold because it hasn't really been anywhere else So I'll do this one gold then Probably a black In fact, I might just leave that like that. I feel like that was too easy and that I'm just asking for trouble having done that so far I'm just brushing this out a little bit So it's not like a full texture Let's try that And move on Hey Margaret because this I'm gonna make the pearl color, which I'm probably almost going to do Actually, I'm gonna mask off the black so it doesn't Move into that and for more on gathering.  It doesn't like Push the next color away Does it repel other colors? I've experienced so far I just don't want this color to cloudy up the pearls. I'm just gonna smooth out some of the thicker areas so it dries more quickly I scared your brother So that's a little bit light.  Enough Move Enough, I'm pretty sure if he sees ghosts and things Pooja? Because for Laila he's been talking an awful lot to somebody And he knows not to pop off But that's me, Miss I'm all though Now we need to add pearls through here And then we can get on with it To the next Thing I'm gonna completely finish this in this one video today. I have decided So this masking is Pretty much dry Maybe I don't want this to look like that But so what I'm gonna do is The pearl kind of like overreached into this aqua color So I'm just gonna try to figure out a way to make that a choice If it actually works that way Maybe I can just cover it up some I think that's important for artwork to look really Worked Not finished But it can be finished And it can be complete without having dark colors And obviously yours But like for my work I like to have really light colors Next to really dark colors Because for me In my work That's how colors stand out the best Shake it again It just starts being like Early and sparkly Pretty as soon as like It moves You can see it glistening You guys can see with that angle Or about that I'll show you all Funny how blending solution always stays shiny Margaret I'm not like a not whole kind of Not whole but like some extra A little bit of imperfection The picture from Find out what's going on Better just disappear the gold In the green Get it Almost get it No getting So Let's add Gold leaf So I'm using metal leaf By speedball This comes in Very delicate sheets Of leafing Like Super Delicate I'm going to also be using This speedball metal leaf And use it If I can get the lid off This stuff is This stickiest thing So you're supposed to put it on Wait till it turns Or white to clear And add the leafing after it turns clear Just like with the masking solution The thinner it is The quicker it dries I'm kind of like Raggedy applying this glue Because I wouldn't mind it if The gold leafing went on Kind of ragged I'm not really looking for A very neat line You can use anything to apply this But if you use a paint brush That would be the last time You use that paint brush To apply Raggedy Applying this So that is enough Of course if you want to Take your time I want to show you guys how Wafer thin is a term But it should be Gold leaf thin Because this stuff is Insanely thin And just like with playing rap It's going to stick to whatever it is Back that up through there Inspire it A bunch of this heat bulb Glue on my hands And pro Obviously They also make this stuff in like A loose Leafing And that's also Awesome to use Whenever Jeff uses his leafing I always like coming behind him To make sure he doesn't waste any of it And see where it comes in This stuff isn't as bad It's not cheap But it's affordable In comparison Then I always just take whatever is On my fingers And tap around So that The gold that's left On my hands It's applied somewhere That's not wasted It also helps to cover up The sticky edge And Move on with the next Area I'm going to do the same to These gold bands because they're kind of dull Especially next to this It's very vibrant so We're going to go ahead And mask off those golds as well These ones I'm not going to Like Really like scraggly etch it I'm going to do it more Great line but still Scratchy Sometimes I feel really bad For you guys having to Disciple what it is I'm trying to say It's actually at makers On morning cutting more clock faces It's so nice to have a partner I don't think I would have been able to take the leaf Into full Art Everything if it weren't for him Kind of a scary leaf you know It's a metal ultimately So you guys speak Erika by now I'm sure The gold up here as well Since we put the Gold alcohol ink down If it doesn't fill in every area That we want to get gold It's okay We're just embellishing it a little bit You know I'm just going ahead and adding The piece of up here Wherever the glue goes Or whatever color you're working on For a bit of heat Not too much because I don't want it to Completely dry out Just a little bit You apply this You can take a brush And like a soft bristle brush And just kind of go over it And it will make it like really Smooth and flat But I don't really want to do that I'm going to do it I'm just a couple little bits I'm taking a little bit I'm really bad on material I'm really making sure The lids are back on You can wait till I'm done It is A boldly knock off It's metal leaf So it ties me On these areas still The glue is completely fed up I think I'm pretty sure it's like 15 minutes It could be completely run It's going to take whatever It comes off To the edges And just Put it in there a little bit So I'm going to zoom this in Leaning up a little bit But I'm going to get it and Transfer it over to this middle area Just play me the sound It just sweeps toys that long And I'm just putting some dust off In this part away And just bringing it over here To get this in It has to be really Like crisp and smooth You want to wait for 15-20 minutes Till you try to dust anything off So that it doesn't Treak at all With the places that I want it to be A better line and just transferring From one area to another What about the sound you guys I am still working on Super zoomed in We've got some white Prepped I don't know If you can just pour directly on this stuff But I made some white coasters And the laser When the laser hits it There's