ฝึกพูดภาษาอังกฤษด้วยเทคนิค Shadowing จากวิดีโอ: Personalised Cancer Care - Prof Mark Middleton
กำลังสร้างบทเรียน...
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So we're going to talk about personalized cancer care
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and the focus is going to be on what we're doing clinically to change what patients across the street
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and here experience if they come to have their cancer care here in Oxford.
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So the key to personalized cancer treatment, and I'll come back to the difference between care and treatment in a minute,
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is really about giving the right treatment, and that today in cancer treatment consists largely of surgery,
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of radiotherapy, or of giving drugs to the right patient.
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And we rely upon a series of tests, which Dr. Xu's going to talk about some of them later, and I'm going to mention during my talk,
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in order to make sure we choose the right patient.
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Then the other thing we have to do is to give it at the right time.
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Most of the treatments that we use for cancer have quite significant side effects
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or time to recover from that in the case of surgery.
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And so we're always having to balance the risks of what we do, which can sometimes prove fatal,
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with the risks of doing nothing or doing something else.
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And I guess that's what we mean by personalized cancer treatment.
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Personalized cancer care is slightly different.
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The right treatment obviously is implicit in choosing the right person to give that to, but it also has to be delivered in the right context.
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And what do I mean by that?
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Well, and it has to have the right support.
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Sorry, my slow reveal of my slide isn't working quite as well as I'd hoped.
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So the right context means about that being a shared decision between us as clinicians and the patient,
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not merely about us handing out a ticket by road as you come through the door, you know, line one, line two, line three and so forth.
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And it also means perhaps considering whether we need to leave the concept of the hospital behind,
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you know, how much of this treatment really needs to be delivered in big centers here in a highly specialized manner.
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What can we do at home?
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What can we do closer to home if we can't actually do it at home?
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and then what support can we offer in delivering that so that it's truly about care, not just about handing out treatment, take it or leave it,
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and then leaving patients and their families to get on with it.
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And that's about having the right information so that patients can make the informed choices.
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And it's also about having the right psychological support in and around the treatments that we offer,
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both from the clinicians offering the treatment informally from professional psychologists and psychiatrists,
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and also the right psychological support out and about away from the hospital, either through peer support by meeting other patients in the same position
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or other families who faced similar decisions and dilemmas about their treatment,
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not just about handing out the drugs, the radiotherapy, the surgery.
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Having said all that, most of what I'm going to talk about this evening is the drugs, the surgery, the radiotherapy.
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Because of the way in which the Biomedical Research Centre is set up and the things that we're researching at the moment, that is the major focus of what we're doing.
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But I wouldn't want to give the impression that as a trust, as a university, we're not interested in the whole of cancer care,
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and in fact we've been joined recently by Professor Mike Sharp, an expert in the psychological aspects of cancer treatment from the University of Edinburgh,
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who's overhauling the way in which we provide a lot of the support
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and building research into psychological support into a lot of what we do.
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So we already deliver personalized cancer treatment.
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If you are diagnosed with a cancer and come to the hospital, you aren't given the same treatment just because you have cancer.
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The way in which we personalize it at the moment is based upon how old you are, how fit you are, what your gender is sometimes,
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and also principally where we found the tumor and where it started in the first place.
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So when we talk about cancers we often show slides such as this saying, you know, what's the most common cancer in a given situation?
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You know, for men it's prostate cancer, for women it's breast cancer.
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And we all think in terms of the treatment with I have breast cancer, I have lung cancer, I have bowel cancer and so forth.
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And that's because that's the way the treatment's set up.
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Partly because the surgeries are different, because the drugs are different, because the radiotherapy is different.
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So one could argue that we already have personalized cancer treatment in the NHS today.
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But what we have is very, very broad brush.
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And what I want to talk about is the ways in
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which we're trying to move on from that and to provide something that's very much more individualized,
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not quite down to the level of each patient as a true individual having something that's absolutely tailored,
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but certainly moving away from groups of dividing cancers up into groups of 10
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or 20 or 30 groups and starting to think about 100, 1000, 10,000 groupings.
