1 00:00:02,680 --> 00:00:06,640 Greetings and welcome to EHA Unplugged, the official podcast 2 00:00:06,640 --> 00:00:10,240 channel of the European Hematology Association, EHA. 3 00:00:10,640 --> 00:00:14,480 Hello, I am Isabella Livera, a medical writer for EHA. 4 00:00:15,480 --> 00:00:19,840 In this series, we are trying to explore the world of hematology 5 00:00:20,000 --> 00:00:22,960 through conversations with leading experts in the field. 6 00:00:24,240 --> 00:00:28,920 Today we are thrilled to have Professor Brian Huntley, Head of 7 00:00:28,920 --> 00:00:32,119 the Department of Hematology at the University of Cambridge. 8 00:00:33,360 --> 00:00:38,240 Professor Huntley is a renowned clinical research scientist and 9 00:00:38,240 --> 00:00:43,160 consultant in hematology at Addenbrooke's Hospital, and he's 10 00:00:43,160 --> 00:00:46,440 known for his groundbreaking work in leukemia stem cell 11 00:00:46,440 --> 00:00:49,200 biology. Thank you for being with us 12 00:00:49,200 --> 00:00:55,520 today. So to start off, we would like 13 00:00:55,520 --> 00:00:59,040 to learn where your journey started. 14 00:01:00,440 --> 00:01:04,000 What is your first memory of hematology? 15 00:01:05,120 --> 00:01:07,080 Thanks for inviting me. It's very nice to be here. 16 00:01:07,680 --> 00:01:10,960 My first memory of hematology was as an undergraduate. 17 00:01:11,200 --> 00:01:15,120 You learn all about body systems, and I think even at 18 00:01:15,120 --> 00:01:18,960 that time blood kind of fascinated me because of its 19 00:01:18,960 --> 00:01:22,040 accessibility. You can take a tissue sample 20 00:01:22,040 --> 00:01:26,240 from literally a blood test. Many of the sort of basic 21 00:01:26,240 --> 00:01:29,200 biochemical principles were worked out in blood and blood 22 00:01:29,200 --> 00:01:34,800 cells, and that kind of subliminally stayed with me and 23 00:01:36,400 --> 00:01:39,200 was one of the reasons that I wanted to take it up as a 24 00:01:39,200 --> 00:01:43,920 clinical specialty, this mix of science and clinical medicine. 25 00:01:44,400 --> 00:01:46,680 And then I think it was one of the things that directed me 26 00:01:46,680 --> 00:01:49,560 towards a sort of career in science. 27 00:01:50,840 --> 00:01:54,480 Because you are a trained medical doctor and then you have 28 00:01:54,680 --> 00:01:59,440 been doing research and translating that research always 29 00:01:59,440 --> 00:02:02,760 to clinics. Yeah, I mean, it's a sort of 30 00:02:02,760 --> 00:02:05,840 circular route. I, I, I wouldn't say that my 31 00:02:07,400 --> 00:02:10,800 trajectory and my path was, was a classical one because I didn't 32 00:02:10,800 --> 00:02:16,880 do much science until I, I had trained and, and specialized as 33 00:02:16,880 --> 00:02:19,160 a hematologist. And then I decided I wanted to 34 00:02:19,160 --> 00:02:25,280 try and do some medical science. So I did a PhD and then I've not 35 00:02:25,280 --> 00:02:29,040 really looked back, but it, it certainly was the, the 36 00:02:29,040 --> 00:02:32,560 application of science and the sort of basic mechanisms that 37 00:02:32,560 --> 00:02:36,080 were much better studied in blood disorders and in other 38 00:02:36,080 --> 00:02:39,680 disorders that made me decide to be a clinical hematologist. 39 00:02:40,120 --> 00:02:43,720 And then when I was studying for my postgraduate hematology 40 00:02:43,720 --> 00:02:46,920 exams, again, I wanted to explore the science more. 41 00:02:47,440 --> 00:02:52,080 So that's why I decided to step back from clinical medicine and 42 00:02:52,080 --> 00:02:57,440 to to pursue a PhD. And what led you to focus on 43 00:02:57,440 --> 00:03:00,960 leukemia and stem cell biology? Yeah. 44 00:03:00,960 --> 00:03:05,080 I mean, I think that as a practicing hematologist in the 45 00:03:05,080 --> 00:03:08,320 UK, your, your practice is dominated by malignant 46 00:03:08,320 --> 00:03:12,040 hematology. And to my mind, not only is it 47 00:03:12,040 --> 00:03:15,680 the most common problem, it's the most intractable problem. 48 00:03:15,680 --> 00:03:19,160 And it, and it continues. So this day, I mean, and I've 49 00:03:19,160 --> 00:03:24,160 been a researcher in hematology for 25 years and I'm embarrassed 50 00:03:24,160 --> 00:03:27,440 to say that we have improved the field, but we still have a great 51 00:03:27,440 --> 00:03:30,200 deal of work to do. And the things that you remember 52 00:03:30,200 --> 00:03:33,360 are probably more your failures rather than your successes. 53 00:03:34,560 --> 00:03:38,200 And I study predominantly acute myeloid leukemia, which is a 54 00:03:38,200 --> 00:03:42,320 very, very aggressive disease. And we still do very poorly in 55 00:03:42,320 --> 00:03:44,560 terms of the numbers of patients that we cure. 56 00:03:44,840 --> 00:03:49,720 However, we do cure a good number of of younger patients. 