obviously Turns to fire So If you guys Want these I'm going to have to Mask this stuff off and cut these We need to use them first Before we even try to sell Because this is kind of a Shiny material I don't even know what's on here But I'll show you what I mean When I say I have to mask it off I have to put They call it laser paper But it's basically just a white Shelf paper On here you can see where It's burning the edges And you take that off And clean They can't even see it We're going to use them first And then if they work They'll put them on See they're kind of shiny We have round Let us use them first And then we'll let you guys Put them on The application The extra shine to it I think And I thought I was going to add stones I want to Not going to do a lot right now It's not like billiards Which is awesome That isn't funny But we like to stop things They'll sneak up on them And pack it This is the white paint pen from Pintouch I was saying I'm going to have a line But I don't know that I'm going to Be too hard of a line They're playing before And close these up Is it still happening Janice? I don't know I thought you were falling Before you started doing this Better stuff So we're all for the win I don't have any fans on I don't know what that would be You know You do not have to finish it The edges So because this was wood The edges Aren't finished So Let's get all this stuff out of the way And we'll do two edges I'm going to do the whole back I'm not going to use too much This shape at the front a little bit Just wiping that off It's fine because I masked it anyways You know right there I think I should add stones in the middle Or a lid I just called Can you hear me? You're singing now


You know, if we are going to talk about the central dogma, we have to have some dogs to join us. And would you agree that perhaps this is the central dogma? Sorry. Okay, the central dogma describes how the information from the DNA gets made into a protein and it begins with DNA in the nucleus in the case of eukaryotes. DNA goes through a process called transcription. And yes, we will talk about transcription. The good news is transcription is actually very similar to DNA replication. So it's going to feel familiar. The result of transcription is the production of a messenger RNA molecule. So mRNA stands for messenger RNA. So DNA codes for the transcription of messenger RNA. And then the messenger RNA contains the instructions, the messenger RNA leaves the nucleus where transcription takes place and heads to the cytoplasm, I got there, where we get protein. And this process is called translation. Translation takes place in the cytoplasm. And in the case of eukaryotes, transcription takes place in the nucleus. Translation, we have a main kid, a main player, just like when we talked about photosynthesis, our organelle of the day was the chloroplast. And when we talked about cellular respiration, the organelle of the day was the mitochondria. When we talk about protein synthesis, really the organelle of the day is the ribosome. The ribosome is the organelle that takes that messenger RNA code, the instructions in the messenger RNA goes through the process of translation and produces a protein. How does transcription happen?  And I'm going to tell you the name of this enzyme, because it's should be familiar after we talked about DNA replication, we've seen this name before, the main enzyme that facilitates transcription is RNA polymerase. Okay, that's it. That's the central dogma. Now, a couple of thoughts about this. First of all, it's a complicated two step process, very molecular, very wild, very complicated, much more complicated than what we are going to have time or energy or capacity to talk about in this class. Why do we have two stages, especially like why in eukaryotes do we have two stages of this? Why can't we just take the DNA, the information from the DNA and take it to the ribosome to be translated into proteins? Well, the fact is, think about it a second. If you had to take an entire giant molecule of DNA and a whole chromosome of DNA out of the nucleus and into the cytoplasm, it's that is going to be an inefficient process. I often think of the DNA as like, I don't know, like a whole set of encyclopedias, like imagine the internet but printed.   And so you wouldn't, you'd go to the library. I remember doing this. I would go to the library, I would grab a book and I would take notes on the part that I needed. I didn't need to check out that entire massive book because usually there were like three pages that had the information that I wanted. And then I would take notes. That's what's happening here. The DNA doesn't have to go to the ribosome to produce the protein because we're just going to take the one recipe, the notes required to build just the one protein that we need in this situation. Then that messenger RNA goes out and it's little. And I say it's little. It's little compared to the entire DNA strand. Remember the DNA, like I don't know what was it, chromosome number one had like 4,000 genes on it. That means that it has 4,000 strings of DNA, pieces of DNA that code for proteins. But the amazing thing is that not all of our DNA codes for proteins. In fact, it's like 1% of our DNA that actually codes for proteins and the rest of it is regulatory. And we'll talk about that later in this section. But why take all that regulatory DNA out? Why take all that extra stuff when really all you need is that one example? I also think of it as like a recipe book and recipe cards. Like you copy the recipe you want onto a recipe card and then you take that to your kitchen and make the recipe, make the product, which is the meal. I would make cookies. I wouldn't make anything else. What about you? It's often helpful to come up with an analogy that works for you that helps you remember the central dogma. And it's always helpful to get pictures of dogs. There's a whole section on Wikimedia that is three dogs. So you can look it up and you can find like hundreds of pictures of three dogs. Okay, I'm going to go away and let's see what are we doing next. We're going to talk about transcription.