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So if you take a very rare tumor, sarcoma, which is treated mostly here at the Nuffield Orthopedic Centre
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and is too rare to even feature on this top 10 slide here,
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then we already know that that is now over 100 different types of cancer.
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all of which have a hundred different types of behavior, a hundred different types of outlook, and therefore the idea that we put everybody in a sarcoma box
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and treat them all in the same way simply doesn't hold water.
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So from that, the question is, well, how do we then define these hundred different groups?
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Because until we've defined them, we aren't in a position to start to sort out what the best approach to treating them is
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and to therefore looking after the patient who has that particular type of cancer.
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So one of the principal ways in which we're starting to change that, and Dr. Su is going to talk about that later, is genetics.
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And through detailed genetic analysis, and Chris alluded to the fact
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that we use what's called next generation sequencing now to get
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a more detailed genetic profile of the cancer as part of what we do.
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And this is already routine in some areas like sarcoma, in the blood cancers in particular, a variety of tests are used as a matter of course
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in order much better to define what the appropriate approach to treatment might be.
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We also have to consider in this the patient
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because important aspects of our treatment now use the patient as our principal weapon against the cancer.
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In particular what I'm talking about here is immunotherapy.
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We all have functioning immune systems that keep us alive from attack from bugs, outside poisons and so forth.
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And increasingly we're starting to see that there's a way of harnessing
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that to treat cancers as foreign and undesirable and use the immune system to eradicate them.
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And I'd argue that that's probably the purest type of personalized therapy that you can have.
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There's been a lot in the press recently about major breakthroughs in my particular field, which is melanoma.
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and clearly this is going to play out quite considerably over the next decade or so, and have a very, very large impact on the sorts of treatment that we offer here in Oxford,
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and indeed worldwide for cancer.
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But I'm not really going to talk about that much today because this is at a very,
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very early stage and not something that we can really go into too much detail at the moment.
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We're just starting out on that journey.
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The other way in which we define cancers and have done for many, many years in the pathology lab is to look at the levels of particular proteins on the cell surfaces.
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This tells us a little bit by one remove about how the cancer is likely to behave.
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It can also allow us to use our current sorting method as effectively as possible
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because by seeing what proteins are in a cell, we can sometimes tell where it came from in the first place.
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So if we find a tumor in the lung, this is the method that we currently use to tell whether it's a primary lung cancer, so it's started in the lung,
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or whether it's perhaps a breast cancer or a bowel cancer that's traveled there.
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It's therefore secondary and demands a different approach.
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The other way in which we look at this is to look at things like cell shape and cell behavior.
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And cell behavior in particular is important.
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We have very, very sophisticated scanners now to look at the shape of what's going on inside us,
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but they increasingly pick up lumps that we're not really sure what they mean.
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And by looking at how the cell behaves, in particular what its metabolism is doing, using PET scans and so forth,
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that can give us a handle on whether we're looking at something that's really a problem
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or whether this is an incidental finding that could be left to one side, not a cancer, as one example.
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But also how cells behave, as I'll show you later, is also an indicator of how we might approach treating them.
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So just to touch briefly on the genetics, this is an example going back to what we talked about, a hundred different types of sarcoma.
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What you can see here in A, C, D and E, ignore the bottom line which is a slightly different bunch, is a bunch of sarcomas,
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and this is looking at chromosomal rearrangements, if you look at the lines inside the circles here, you can see that the key point I'm trying to make is they're all radically different.
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And therefore the assumption
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that we can manage all of these in the same way is probably not valid and something that we need to reconsider.
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The main way though at the moment in which we look at the differences between particular tumors is down the microscope,
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looking at the shape, the organization of the cells, but we are conscious of the fact
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that whilst doing this we leave a lot of information behind
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because we only make a relatively cursory inspection and usually focus down on one,
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two, half a dozen proteins in order to tell us what to do.
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The purpose of this slide isn't to illustrate anything other than the fact that very, very detailed looking at the proteins and starting to go back right to the beginning
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and look at everything and not throw away a lot of the information that we've previously ignored
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is leading to new insights about how best to look after patients and whether to start treatment at all in some instances.
