WEBVTT 1 00:00:00.720 --> 00:00:06.980 This session of the 2013 Adelaide Festival of Ideas was recorded by Radio Adelaide, 2 00:00:07.020 --> 00:00:10.500 through the support of the Bar Smith Library, University of Adelaide, 3 00:00:10.620 --> 00:00:14.480 the University of South Australia Library and Flinders University Library. 4 00:00:15.460 --> 00:00:18.420 I'm Chris Burrell from the University of Adelaide, 5 00:00:18.540 --> 00:00:21.640 and I'm looking after the session this afternoon as your MC. 6 00:00:23.300 --> 00:00:28.400 The session is entitled, So We Cracked the Human Genome, Now What? 7 00:00:28.400 --> 00:00:33.620 And the session is presented in association with Cosmos Media. 8 00:00:34.660 --> 00:00:39.700 Now, we'd like to acknowledge that today we are gathered in the country of the Kaurna people, 9 00:00:39.860 --> 00:00:43.860 of the Adelaide Plains, and we recognise their cultural heritage, 10 00:00:44.160 --> 00:00:46.800 their beliefs and their relationships with the land, 11 00:00:46.980 --> 00:00:53.340 and we acknowledge they are of continuing importance to the Kaurna people who live now, 12 00:00:54.040 --> 00:00:55.280 and we respect their elders. 13 00:00:56.520 --> 00:00:57.580 A few... 14 00:00:58.400 --> 00:00:59.660 A few practical notes. 15 00:01:00.520 --> 00:01:05.560 Please, if there's anyone with a mobile phone that you don't wish to share with your neighbours, 16 00:01:05.680 --> 00:01:07.320 could you please remember to turn it off? 17 00:01:08.580 --> 00:01:11.560 You can connect with the festival. 18 00:01:11.660 --> 00:01:16.260 The tweet handle is at ADLFOI. 19 00:01:18.160 --> 00:01:21.740 The hashtag is hash ADLFOI. 20 00:01:21.840 --> 00:01:27.780 The Instagram is at ADLFOI or hash ADLFOI. 21 00:01:28.400 --> 00:01:31.240 So you can see there's a system behind it all. 22 00:01:33.040 --> 00:01:36.900 We're not allowed for people to take any recordings of the session, 23 00:01:37.580 --> 00:01:42.880 but the session is being recorded by Radio Adelaide for broadcast and for podcasts. 24 00:01:44.260 --> 00:01:47.420 Our speaker, as you know, Elizabeth Finkel, 25 00:01:48.720 --> 00:01:56.380 had a 10-year career in scientific research as a biochemist in California. 26 00:01:57.080 --> 00:01:58.380 Since then, she's... 27 00:01:58.400 --> 00:02:01.640 worked mainly as a science journalist. 28 00:02:03.020 --> 00:02:07.040 She's the co-founder of Cosmos, the science magazine, 29 00:02:07.400 --> 00:02:09.380 which I'm sure is known to many of you. 30 00:02:09.840 --> 00:02:11.640 She's written two books, 31 00:02:12.740 --> 00:02:16.160 Stem Cells, Controversy at the Frontiers of Science, 32 00:02:16.920 --> 00:02:19.700 and The Genome Generations, 33 00:02:20.440 --> 00:02:25.340 and these books will be on display in the foyer after the talk, 34 00:02:25.420 --> 00:02:27.920 and Elizabeth's agreed to sign these books. 35 00:02:27.920 --> 00:02:28.900 If anyone would like that. 36 00:02:30.420 --> 00:02:32.360 She broadcasts regularly on Radio National, 37 00:02:33.380 --> 00:02:34.720 programs like Occam's Razor, 38 00:02:34.780 --> 00:02:39.500 and she's won a large number of awards as Journalist of the Year 39 00:02:39.500 --> 00:02:43.560 for medical journalism and for radio broadcasting. 40 00:02:45.940 --> 00:02:50.500 Now she's having another career change to become the editor of Cosmos magazine. 41 00:02:51.660 --> 00:02:54.080 She's thoughtful about science, 42 00:02:54.280 --> 00:02:57.900 and she has a gift for explaining biological science. 43 00:02:59.500 --> 00:03:04.280 Now I guess we all know something about Watson and Crick and the double helix, 44 00:03:04.320 --> 00:03:08.580 and we all vaguely know that a human genome has been sequenced. 45 00:03:08.840 --> 00:03:11.880 But in the last three to six years, 46 00:03:11.960 --> 00:03:15.140 the pace of all of this is absolutely extraordinary. 47 00:03:15.540 --> 00:03:18.300 The speeded up technology in sequencing, 48 00:03:18.500 --> 00:03:20.580 computer analysis of it all. 49 00:03:20.920 --> 00:03:24.320 But for what point? Where's it all going? 50 00:03:24.960 --> 00:03:26.340 And this is... 51 00:03:26.340 --> 00:03:27.900 the subject of... 52 00:03:27.900 --> 00:03:29.480 Elizabeth's talk this afternoon, 53 00:03:29.680 --> 00:03:31.380 and I very much look forward to it. 54 00:03:32.400 --> 00:03:32.820 Thank you, Elizabeth. 55 00:03:34.600 --> 00:03:36.160 Thanks very much, Chris. 56 00:03:38.400 --> 00:03:40.880 Well, thank you very much for coming, 57 00:03:41.900 --> 00:03:42.880 and for being interested. 58 00:03:43.900 --> 00:03:46.760 And I'll do my best to demystify 59 00:03:46.760 --> 00:03:51.560 those issues that Chris alluded to about the human genome. 60 00:03:53.300 --> 00:03:53.960 So... 61 00:03:57.900 --> 00:03:59.560 the human genome project. 62 00:04:00.620 --> 00:04:07.680 So I put it to you that not since Eve took her bite from the apple 63 00:04:08.400 --> 00:04:11.480 have we ever been taking such a... 64 00:04:11.480 --> 00:04:14.600 have we ever taken such a huge bite from the tree of knowledge. 65 00:04:15.080 --> 00:04:18.340 So with the human genome project, 66 00:04:18.460 --> 00:04:22.660 we've glimpsed into the code of a human being. 67 00:04:23.200 --> 00:04:24.680 And this is what... 68 00:04:24.680 --> 00:04:26.120 this code 69 00:04:26.120 --> 00:04:27.880 is written in language. 70 00:04:27.900 --> 00:04:28.900 It's letters of DNA, 71 00:04:29.900 --> 00:04:34.000 which is what is illustrated in this slide. 72 00:04:34.960 --> 00:04:37.300 The iconic double helix. 73 00:04:37.620 --> 00:04:42.360 Along its length, this linear code of three billion letters. 74 00:04:43.220 --> 00:04:46.780 Only four different types, A, G, C and T. 75 00:04:47.700 --> 00:04:50.060 And those three billion... 76 00:04:50.060 --> 00:04:53.920 a set of three billion that you got from each of your parents, 77 00:04:54.020 --> 00:04:55.900 so altogether you have six billion, 78 00:04:55.900 --> 00:04:57.820 are what makes you, you. 79 00:04:58.540 --> 00:04:59.200 These... 80 00:04:59.900 --> 00:05:03.060 the string of code, the helix, 81 00:05:03.860 --> 00:05:05.180 is wound... 82 00:05:05.180 --> 00:05:07.920 it's like a gossamer-thin thread, 83 00:05:08.140 --> 00:05:09.780 and the only way to manage it 84 00:05:09.780 --> 00:05:11.920 is to spool it into 85 00:05:11.920 --> 00:05:16.480 little proteins into the shape of a chromosome, 86 00:05:16.700 --> 00:05:19.560 and then package it up for safekeeping 87 00:05:19.560 --> 00:05:21.780 into the nucleus of the cell. 88 00:05:23.420 --> 00:05:25.780 So why do I have a Mona Lisa here? 89 00:05:25.900 --> 00:05:30.500 Because that code of four different units 90 00:05:31.980 --> 00:05:34.380 reads out to make a human being. 91 00:05:34.680 --> 00:05:37.640 And it's sort of a hard concept, 92 00:05:37.700 --> 00:05:40.780 but it helps me to think that this image of Mona Lisa 93 00:05:40.780 --> 00:05:42.500 has been generated by a computer 94 00:05:42.500 --> 00:05:46.400 just from two units of information, ones and zeros. 95 00:05:48.260 --> 00:05:48.900 So... 96 00:05:52.900 --> 00:05:54.240 the human genome... 97 00:05:54.240 --> 00:05:54.960 it... 98 00:05:54.960 --> 00:05:58.300 embedded in that code of three billion letters, 99 00:05:58.340 --> 00:05:59.340 two sets of it, 100 00:06:00.460 --> 00:06:03.800 is the information for making a human being. 101 00:06:04.080 --> 00:06:07.000 We're all 99.5% similar, 102 00:06:07.080 --> 00:06:09.040 but that 0.5% difference 103 00:06:09.040 --> 00:06:11.040 is the difference between making 104 00:06:11.960 --> 00:06:14.600 an Einstein or an Usain Bolt, 105 00:06:14.740 --> 00:06:18.640 the world sprint record holder. 106 00:06:19.960 --> 00:06:20.920 And so... 107 00:06:21.460 --> 00:06:24.000 for a very long time, all we could do 108 00:06:24.000 --> 00:06:28.620 was to read maybe a few thousand letters of that code at a time, 109 00:06:28.700 --> 00:06:30.340 just one gene at a time. 110 00:06:30.540 --> 00:06:32.360 But around about 1989, 111 00:06:33.480 --> 00:06:37.080 the techniques for reading DNA were getting better and better, 112 00:06:37.200 --> 00:06:39.660 and a bold idea hatched itself. 113 00:06:39.860 --> 00:06:42.340 Why not just read the whole damn thing? 114 00:06:43.320 --> 00:06:47.200 And it was a big project for biology. 115 00:06:47.320 --> 00:06:50.120 Biology had never attempted anything so big before. 116 00:06:50.160 --> 00:06:52.800 By and large, biologists were individuals 117 00:06:52.800 --> 00:06:55.340 tucked away in their laboratories doing, 118 00:06:55.520 --> 00:06:56.800 you know, if they were lucky, 119 00:06:56.880 --> 00:06:59.800 studying a whole gene for their whole lifetime. 120 00:07:00.220 --> 00:07:03.600 So now we had scientists all over the world 121 00:07:03.600 --> 00:07:06.100 coming together in the same way that they came together 122 00:07:06.100 --> 00:07:07.280 to put a man on the moon 123 00:07:07.800 --> 00:07:09.860 to try and read the whole human genome. 124 00:07:10.320 --> 00:07:12.360 And they achieved it, 125 00:07:12.380 --> 00:07:13.520 ahead of time, 126 00:07:14.580 --> 00:07:16.000 in 11 years, 127 00:07:16.300 --> 00:07:18.560 at a cost of three billion dollars. 