Sam will give the talk, yeah. All right, so hi everyone, I'm Sam, and I'll be talking about private puncturable PRFs today. So there's a joint work with Dan Bonet and Harp Montgomery. Okay, so let me start off the talk by recalling the notion of pseudo-random functions. So pseudo-random functions or PRFs are very basic building blocks in cryptography. So it's just a key function with some associated domain and range such that the following two distributions are indistinguishable. Okay, so in the first distribution, an adversary makes a number of adaptive evaluation queries to the challenger, and the challenger answers the adversary by evaluating the real of PRF function f to each of the adversary's queries. In the second distribution, an adversary makes a number of adaptive evaluation queries, and this time the challenger evaluates a truly random function to each of the adversary's queries. Okay, and PRF security states that these two distributions are indistinguishable. All right, so recently, three independent works, Bonet Waters 13, Boilat et al. 13, and Kayes et al. 13, introduced this notion of constrained PRFs. So constrained PRFs are just like regular PRFs, but they have an additional functionality. They have an additional algorithm called the constraint algorithm. And so what is this constraint algorithm? It basically takes in a regular PRF key k and also a constraint function or a constraint predicate f and generates another PRF key that we know the case of f and we call a constraint key. And this constraint key can be used to evaluate the PRF at all points x in the domain where f of x equals to one. Okay, so it's basically taking a regular PRF key k that can be used to evaluate the PRF at all points in the domain and it's generating a more restricted key that can only evaluate the PRF at only a subset of the domain. All right, so for correctness, we require that the PRF evaluation using the constraint key at points x where f of x equals to one, this should yield the correct PRF, the real PRF evaluation at x. And for security, we require that the PRF evaluation at points x where f of x equals to zero. So this should look indistinguishable for random to an adversary who is given the constraint key. Right, so constrained PRFs are very useful on ocean syncryptography. It has many applications. So for instance, it can be used to construct the identity-based key exchange. It gives rise to optimal broadcast encryption schemes and so on. So for this talk, I'll be talking about a special family of constrained PRFs called puncturable PRFs. And in particular, these family of constrained PRFs have been used quite widely in the punctured programming paradigm of the high-end waters for constructing schemes from indistinguishability obfuscation. All right, so since I'll be talking about puncturable PRFs, let's find these a little bit more specifically. So these are just constrained PRFs where we restrict family of constrained functions to just be point functions or complement of point functions. So a constrained function is defined with respect to a single point in the domain, C in this case. So the constrained function on input x evaluates to one on inputs that are not equal to C and evaluates to zero on inputs that are equal to C. So all this is basically saying is with the puncture key, you can evaluate the PRF at all points except for at the puncture point, except for at the single point. So it turns out that puncturable PRFs can be constructed from standard GGM tree-based construction in a pretty straightforward way. But one thing to note about this construction is that the puncture key must necessarily contain information about the actual puncture point C. Okay, so a natural question that we can actually ask is can we construct a puncturable PRF where the puncture key does not leak any information about the underlying puncture point C? And so more generally, this is, we can ask the question of can we build a constrained PRF where the constrained key does not leak any information about the associated constrained function F? And this is the question that Bonnet et al asked recently. And so how do we actually formalize this notion? So it's pretty simple, right? So we can define it in terms of security game where an adversary first commits to a pair of functions, F0 and F1. These are constrained functions. And in the first game, the challenger generates a constrained key with respect to the function F0. And in the second game, the challenger generates a constrained key with respect to the function F1. Okay, and privacy requirement states that these two distributions should be in this emotional, all right? So for this talk, I'll be focusing mainly on private puncturable PRFs. For in the next talk, you'll hear from Yolei about more general privately constrained PRFs for more general circuit constraints. All right, so okay, so for this talk, we'll be focusing on private puncturing. So this is basically puncturable PRF that satisfies these three properties. So for correctness, we require that if you evaluate the PRF using the punctured key, then this should yield the correct PRF output at all points, X that's not equal to function point C. And it should satisfy sort of randomness. So the PRF evaluation at punctured point should be, can everybody hear me? Sorry about that. Okay, so for sort of randomness, we require that PRF evaluation at the punctured point should look indistinguishable for random to an adversary who is given the punctured key. Yeah, so for privacy, we require that the