57 00:03:50,400 --> 00:03:55,080 And so it was interesting, it was difficult and we weren't 58 00:03:55,080 --> 00:03:57,720 really doing very well. So that was the reason for sort 59 00:03:57,720 --> 00:04:02,320 of gravitating towards leukemia biology rather than studying 60 00:04:02,720 --> 00:04:05,960 blood coagulation or or red blood cell disorders, which are 61 00:04:06,240 --> 00:04:10,360 equally interesting. But in my practice, we're just 62 00:04:10,360 --> 00:04:14,320 not as difficult problems and and I felt that that there was 63 00:04:14,320 --> 00:04:16,880 more needed to be done in those than in other areas. 64 00:04:21,200 --> 00:04:25,960 So your research has had several notable discoveries. 65 00:04:28,520 --> 00:04:32,160 One of the significance findings was that the demonstration that 66 00:04:32,160 --> 00:04:36,440 chronic and acute myeloid leukaemia may arise in separate 67 00:04:36,440 --> 00:04:42,760 stem cell progenitor cells. Why is this important? 68 00:04:43,680 --> 00:04:49,480 Well, I think it's, it's important to know how cancer 69 00:04:49,480 --> 00:04:53,280 changes the normal behaviour of a tissue system. 70 00:04:54,560 --> 00:04:58,080 And it's important to know where it comes from and how it 71 00:04:58,080 --> 00:05:00,240 develops. And, and with that knowledge, 72 00:05:00,240 --> 00:05:05,840 you can understand how you might be able to target it when it 73 00:05:06,360 --> 00:05:08,400 develops as a full blown disease. 74 00:05:08,480 --> 00:05:12,720 But also it, it, it provides the basis for working out how it 75 00:05:12,720 --> 00:05:15,440 develops. And there's this concept of 76 00:05:15,440 --> 00:05:18,480 earlier interception now where you can intervene earlier in 77 00:05:18,480 --> 00:05:21,480 processes. And if you know the, the cell 78 00:05:21,480 --> 00:05:26,240 that is giving rise to the, the problem and the cell that causes 79 00:05:26,360 --> 00:05:32,720 relapses of disease, then it's easier to try and target that 80 00:05:32,720 --> 00:05:36,520 that cell and to potentially eradicate the, the, the 81 00:05:36,520 --> 00:05:39,880 leukemia. So we need to sort of understand 82 00:05:40,400 --> 00:05:45,600 how the hierarchies of normal blood formation are aberrant 83 00:05:45,600 --> 00:05:51,200 within leukemias, and that helps us to think about how we might 84 00:05:51,200 --> 00:05:56,360 target leukemia stem cells for better eradication and what I 85 00:05:56,360 --> 00:05:59,400 was talking about, which is trying to improve cure rates. 86 00:06:02,520 --> 00:06:07,840 Another milestone in your career is that you describe what it's 87 00:06:07,840 --> 00:06:13,800 the essential role for BET transcription and regulators in 88 00:06:13,800 --> 00:06:20,440 AML RBT inhibitors, now a novel therapeutic approach, are they 89 00:06:20,440 --> 00:06:22,840 being used? So the BET proteins are, are 90 00:06:24,360 --> 00:06:27,560 transcriptional regulators and they're involved with various 91 00:06:27,560 --> 00:06:32,640 stages of transcription and they're cancer cells are 92 00:06:32,640 --> 00:06:36,000 addicted to them. So they are, they're, they're 93 00:06:36,000 --> 00:06:40,840 obvious targets like a lot of these transcriptionally active 94 00:06:40,840 --> 00:06:47,160 proteins, they are important for cancers. 95 00:06:47,600 --> 00:06:53,680 But over a long period of time and as single targets, the the 96 00:06:53,680 --> 00:06:58,640 inhibitors have been not particularly successful, but 97 00:06:58,640 --> 00:07:03,280 they're now moving into combination studies and my hope 98 00:07:03,280 --> 00:07:05,880 is that they will be much more successful there. 99 00:07:06,720 --> 00:07:13,400 You have also done work looking at the sale of origin of 100 00:07:13,400 --> 00:07:15,840 malignant lymphomas. What can you say about this? 101 00:07:16,600 --> 00:07:20,800 We performed a study to look at one of the mutations that is 102 00:07:20,800 --> 00:07:24,280 associated with a number of forms of lymphoma called Kreb 103 00:07:24,280 --> 00:07:27,040 BP. Like the BET proteins, it's 104 00:07:27,040 --> 00:07:32,400 again a transcriptional active protein and it has a number of 105 00:07:32,400 --> 00:07:38,520 functions. What we found was that if you 106 00:07:39,400 --> 00:07:43,560 lost the activity of this protein at different stages 107 00:07:43,560 --> 00:07:49,280 within B cell development, that it had different consequences. 