128 00:07:18.900 --> 00:07:20.100 And here we see 129 00:07:21.000 --> 00:07:22.660 Bill Clinton in 2000, 130 00:07:24.300 --> 00:07:25.940 celebrating that achievement, 131 00:07:26.700 --> 00:07:28.060 decoding the Book of Life, 132 00:07:28.180 --> 00:07:29.500 a milestone for humanity. 133 00:07:30.180 --> 00:07:32.880 And he predicted it would lead to new ways 134 00:07:32.880 --> 00:07:35.900 to prevent, diagnose, treat, and cure disease. 135 00:07:36.960 --> 00:07:38.640 Well, was he right? 136 00:07:39.040 --> 00:07:39.980 I think so. 137 00:07:41.880 --> 00:07:44.520 One of the most extraordinary things that's happened 138 00:07:44.520 --> 00:07:47.320 is that while it took three billion dollars 139 00:07:47.320 --> 00:07:49.040 to read the first human genome 140 00:07:49.040 --> 00:07:51.180 and a small army of scientists 141 00:07:51.180 --> 00:07:52.780 in the UK and America, 142 00:07:52.780 --> 00:07:55.160 the cost of reading a genome 143 00:07:55.160 --> 00:07:58.380 has plummeted at a remarkable rate. 144 00:07:58.660 --> 00:07:59.980 So in 2001, 145 00:08:00.220 --> 00:08:02.340 it cost about a hundred million dollars 146 00:08:02.340 --> 00:08:04.400 to read an individual's genome. 147 00:08:04.600 --> 00:08:07.360 When James Watson, the discoverer of DNA, 148 00:08:07.520 --> 00:08:08.400 had his genome read, 149 00:08:08.480 --> 00:08:10.320 that was the price tag. 150 00:08:10.500 --> 00:08:11.640 But look what's happened. 151 00:08:13.960 --> 00:08:16.820 Today, you could go and have your genome read 152 00:08:16.820 --> 00:08:21.040 for around about, somewhere between a thousand and five thousand dollars. 153 00:08:21.040 --> 00:08:26.620 And of course, people couldn't resist comparing this with Moore's Law, 154 00:08:26.720 --> 00:08:29.080 which is the gold standard for innovation 155 00:08:29.080 --> 00:08:32.680 that gives us, on average, every 18 months, 156 00:08:32.880 --> 00:08:36.960 doubling the microprocessor power in our computers. 157 00:08:37.340 --> 00:08:41.020 Well, the speed at which we've been reading genomes 158 00:08:41.020 --> 00:08:43.340 has left Moore's Law in the dust. 159 00:08:43.900 --> 00:08:48.540 And this has led to an onslaught, 160 00:08:48.620 --> 00:08:49.660 a step change. 161 00:08:49.800 --> 00:08:50.860 All sorts of... 162 00:08:51.040 --> 00:08:54.000 things are happening that it's making it very hard 163 00:08:54.000 --> 00:08:58.240 to tell the difference between science fiction and fact. 164 00:08:58.780 --> 00:09:00.820 So, here's an example. 165 00:09:02.740 --> 00:09:04.600 What if you were designing a product 166 00:09:04.600 --> 00:09:06.440 that would last well beyond your lifetime? 167 00:09:08.040 --> 00:09:10.000 A product that was made in collaboration 168 00:09:10.000 --> 00:09:11.440 with your closest partner? 169 00:09:13.540 --> 00:09:14.700 Would you test it? 170 00:09:16.460 --> 00:09:17.900 Would you prototype it? 171 00:09:19.640 --> 00:09:21.020 Would you use the most advanced technology 172 00:09:21.020 --> 00:09:22.320 and advanced knowledge to find out 173 00:09:23.740 --> 00:09:24.940 if it was perfect? 174 00:09:28.600 --> 00:09:31.300 The perfect 46 175 00:09:31.300 --> 00:09:34.720 The perfect 46 176 00:09:34.720 --> 00:09:35.400 Fact or fiction? 177 00:09:36.000 --> 00:09:37.840 Who thinks it's fiction? 178 00:09:39.100 --> 00:09:40.480 Who thinks it's fact? 179 00:09:42.600 --> 00:09:44.380 Actually, this is a movie, 180 00:09:44.580 --> 00:09:45.740 The Perfect 46, 181 00:09:46.300 --> 00:09:50.120 which was screened on September the 26th in Boston. 182 00:09:51.640 --> 00:10:18.880 It became the first movie in the world to have a 183 00:10:06.020 --> 00:10:17.440 ! 184 00:10:21.020 --> 00:10:24.060 were roaring designer babies. 185 00:10:24.740 --> 00:10:29.900 So this is just a little bit more about this movie, 186 00:10:30.060 --> 00:10:31.040 The Perfect 46. 187 00:10:31.400 --> 00:10:36.660 So the premise is a geneticist develops a website. 188 00:10:37.800 --> 00:10:41.740 It's a dating site, if you like, with a difference 189 00:10:41.740 --> 00:10:45.700 where you can come and read the genome. 190 00:10:45.840 --> 00:10:48.160 You put your own genome up there. 191 00:10:48.260 --> 00:10:50.820 You look for somebody else's genome. 192 00:10:51.020 --> 00:10:55.060 And you get an idea of what sort of babies you would produce 193 00:10:55.060 --> 00:10:59.920 or the likelihood that if you were to have babies 194 00:10:59.920 --> 00:11:04.340 with a particular person that the child would suffer 195 00:11:04.340 --> 00:11:06.020 from a particular defect. 196 00:11:06.380 --> 00:11:08.920 So the name of the company says it all, 197 00:11:09.000 --> 00:11:14.440 The Perfect 46, two sets of perfect 23 chromosomes. 198 00:11:15.740 --> 00:11:20.340 But as I say, the following week the headlines were, 199 00:11:21.020 --> 00:11:27.660 Roaring designer babies. 200 00:11:28.260 --> 00:11:29.720 What was that all about? 201 00:11:29.900 --> 00:11:35.380 A company in America, one of the first companies to offer profiling of your genome 202 00:11:35.380 --> 00:11:39.620 called 23andMe for your 23 chromosomes, 203 00:11:41.260 --> 00:11:45.560 had been awarded a patent for precisely doing that. 204 00:11:46.260 --> 00:11:48.200 It was called an inheritance calculator. 205 00:11:48.620 --> 00:11:51.000 So the idea was that if you... 206 00:11:51.020 --> 00:11:53.380 and your partner wanted to have a child, 207 00:11:53.520 --> 00:11:57.320 it would predict the likely characteristics of that child. 208 00:11:58.600 --> 00:12:02.840 And the company was taken a little bit aback by this 209 00:12:03.620 --> 00:12:06.240 sobriquet of designer babies. 210 00:12:06.580 --> 00:12:09.480 And they said, no, no, no, we're not making designer babies. 211 00:12:09.580 --> 00:12:14.820 All we're doing is at the moment offering a test for about six different characteristics. 212 00:12:14.900 --> 00:12:19.120 Nothing earth-shattering, eye color, ear wax consistency, 213 00:12:19.980 --> 00:12:21.000 and things like that. 214 00:12:22.440 --> 00:12:25.340 Amongst them, interestingly, athletic performance. 215 00:12:26.400 --> 00:12:30.780 But anyway, I rest my case. 216 00:12:30.860 --> 00:12:35.400 It's getting very hard to tell the difference between science fiction and reality. 217 00:12:38.780 --> 00:12:44.100 So let me take this a little bit further and do some imagining. 218 00:12:44.360 --> 00:12:49.600 So let's say this company that's imagined in the movie, 219 00:12:49.680 --> 00:12:50.980 The Perfect 46, 220 00:12:51.640 --> 00:12:54.980 let's say they have a niche part of their website for athletes. 221 00:12:55.340 --> 00:12:58.760 Let's call it Perfect 46 Athletes. 222 00:12:58.800 --> 00:13:03.720 And let's say James and Julia, they go to this website. 223 00:13:04.220 --> 00:13:07.680 They really...they like the look of each other. 224 00:13:07.940 --> 00:13:12.280 And what they like even better is they like each other's genomes, 225 00:13:12.280 --> 00:13:14.120 which are also up on this website. 226 00:13:14.360 --> 00:13:20.960 Because James and Julia both harbor an ambition to parent an adult. 227 00:13:20.960 --> 00:13:22.140 They harbor an ambition to be an athletic child. 228 00:13:22.860 --> 00:13:27.500 They harbor an ambition for that child to do what they themselves never achieved, 229 00:13:27.640 --> 00:13:31.760 to be an Olympian sprinter. 230 00:13:34.760 --> 00:13:36.900 So is it plausible? 231 00:13:37.960 --> 00:13:41.060 So let me show you what we have found from the genome. 232 00:13:43.700 --> 00:13:46.620 So Iroh Mantiranta, 233 00:13:46.920 --> 00:13:50.000 who was a gold medalist, 234 00:13:50.000 --> 00:13:52.660 a ski champion. 235 00:13:53.040 --> 00:13:57.500 It turned out he had a particular version of the erythropoietin gene. 236 00:13:57.640 --> 00:14:00.280 So he had natural doping going on. 237 00:14:00.580 --> 00:14:04.340 That gene naturally gave him extra red blood cells. 238 00:14:05.040 --> 00:14:06.860 Look at Usain Bolt here. 239 00:14:07.220 --> 00:14:13.160 He probably, very likely, carries two copies of the actinine 3 gene. 240 00:14:13.500 --> 00:14:16.500 It tends to be enriched in sprinters. 241 00:14:17.760 --> 00:14:19.240 Then we have... 242 00:14:19.240 --> 00:14:20.820 the myostatin gene, 243 00:14:21.680 --> 00:14:27.620 which you can see in this Belgian blue highly ripped cow, 244 00:14:27.820 --> 00:14:30.160 because it carries two copies of this gene. 245 00:14:30.280 --> 00:14:32.820 But you find it in human beings too. 246 00:14:32.900 --> 00:14:36.440 Little Liam Hoekstra was born with a similar genetic mutation. 247 00:14:36.620 --> 00:14:38.440 And there he is, lifting weights. 248 00:14:38.680 --> 00:14:40.740 I don't think he's even two years old there. 249 00:14:41.160 --> 00:14:43.920 And then we have another set of genes we've discovered. 250 00:14:44.240 --> 00:14:46.820 There's a thing called VO2max. 251 00:14:47.040 --> 00:14:49.220 If any of you do athletic training, 252 00:14:49.220 --> 00:14:50.840 you'll know about that. 253 00:14:50.900 --> 00:14:55.080 That's a measure of how well you use oxygen when you train. 