punctured key to not leak any information about the punctured point C. So what does this privacy give us? So why is this an interesting notion? So there are a number of applications. So many of them are highlighted in the original paper, the BLW paper that introduced the notion. So for this talk, I'll just talk about one particular application. And this is for, this is application to private keyword search in distributed database. So one way of viewing private puncturable PRFs is as an advanced form of distributed point functions. Okay, so distributed point functions or DPFs is a notion that was introduced by Gilbo and Asha in 2014. And the idea is the following, right? So you start off with a point function, P sub C, okay? And we basically secret share this function into two distributed point functions, F zero and F one. So let me put a tilde there just to distinguish it from the PRF. And these two functions have the property that if you evaluate each of these functions separately on an input X and basically sum up the result together, then you should basically get a point function, okay? So on input X that is equal to C. If you sum them up, then you should get a non-zero value. And if you, for inputs that are not equal to C, if you sum them up, then you should basically get zero, right? So you can actually instantiate distributed point functions using private puncturing by defining the first function to just be the regular PRF evaluation function using the regular PRF key K. And you just define the second function to be the PRF evaluation using the puncture key. Okay, and by PRF by correctness of our construction, if you evaluate the first and the second functions separately and just, and I guess in this case, subtract the result, then you should get a non-zero value for inputs X that are equal to C and you should get zero for inputs that are not equal to C. Oh, and I forgot to mention the private security requirement that the security requirement for distributed point functions is that for an adversary who is given only one of the two functions, then the adversary should not learn any information about the underlying point C, right? So one difference between a DPF and a private puncturable PRF is the following, right? So for distributed point function as set up, or once the point function is set, you come up with these two functions, F0 and F1 simultaneously. So you have to generate them together. But for private puncturable PRF, you have this sort of adaptive property where even before, in the offline phase, even before you commit to the point function C, to the point C, you can actually just instantiate the first function by generating just a regular PRF key key. Okay, and at a later point in time, once you decide on the point C, then you can actually instantiate the second function by generating the puncture key. Okay, and this leads to a number of applications. So one application of distributed point functions is in the setting of distributed database in private keyword search. So in this setting, we have two servers holding a database of our keywords. So W1 all the way to WN. And we have a user who wants to check whether a particular keyword is contained in the database. Okay, so W sub j. And the user wants to check whether keyword is contained in the database without revealing what the keyword W sub j is to each of the servers. So one way of doing this is to define a point function with respect to the keyword W sub j, and basically generate two distributed point functions, F0 and F1 with respect to this point function. Okay, and basically sends these two functions to the servers, and the server evaluates these functions to each of the keywords in the database, sums them up, and basically sends them back to the user. And the user can just add these two results up. And if the result is non-zero, then it knows that the keyword W sub j is contained in the database. And if the result is zero, then it knows that the keyword is not contained in the database. All right. And the privacy property of DPFs guarantees that each of the servers do not learn information about the keyword W sub j. Right, so using private punctual PRFs, you can actually emulate this protocol, but this offline, online property of private punctual PRFs translates to the setting. Okay, so in the setting, the user can just, even before knowing which keyword to search the database, it can just generate a real PRF key and just sends it to one of the servers. And the server, to a single server, and the server can follow the protocol by applying the PRF on each of the keywords and just sum the results and sends them back. And the server can actually just go offline. It does not get involved in the protocol. Okay, and at a later point in time when the user wants to query the database on a particular keyword, then the user can just generate a punctual key with respect to the keyword W sub j and just sends it to the other server. Okay, right, and the other server basically just follows the protocol by applying the function to each of the keywords and just summing up the result. Okay, so this has a property that the user actually just has to interact with one of the server, and one of the servers can actually just be offline. All right, so let's talk about one of the constructions. So punctual PRFs prior to this work had a very extreme state of affairs. So to actually get public puncturing, you just require one-way functions using the GGM tree-based construction. To actually get private puncturing, you actually had