108 00:07:49,280 --> 00:07:53,280 And we could show that malignant lymphoma was only developed when 109 00:07:53,280 --> 00:07:58,000 it was lost earlier in lymphoid development rather than within 110 00:07:58,240 --> 00:08:02,920 mature lymphoid cells. And I think this fits with some 111 00:08:02,920 --> 00:08:06,000 of the data from human studies where it's suggested to be a 112 00:08:06,000 --> 00:08:10,320 very early and possibly even an initiating event. 113 00:08:10,320 --> 00:08:14,800 And again, it suggests that we should perhaps be thinking about 114 00:08:14,800 --> 00:08:18,600 targeting these earlier events in these earlier cell 115 00:08:18,600 --> 00:08:21,800 compartments. And, and, and that's what we're 116 00:08:21,800 --> 00:08:24,880 studying further at the moment and we're looking into its 117 00:08:24,880 --> 00:08:30,240 effects to modulate metabolism. So now you're looking how to 118 00:08:32,520 --> 00:08:36,240 target earlier stages of differentiation. 119 00:08:38,600 --> 00:08:42,280 In which way study? So we we've been looking at 120 00:08:42,720 --> 00:08:46,000 studies to see how these diseases develop. 121 00:08:46,000 --> 00:08:51,360 We do a lot of studies which look at early mutations in 122 00:08:51,400 --> 00:08:57,480 leukaemias and lymphomas and how these diseases evolve and 123 00:08:57,960 --> 00:09:02,160 important processes have to occur to fully transform cells. 124 00:09:02,720 --> 00:09:05,520 And we've been doing a number of studies across a number of 125 00:09:05,520 --> 00:09:09,880 diseases which are trying to identify targets for therapeutic 126 00:09:09,880 --> 00:09:13,880 intervention and then possibly to think about ways that we 127 00:09:13,880 --> 00:09:16,080 might intervene as early as possible. 128 00:09:16,520 --> 00:09:21,160 If you look across the majority of cancers and the earlier that 129 00:09:21,160 --> 00:09:25,120 you initiate treatment, often the better are the consequences. 130 00:09:25,560 --> 00:09:29,480 And it's not a weird science to think that we might be able to 131 00:09:29,480 --> 00:09:34,240 significantly delay the progression of earlier diseases 132 00:09:34,240 --> 00:09:38,440 into more aggressive ones or possibly even think about 133 00:09:38,440 --> 00:09:41,920 prevention of some of these hematologic malignancies. 134 00:09:41,920 --> 00:09:46,520 And we're interested in that early biology and whether or not 135 00:09:46,520 --> 00:09:50,120 you can identify targets that you can think about intervening 136 00:09:50,120 --> 00:09:52,280 as soon as you know that there's there's an issue. 137 00:09:54,240 --> 00:09:57,560 So for the moment you're trying to understand what happens 138 00:09:57,600 --> 00:10:03,360 early, but there is not always then a drug or a treatment that 139 00:10:03,360 --> 00:10:06,040 will come out of it. You're very interested in the 140 00:10:07,360 --> 00:10:13,240 basic mechanism. The majority of the lab kind of 141 00:10:13,240 --> 00:10:17,320 focuses on the mechanisms of why these things happen, why these 142 00:10:17,320 --> 00:10:20,520 diseases develop, how they change through that evolutionary 143 00:10:20,520 --> 00:10:24,760 process. But the, the, the, the way that 144 00:10:24,760 --> 00:10:28,160 I have trained as a doctor first and a scientist second, I, I 145 00:10:28,160 --> 00:10:31,920 think you always have that line of sight to the clinic. 146 00:10:31,920 --> 00:10:35,160 You're always thinking about not just a mechanism, but a 147 00:10:35,160 --> 00:10:39,120 potential target. We almost always try to make 148 00:10:39,120 --> 00:10:43,680 comparisons between malignant tissues, whether those are 149 00:10:43,680 --> 00:10:48,160 myeloid cells or lymphoid cells, and their normal counterpart. 150 00:10:48,600 --> 00:10:51,640 You know, if we're looking at a leukemia stem cell, we're always 151 00:10:51,640 --> 00:10:54,320 trying to compare the differences with a normal stem 152 00:10:54,320 --> 00:10:58,120 cell and we're looking to, to find things that are specific to 153 00:10:58,120 --> 00:11:02,360 the disease because they're much likely to be better targets. 154 00:11:02,600 --> 00:11:06,320 You, you, you, you can't just target things that are required 155 00:11:06,320 --> 00:11:09,520 for normal stem cell function or you'll just disable blood 156 00:11:09,520 --> 00:11:11,840 formation completely. And that's not going to be any 157 00:11:11,840 --> 00:11:14,520 better than the current chemotherapies that we use. 158 00:11:15,680 --> 00:11:19,680 How does this research integrate with your clinical practice? 