254 00:14:55.420 --> 00:14:58.760 And there are some people, about 50% of the population, 255 00:14:59.160 --> 00:15:02.800 when they train, they get fitter and fitter and fitter. 256 00:15:03.060 --> 00:15:05.660 And that's because they have these responder genes. 257 00:15:05.980 --> 00:15:08.320 On the other hand, if you don't have them, 258 00:15:08.500 --> 00:15:11.640 you respond pretty poorly to training, unfortunately. 259 00:15:14.520 --> 00:15:15.160 So... 260 00:15:17.120 --> 00:15:17.760 So... 261 00:15:17.760 --> 00:15:19.720 What would we call them? James and Julia. 262 00:15:19.980 --> 00:15:20.360 OK. 263 00:15:20.960 --> 00:15:21.560 So... 264 00:15:22.900 --> 00:15:24.800 They like each other's genomes, 265 00:15:24.860 --> 00:15:26.760 because what they've seen is... 266 00:15:27.540 --> 00:15:28.140 Oops. 267 00:15:28.520 --> 00:15:31.200 They've seen that they each carry... 268 00:15:31.760 --> 00:15:33.860 One or the other of them carries these genes, 269 00:15:34.120 --> 00:15:35.740 or varieties of these genes. 270 00:15:35.980 --> 00:15:37.920 So they try for a baby. 271 00:15:39.420 --> 00:15:40.620 And Julia... 272 00:15:41.760 --> 00:15:44.960 takes advantage of a technology that already exists. 273 00:15:45.440 --> 00:15:46.880 In her first... 274 00:15:46.880 --> 00:15:49.080 six weeks of pregnancy, 275 00:15:49.800 --> 00:15:52.160 she has her blood taken 276 00:15:52.160 --> 00:15:54.860 and sent to a company called Verinata. 277 00:15:55.880 --> 00:15:57.740 And what this company has learnt to do 278 00:15:57.740 --> 00:16:01.660 is to take from the mother's blood 279 00:16:02.600 --> 00:16:05.720 DNA that has come from the foetus. 280 00:16:06.320 --> 00:16:10.000 And this is a test that is being done already. 281 00:16:10.520 --> 00:16:12.580 A woman who's pregnant, 282 00:16:12.700 --> 00:16:15.900 who's worried that she might have a baby with Down's syndrome, 283 00:16:15.980 --> 00:16:16.860 doesn't have to wait. 284 00:16:16.860 --> 00:16:20.120 The ten weeks to do chorionic villus sampling. 285 00:16:20.400 --> 00:16:22.320 In the first few weeks of pregnancy, 286 00:16:22.740 --> 00:16:25.640 she can just merely have some of her blood taken 287 00:16:25.640 --> 00:16:27.880 and sent off to this company, Verinata. 288 00:16:28.140 --> 00:16:30.960 And they can sift from her blood 289 00:16:30.960 --> 00:16:33.080 the foetus's DNA 290 00:16:33.080 --> 00:16:35.980 and tell her if she's got... 291 00:16:35.980 --> 00:16:38.000 if the baby's carrying Down's syndrome. 292 00:16:38.240 --> 00:16:43.200 And they also can read the entire genome of that foetus. 293 00:16:43.440 --> 00:16:46.340 Although it's considerably expensive at the moment, 294 00:16:46.340 --> 00:16:47.600 but we've seen how quickly 295 00:16:47.600 --> 00:16:49.400 the rate of... 296 00:16:50.340 --> 00:16:53.400 the price of DNA sequencing comes down. 297 00:16:54.300 --> 00:16:56.760 So she sends off her blood to Verinata. 298 00:16:57.980 --> 00:16:59.940 Unfortunately, this particular foetus 299 00:16:59.940 --> 00:17:01.500 has got a bad combination of genes. 300 00:17:01.760 --> 00:17:02.920 She aborts it. 301 00:17:03.320 --> 00:17:05.000 She tries two more times. 302 00:17:05.480 --> 00:17:07.460 Finally, she gets a foetus 303 00:17:07.460 --> 00:17:09.800 that seems to have the perfect flush of genes. 304 00:17:11.340 --> 00:17:13.200 Now, I didn't make up this scenario. 305 00:17:13.300 --> 00:17:16.320 I have to credit that to Bob Williams, 306 00:17:16.340 --> 00:17:19.360 a Melbourne-based geneticist 307 00:17:19.360 --> 00:17:21.880 who's had a long career in genetics 308 00:17:21.880 --> 00:17:24.580 and is very good at peering into the future. 309 00:17:25.440 --> 00:17:28.100 And she gives birth to this baby. 310 00:17:28.240 --> 00:17:30.780 Is this baby actually really likely 311 00:17:30.780 --> 00:17:32.500 to be an Olympian sprinter? 312 00:17:34.020 --> 00:17:35.480 Unlikely, I have to say, 313 00:17:35.600 --> 00:17:38.420 because even if this baby 314 00:17:38.420 --> 00:17:40.560 has this wonderful set of genes 315 00:17:41.340 --> 00:17:43.400 that we know from various studies 316 00:17:43.400 --> 00:17:46.320 are associated with high blood pressure, 317 00:17:46.340 --> 00:17:47.160 high athletic performance, 318 00:17:48.340 --> 00:17:50.880 even putting them together in this baby 319 00:17:50.880 --> 00:17:52.640 is no guarantee that that baby 320 00:17:52.640 --> 00:17:54.380 will be an Olympian sprinter. 321 00:17:54.580 --> 00:17:57.680 And for two or maybe three reasons. 322 00:17:57.840 --> 00:18:02.500 Firstly, when we're dealing with a simple trait, 323 00:18:03.340 --> 00:18:06.340 a tragic trait like cystic fibrosis, 324 00:18:06.360 --> 00:18:08.520 that is caused by a single gene. 325 00:18:08.720 --> 00:18:10.720 So if you inherit a single copy 326 00:18:11.340 --> 00:18:15.180 or, you know, rather a bad set of those genes, 327 00:18:15.280 --> 00:18:16.140 one from each parent, 328 00:18:16.340 --> 00:18:19.040 you're guaranteed to get cystic fibrosis. 329 00:18:19.120 --> 00:18:21.340 But a trait like athletic ability 330 00:18:21.340 --> 00:18:23.220 is what we call a complex trait. 331 00:18:23.520 --> 00:18:25.640 There are hundreds and hundreds of genes 332 00:18:25.640 --> 00:18:28.380 that go towards making athletic ability. 333 00:18:28.800 --> 00:18:31.820 So even though we've been able to pick these few genes, 334 00:18:32.000 --> 00:18:34.280 bringing them together in this baby 335 00:18:34.280 --> 00:18:35.840 is no guarantee at all 336 00:18:35.840 --> 00:18:37.760 that that baby will have a perfect set 337 00:18:37.760 --> 00:18:39.560 because we know it takes hundreds of genes 338 00:18:39.560 --> 00:18:41.700 of which we still, you know, 339 00:18:41.700 --> 00:18:43.620 have only identified just a handful. 340 00:18:43.620 --> 00:18:47.920 And then, of course, there's the environmental factor. 341 00:18:48.620 --> 00:18:53.640 So sadly, for all the effort that Julia and James go to, 342 00:18:53.740 --> 00:18:55.600 they're actually not guaranteed 343 00:18:55.600 --> 00:18:57.840 of having an Olympian sprinter. 344 00:19:01.140 --> 00:19:05.780 But as I've said, they could certainly try and do it. 345 00:19:06.320 --> 00:19:08.640 All the pieces are in place. 346 00:19:09.120 --> 00:19:13.060 There are companies that will peer into the genome 347 00:19:13.060 --> 00:19:16.140 if you want to use a sperm bank. 348 00:19:17.200 --> 00:19:22.080 They will peer into the genomes of the sperm donor. 349 00:19:22.660 --> 00:19:24.700 Council and Good Start Genetics 350 00:19:24.700 --> 00:19:28.140 are these sort of sites like the perfect 46 351 00:19:28.140 --> 00:19:29.960 that will screen partners 352 00:19:29.960 --> 00:19:34.340 to see if they carry any DNA variants 353 00:19:34.340 --> 00:19:35.940 that could cause disease. 354 00:19:37.000 --> 00:19:38.340 23andMe, as I've said, 355 00:19:38.380 --> 00:19:39.840 has its inheritance calculator 356 00:19:39.840 --> 00:19:42.120 for six different characteristics. 357 00:19:42.120 --> 00:19:44.580 And Verinata, as I've already mentioned, 358 00:19:44.800 --> 00:19:47.340 is one of the four American companies 359 00:19:47.340 --> 00:19:50.500 already offering prenatal DNA testing 360 00:19:50.500 --> 00:19:51.680 from the mother's blood. 361 00:19:55.720 --> 00:19:59.620 So, as I've already hinted to you, 362 00:19:59.720 --> 00:20:01.800 you can have these tests, 363 00:20:02.020 --> 00:20:03.640 but what are they really going to predict? 364 00:20:03.980 --> 00:20:07.260 Yes, they will certainly predict 365 00:20:07.260 --> 00:20:09.520 these very severe diseases 366 00:20:09.520 --> 00:20:11.760 that are caused by single genes. 367 00:20:11.760 --> 00:20:13.680 Down's, cystic fibrosis, 368 00:20:13.880 --> 00:20:15.060 Huntington's disease, 369 00:20:15.320 --> 00:20:16.040 Thai's, SACS. 370 00:20:16.200 --> 00:20:17.500 And there's nothing new here. 371 00:20:17.560 --> 00:20:20.820 We've had these sorts of screens around for a long time, 372 00:20:20.880 --> 00:20:23.100 albeit with much more cumbersome methods 373 00:20:23.100 --> 00:20:25.000 to identify these genes. 374 00:20:26.140 --> 00:20:29.940 These tests are not going to identify athletic ability, 375 00:20:30.340 --> 00:20:34.160 intelligence, personality, educational attainment. 376 00:20:34.240 --> 00:20:36.380 These are all complex traits. 377 00:20:36.760 --> 00:20:39.200 Hundreds of genes go into making them, 378 00:20:39.300 --> 00:20:41.680 and we have no idea 379 00:20:41.760 --> 00:20:44.240 really how to make these traits. 380 00:20:46.460 --> 00:20:50.220 Nevertheless, we're going to be facing dilemmas pretty soon. 381 00:20:50.460 --> 00:20:54.820 And I think one such dilemma was highlighted to me 382 00:20:54.820 --> 00:20:56.340 by my cousin, 383 00:20:56.500 --> 00:20:59.440 whose son suffers from Crohn's disease. 384 00:20:59.940 --> 00:21:02.640 And as I was telling her 385 00:21:02.640 --> 00:21:05.260 about the research I was doing for my book 386 00:21:05.260 --> 00:21:06.400 and telling her that actually 387 00:21:06.400 --> 00:21:08.300 they have found a gene 388 00:21:08.300 --> 00:21:11.200 that strongly increases the risk 389 00:21:11.200 --> 00:21:12.880 of developing Crohn's disease. 