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And we're starting to harness the power of computers and machine learning in order to do that.
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So as we gather more information and we don't throw it away, it very, very soon gets beyond our ability to process it.
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We simply can't understand it.
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So, what we can do though is use machines to learn
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which aspects are important and rather than our biases
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that we arrived at when we first looked at the slide down the microscope, we can get the machine to tell us whether there are better markers that we can look at in doing this,
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that give us better quality information about the patient.
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So that's really a brief synopsis of the ways in
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which we're trying to describe the tumors better so that we can target our treatments more effectively.
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But that gives rise to a different question which is how does cancer treatment improve?
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And I just wanted to touch on that briefly.
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So if you read the papers, then cancer treatment improves in giant leaps through magic bullets.
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And that's a horrible mixed metaphor, I apologize for that.
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And here's the poster child of the magic bullet.
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So in chronic myeloid leukemia, it's long been known that there's been a rearrangement in chromosomes.
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If you start on the left, you've got the normal chromosome 9, the normal chromosome 22.
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When they break and rearrange, this forms a fusion called the Philadelphia chromosome, which gives rise to an active protein that changes cell behavior
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and is responsible for what we call in the jargon the malignant transformation and the cancerous nature of the leukemia cells.
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And about ten years ago we found a drug imatinib that can essentially counteract this overactive protein.
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And it can make the chronic myeloid leukemia go into remission, it can hold it in remission for a time,
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and new developments in next generations of drugs have extended the time in which that can be held.
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So this is the archetypal Daily Mail, Daily Express, Daily Telegraph, Daily whatever your favorite read is,
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view of how we make changes in cancer.
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But in fact, for every poster child like this, there's another non-poster child that gets slightly glossed over.
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And rather than rain on anybody's parade other than my own, I'm going to take an example from my field to show
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perhaps a slightly more mundane reality with some of these magic bullets.
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So we have a similar situation in melanoma where about half
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of patients in their melanoma we can find in this case a mutation in a gene
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which leads to an overactive protein called BRAF.
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and about five years ago the news broke through clinical trials of a drug now called Vemurafenib
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which can inhibit this overactive form of BRAF.
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So when BRAF is mutated and overactive it makes the cell grow.
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If you switch that off you remove the growth driver to the melanoma cell.
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And that had very, very spectacular effects.
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So, on the left you see a PET scan, it's like the old-fashioned PET scan showing very,
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very metabolically active tumors in a patient who's standing facing the camera.
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You can see the brain,
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the heart, and the bladder in outline within that because they're metabolically active in their own right.
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But all the other dark spots on the left-hand picture are either small amounts of bone marrow or active areas of tumor.
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And a couple of weeks after starting on the drug, this is what's happened to the scan on the right-hand side.
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So it's a very, very spectacular effect.
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The tumors shrink with this.
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The patient feels better.
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But that effect is lost very rapidly within months.
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And that's the reality for almost all of the patients whom we treat with this drug.
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And I'll come back to this later on in the talk about why
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that might be and what we can do to try and tease some of that out.
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But what this means is that cancer treatment doesn't really undergo revolutions.
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It, you know, these magic bullets aren't out there all the time.
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And actually the way in which we make pro, progress is, more prosaic.
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And in fact, one of the biggest contributions
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that Oxford's made to cancer care is actually by synthesizing the results of hundreds if not thousands of researchers around the world,
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in particular in the field of breast cancer.
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at the Clinical Trial Support Unit which is in the Richard Dole building across the street, they've brought together the results of all the breast cancer studies
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that have been done and asked a series of questions
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and made some definitive observations about the best ways in which to treat particular types of breast cancer.
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And this example here looks at the chances of a breast cancer coming back in women who've either had breast conserving surgery,
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BCS here, if you look at the left hand curve, or some radiotherapy on top of that.
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What you can see is a very much diminished chance, that's ten years, of the cancer coming back,
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if you have a radiotherapy on top of the surgery.