159 00:11:19,840 --> 00:11:22,080 Yeah, in two ways. So, So first of all, my, my 160 00:11:22,080 --> 00:11:25,880 clinical plaque practice is less than it used to be, given that 161 00:11:25,880 --> 00:11:28,800 I've got a lot of administrative duties nowadays as well. 162 00:11:29,640 --> 00:11:35,280 But it's always informed my clinical practice in terms of 163 00:11:35,280 --> 00:11:39,280 trying to think of better ways to treat people, more clever 164 00:11:39,280 --> 00:11:42,480 ways to treat people, thinking about better combinations for 165 00:11:42,480 --> 00:11:44,360 them. But I think it works in the 166 00:11:44,360 --> 00:11:49,200 opposite direction as well. And I come out of clinic 167 00:11:49,520 --> 00:11:52,680 sometimes quite frustrated because I can't do things for 168 00:11:52,680 --> 00:11:56,920 people. So it makes me committed and 169 00:11:57,120 --> 00:12:01,880 motivated to get back to the lab and to try and work a little bit 170 00:12:01,880 --> 00:12:04,280 harder. Or sometimes you identify a 171 00:12:04,280 --> 00:12:08,040 problem from a clinical encounter and you think that's 172 00:12:08,040 --> 00:12:10,800 very interesting. I wonder how that works. 173 00:12:10,800 --> 00:12:14,240 And that might give you a research idea for, for a next 174 00:12:14,240 --> 00:12:17,960 project or it will inform the way that you deal with a current 175 00:12:17,960 --> 00:12:21,280 project. So I I like the the way that 176 00:12:21,280 --> 00:12:25,320 they work together, but it does make your life quite busy. 177 00:12:26,480 --> 00:12:32,040 Do you have any specific example of something that you discovered 178 00:12:32,040 --> 00:12:36,760 in a pension that you wanted to understand and took back to the 179 00:12:36,760 --> 00:12:39,240 lab? But there's lots of things. 180 00:12:39,240 --> 00:12:43,600 I mean, the, the most obvious one would be our group are 181 00:12:43,600 --> 00:12:47,760 becoming very interested in the development of resistance to to 182 00:12:48,440 --> 00:12:51,640 therapies, particularly newer targeted therapies. 183 00:12:52,800 --> 00:12:58,560 And that's always really bugged me about why these patients 184 00:12:58,560 --> 00:13:03,680 develop resistance because often with leukemias, it's patients 185 00:13:03,680 --> 00:13:05,440 don't die from the primary disease. 186 00:13:05,440 --> 00:13:08,720 They die because the disease comes back and it comes back and 187 00:13:08,720 --> 00:13:12,400 it's more resistant. So I think that has informed a 188 00:13:12,400 --> 00:13:16,000 whole, you know, perhaps 1/3 of my lab work on resistance to 189 00:13:16,040 --> 00:13:19,400 therapeutics and and that has come from the frustration of 190 00:13:19,400 --> 00:13:22,200 seeing patients relapse continuously. 191 00:13:26,120 --> 00:13:28,640 So you're a member of the European Hematology Association, 192 00:13:28,640 --> 00:13:32,080 EHA, and you are a very active member. 193 00:13:32,080 --> 00:13:37,440 You're in the executive board. How has EHA influenced your 194 00:13:37,440 --> 00:13:40,360 career? I think in in quite a number of 195 00:13:40,360 --> 00:13:44,800 ways, the first international conference I ever went to was 196 00:13:44,800 --> 00:13:51,520 EHA in Barcelona in the last, the last Millennium. 197 00:13:51,760 --> 00:13:56,440 The first conference that I actually gave an oral 198 00:13:56,440 --> 00:14:05,200 presentation was EHA and during my PhD, and I was very lucky 199 00:14:05,200 --> 00:14:09,840 when I came back from the, my postdoc in the States that EHA 200 00:14:09,840 --> 00:14:12,320 gave me some money at a time when I was setting up my own 201 00:14:12,320 --> 00:14:15,440 group. And that was hugely appreciated. 202 00:14:15,840 --> 00:14:18,480 All of the other people that gave me money had, you know, I 203 00:14:18,480 --> 00:14:22,240 had to follow a very rigorous, you can spend on this, you can 204 00:14:22,240 --> 00:14:25,040 spend on that. EHA gave me the money and said, 205 00:14:25,040 --> 00:14:27,760 you know, you do what you you think is best to further your 206 00:14:27,760 --> 00:14:30,920 career. So that was both appreciated and 207 00:14:30,920 --> 00:14:33,480 the freedom to do what I wanted with it, which which was 208 00:14:33,480 --> 00:14:37,280 something a little bit more risky and that perhaps the 209 00:14:37,280 --> 00:14:40,520 funding agencies in the UK wouldn't have allowed me to do. 210 00:14:41,160 --> 00:14:45,600 So I sort of decided that I would, you know, try and pay Jay 211 00:14:45,600 --> 00:14:48,880 back. I've sat in a lots of committees 212 00:14:48,880 --> 00:14:53,720 and and, and various organizing committees for some of the 213 00:14:53,720 --> 00:14:57,480 scientific meetings. But but it's it's great fun as 214 00:14:57,480 --> 00:15:01,000 well. So I'm you you give, but you get 215 00:15:01,000 --> 00:15:02,360 back. And I think it's a very 216 00:15:02,360 --> 00:15:05,640 worthwhile organization or, you know, I probably wouldn't be 217 00:15:05,640 --> 00:15:09,160 doing half the things that I do, but yeah. 218 00:15:09,160 --> 00:15:11,720 So I I've kind of grown up with the HA. 219 00:15:11,800 --> 00:15:17,960 I've been a member for yeah, more than 25 years it. 220 00:15:18,520 --> 00:15:23,600 Has really been there for you during your whole career? 