390 00:21:13.100 --> 00:21:14.040 It's called NOD2. 391 00:21:14.300 --> 00:21:15.700 And if you carry this gene, 392 00:21:15.780 --> 00:21:19.300 it's calculated that you have a 40-fold increased risk 393 00:21:19.300 --> 00:21:21.120 of developing Crohn's disease. 394 00:21:21.420 --> 00:21:22.320 Not a guarantee, 395 00:21:22.480 --> 00:21:24.580 not like carrying the cystic fibrosis gene, 396 00:21:24.740 --> 00:21:27.420 but that's a significantly increased risk. 397 00:21:27.920 --> 00:21:29.600 And my cousin said to me, 398 00:21:30.220 --> 00:21:33.180 because she's seen the suffering her son's gone through, 399 00:21:33.580 --> 00:21:36.740 do you think when it's time for him to have children, 400 00:21:36.900 --> 00:21:40.440 he could have his embryos screened 401 00:21:40.440 --> 00:21:43.100 to make sure they're not carrying the NOD2 gene? 402 00:21:43.700 --> 00:21:45.300 And it took me aback, 403 00:21:45.300 --> 00:21:50.200 because this is some very gnarly territory 404 00:21:50.200 --> 00:21:51.820 we're entering into now. 405 00:21:52.080 --> 00:21:55.520 So now these are not the kind of genes like cystic fibrosis. 406 00:21:55.560 --> 00:21:57.460 They're not guaranteed to give you a disease. 407 00:21:58.040 --> 00:22:01.360 They're genes that are part of complex traits 408 00:22:01.360 --> 00:22:04.260 that do strongly increase your risk. 409 00:22:04.560 --> 00:22:05.820 They're a grey area. 410 00:22:05.980 --> 00:22:07.380 And what is going to happen 411 00:22:07.380 --> 00:22:10.340 when people like my cousin's son 412 00:22:10.440 --> 00:22:12.440 have a child and actually say, 413 00:22:12.560 --> 00:22:14.920 well, I would like my embryos screened 414 00:22:14.920 --> 00:22:17.420 to make sure that they don't get the NOD2 gene? 415 00:22:17.700 --> 00:22:21.080 Or if you happen to carry the APOE3 gene, 416 00:22:21.260 --> 00:22:23.440 which increases your risk of Alzheimer's 417 00:22:24.080 --> 00:22:26.700 in your senior years by tenfold, 418 00:22:26.900 --> 00:22:30.360 are you going to ask to screen those embryos away? 419 00:22:30.780 --> 00:22:33.020 It's a very tricky area. 420 00:22:33.240 --> 00:22:35.180 And here's at least one reason why. 421 00:22:36.220 --> 00:22:40.420 Some genes, even though they seem to be 422 00:22:40.420 --> 00:22:43.240 doing bad things, 423 00:22:43.520 --> 00:22:47.180 are kept in the population for a reason. 424 00:22:47.700 --> 00:22:51.480 One example is the gene that causes sickle cell anemia. 425 00:22:51.960 --> 00:22:55.100 Now, if you get two copies of this gene, 426 00:22:55.180 --> 00:22:57.860 you are severely debilitated 427 00:22:58.420 --> 00:23:02.020 by red blood cells that are forever forming clots. 428 00:23:02.220 --> 00:23:05.620 But if you get a single copy of the sickle cell anemia gene, 429 00:23:05.860 --> 00:23:08.300 you're resistant to malaria. 430 00:23:08.920 --> 00:23:10.400 And that's why that gene is called 431 00:23:10.420 --> 00:23:10.560 the NOD2 gene. 432 00:23:10.680 --> 00:23:14.680 And that gene has persisted in the population for eons 433 00:23:14.680 --> 00:23:17.680 because it has protected certain members of the population 434 00:23:18.420 --> 00:23:21.320 from malaria at the cost that if you get a double copy, 435 00:23:21.580 --> 00:23:22.480 you're in trouble. 436 00:23:23.120 --> 00:23:26.200 And there are plenty, plenty of examples like that. 437 00:23:26.500 --> 00:23:30.180 What is the NOD2 gene doing? 438 00:23:30.440 --> 00:23:33.380 Well, it turns out, yes, they've found it causes 439 00:23:33.380 --> 00:23:36.260 an increased risk of developing Crohn's disease 440 00:23:36.260 --> 00:23:38.060 in the affluent world. 441 00:23:38.160 --> 00:23:40.400 But amongst people who have had the NOD2 gene 442 00:23:40.420 --> 00:23:46.560 in developing countries who are suffering from microbial diseases, 443 00:23:46.800 --> 00:23:48.860 it actually protects against leprosy. 444 00:23:49.360 --> 00:23:52.980 So do we really want to start removing this gene from the gene pool? 445 00:23:53.760 --> 00:23:55.900 So all sorts of gnarly issues ahead. 446 00:23:56.100 --> 00:23:58.460 And when I've asked clinical geneticists, 447 00:23:58.460 --> 00:24:00.300 what would you do in this scenario, 448 00:24:02.020 --> 00:24:04.240 they don't know what to do at the moment. 449 00:24:06.360 --> 00:24:09.420 But there's one place where there really are no dilemmas. 450 00:24:10.420 --> 00:24:11.880 And that is... 451 00:24:15.140 --> 00:24:19.220 ..two areas where we are dealing with very, very sick people, 452 00:24:19.300 --> 00:24:23.340 where it has become conceivable to do what was once 453 00:24:23.340 --> 00:24:27.780 completely inconceivable to read their whole genome 454 00:24:28.420 --> 00:24:30.560 and try to figure out what is going on. 455 00:24:30.960 --> 00:24:35.920 So one of these areas where there are a number of very dramatic stories 456 00:24:35.920 --> 00:24:39.960 coming out is with children who are born with a congenital illness. 457 00:24:40.420 --> 00:24:42.440 And another is with cancer. 458 00:24:44.260 --> 00:24:48.540 So let me come first to the story of congenital illnesses. 459 00:24:49.160 --> 00:24:54.820 So about one in 100 children are born with a very serious congenital illness. 460 00:24:55.240 --> 00:24:59.060 And sometimes the geneticists know what it is. 461 00:24:59.380 --> 00:25:02.420 It's Down's, it's Huntington's, it's Ty Sachs. 462 00:25:02.940 --> 00:25:04.080 They know those genes. 463 00:25:04.320 --> 00:25:06.440 In most cases, they don't. 464 00:25:07.420 --> 00:25:09.460 The child may look normal at birth, 465 00:25:09.460 --> 00:25:13.200 but as the child develops, it's clear something's wrong. 466 00:25:13.360 --> 00:25:17.340 There's a developmental delay, or they're not growing properly. 467 00:25:17.880 --> 00:25:21.160 It's agony for everybody involved 468 00:25:21.160 --> 00:25:24.880 because you don't know how to help this child 469 00:25:24.880 --> 00:25:26.700 because you don't know what's broken. 470 00:25:27.120 --> 00:25:30.120 And you don't know what lies ahead for this child. 471 00:25:30.420 --> 00:25:35.980 Do they have a life expectancy of five years, like a Ty Sachs child? 472 00:25:36.260 --> 00:25:39.440 Or will they actually, you know, make it? 473 00:25:39.460 --> 00:25:42.880 Make it into adult life, like somebody with cystic fibrosis, 474 00:25:42.880 --> 00:25:44.440 with some assistance. 475 00:25:46.760 --> 00:25:47.800 Second chance. 476 00:25:48.220 --> 00:25:51.660 Okay, these are the Beery twins, Noah and Alexis Beery. 477 00:25:52.360 --> 00:25:53.780 They live in Texas. 478 00:25:54.160 --> 00:25:57.960 And they were born as floppy babies, twins. 479 00:25:58.500 --> 00:26:01.780 The mother was told cerebral palsy, 480 00:26:02.680 --> 00:26:04.400 you know, which is caused... 481 00:26:04.400 --> 00:26:05.720 It's not a genetic disease. 482 00:26:05.800 --> 00:26:08.160 The baby is deprived of oxygen 483 00:26:08.160 --> 00:26:10.600 during birth and they suffer brain damage. 484 00:26:11.040 --> 00:26:13.020 Somehow, as the children grew, 485 00:26:13.280 --> 00:26:16.840 it didn't seem to fit with cerebral palsy. 486 00:26:17.140 --> 00:26:22.660 And the mother, you know, read the medical literature 487 00:26:22.660 --> 00:26:27.180 and read about a case that seemed more similar to her children 488 00:26:27.180 --> 00:26:28.500 called dystonia 489 00:26:29.280 --> 00:26:35.040 and went and found the scientists who'd treated this patient 490 00:26:35.040 --> 00:26:37.500 and got them to have a look at her twins. 491 00:26:37.500 --> 00:26:41.620 And they said, okay, you know, maybe your twins do have dystonia. 492 00:26:41.720 --> 00:26:43.540 And the treatment for that is dopamine. 493 00:26:44.220 --> 00:26:47.700 The twins were treated with dopamine and improved. 494 00:26:48.600 --> 00:26:50.580 They were able to walk. 495 00:26:51.160 --> 00:26:52.920 They were able to sleep. 496 00:26:53.360 --> 00:26:55.860 In a way, they hadn't been able to sleep. 497 00:26:56.400 --> 00:26:58.380 It was a great step forward. 498 00:26:58.480 --> 00:27:01.880 But still, still they were not fixed. 499 00:27:02.680 --> 00:27:07.480 And the father of these twins actually worked in a DNA sequencing company. 500 00:27:07.480 --> 00:27:10.580 And he raised the money from friends 501 00:27:10.580 --> 00:27:14.240 and members of patients' groups 502 00:27:14.240 --> 00:27:16.760 because it was very expensive still at that time. 503 00:27:16.900 --> 00:27:20.740 And he sequenced the genome of the twins. 504 00:27:24.200 --> 00:27:25.920 And they found the defect. 505 00:27:27.120 --> 00:27:28.480 Now, this is Richard Gibbs. 506 00:27:28.740 --> 00:27:29.920 He's an Australian. 507 00:27:29.960 --> 00:27:35.160 He heads the Baylor College of the sequencing facility there. 508 00:27:35.780 --> 00:27:36.560 And so... 509 00:27:37.480 --> 00:27:41.080 So he read the genome of these two twins. 510 00:27:41.380 --> 00:27:45.520 And the gene turns out to be seriaptorin reductase. 