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Perhaps more surprisingly, because this is a treatment that's local, it's applied only to the breast, not all over the body,
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this also has an impact upon the chances of dying of breast cancer further down the line.
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But the thing I want to draw your attention to, rather than those results and that observation, is the fact
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that this is a result that's come from looking at over
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10,000 women who took part in 17 different trials around the world.
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So this wasn't a magic bullet, an observation, suddenly it's all going away.
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This is years and years of incremental work.
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And the same is true, and this is again from the same group,
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looking at whether adding chemotherapy in a similar situation has the same effect.
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And again, this is now long-term outcome from over 100,000 women in over 100 different studies.
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It makes very clear what you can get out of conventional chemotherapy, but it also makes it very clear
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that you have to be in this for the long term in order to be absolutely clear
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that what you're doing is helpful.
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So, cancer treatment evolves, it's evolution not revolution, and the reason I've stuck up Chris Hoy there is really,
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it's a similar approach, if you like, to the British Olympic cycling team.
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The way they said they set out to be the best in the world was that no gain was too small, half of 1% was good enough,
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because by the time you added up all the halves of 1%, you got something tangible and substantial.
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So, bearing that in mind, what are we doing then in this long game in order to improve things for patients?
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Well, if we take another step back, at the moment the way in which we cure cancer is by cutting it out, by and large.
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That's responsible for the majority of cures.
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This is now about curing, not just treating.
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And then for the substantial part of the rest of the patients who are cured, that's done by using radiotherapy.
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Drugs contribute only a relatively modest part of cure, and that's really only in a relatively narrow group of cancers,
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affecting children, germ cell cancers, hematological cancers, blood cancers.
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But you wouldn't believe that from reading about how cancer treatment evolves in the press.
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So I want to take a little bit of time to talk about what we're doing with surgery
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and with radiotherapy to make that personal to each individual patient.
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Obviously surgery to a certain extent is personal, you get a bespoke operation every time.
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We follow procedures and protocols to make that operation as safe and as effective as possible but as you'd anticipate, when a surgeon is cutting a tumor out,
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he or she does that on a very individual basis.
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However, that doesn't mean there isn't room for improving the personalization and making it truly more effective, and a lot of the attempts
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that we have done to move this on over the years
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have been based around doing less damage as we go about that process.
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taking less normal tissue along with the tumor
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and being much clearer about what does and doesn't work
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and making sure that we only get really aggressive with our operations when that's truly effective.
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And one of the approaches within the Biomedical Research Center
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that we're pioneering to try and improve upon this is fluorescence image guided surgery.
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So what you can see, probably not very well, and I apologize for that, in the left-hand panel on the top is what the surgeon sees with the naked eye,
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with a very powerful light
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when they're looking inside an abdomen trying to identify where the cancer is and to decide where to do their operation.
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Now, using fluorescent tags that pick out cancer cells, you can get the image on the right.
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You do have to turn the main light off in theater, so it's a slightly surreal experience and a little bit alarming,
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the idea that people are wielding knives in the dark,
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but it does mean that you can pick out much more accurately where the cancer is
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and guide your surgery much more effectively for that reason.
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And this is now being used in gynaecological surgery.
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I think this was the only picture we thought we could show that wouldn't necessarily be off-putting.
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And this is a reality in operating theaters across the street at the Churchill Hospital.
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And it's being used to guide the extent of surgery for women with ovarian cancer.
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And at the moment this is at the stage of proof of principle.
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Assuming that we can prove this principle, which I think we're reasonably confident we can, what we'll then need to do is to construct clinical trials
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to show whether doing this improves the outcome for patients beyond conventional surgery.
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So turning to radiation treatment, the problems there are very similar.
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Both surgery and radiation are extremely effective at getting rid of cancer, but the trick is not to damage the patient in the process.
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And with both treatments, the bigger the amount of radiation, the bigger the surgery you do,
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the more likely you are to create damage that then becomes permanent permanent
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and has a real impact on patients' lives as increasingly they survive and live beyond their cancer.