221 00:15:23,840 --> 00:15:28,840 It has help you grow also being eha by the connections or. 222 00:15:28,960 --> 00:15:33,880 I think it has, and it's given me a great kind of venue through 223 00:15:33,880 --> 00:15:37,400 the Congress to present my science. 224 00:15:37,680 --> 00:15:40,200 I've been lucky enough to give lots of presentations, so it's 225 00:15:40,200 --> 00:15:43,520 helped my career. It's very sociable. 226 00:15:43,600 --> 00:15:46,920 I mean, it's, it's always nice going to a nice European city in 227 00:15:46,920 --> 00:15:48,880 the summer, meeting up with your friends. 228 00:15:49,480 --> 00:15:51,920 Latterly, when I've been more heavily involved in the 229 00:15:51,920 --> 00:15:55,440 organization, it's given me a lot of pride to, you know, to 230 00:15:55,440 --> 00:16:00,560 have organised things. So yeah, it's been, yeah, very 231 00:16:00,880 --> 00:16:07,800 enjoyable, but also rewarding. So you have so many different 232 00:16:07,800 --> 00:16:12,440 activities because as a you are a clinician, although now a 233 00:16:12,440 --> 00:16:15,720 little bit less, but during your life you have been very involved 234 00:16:15,720 --> 00:16:21,600 with patients, also in research, I imagine in education and also 235 00:16:21,640 --> 00:16:24,480 in all these societies, specifically EHA. 236 00:16:24,880 --> 00:16:27,920 Which one of these activities do you enjoy the most? 237 00:16:28,720 --> 00:16:32,800 And the science, definitely the science. 238 00:16:34,040 --> 00:16:37,560 I like the variety. And you know, I get asked this 239 00:16:37,560 --> 00:16:41,000 quite a lot by younger clinician scientists because it's quite 240 00:16:41,000 --> 00:16:44,920 difficult to try and balance all of these variable parts of your 241 00:16:44,920 --> 00:16:48,640 career. But I think it's it's good as 242 00:16:48,640 --> 00:16:53,600 well because you don't get the chance to become stale and 243 00:16:53,600 --> 00:16:55,520 you're moving from one thing to another. 244 00:16:56,520 --> 00:17:02,840 And particularly with medicine and with science, they work on 245 00:17:02,840 --> 00:17:07,280 completely different timescales. So in medicine you can see a 246 00:17:07,280 --> 00:17:09,920 patient in clinic, see a patient on the ward, you can immediately 247 00:17:09,920 --> 00:17:13,040 help them and, and you know, you get a lot of satisfaction for 248 00:17:13,040 --> 00:17:16,599 that. In science project projects can 249 00:17:16,599 --> 00:17:19,200 take years, literally years to read out. 250 00:17:19,720 --> 00:17:22,680 With both of them. There are peaks and troughs, but 251 00:17:22,680 --> 00:17:24,319 they work on different time scales. 252 00:17:24,319 --> 00:17:29,440 And I think they, they, they dovetail quite nicely and they 253 00:17:29,440 --> 00:17:33,040 feed off each other. I do a lot of administration as 254 00:17:33,040 --> 00:17:36,680 well. And that can again be quite 255 00:17:36,680 --> 00:17:39,600 harrowing. But again, it can give you 256 00:17:39,600 --> 00:17:41,560 pleasure. And I always say that it's very 257 00:17:41,560 --> 00:17:47,080 seldom that I'm having a bad day in the clinic, in the admin and 258 00:17:47,080 --> 00:17:49,720 with the science, at least one of them is giving you some 259 00:17:49,720 --> 00:17:51,880 pleasure. I can certainly work a lot 260 00:17:51,880 --> 00:17:56,840 harder if I'm doing one thing, then another thing, then another 261 00:17:56,840 --> 00:18:00,640 thing back to the first one. If I was doing the same thing 262 00:18:00,640 --> 00:18:04,880 for 10 hours a day, then I think I'd find it both boring and 263 00:18:04,880 --> 00:18:07,240 tiring. But if, if you have variety, 264 00:18:07,720 --> 00:18:12,200 then I think it's it's interesting and it, it allows 265 00:18:12,200 --> 00:18:17,120 you to, to sort of do a lot. So you enjoy very much changing 266 00:18:17,160 --> 00:18:19,800 and the. Variety of not all the time, but 267 00:18:19,800 --> 00:18:24,240 yeah, in, in general, you're not having a bad time with with 268 00:18:24,240 --> 00:18:25,960 everything. There's always something that 269 00:18:25,960 --> 00:18:28,800 you can get satisfaction from and something that you can feel 270 00:18:28,800 --> 00:18:34,040 that you've done a good job on. So looking back at all this 271 00:18:34,040 --> 00:18:41,880 work, what would you recommend to a young medical doctor that 272 00:18:41,880 --> 00:18:46,840 is choosing their path now? I think you've got to do things 273 00:18:46,840 --> 00:18:49,960 that that you're passionate about. 