511 00:27:45.600 --> 00:27:47.120 What does this gene do? 512 00:27:47.240 --> 00:27:50.100 It's important for making not just dopamine 513 00:27:50.100 --> 00:27:54.340 but another important brain chemical called serotonin. 514 00:27:54.760 --> 00:27:56.820 Once they realised what was broken, 515 00:27:57.040 --> 00:27:58.760 they knew how to fix it, 516 00:27:58.800 --> 00:28:00.900 and they gave the twins serotonin. 517 00:28:01.200 --> 00:28:06.200 And I was speaking to Richard Gibbs at a conference in Sydney last year, 518 00:28:06.200 --> 00:28:08.100 and he got a text from the mother 519 00:28:08.100 --> 00:28:13.500 to tell him that Alexis had just won a race at school. 520 00:28:13.960 --> 00:28:15.520 It's an extraordinary story. 521 00:28:18.260 --> 00:28:19.760 Here's another story. 522 00:28:20.180 --> 00:28:21.220 Bea Reinhof. 523 00:28:22.520 --> 00:28:24.080 When she was born, 524 00:28:25.760 --> 00:28:29.860 her father, who's also a clinical geneticist... 525 00:28:29.860 --> 00:28:32.920 Interestingly, all these people who've driven this forward 526 00:28:32.920 --> 00:28:35.800 are parents of children 527 00:28:36.200 --> 00:28:37.660 born with a congenital disease 528 00:28:37.660 --> 00:28:41.420 who happen to be involved in DNA in some way or another. 529 00:28:41.840 --> 00:28:45.060 So her father, Hugh Reinhof, was present at her birth, 530 00:28:45.220 --> 00:28:50.580 very happy to see the birth of his third child or daughter. 531 00:28:51.420 --> 00:28:55.780 But his eye immediately caught something a little strange about her. 532 00:28:55.860 --> 00:28:59.720 Her feet were very long and thin and curled. 533 00:29:00.140 --> 00:29:03.060 Well, all babies' feet and hands are curled, 534 00:29:03.100 --> 00:29:06.080 but Bea's hands and feet never uncurled. 535 00:29:06.200 --> 00:29:09.040 And he realised there was something wrong with her. 536 00:29:09.100 --> 00:29:10.620 She didn't put on weight. 537 00:29:11.720 --> 00:29:13.600 Even when she was two years old, 538 00:29:14.200 --> 00:29:16.680 she could barely get herself up from the floor 539 00:29:16.680 --> 00:29:18.760 without bracing herself with her hands. 540 00:29:21.120 --> 00:29:24.200 Here you see a little bird-like body. 541 00:29:24.500 --> 00:29:26.020 A very touching story. 542 00:29:26.260 --> 00:29:30.320 Well, her father was determined to find out what was wrong with her. 543 00:29:30.460 --> 00:29:33.440 He was terrified that she had Marfan syndrome, 544 00:29:33.440 --> 00:29:39.460 which is a defect in the glue that holds cells together. 545 00:29:39.980 --> 00:29:42.580 And children born with this syndrome 546 00:29:42.580 --> 00:29:45.340 end up with very serious consequences, 547 00:29:45.600 --> 00:29:47.440 heart disease and so on. 548 00:29:47.900 --> 00:29:50.880 He was terrified of what lay ahead for her. 549 00:29:50.960 --> 00:29:53.080 He needed to know what she had, 550 00:29:53.260 --> 00:29:56.400 both to know what lay ahead and how to fix it, 551 00:29:56.480 --> 00:29:59.020 and to make damn sure that if he ever had another child, 552 00:29:59.140 --> 00:30:02.780 that child could be screened not to carry that same gene. 553 00:30:03.580 --> 00:30:05.880 It took him ten years. 554 00:30:08.200 --> 00:30:10.520 This year, he found it. 555 00:30:12.720 --> 00:30:15.900 Published in Nature on June 26. 556 00:30:16.320 --> 00:30:18.520 Father's genetic quest pays off. 557 00:30:19.000 --> 00:30:22.340 It turns out, cause for relief. 558 00:30:22.460 --> 00:30:26.400 She didn't have a mutation in the genes 559 00:30:26.400 --> 00:30:28.780 that are associated with heart disease. 560 00:30:29.120 --> 00:30:31.020 She turns out to have something new, 561 00:30:31.140 --> 00:30:33.420 a mutation in a gene called TGF, 562 00:30:33.440 --> 00:30:34.080 TGF-beta. 563 00:30:34.560 --> 00:30:39.580 So far, Bea, though she's weak and needs supports, 564 00:30:40.440 --> 00:30:44.180 splints for her legs so that she can walk, 565 00:30:44.320 --> 00:30:46.280 is developing quite normally. 566 00:30:46.340 --> 00:30:47.600 She's extremely bright. 567 00:30:49.000 --> 00:30:55.180 But knowing the genetic defect gives her father a clue. 568 00:30:55.540 --> 00:31:01.800 Because for the last 30, 40 years of biochemistry and genetics, 569 00:31:01.800 --> 00:31:03.420 we've been busy. 570 00:31:04.280 --> 00:31:09.060 We've been turning, you know, really biochemistry... 571 00:31:09.060 --> 00:31:12.360 If you go to one of these biochemistry or genetics conferences, 572 00:31:12.500 --> 00:31:15.740 when the lecturers put their slides up, 573 00:31:15.840 --> 00:31:17.200 it's hard to look at. 574 00:31:17.260 --> 00:31:18.760 It looks like a circuit board. 575 00:31:18.960 --> 00:31:21.260 There are components everywhere 576 00:31:21.260 --> 00:31:23.240 and arrows pointing every which way. 577 00:31:23.320 --> 00:31:27.160 I'm quite glad I got out of doing genetic research myself. 578 00:31:27.280 --> 00:31:30.340 I don't think I could cope with that sort of complexity. 579 00:31:30.340 --> 00:31:32.720 But that's what they've been doing, 580 00:31:32.740 --> 00:31:35.600 working damn hard to find the circuit components 581 00:31:35.600 --> 00:31:38.700 for how human beings are built, 582 00:31:38.760 --> 00:31:41.460 how our biochemistry pathways operate. 583 00:31:41.780 --> 00:31:46.580 And now that he's found that it's a defect in her TGF-beta gene, 584 00:31:46.720 --> 00:31:50.520 and even knowing just exactly where the mutation lies, 585 00:31:50.840 --> 00:31:52.840 they go back to their circuit board 586 00:31:52.840 --> 00:31:55.040 and they try to figure out what can fix it. 587 00:31:55.180 --> 00:31:56.840 And this is not science fiction. 588 00:31:58.220 --> 00:32:00.160 He's already got Bea on the line. 589 00:32:00.160 --> 00:32:03.380 He's working on a drug that is related to this particular circuit pathway. 590 00:32:05.120 --> 00:32:06.900 Here's another poignant example. 591 00:32:07.460 --> 00:32:13.460 James Lupski was born with Charcot-Marie-Tooth syndrome. 592 00:32:14.380 --> 00:32:16.260 It's caused by many genes. 593 00:32:16.620 --> 00:32:18.900 And it's more named for the syndrome 594 00:32:18.900 --> 00:32:21.260 where people walk as if they're drunk. 595 00:32:22.160 --> 00:32:24.280 There's a problem with their peripheral nerves. 596 00:32:24.500 --> 00:32:26.600 And poor old James Lupski, 597 00:32:26.680 --> 00:32:29.240 he's forever being thrown out of places, 598 00:32:30.160 --> 00:32:30.880 and he's used to being a drunk. 599 00:32:30.960 --> 00:32:31.780 Well, he's not a drunk. 600 00:32:31.880 --> 00:32:33.640 He's just got this dreadful syndrome. 601 00:32:34.020 --> 00:32:36.800 But he too has become a geneticist, 602 00:32:36.840 --> 00:32:40.280 and he also spent 10 years trying to track down 603 00:32:40.280 --> 00:32:42.920 what has gone wrong with his circuitry, 604 00:32:42.940 --> 00:32:44.260 what is the particular gene. 605 00:32:44.460 --> 00:32:46.740 Here he is with his colleague Richard Gibbs, 606 00:32:46.880 --> 00:32:51.980 and he too managed to find the defect in his genome. 607 00:32:52.240 --> 00:32:56.300 And it informs him as to what sort of drugs 608 00:32:56.300 --> 00:32:58.880 he could possibly look for to try to fix it. 609 00:33:00.340 --> 00:33:01.660 So let's move on. 610 00:33:03.600 --> 00:33:05.560 But I'll just say one thing. 611 00:33:06.340 --> 00:33:10.220 So Richard Gibbs sent me an email the other day. 612 00:33:10.300 --> 00:33:11.720 They've just published a paper 613 00:33:11.720 --> 00:33:14.680 on what they're finding in their clinic 614 00:33:14.680 --> 00:33:19.480 when children, babies, their DNA is being sent in 615 00:33:19.480 --> 00:33:22.180 because parents don't know what the hell is wrong with their children. 616 00:33:22.660 --> 00:33:26.720 About a third of the time, they're finding the defective gene. 617 00:33:28.740 --> 00:33:33.400 So another area where we would really like to know 618 00:33:33.400 --> 00:33:36.160 what's gone wrong with the circuitry is cancer. 619 00:33:36.680 --> 00:33:39.740 So cancer is an incredibly complex disease. 620 00:33:40.100 --> 00:33:42.900 And if I stay with my circuit metaphor, 621 00:33:43.120 --> 00:33:47.080 well, somehow the cancer cell has short-circuited 622 00:33:47.080 --> 00:33:50.420 all the normal controls that apply to a cell. 623 00:33:50.760 --> 00:33:53.460 Your normal cells are very tightly controlled. 624 00:33:53.660 --> 00:33:54.280 They won't... 625 00:33:54.280 --> 00:33:56.400 They will stay... 626 00:33:56.400 --> 00:33:56.700 They will stay... 627 00:33:56.720 --> 00:33:57.620 They will stay in place. 628 00:33:57.800 --> 00:33:58.300 They won't... 629 00:33:58.300 --> 00:34:02.440 They won't multiply unless they're allowed to. 630 00:34:02.700 --> 00:34:06.020 A cancer cell short-circuits all those controls. 631 00:34:06.200 --> 00:34:08.360 It breaks out of that regulated growth. 632 00:34:08.480 --> 00:34:09.740 It moves around the body. 633 00:34:09.980 --> 00:34:13.240 So what the hell is it doing to the circuitry? 634 00:34:13.380 --> 00:34:17.740 And again, being able to read the genomes of cancer, 635 00:34:17.980 --> 00:34:21.700 something that would have been an absurd proposition 636 00:34:21.700 --> 00:34:24.920 even five years ago, has now become possible. 