to go all the way to multi-layer maps or IO. So this construction is due to the original BLW paper. And this work basically, we basically push the minimum assumption that's required for private puncturing to just be LWE. It's just we just constructed from lattices. Okay, and of course the natural open problem is can we actually move it even further? So since we can get public puncturing from one-way functions, there isn't really a reason why we can't get private puncturing from one-way functions. And I think this is a really nice open problem that I just wanted to mention. All right, so let me just give a quick overview of what we do in a construction. So we just work with learning with errors. So for a uniformly generated matrix A and a randomly sampled vector S and E from some low-norm error distribution, LWE just says that the following two distributions are indistinguishable. So in the first distribution, the adversary gets the public matrix A and also this noisy vector matrix product S times A plus E. And in the second distribution, the adversary gets the public matrix A and also this time a uniformly sampled vector U. And LWE just states that these two distributions are indistinguishable. All right, so the basic technique that we just used is this matrix circuit encodings that was first used by Bonnet et al in 2014 in the setting of attribute-based encryption. So this is just an encoding scheme. So you start off, okay, so you have encoding scheme for scalar elements, serving elements or field elements. So to encode an element X of I with respect to a public LWE matrix A sub I, then you just compute this vector S times AI plus Xi times G, where G is this public gadget matrix and you just add some noise to it. And the benefit of encoding and encoding elements this way is that it allows for homomorphic operations on the encodings. And in particular, for a circuit F, we can just homomorphically derive the encoding of the value F of X with respect to the public matrix A sub F. And a nice property of this homomorphic operations is that we have an analogous homomorphic operation on the public matrices, A1 through AL, and we can, and to derive the matrix A sub F. And this public matrix homomorphic operation does not require any information about the underlying encoded values or the encodings. All right, so in particular, if you actually encode our puncture point, the string C of length N, and using this encoding, then we can actually just compute the equality check circuit with a PRF input X hardcoded inside the circuit and get an encoding of the result of the equality check circuit on the puncture point. Okay, in particular, this equality check circuit will output zero if X and C are different and it will evaluate to one if X and C are equal. And the basic idea of our PRF is to just define our puncture key to be these encodings of the puncture point C. Okay, and if we actually define our PRF to be what looks like an elderly sample with respect to the matrix A sub X, so we define our PRF to be S transpose A sub X plus E and then using the puncture key, you can actually just derive the PRF output by running the equality check circuit on the encodings. And so since PRF have to be a determinist function, we basically, instead of adding noise, we just round the result. And it turns out with some small modifications, we can actually prove this PRF to be secure. And this is actually a special case of constraint PRF construction due to Berkersky and by Kuntanathan. And this actually leads to a public puncturable PRF.  Okay, so to actually get private puncturing, we borrow the ideas from the predicate encryption constructions of Gorbner-Fettel. So before we encoded in this encoding, we just encrypted using a fully homomorphic encryption scheme. And then we just encoded. Yep, and then we basically just compute the equality check circuit inside the FHG homomorphic operations. Right, so a problem with this approach is that the quality, at the end of the day, after you finish the quality check circuit, the result of the quality check is encoded inside the FHG encryption. Okay, so there must be a way to actually extract this information. And we resolve this by just publish, just including as in the puncture key, the encodings of FHG decryption key. And we use the fact that to actually multiply, for these homomorphic operations, to actually multiply two encodings, you actually need just one of the encodings to one of the encoded values and not the other. And this allows us to compute inner products of the FHG, of the encryption of the quality check circuit and the FHG secret key. And we use the property that for FHG decryption is a noisy inner product. And there's some technicalities here that we have to actually take care of the noise that comes out of the FHG decryption. And for this, due to time constraints, I will not be able to actually talk about this. So I'll just refer to the paper. And to conclude, so I want to mention a concurrent work by Kanedi and Chen. So I think you'll hear from Yole in a second in the next talk. So the techniques are actually quite different. So they use instances of GGH-15 multilayer maps that are still reducible to LWE. So we use techniques from attributes encryption and predicate encryption. So I also want to mention some extensions. So we were able to extend these techniques that are used in this work to get watermarkable PRFs from LWE. And this was only previously known from obfuscation. So you'll hear more about this in the run session tomorrow. And so let me