274 00:18:50,200 --> 00:18:55,040 It's not easy and not suggesting it is easy to you, you really 275 00:18:55,040 --> 00:18:58,080 have got to want to do it because it will be difficult at 276 00:18:58,080 --> 00:19:01,200 times and you'll need to fall back on something that really 277 00:19:02,160 --> 00:19:04,320 excites you or drives you and motivates you. 278 00:19:04,320 --> 00:19:07,280 So I would always say sort of follow your passions. 279 00:19:08,800 --> 00:19:12,000 You've got to be quite disciplined with your time. 280 00:19:12,000 --> 00:19:14,040 Well, I do, I do far too many things. 281 00:19:14,040 --> 00:19:17,240 And most people, they do research on one thing and they 282 00:19:17,240 --> 00:19:19,800 do more and more. I do biz that and that and that. 283 00:19:20,480 --> 00:19:23,720 But it's, you know, it's what what interests me. 284 00:19:23,720 --> 00:19:26,560 So I always I've always done what I've found interesting. 285 00:19:26,720 --> 00:19:28,360 So I. Think what you do is closer to 286 00:19:28,360 --> 00:19:32,080 what I used to do because I was working reading stem cells and 287 00:19:32,600 --> 00:19:34,680 for me it was how does this work? 288 00:19:34,840 --> 00:19:39,360 Those basic questions of what is the sale of origin? 289 00:19:39,360 --> 00:19:42,920 For me, it's always what I'm thinking of when I see all 290 00:19:42,920 --> 00:19:46,000 these, you know, the new treatments or everything. 291 00:19:46,160 --> 00:19:48,280 Where where does this? Come from, you know, the fact 292 00:19:48,280 --> 00:19:51,600 that these things keep on coming back, you know, we're either not 293 00:19:51,600 --> 00:19:55,360 getting to the root or they're just developing ways around it. 294 00:19:55,360 --> 00:20:01,760 So yeah, it it it it both interests and annoys me in equal 295 00:20:01,760 --> 00:20:05,760 measure. And now with all the tools to, 296 00:20:05,760 --> 00:20:10,560 you know, sequence everything at the same time, and with AI to 297 00:20:10,560 --> 00:20:15,320 compare this in a much more efficient way, are you advancing 298 00:20:15,320 --> 00:20:16,920 quicker? I think we're advancing 299 00:20:16,920 --> 00:20:21,240 knowledge quicker than therapy. And unfortunately the, the, the 300 00:20:21,240 --> 00:20:26,840 advances in knowledge let us know how oversimplified we've 301 00:20:26,840 --> 00:20:32,360 thought about the problems. 10 or 15 years ago, we thought of 302 00:20:32,560 --> 00:20:35,240 tumors as much more sort of homogeneous entities. 303 00:20:35,240 --> 00:20:39,360 Now we've got sort of cell biological hierarchies. 304 00:20:39,720 --> 00:20:42,480 And even if you look at things that that are supposedly the 305 00:20:42,480 --> 00:20:45,560 same type of cell, you look at the genetics in them, they're 306 00:20:45,560 --> 00:20:48,200 slightly different. You look at the transcription 307 00:20:48,200 --> 00:20:49,760 within them, they're definitely different. 308 00:20:49,760 --> 00:20:51,760 You look at the proteins, they're even more different. 309 00:20:51,760 --> 00:20:56,720 So we're sort of dealing with a much more complicated problem 310 00:20:56,720 --> 00:21:03,200 than we had imagined. But you know, those advances 311 00:21:03,200 --> 00:21:06,240 that we've made in terms of knowledge are really translating 312 00:21:06,240 --> 00:21:10,960 greatly into new drugs. There's not that many of them 313 00:21:10,960 --> 00:21:16,240 that are complete step changes. I I would say that things like 314 00:21:16,240 --> 00:21:20,000 CAR T cells and immunotherapy, they, they really are a whole 315 00:21:20,000 --> 00:21:25,480 new sort of modality and, and they are significantly changing 316 00:21:25,480 --> 00:21:28,840 things, but they again are not curing everybody. 317 00:21:28,840 --> 00:21:31,920 We're catching up, but the problem's becoming more 318 00:21:31,920 --> 00:21:35,520 difficult as well because our knowledge is improving. 319 00:21:35,600 --> 00:21:40,320 I'm very confident that we can significantly improve on how 320 00:21:40,320 --> 00:21:43,440 well we're doing. And you know, what I was trying 321 00:21:43,440 --> 00:21:51,040 to get through was that we now know about how long period these 322 00:21:51,600 --> 00:21:56,760 diseases develop over and we we thought they kind of happened. 323 00:21:56,760 --> 00:21:59,280 It was all kind of perfect storm, everything come together 324 00:21:59,280 --> 00:22:01,600 and and all of a sudden, bingo, you've got cancer. 325 00:22:01,600 --> 00:22:04,560 It's not like that at all. You know, with blood cancers, 326 00:22:04,560 --> 00:22:08,960 some of these complicated ones can take 20, thirty, 40-50 years 327 00:22:10,360 --> 00:22:16,720 and we can detect some of these pre malignant mutations at 328 00:22:17,520 --> 00:22:21,640 earlier stages. And that gives us, I think and 329 00:22:21,640 --> 00:22:24,520 the opportunity to think about intervening earlier. 