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So I've talked a little bit about how radiotherapy, how surgery is becoming more personalized,
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more individualized to the patients by individual planning and so forth.
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I think we've also covered a little bit about how functional imaging, I'm going to talk about that for a couple of minutes
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means that how the tumors behaving can also guide what we do
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and allow us to think about new ways of combining treatments to make the existing ones more effective.
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And then finally, I think we can talk about how by using our molecular understanding of cancers, we can divide them into much smaller groups,
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which mean that we can give treatments much more precisely in a way
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that allows us to have greater confidence that they're likely to be successful in the longer term.
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So this is work in breast cancer from Professor Adrian Harris, one of my colleagues in medical oncology.
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We've known for a long time that an anti-blood vessel treatment called Avastin can be very effective in breast cancer.
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But as we've used it more and more, we've found it to be less and less effective.
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And so what's clear from this is that there are a group of women who do benefit from the drug,
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drug, but as you widen the women that you give it to, that group doesn't change and so the overall impression is the drug is less effective.
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So the question becomes how do you choose who should get this drug?
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Because it has side effects, we could use other drugs instead of it
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and therefore it's not just a question of whether you give it and if it doesn't work well so what?
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And that's even before you get on to the issue of cost.
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And so what Professor Harris described was three different ways in which breast cancers respond,
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which are shown here, to the Avastin.
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So on the left-hand side you see a picture of a tumor in a breast, the tumor, the breast is blue,
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the tumor is yellow or red according to the leakiness of the blood vessels in the tumor, and then the effect of the Avastin in each case.
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So on the top what you see is the effect that we're looking for,
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which is the blood vessel abnormality essentially being corrected by the Avastin.
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Below you see two ways in which it doesn't work terribly effectively.
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Bottom right what you're seeing is the tumor basically ignoring the Avastin,
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And what you're seeing on the left is that the central part of the tumor is responding,
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but the growing rim of the tumor around the edge is effectively ignoring the Avastin, and so that's unlikely to have a material effect upon how the tumor behaves
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and improve the treatment that's been given with surgery and chemotherapy alongside this.
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Now those are the clearest examples, indicated by the arrows really,
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of a whole different series of responses that we can measure by using MRI scanning.
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But more importantly, what we can then do is having seen this on our MRI scanner,
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this was done in ladies who are going to have surgery for their breast cancer anyway, anyway, we can then go in and take a sample of the tumor
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and look at what genetic changes are happening and how the genetics in each tumor differs according to the response of the,
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to the treatment.
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And what we can then do is to categorize those genes as shown here
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and then link them back to the pictures that have been taken in order to define,
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well, in order to detect what defines who responds best to the treatment.
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In the interest of time I'll skip on from that though.
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So that's just an example really of how the genetic side of things is linking in with the imaging
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and allowing us to look at how tumors function and relate
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that to their genetics and then
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that gives us a clue as to what particular aspects of
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a tumor need to be in place for a particular treatment to work
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which is in itself interesting
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because it allows us to choose whom to give a treatment to
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but it also tells us why it doesn't work in the other people
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and suggests ways in which we could perhaps make it work by manipulating tumor behavior in the future.
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So, to come back to genetics now for the last couple of minutes that I'm going to talk, and then I'm going to hand over to Dr. Xu.
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Our concepts of site-specific cancer are changing rapidly rapidly, we can now divide up things like lung cancer,
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like melanoma, into different groups based purely on the genetics.
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And here are a number of mutations that can be found in lung cancer.
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Now, in some tumors, lung cancer, melanoma, there are 30,000 genetic abnormalities if you sequence the whole genome of a cancer.
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So one of the issues we struggle with is what are the driver mutations, the mutations that dictate cancer behavior, as opposed to the passenger mutations or changes,
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the ones that are just there for the ride
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that really are irrelevant to how the tumor's going to behave and therefore how it's best treated.
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And that's a significant work in progress.
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But these ones here, KRAS, EGFR, EM4ALP, these are all abnormalities that we can target with drug treatments at the moment.
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So this isn't a theoretical exercise, this is a clinical reality that's defining who gets what drug
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and how we get the best possible response for the least possible side effects for our patients.