637 00:34:26.740 --> 00:34:30.920 And I find this a really compelling metaphor. 638 00:34:31.720 --> 00:34:34.020 So during World War II, 639 00:34:34.100 --> 00:34:37.680 you might be familiar with the Enigma project, 640 00:34:37.860 --> 00:34:43.500 where German U-2 submarines in the Atlantic 641 00:34:43.500 --> 00:34:48.440 were communicating with the control centres in Berlin 642 00:34:48.440 --> 00:34:49.900 through some sort of code. 643 00:34:50.720 --> 00:34:53.240 And the British wanted to crack that code 644 00:34:53.240 --> 00:34:56.700 so they could figure out what these submarines were doing. 645 00:34:56.700 --> 00:34:58.960 And they were doing it because they were mercilessly blowing up 646 00:34:58.960 --> 00:35:01.040 all these British ships in the Atlantic. 647 00:35:01.600 --> 00:35:04.840 So they got their top code-crackers together 648 00:35:04.840 --> 00:35:07.540 at Bletchley Park in this mansion, 649 00:35:08.220 --> 00:35:10.540 all the world's best code-breakers, 650 00:35:10.620 --> 00:35:12.200 or the British, anyway, 651 00:35:12.420 --> 00:35:16.260 and they developed this decoding machine called the Bomb. 652 00:35:16.600 --> 00:35:20.120 Well, something similar is happening with cancer now. 653 00:35:20.280 --> 00:35:23.380 We have a project called the Cancer Genome Atlas, 654 00:35:23.660 --> 00:35:26.520 where cancer researchers from all over the world 655 00:35:26.700 --> 00:35:29.460 are being funded to come together, 656 00:35:29.560 --> 00:35:32.260 read the genomes of cancers, 657 00:35:32.520 --> 00:35:36.460 and see if they can decode what it is 658 00:35:36.460 --> 00:35:38.500 that these cancers are doing 659 00:35:38.500 --> 00:35:41.060 to short-circuit the normal controls. 660 00:35:45.400 --> 00:35:51.500 So we actually have a precedent for success in doing this. 661 00:35:51.600 --> 00:35:55.500 So decades ago, when you treated a cancer, 662 00:35:55.500 --> 00:35:57.360 it was a scorched-earth type policy. 663 00:35:58.100 --> 00:36:01.540 You used radiotherapy, which we still use now, 664 00:36:01.680 --> 00:36:06.400 or you used very broad specificity drugs 665 00:36:06.400 --> 00:36:08.660 that would kill any multiplying cell. 666 00:36:08.960 --> 00:36:10.740 It was a kind of scorched-earth policy 667 00:36:10.740 --> 00:36:15.880 because you weren't able to get at the real Achilles' heel of the cancer. 668 00:36:16.320 --> 00:36:21.120 You were targeting many types of cells in the human body, 669 00:36:21.220 --> 00:36:23.900 and so you were very limited with what you could do. 670 00:36:24.000 --> 00:36:25.480 If you were really going to wipe out the cancer, 671 00:36:25.480 --> 00:36:28.800 you were probably going to wipe out the person as well. 672 00:36:29.040 --> 00:36:31.560 And we started seeing real successes 673 00:36:31.560 --> 00:36:36.260 when we zeroed in on specifically what the cancer is doing. 674 00:36:36.680 --> 00:36:42.140 And one of the success stories we saw was in 2001 675 00:36:42.880 --> 00:36:47.880 with a type of leukemia, chronic myelogenous leukemia, 676 00:36:48.000 --> 00:36:53.180 where they'd found that the circuit component that had gone faulty 677 00:36:53.180 --> 00:36:55.260 was something called the Abel gene. 678 00:36:55.480 --> 00:36:57.880 And they developed a drug called Gleevec, 679 00:36:58.000 --> 00:36:59.940 which targeted just that gene, 680 00:37:00.120 --> 00:37:02.100 so they could give it in high doses 681 00:37:02.100 --> 00:37:04.920 without damaging the other cells of the human body, 682 00:37:05.020 --> 00:37:06.820 and they got terrific successes. 683 00:37:07.320 --> 00:37:10.540 I mean, not necessarily a cure, 684 00:37:10.700 --> 00:37:15.140 but improving survival from less than a year to seven years, 685 00:37:15.380 --> 00:37:18.160 which in some patients will mean a cure, 686 00:37:18.180 --> 00:37:19.380 in other patients it won't. 687 00:37:20.860 --> 00:37:23.400 So that's the poster child 688 00:37:23.400 --> 00:37:25.400 for this kind of targeted, 689 00:37:25.480 --> 00:37:26.220 targeted therapy, 690 00:37:26.380 --> 00:37:29.840 really getting at what the cancer cell strategy is, 691 00:37:30.480 --> 00:37:32.540 homing in on it and nailing it. 692 00:37:33.180 --> 00:37:37.900 And here's another success story from the Cancer Genome Atlas, 693 00:37:38.180 --> 00:37:41.200 just reported a few weeks ago. 694 00:37:41.480 --> 00:37:46.180 So glioblastoma is one of the most common brain tumours 695 00:37:46.180 --> 00:37:48.720 and very, very hard to treat. 696 00:37:50.020 --> 00:37:53.280 What did they find when they read the genomes 697 00:37:53.280 --> 00:37:54.900 of this particular cancer? 698 00:37:55.480 --> 00:37:56.080 Oh. 699 00:37:58.400 --> 00:38:00.620 So here's a glioblastoma. 700 00:38:00.760 --> 00:38:05.620 They found something that we refer to as actionable drug targets. 701 00:38:05.880 --> 00:38:09.600 So they recognised these particular genes, 702 00:38:09.900 --> 00:38:12.420 BRAF, FGFR and EGFR, 703 00:38:12.780 --> 00:38:16.220 the circuit components that they already know, 704 00:38:16.380 --> 00:38:19.460 and they already have drugs that can knock them out, 705 00:38:19.580 --> 00:38:21.360 drugs that are already on the shelf. 706 00:38:21.560 --> 00:38:23.820 So it offers new strategies 707 00:38:23.820 --> 00:38:25.460 for getting at this very issue. 708 00:38:25.480 --> 00:38:26.320 So this is the biopsy of intractable cancer. 709 00:38:27.680 --> 00:38:32.240 And similar studies are going on with other very nasty cancers. 710 00:38:32.380 --> 00:38:36.080 Pancreatic cancer, finding genes that they didn't expect, 711 00:38:36.260 --> 00:38:38.640 like a breast cancer gene often going awry, 712 00:38:38.800 --> 00:38:43.240 melanoma, the BRAF gene that they have drugs to treat, 713 00:38:45.760 --> 00:38:48.580 adenocolorectal cancer, these new targets. 714 00:38:49.100 --> 00:38:52.660 So, sorry, that's probably quite deadening to look at that, 715 00:38:52.660 --> 00:38:54.160 so I'll just move right along. 716 00:38:54.300 --> 00:38:58.200 But anyway, I think I'll just end with saying that... 717 00:38:58.840 --> 00:39:03.640 So I wrote my book and I finished it in early 2012. 718 00:39:03.880 --> 00:39:06.500 And really, at that time, 719 00:39:08.300 --> 00:39:11.080 if I spoke to a clinical geneticist, 720 00:39:11.080 --> 00:39:12.180 they would say to me, 721 00:39:12.940 --> 00:39:14.220 oh, well, you know, 722 00:39:14.220 --> 00:39:17.940 we're not really seeing any impact at all of the Human Genome Project. 723 00:39:19.460 --> 00:39:22.240 And scientists, you know, were a little different, 724 00:39:22.240 --> 00:39:24.920 because they get things a little earlier on in the pipeline. 725 00:39:25.100 --> 00:39:26.220 They were more excited. 726 00:39:26.300 --> 00:39:27.080 They were saying, no, no, 727 00:39:27.100 --> 00:39:30.440 we are starting to see something new happening 728 00:39:30.440 --> 00:39:33.040 as the costs of genomes are coming down. 729 00:39:33.180 --> 00:39:37.720 We're getting these amazing research tools that we never had before. 730 00:39:38.740 --> 00:39:41.440 But because I knew I was speaking at this conference, 731 00:39:41.520 --> 00:39:47.000 I called up my regular cohort of experts just a few weeks ago, 732 00:39:47.120 --> 00:39:50.320 and they were all singing a completely different tune. 733 00:39:51.000 --> 00:39:52.040 Martin Delaticchi, 734 00:39:52.100 --> 00:39:52.220 who is a professor at the University of New York, 735 00:39:52.240 --> 00:39:54.980 who's head of clinical genetics at the Murdoch, 736 00:39:55.060 --> 00:39:57.360 who just a year ago was saying, 737 00:39:57.460 --> 00:39:59.260 eh, we're not seeing much in the clinic. 738 00:39:59.540 --> 00:40:00.980 What did he say? 739 00:40:01.020 --> 00:40:02.100 I think I've written it up here. 740 00:40:03.440 --> 00:40:06.020 It's such an unbelievably exciting time 741 00:40:06.020 --> 00:40:07.820 and things are changing daily. 742 00:40:08.360 --> 00:40:12.360 He's referring to the fact that now when he gets these children coming in, 743 00:40:12.400 --> 00:40:13.560 he can find out, 744 00:40:13.580 --> 00:40:17.100 he can send their DNA off to be sequenced 745 00:40:17.100 --> 00:40:20.760 and get a result that would have been unbelievable for him before. 746 00:40:21.820 --> 00:40:25.620 The people are making comments like, 747 00:40:25.700 --> 00:40:26.320 it's a flood. 748 00:40:26.460 --> 00:40:29.840 The rate of discovery and the implications are unheard of 749 00:40:29.840 --> 00:40:31.060 in my academic lifetime. 750 00:40:31.300 --> 00:40:34.920 That's from Ed Loo when he was president of the Human Genome Organisation. 751 00:40:35.380 --> 00:40:38.540 Or it's streaming ahead into the clinic in a way that's blinding. 752 00:40:38.580 --> 00:40:39.440 Richard Gibbs. 753 00:40:39.880 --> 00:40:42.940 So, you know, brace yourselves. 754 00:40:43.140 --> 00:40:44.780 The genome is here. 755 00:40:45.260 --> 00:40:46.120 Thank you. 756 00:40:56.080 --> 00:40:56.720 APPLAUSE 757 00:40:56.720 --> 00:40:58.960 Thank you very much, Elizabeth. 