330 00:22:24,680 --> 00:22:30,960 Now the difficulty is that patients will go 25 of those 30 331 00:22:30,960 --> 00:22:34,120 years without a diagnosis. They're not patients. 332 00:22:34,120 --> 00:22:40,160 We don't really have a reason to look for these disorders, and 333 00:22:40,160 --> 00:22:43,760 they're not common enough for us to be able to justify whole 334 00:22:43,920 --> 00:22:47,480 scale screening projects for them. 335 00:22:47,760 --> 00:22:50,520 So we're getting a better idea of the sort of Natural History 336 00:22:50,520 --> 00:22:57,920 of these disorders, and we're also trying to work out how 337 00:22:57,920 --> 00:23:02,600 related they are because you can have different mutations which 338 00:23:02,600 --> 00:23:08,680 probably do different things to the same cell and from each 339 00:23:08,680 --> 00:23:11,120 other. We don't know whether or not the 340 00:23:12,520 --> 00:23:17,000 generate vulnerabilities within the cell and and then the aim 341 00:23:17,000 --> 00:23:19,760 would be to try and work out what those vulnerabilities are 342 00:23:19,880 --> 00:23:25,280 and can we come up with therapies that are safe enough 343 00:23:25,280 --> 00:23:29,200 and non-toxic enough to think about giving them to people who 344 00:23:29,200 --> 00:23:33,000 are not yet patients. And there are there are 345 00:23:33,000 --> 00:23:36,600 significant ethical questions. There's questions about whether 346 00:23:36,600 --> 00:23:42,680 they should know because we cannot tell them confidently 347 00:23:42,840 --> 00:23:45,720 what will happen. We can tell them what might 348 00:23:45,720 --> 00:23:49,360 happen. So we're at that stage where we 349 00:23:49,360 --> 00:23:53,280 know a lot, but we're just trying to learn a little bit 350 00:23:53,280 --> 00:23:57,160 more about how to predict what would happen, because not all of 351 00:23:57,160 --> 00:24:01,320 these patients with one mutation will go on to develop a 352 00:24:01,320 --> 00:24:04,040 significant disease. Knowledge is great, but it 353 00:24:04,040 --> 00:24:07,760 brings responsibility with it. It's easy to describe things, 354 00:24:07,760 --> 00:24:10,080 but it's difficult to tell what's going to happen 355 00:24:10,080 --> 00:24:13,920 thereafter. So we're at a great stage, but 356 00:24:13,920 --> 00:24:17,240 we need to know a lot more. We need to predict a lot better, 357 00:24:17,280 --> 00:24:20,040 identify the patients that are really going to do badly. 358 00:24:20,400 --> 00:24:24,920 So is it? Each patient will have a very a 359 00:24:25,000 --> 00:24:26,760 unique cancer at the end of the day. 360 00:24:27,200 --> 00:24:30,760 Even in relatively simple cancers like acute leukemias, 361 00:24:30,760 --> 00:24:36,120 which have between 3:00 and 5:00 mutations, if you catalogue all 362 00:24:36,120 --> 00:24:40,920 of the mutations within those patients and all of the other 363 00:24:41,720 --> 00:24:47,760 abnormalities that are non genetic, it's it's not crazy to 364 00:24:47,760 --> 00:24:51,320 say that almost every cancer is slightly different. 365 00:24:51,960 --> 00:24:55,240 But we do know that some of them are very similar. 366 00:24:55,760 --> 00:24:58,840 And we take advantage of that through personalized medicine 367 00:24:58,840 --> 00:25:03,640 to, to, to treat the common single mutations, the common Co 368 00:25:03,640 --> 00:25:06,680 occurring mutations. If you really look hard with the 369 00:25:06,680 --> 00:25:09,960 magnifying glass, they, they will all be slightly different 370 00:25:10,600 --> 00:25:14,360 and the genetic makeup of every patient will be different and 371 00:25:14,360 --> 00:25:18,680 the genetic, their background genetic makeup will dictate how 372 00:25:18,760 --> 00:25:23,880 they respond to therapies and, and their lifestyles will depend 373 00:25:23,880 --> 00:25:26,680 on that and their premorbid condition will depend on that. 374 00:25:26,680 --> 00:25:29,920 So there, there's a lot of heterogeneity that we need to 375 00:25:29,920 --> 00:25:32,880 factor in, but this sort of takes us into the, the, the, 376 00:25:33,000 --> 00:25:37,800 the, the area of personalized medicine because it's not just 377 00:25:38,000 --> 00:25:41,080 personalized for the tumor, it's personalized for the way that 378 00:25:41,080 --> 00:25:44,760 the patient will respond, what other medical conditions that 379 00:25:44,760 --> 00:25:51,320 the patient might have. So there are tumour specific and 380 00:25:51,360 --> 00:25:54,440 tumour nonspecific areas to personalized medicine. 