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And that's summarized really at the moment we have four genes in solid tumors as opposed to blood tumors
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that we look at in detail as part of our routine
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testing for these groups of patients to tell us what to do if the spread of the tumor throughout the body.
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But we've gone beyond that and extended the range of mutations quite considerably that we look at as a matter of routine,
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because it's not just a question of seeing something that we can throw a drug at.
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What's going on elsewhere in the tumor, those other 30,000 events, or in this case a rather smaller number, because that's what we can get a handle on at the moment,
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also tell us about the chances of treating the index mutation.
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You know, how is that going to work out?
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So it's not just a question of focusing on one thing, knocking it off, because then you've got, you know, the question becomes what's the next thing, what's the next thing after that, and so forth.
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If we come back to the drug vemirafenib that I talked about at the beginning, which targets this BRAF mutation, and which, you know, as I showed with the PET scan,
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what happens is it works very, very well, and as this graph shows, much more effectively than chemotherapy with decarbazine as a means of holding the tumor in check.
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But the key thing to notice here on this curve, which shows the proportion of patients on each drug whose tumor is under control, with everybody under control at the beginning,
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very quickly within nine months, nobody's tumor is under control.
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So this resistance that I showed with the PET scans developing in everybody.
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And what we understand from that is if we look at BRAF here in the middle of this signaling pathway,
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all the orange bits, all the writing in black is showing ways in which resistance can develop.
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So by understanding and looking at the mutations right across the piece,
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we can start to pick out who benefits from the drug either transiently for the long term, and also how that changes.
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None of this is set in stone.
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This all changes as patients are on treatment, so we don't just measure once but we go back and we measure time and again.
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And hopefully in time this will become slick enough and quick enough
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that it will allow us to alter what we do as we go along, rather than waiting for the tumor to come back in order to change our treatment.