just conclude with some open problems. So I guess a nice open problem, like I mentioned, is can we actually get private punctual PRFs from other assumptions like the DH pairings or just even more functions? So are there other applications of privacy in constraint PRFs? And also, so I wasn't able to talk about the new techniques for this talk, but can we actually apply the techniques in this work to the setting of predicate encryption, for instance? I think that these are very nice open problems. Okay, and with that, I will conclude. Okay, so are there any questions? Are private punctual PRFs known to imply anything stronger than one way functions like OT or PKE? Yeah, so for actually constraint PRFs for two keys actually implies IO, but for punctual PRFs, you can actually just publish only a single key, right? So if you actually publish two punctured keys, then you can evaluate the PRF on all points. So you can't actually have a well-defined notion of security in that notion. So does that answer your... No, the question is if the existence of private punctual PRFs is known to imply anything beyond one way functions? Oh, no, I don't think it's not really known, yeah. So the template you described didn't seem to use anything very special about equality. Can you say a little bit about why you would like, you know, restricts you to point puncturing rather than general functions? Well, so yeah, so I was hiding all the details under the rug, but first we weren't able to get the parameters to work out, so the parameters are kind of becomes circular, so we couldn't find the parameter that worked out. And so to actually get, and we thought it was quite, so since we can only publish a single key anyway, so we thought actually private puncturing is actually more natural, so yeah. So did you look at PRFs that have unbounded inputs on to achieve this private puncturing? It seems that these techniques do not extend naturally to unbounded input, right? Because they reveal the size of the input. Right, right, so for punctual PRFs, you actually need the puncture point to be fixed because we need the puncture key to be finite. So the techniques used in this work does not, I'm not sure if it's even well-defined from unbounded inputs. I mean, in the challenge experiment, if I give you two X's of varying length, then depending on the size of the key that I get, I can distinguish easily because the size of the key would be kind of linear in the size of the input. So the PRF has to be a fixed input, no? Right, right, right, yes, I think we're right here, right? Yeah, okay, thanks.


From VOA Learning English, this is the Agriculture Report. Farmers in the United States are experiencing two big problems. There is a shortage of people to work in their fields. The workers they do have are mostly from Latin America, but many have entered the country with false documents. Farmers say that without immigration reform, both problems will continue. The Imperial Valley is an agricultural area in the western state of California, near the border with Mexico. Farmers there are above 38 degrees Celsius during the summer months. As a result, not much grows in the Imperial Valley at this time of year. But in the winter, the fields are filled with lettuce and celery, and in the spring, farmers grow fruit like cantaloupe and watermelon. Here also is work to do in the fields during the summer. Francisco Sosado uses farm equipment to prepare the land for planting in the autumn. He lives in Mexico and wakes up in the middle of the night, so he can avoid long lines at the border crossing. Mr. Sosado says that if he did this kind of work in Mexico, he would earn about $6 a day. But in the United States, he makes as much as $90 a day. Farmer Larry Cox says growing and harvesting vegetables depends on migrants or day laborers from Mexico. But he says not enough laborers are crossing the border. Mr. Cox says it is difficult to get visas to work in the United States. As a result, many farm workers from Latin America carry false documents. Tom Nasif is president of the Western Growers Association, a U.S. farmers business group. He says there are about 11 million workers in the United States with false documents. More than one million of them work in agriculture. For VOA Learning English, I'm Carolyn Presuti.


Hello friends, and how are you all doing today? Let us integrate this function. We have the function as tan cube 2x into secant 2x into dx. Now, we can write tan cube 2x as tan square 2x into tan 2x, right? We will get multiplied by secant 2x into dx. Further, we know that tan square 2x can also be written as secant square 2x minus 1. So secant square 2x minus 1 will get multiplied by tan 2x and also secant 2x into sorry here it was dx into dx. Further, we have to let t be equal to secant 2x. So dt will be equal to the derivative, that will be 2 secant 2x into tan 2x dx. So here tan 2x and secant 2x into dx can be written as we need to take secant square 2x minus 1 sorry here since secant 2x is taken as t. So it will be t square minus 1 into dt divided by 2. Further, 1 by 2 into integral of t square into dt minus 1 by 2 into integral of 1 into dt. So we have the answer as 1 by 2 into t cube divided by 3 minus 1 by 2 into t plus c. Further can be written as 1 by 6 t cube minus 1 by 2 t plus c. Now here in place of t we can write secant 2x. So we have 1 by 6 secant cube 2x minus 1 by 2 secant 2x plus c and this is the required answer to the session This completes it. Hope you understood and enjoy it too. Have a nice day ahead