381 00:25:55,640 --> 00:26:00,440 I'm thinking about AI because there's a lot of talk about 382 00:26:00,440 --> 00:26:02,080 synthetic patients. Yep. 383 00:26:03,640 --> 00:26:09,600 So with AI to create patients based on what a typical patient 384 00:26:09,800 --> 00:26:12,480 will be like with what we already know. 385 00:26:13,120 --> 00:26:16,880 Yeah. But at the end of the day, the 386 00:26:16,880 --> 00:26:23,480 point of a clinical trial is to see also the things that we 387 00:26:23,480 --> 00:26:26,000 don't know. If we're going to be basing our 388 00:26:26,000 --> 00:26:29,680 knowledge on something synthetic, we're taking out a 389 00:26:29,680 --> 00:26:33,120 lot of complexity that we do not master. 390 00:26:33,280 --> 00:26:38,800 I think that that AI can be applied to any number of 391 00:26:39,600 --> 00:26:43,040 projects to improve our understanding and hematology 392 00:26:43,040 --> 00:26:45,520 that we can discuss. But in terms of synthetic 393 00:26:45,880 --> 00:26:50,000 patients, the, the, the area that they're most being 394 00:26:50,240 --> 00:26:57,720 discussed is to form the control group because in standards, 395 00:26:57,760 --> 00:27:03,280 randomised clinical trials, even if you have more patients that 396 00:27:03,280 --> 00:27:07,680 go into the treatment arm, you always have standard of care or 397 00:27:07,760 --> 00:27:10,960 a placebo. Now that means that, you know, 398 00:27:10,960 --> 00:27:14,760 half of your patients or a third of your patients are actually 399 00:27:14,760 --> 00:27:18,000 not getting anything that might improve them above what they, 400 00:27:18,000 --> 00:27:20,960 they could get outside of the clinical trial. 401 00:27:21,560 --> 00:27:27,200 And so the idea of synthetic patients is to really have a 402 00:27:27,200 --> 00:27:32,360 standard to compare. So if you can generate that data 403 00:27:32,360 --> 00:27:35,000 synthetically, then that means that more patients can be 404 00:27:35,000 --> 00:27:38,200 treated. So I think that that is a a 405 00:27:38,200 --> 00:27:41,840 possible area that that we can improve trial design. 406 00:27:42,360 --> 00:27:46,760 But and there are not really any standards at the moment for what 407 00:27:46,760 --> 00:27:50,800 constitutes a good synthetic and set of patients. 408 00:27:51,960 --> 00:27:56,840 And if you get your control arm wrong, then you can't see 409 00:27:56,840 --> 00:27:58,800 anything about the patients that are treated. 410 00:27:59,120 --> 00:28:02,600 So, you know, you don't want to run a clinical trial that can 411 00:28:02,600 --> 00:28:06,560 say nothing just because your control arm is very poor. 412 00:28:07,040 --> 00:28:11,120 So I think it's an area of very active discussion and debate. 413 00:28:12,360 --> 00:28:14,800 The other people that we need to bring into that conversation 414 00:28:14,800 --> 00:28:18,080 very much of the regulators because clinical trials are 415 00:28:19,040 --> 00:28:23,720 generally done to improve clinical practice, but they are 416 00:28:23,720 --> 00:28:27,680 often done with new agents to get them regulatory potential to 417 00:28:27,680 --> 00:28:32,640 be given as standard of care. And I think that again, it's 418 00:28:32,640 --> 00:28:36,760 important that these trials which cost a lot of money and in 419 00:28:36,880 --> 00:28:39,240 my opinion are always done too slow. 420 00:28:39,360 --> 00:28:44,440 We've got to do them properly because and there are not enough 421 00:28:44,440 --> 00:28:47,440 new medications coming in. So you think, yeah, the 422 00:28:47,440 --> 00:28:50,040 synthetic patients will have a place in this control? 423 00:28:50,120 --> 00:28:52,640 Area I think that they will do could be that there are some 424 00:28:52,640 --> 00:28:57,360 controls, but they are in some way synthetically increased in 425 00:28:57,360 --> 00:29:01,160 number to allow the statistical comparisons that are required. 426 00:29:01,600 --> 00:29:04,800 But I think it needs to be done through a lot of discussion. 427 00:29:04,800 --> 00:29:08,000 And I know that EHA is involved significantly in these 428 00:29:08,000 --> 00:29:12,400 conversations with European Affairs and the, the, the health 429 00:29:12,400 --> 00:29:15,440 data steering group. And you know, these are 430 00:29:15,440 --> 00:29:18,800 discussions that are occurring with EMA, so the the the 431 00:29:18,800 --> 00:29:22,560 regulators at the highest level. Thank you very much, Professor 432 00:29:22,560 --> 00:29:25,560 Huntley, for being with us today, for sharing your 433 00:29:25,560 --> 00:29:29,200 expertise with us, and thank you to all of you for listening. 434 00:29:29,240 --> 00:29:31,640 And please tune in for our next chapters. 435 00:29:32,240 --> 00:29:33,320 It's a pleasure. Thank you.