758 00:40:59.360 --> 00:41:00.180 Is this on? 759 00:41:00.600 --> 00:41:01.240 Yes. 760 00:41:01.360 --> 00:41:01.680 Yes. 761 00:41:01.880 --> 00:41:03.060 Thank you very much. 762 00:41:03.100 --> 00:41:06.080 That's really some fascinating stories there 763 00:41:06.080 --> 00:41:08.520 and some real examples of success 764 00:41:08.520 --> 00:41:12.560 as models for the further successes that we might expect. 765 00:41:12.920 --> 00:41:14.500 Now, we have some time for questions 766 00:41:14.500 --> 00:41:17.640 and maybe if we could come here 767 00:41:17.640 --> 00:41:20.060 and we might have a very short discussion 768 00:41:20.060 --> 00:41:20.740 and then we'll go on. 769 00:41:20.760 --> 00:41:22.200 And then we'll hand over to the rest of the audience. 770 00:41:22.420 --> 00:41:22.680 OK. 771 00:41:23.680 --> 00:41:24.740 Come and sit here. 772 00:41:28.760 --> 00:41:30.640 It really is an exciting time 773 00:41:30.640 --> 00:41:32.520 and I think you've shown really well 774 00:41:32.520 --> 00:41:34.800 just how fast it's all accelerating. 775 00:41:35.320 --> 00:41:40.020 I've got one question that I'm curious your thoughts on 776 00:41:40.020 --> 00:41:42.740 to do with the ethics involved here. 777 00:41:42.920 --> 00:41:45.700 And it concerns the ownership of sequences. 778 00:41:48.020 --> 00:41:50.740 Where should the ownership of an individual's 779 00:41:50.740 --> 00:41:51.760 sequence lie? 780 00:41:51.900 --> 00:41:54.860 Or the ownership of a generic sequence? 781 00:41:55.120 --> 00:41:58.340 Is it legitimate for a commercial company 782 00:41:58.340 --> 00:42:02.200 to have ownership of a common gene that we all have? 783 00:42:02.520 --> 00:42:05.720 And what about the confidentiality of our own sequence 784 00:42:06.740 --> 00:42:09.760 outside our own little circle of self-interest? 785 00:42:11.220 --> 00:42:14.680 So, I think the US Supreme Court passed, 786 00:42:14.920 --> 00:42:18.360 you know, made a big precedent in June, I think, 787 00:42:18.360 --> 00:42:20.720 by finding that, you know, 788 00:42:20.720 --> 00:42:23.600 DNA as such cannot... 789 00:42:23.600 --> 00:42:27.520 You cannot sustain a patent on a gene... 790 00:42:27.520 --> 00:42:28.420 On the sequence. 791 00:42:28.740 --> 00:42:29.260 On the sequence. 792 00:42:29.580 --> 00:42:29.700 Yeah. 793 00:42:30.720 --> 00:42:35.480 And that finding related to the case of the breast cancer gene, 794 00:42:35.700 --> 00:42:36.980 BRCA1 and BRCA2, 795 00:42:37.720 --> 00:42:41.020 which the company Myriad had indeed patented 796 00:42:41.720 --> 00:42:44.900 and were very aggressively pursuing that patent 797 00:42:45.720 --> 00:42:47.520 to the detriment of the public. 798 00:42:48.420 --> 00:42:49.220 So... 799 00:42:49.220 --> 00:42:52.420 Because they were so aggressive about this patent, 800 00:42:52.660 --> 00:42:56.340 it made it impossible for other companies 801 00:42:56.340 --> 00:42:58.080 to offer the DNA test. 802 00:42:58.300 --> 00:43:00.320 Only their company could offer it, 803 00:43:00.340 --> 00:43:02.300 which made the test rather expensive, 804 00:43:02.620 --> 00:43:04.400 $4,000 for a test. 805 00:43:04.600 --> 00:43:07.400 Although they did have a compassionate clause 806 00:43:07.400 --> 00:43:08.780 for people who couldn't afford it. 807 00:43:08.820 --> 00:43:12.380 But nevertheless, this is how they were proceeding. 808 00:43:13.900 --> 00:43:18.980 And they were very aggressive to researchers as well. 809 00:43:18.980 --> 00:43:21.420 So it intimidated researchers 810 00:43:21.980 --> 00:43:24.800 from doing research on the gene 811 00:43:24.800 --> 00:43:28.760 and particular consequences of having the gene. 812 00:43:28.900 --> 00:43:31.120 So they were very bad citizens. 813 00:43:31.700 --> 00:43:33.200 They're not typical, though. 814 00:43:33.980 --> 00:43:36.840 There are, you know, maybe a handful of companies 815 00:43:36.840 --> 00:43:39.000 who have got a patent on a gene 816 00:43:39.000 --> 00:43:41.180 who've really caused a problem like that. 817 00:43:41.380 --> 00:43:45.460 But my understanding is that, you know, 818 00:43:45.460 --> 00:43:47.300 more than half of our genes 819 00:43:47.300 --> 00:43:48.960 are actually under patent. 820 00:43:48.960 --> 00:43:50.120 Yes. 821 00:43:50.920 --> 00:43:54.360 And by and large, the companies that hold those patents 822 00:43:54.360 --> 00:43:57.720 have not created a problem for public good. 823 00:43:57.740 --> 00:43:59.700 So, for instance, I believe there's a patent 824 00:43:59.700 --> 00:44:01.260 on the insulin gene. 825 00:44:01.500 --> 00:44:05.480 But that's been rather sort of used for good 826 00:44:05.480 --> 00:44:10.240 because it's protected the commercial ability 827 00:44:10.240 --> 00:44:13.740 of companies to put that gene in a bacteria 828 00:44:13.740 --> 00:44:17.980 and then make cheap, safe human insulin. 829 00:44:17.980 --> 00:44:21.480 And if they didn't hold that patent, 830 00:44:21.600 --> 00:44:24.420 would they have developed this as a business model? 831 00:44:25.000 --> 00:44:30.260 So I think, you know, in the hands of a company 832 00:44:30.260 --> 00:44:33.960 that behaves badly, we've had a problem. 833 00:44:34.040 --> 00:44:36.340 But by and large, most of the companies 834 00:44:36.340 --> 00:44:38.920 that hold patents to human genes, 835 00:44:38.980 --> 00:44:42.820 it hasn't ended up in public bad. 836 00:44:42.880 --> 00:44:44.580 It's actually ended up in public good 837 00:44:44.580 --> 00:44:45.740 because we get the drugs. 838 00:44:46.020 --> 00:44:46.440 Mm-hm. 839 00:44:46.440 --> 00:44:47.000 Mm-hm. 840 00:44:47.440 --> 00:44:49.920 I think the issue of genetic privacy. 841 00:44:50.200 --> 00:44:57.140 So I think people really had their telescopes at hand 842 00:44:57.140 --> 00:44:59.740 when they started the Human Genome Project, 843 00:44:59.820 --> 00:45:00.920 peering into the future, 844 00:45:00.960 --> 00:45:04.580 what sort of ethical problems are we going to end up with? 845 00:45:04.740 --> 00:45:06.820 And they set aside a few million dollars 846 00:45:06.820 --> 00:45:10.820 for these ethics researchers to have a look at. 847 00:45:10.880 --> 00:45:12.620 And as a result, you know, 848 00:45:12.640 --> 00:45:15.660 we have laws protecting genetic privacy. 849 00:45:15.660 --> 00:45:21.800 You cannot be discriminated against for health insurance or at work. 850 00:45:21.960 --> 00:45:23.580 There are laws protecting that. 851 00:45:23.860 --> 00:45:25.980 Less clear-cut for life insurance. 852 00:45:27.060 --> 00:45:31.300 So, yes, there are grey areas that we need to be vigilant about. 853 00:45:31.480 --> 00:45:33.420 But I think by and large, 854 00:45:35.220 --> 00:45:37.240 people have been looking ahead 855 00:45:37.240 --> 00:45:39.760 to see what the problems could be. 856 00:45:39.860 --> 00:45:41.300 And there are laws in place. 857 00:45:42.280 --> 00:45:44.620 Is there a risk that this new ruling 858 00:45:44.620 --> 00:45:47.160 about not being able to patent a sequence 859 00:45:47.160 --> 00:45:50.420 is going to impair commercial investment 860 00:45:50.420 --> 00:45:52.980 in this sort of research? 861 00:45:53.660 --> 00:45:56.520 I think the feeling is not 862 00:45:56.520 --> 00:46:02.380 because it doesn't... 863 00:46:02.380 --> 00:46:03.720 If I remember correctly, 864 00:46:03.900 --> 00:46:06.340 the patent applied to the sequence of the gene 865 00:46:06.340 --> 00:46:11.520 and there are lots of different processes by way... 866 00:46:11.520 --> 00:46:11.720 Yes. 867 00:46:12.540 --> 00:46:14.600 ..that are not affected by the gene. 868 00:46:14.620 --> 00:46:15.100 There are lots of different processes by way of how you apply that patent, 869 00:46:15.180 --> 00:46:15.960 process patents. 870 00:46:16.340 --> 00:46:19.180 So if you read the gene in different ways, 871 00:46:20.020 --> 00:46:22.360 you can still get a patent 872 00:46:22.360 --> 00:46:25.060 on developing different ways to read a gene. 873 00:46:25.180 --> 00:46:27.660 But the gene itself, the sequence itself, 874 00:46:27.780 --> 00:46:30.400 I believe, will not be patentable 875 00:46:30.400 --> 00:46:33.180 or will certainly now be open to huge contest 876 00:46:33.180 --> 00:46:34.800 if anybody tries. 877 00:46:35.160 --> 00:46:36.200 Yeah, that's terrific. 878 00:46:36.580 --> 00:46:39.500 Now, I think we have time for some questions from the audience. 879 00:46:39.740 --> 00:46:41.560 Is there anyone who'd like to ask a question? 880 00:46:44.820 --> 00:46:45.900 You're quite close. 881 00:46:47.780 --> 00:46:50.740 How long would you guess that it would be 882 00:46:50.740 --> 00:46:54.720 before people who fronted up and got a diagnosis of cancer 883 00:46:55.400 --> 00:46:59.000 would automatically have their whole genome scanned? 884 00:47:00.580 --> 00:47:02.440 How soon would you say that would happen? 885 00:47:05.740 --> 00:47:06.300 Hmm. 886 00:47:07.820 --> 00:47:08.380 Automatically. 