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So what I'm going to do now I think is break off there
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and hand over to Dr. Xu to talk a little bit more about some of this some of this
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and then I'll come back for a couple of minutes.
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คำศัพท์และข้อสังเกตด้านการพูดสำหรับบทเรียนนี้
วิดีโอนี้มี 312 ประโยค และ 5017 คำ สำหรับฝึกพูดตาม ช่วงที่มีเสียงพูดยาว 29:45 ผู้พูดพูดด้วยความเร็วเป็นธรรมชาติ ประมาณ 169 คำต่อนาที ใกล้เคียงกับบทสนทนาในชีวิตประจำวัน 86% ของคำอยู่ใน 3,000 คำที่ใช้บ่อยที่สุดในภาษาอังกฤษ ส่วนที่เหลือควรดูไว้ก่อนเริ่มฝึก
คำศัพท์สำคัญในวิดีโอนี้
คำที่ควรเรียนรู้ 15 คำจากวิดีโอ พร้อมคำอ่านและความหมาย:
| คำศัพท์ | คำอ่าน | ความหมาย |
|---|---|---|
| tumor คำนาม | /tuː.məɹ/ | เนื้องอก |
| breast คำนาม | /bɹɛst/ | เต้านม, นม |
| mutation คำนาม | /mjuˈteɪʃən/ | การกลายพันธ์, การผ่าเหล่า |
| lung คำนาม | /ˈlʌŋ/ | ปอด |
| genetics คำนาม | /dʒəˈnɛt.ɪks/ | พันธุศาสตร์ |
| slide คำนาม | /ˈslaɪ̯d/ | กระดานลื่น |
| bullet คำนาม | /ˈbʊlɪt/ | กระสุน |
| ignore คำกริยา | /ɪɡˈnɔː/ | เมิน |
| gene คำนาม | /d͡ʒiːn/ | หน่วยพันธุกรรม |
| cure คำกริยา | /kjɔː/ | รักษา, เยียวยา |
| vessel คำนาม | /ˈvɛsəl/ | เรือ |
| poster คำนาม | /ˈpoʊstɚ/ | โปสเตอร์ |
| observation คำนาม | /ˌɑbzɚˈveɪʃn̩/ | การสังเกต |
| behave คำกริยา | /bɪˈheɪv/ | ประพฤติ, ทำตัว |
| extent คำนาม | /ɪkˈstɛnt/ | ขอบข่าย, ขนาด |
กริยาวลีที่คุณจะได้ยิน
| คำศัพท์ | ความหมาย |
|---|---|
| go back คำกริยา | กลับไป |
| come back คำกริยา | กลับมา |
| pick up คำกริยา | ยก, หยิบ |
| throw away คำกริยา | ทิ้ง |
ไวยากรณ์ในวิดีโอนี้
โครงสร้างที่ผู้พูดใช้บ่อยที่สุด พร้อมคำพูดจริงจากวิดีโอ:
| โครงสร้าง | ในวิดีโอ |
|---|---|
| Present perfect have/has + กริยาช่อง 3 — เหตุการณ์ในอดีตที่ยังเกี่ยวข้องกับปัจจุบัน | we've been joined · have personalized · we've defined |
| Passive voice be + กริยาช่อง 3 — เน้นสิ่งที่เกิดขึ้น ไม่ใช่ผู้กระทำ | be delivered · is set · we've been joined |
| Relative clauses who / which + อนุประโยค — ข้อมูลเพิ่มเติมเกี่ยวกับคนหรือสิ่งของ | sarcoma, which is · field, which is · line which is |
การออกเสียงที่ควรระวัง
ผู้พูดใช้รูปย่อและรูปลดเสียง 81 ครั้ง เช่น we're, I'm, doesn't ให้พูดแบบสั้นตามที่ได้ยิน
- เสียง “th”: chemotherapy /ˌkiːməʊˈθɛɹəpi/, theater /ˈθi(ə)tɚ/, gather /ˈɡæðɚ/, theoretical /ˌθi.əˈɹɛt.ɪ.kəl/, pathway /ˈpæθˌweɪ/
- เสียง “sh” และ “zh”: mutation /mjuˈteɪʃən/, radiation /ˌɹeɪ.diˈeɪ.ʃən/, observation /ˌɑbzɚˈveɪʃn̩/, essentially /ɪˈsɛnʃəli/, impression /ɪmˈpɹɛʃn̩/
- คำยาว — ลงเสียงหนักให้ถูกพยางค์: psychological /ˌsaɪ.kəˈlɑː.d͡ʒɪ.kl̩/, chemotherapy /ˌkiːməʊˈθɛɹəpi/, radiation /ˌɹeɪ.diˈeɪ.ʃən/, essentially /ɪˈsɛnʃəli/, apologize /əˈpɑləˌd͡ʒaɪz/
วิธีฝึกกับวิดีโอนี้
- ฟังวิดีโอให้จบหนึ่งรอบโดยยังไม่ต้องพูด แล้วจดคำที่ยังไม่รู้จัก
- เริ่มที่ความเร็ว 0.75× พูดตามทีละประโยค แล้วกลับไปใช้ความเร็วปกติเมื่อเริ่มคล่อง
- อัดเสียงตัวเองแล้วเทียบกับต้นฉบับ โดยสังเกตคำอย่าง tumor, breast, mutation เป็นพิเศษ
เทคนิค Shadowing คืออะไร?
Shadowing เป็นเทคนิคการเรียนรู้ภาษาที่ได้รับการรับรองทางวิทยาศาสตร์ พัฒนาขึ้นสำหรับการฝึกนักแปลมืออาชีพ วิธีการนี้เรียบง่ายแต่ทรงพลัง: คุณฟังเสียงภาษาอังกฤษจากเจ้าของภาษาและพูดตามทันที — เหมือนเงาที่ตามผู้พูดด้วยช่วงเวลาห่าง 1-2 วินาที การวิจัยแสดงว่าเทคนิคนี้ปรับปรุงความแม่นยำในการออกเสียง ทำนองเสียง จังหวะ การเชื่อมเสียง การฟังเข้าใจ และความคล่องแคล่วในการพูดได้อย่างมีนัยสำคัญ