887 00:47:08.900 --> 00:47:12.520 I guess that what we're going to have to see 888 00:47:12.520 --> 00:47:14.600 is some proof of that. 889 00:47:14.620 --> 00:47:15.740 I think there's a proof of concept to show 890 00:47:15.740 --> 00:47:20.760 that patients who get their genomes scanned 891 00:47:20.760 --> 00:47:23.180 and then get this targeted therapy 892 00:47:23.180 --> 00:47:25.420 that zeroes in straight on their drug... 893 00:47:25.420 --> 00:47:28.160 Sorry, straight on their defective genes, 894 00:47:28.360 --> 00:47:30.400 that their survival is improved, 895 00:47:30.760 --> 00:47:33.360 that they've cost the health system less. 896 00:47:33.760 --> 00:47:38.580 And certainly researchers like Andrew Biancan in Sydney, 897 00:47:39.360 --> 00:47:41.500 firmly... He's at the Garvan, right? 898 00:47:41.560 --> 00:47:43.120 He firmly believes 899 00:47:44.620 --> 00:47:46.880 that if you look at the costs of treating a patient, 900 00:47:47.960 --> 00:47:50.660 all the scans that have to be done 901 00:47:50.660 --> 00:47:52.700 to track the progress of the cancer, 902 00:47:53.780 --> 00:47:55.920 it gets tremendously expensive. 903 00:47:56.460 --> 00:47:59.440 And in his view, when you calculate it all out, 904 00:47:59.660 --> 00:48:01.600 the cost of reading the genome, 905 00:48:01.680 --> 00:48:03.380 which is getting cheaper and cheaper and cheaper, 906 00:48:04.300 --> 00:48:06.380 would compare quite favourably. 907 00:48:06.780 --> 00:48:10.760 So I think it could happen quite quickly now. 908 00:48:14.620 --> 00:48:15.340 You want me to guess? 909 00:48:15.900 --> 00:48:16.820 Three years. 910 00:48:17.440 --> 00:48:20.180 Because I think you know quite quickly... 911 00:48:21.480 --> 00:48:24.500 So the trials are happening already. 912 00:48:25.660 --> 00:48:29.900 You can see with a lot of these rare and very severe cancers, 913 00:48:29.940 --> 00:48:31.300 like pancreatic cancer, 914 00:48:31.420 --> 00:48:33.580 that a person may... 915 00:48:33.580 --> 00:48:36.420 Within a year, a person may not survive, 916 00:48:36.600 --> 00:48:37.820 or these glioblastomas. 917 00:48:38.000 --> 00:48:40.060 So you're going to get a result very quickly. 918 00:48:41.460 --> 00:48:42.020 So... 919 00:48:42.620 --> 00:48:43.340 There's been talk. 920 00:48:44.620 --> 00:48:45.300 Fairly recently, 921 00:48:45.440 --> 00:48:48.260 about doing newborn screening 922 00:48:48.260 --> 00:48:50.860 and using the whole human genome 923 00:48:50.860 --> 00:48:53.940 in place of the tests that are present, 924 00:48:54.040 --> 00:48:56.100 have been done for 50 years nearly. 925 00:48:57.020 --> 00:48:57.600 Um... 926 00:48:57.600 --> 00:49:00.020 One, is that a good thing? 927 00:49:00.960 --> 00:49:02.900 Because people will discover 928 00:49:02.900 --> 00:49:04.820 that perhaps that their child 929 00:49:04.820 --> 00:49:07.260 has a tendency to Alzheimer's disease 930 00:49:07.260 --> 00:49:08.180 when it's 70, 931 00:49:08.460 --> 00:49:12.700 or may discover that it's got something awful, 932 00:49:13.000 --> 00:49:14.480 like hunting diseases, 933 00:49:14.620 --> 00:49:18.880 long before the child's going to get it. 934 00:49:18.980 --> 00:49:19.940 That's one question. 935 00:49:20.240 --> 00:49:21.320 But the next one is, 936 00:49:21.420 --> 00:49:23.280 why screen the newborn baby? 937 00:49:23.440 --> 00:49:24.720 Why not screen the parents? 938 00:49:25.340 --> 00:49:27.120 It seems silly to me 939 00:49:27.120 --> 00:49:29.180 to detect things in a newborn 940 00:49:29.180 --> 00:49:30.820 that you could have prevented 941 00:49:30.820 --> 00:49:32.960 by testing the parents. 942 00:49:34.600 --> 00:49:37.280 The second one is easy to answer. 943 00:49:37.400 --> 00:49:38.760 And that is because... 944 00:49:40.680 --> 00:49:42.860 Babies can get new mutations. 945 00:49:43.060 --> 00:49:44.100 On average. 946 00:49:44.100 --> 00:49:47.540 A baby gets one new mutation. 947 00:49:48.160 --> 00:49:51.260 So sometimes when they're screening these children 948 00:49:51.260 --> 00:49:52.940 with congenital defects, 949 00:49:53.420 --> 00:49:55.240 it's in neither of the parents. 950 00:49:56.360 --> 00:49:57.040 So... 951 00:49:57.040 --> 00:49:59.120 As to your first question, 952 00:49:59.420 --> 00:50:01.500 they've just announced a study, 953 00:50:01.500 --> 00:50:02.840 I believe, from the NIH, 954 00:50:02.960 --> 00:50:05.220 to look at that very question. 955 00:50:05.320 --> 00:50:10.000 If you start reading the genomes of newborns, 956 00:50:10.000 --> 00:50:14.080 does the downside outweigh the upside? 957 00:50:14.080 --> 00:50:18.040 So I think people are very aware of that dilemma, 958 00:50:18.180 --> 00:50:22.240 because you will certainly find things like, 959 00:50:22.300 --> 00:50:23.520 as you say, 960 00:50:23.680 --> 00:50:26.360 the Alzheimer's predisposition gene 961 00:50:27.980 --> 00:50:29.920 and many others 962 00:50:29.920 --> 00:50:34.560 that raise risk for certain diseases. 963 00:50:34.880 --> 00:50:36.000 There's no guarantee 964 00:50:36.000 --> 00:50:38.700 that the child will get those diseases. 965 00:50:38.960 --> 00:50:41.980 And then what does the parent do with that information? 966 00:50:42.400 --> 00:50:44.060 I think people like Bob, 967 00:50:44.080 --> 00:50:44.820 Bob Williamson, 968 00:50:44.820 --> 00:50:48.520 believe it's good to empower people with that information. 969 00:50:49.300 --> 00:50:52.340 His view is that if you find out that you carry 970 00:50:52.340 --> 00:50:54.940 the risky Alzheimer's gene, 971 00:50:55.500 --> 00:50:58.620 it just is information you may be able to use 972 00:50:58.620 --> 00:50:59.860 in a constructive way. 973 00:51:00.920 --> 00:51:03.980 Maybe you'll make your will at 60 rather than 80, 974 00:51:04.160 --> 00:51:04.900 for instance. 975 00:51:07.560 --> 00:51:08.840 On the other hand, 976 00:51:09.520 --> 00:51:11.500 it will just make people, 977 00:51:11.600 --> 00:51:13.060 certain types of people, 978 00:51:13.060 --> 00:51:14.200 very stressed out. 979 00:51:14.340 --> 00:51:16.980 So I guess you have to know what sort of a person you are. 980 00:51:17.020 --> 00:51:18.240 If you're an anxious person 981 00:51:18.240 --> 00:51:22.000 and you're not going to respond to that sort of information well, 982 00:51:22.920 --> 00:51:25.040 maybe you shouldn't get that sort of information. 983 00:51:25.220 --> 00:51:26.000 On the other hand, 984 00:51:26.080 --> 00:51:29.320 there are other mutations that you can do things about, 985 00:51:29.460 --> 00:51:33.180 like a gene for hypercholesterolemia, 986 00:51:33.300 --> 00:51:37.120 which means you will produce too much cholesterol. 987 00:51:37.260 --> 00:51:43.040 So I think that these studies will have to figure these questions out. 988 00:51:43.060 --> 00:51:45.060 Just trying to understand, 989 00:51:45.360 --> 00:51:50.460 are the treatments trying to supplement what the gene isn't doing 990 00:51:50.460 --> 00:51:53.060 or are they affecting the gene itself? 991 00:51:53.300 --> 00:51:54.500 Is there technology to, 992 00:51:54.640 --> 00:51:55.740 you're seeing that mutation, 993 00:51:56.080 --> 00:51:56.980 can you fix the mutation 994 00:51:56.980 --> 00:51:58.880 or can you just balance out what it's not doing 995 00:51:58.880 --> 00:52:00.180 when it should have been doing it in the first place? 996 00:52:00.340 --> 00:52:01.640 I'm so glad I looked this up 997 00:52:01.640 --> 00:52:04.140 just five minutes before this session. 998 00:52:04.300 --> 00:52:07.240 There is this new drug out there for cystic fibrosis 999 00:52:07.240 --> 00:52:08.680 called Kalydeco. 1000 00:52:08.760 --> 00:52:11.760 K-L-Y-D-E-C-O. 1001 00:52:11.760 --> 00:52:15.500 Now the cystic fibrosis gene 1002 00:52:16.580 --> 00:52:17.580 is a, 1003 00:52:17.660 --> 00:52:20.440 it transports ions, 1004 00:52:20.580 --> 00:52:21.660 the chloride ion, 1005 00:52:21.820 --> 00:52:22.720 across the membrane. 1006 00:52:23.760 --> 00:52:25.120 And in a particular mutation, 1007 00:52:25.460 --> 00:52:28.720 not everybody carries the same fault in this gene, 1008 00:52:28.840 --> 00:52:31.140 but if you carry this particular fault, 1009 00:52:31.580 --> 00:52:33.760 they've figured out how to fix it 1010 00:52:33.760 --> 00:52:36.040 with this particular drug. 1011 00:52:36.980 --> 00:52:38.800 So we really, 1012 00:52:39.240 --> 00:52:39.740 that's why, 1013 00:52:39.860 --> 00:52:40.200 you know, 1014 00:52:40.200 --> 00:52:42.820 I think this metaphor of the circuit diagram is apt. 1015 00:52:43.360 --> 00:52:44.300 We, you know, 1016 00:52:44.320 --> 00:52:47.180 the 40 or 50 years of biochemistry 1017 00:52:47.180 --> 00:52:49.200 have turned us into a circuit board 1018 00:52:49.200 --> 00:52:52.660 and we are zeroing in with such precision now. 1019 00:52:53.160 --> 00:52:55.240 I think drugs like Kalydeco 1020 00:52:55.240 --> 00:52:56.900 is the drug of the future 1021 00:52:56.900 --> 00:52:59.760 and that is why people like James Lupski 1022 00:52:59.760 --> 00:53:01.620 are sequencing their genomes. 1023 00:53:01.700 --> 00:53:02.600 They want to find out, 1024 00:53:02.640 --> 00:53:04.060 not just the gene, 1025 00:53:04.220 --> 00:53:05.900 exactly what is the mutation. 1026 00:53:06.220 --> 00:53:08.220 I know all the circuit pathways. 1027 00:53:08.460 --> 00:53:09.600 I'm going to find something 1028 00:53:09.600 --> 00:53:11.160 to fix my mutation. 1029 00:53:12.120 --> 00:53:13.380 That's what we're looking at. 1030 00:53:14.260 --> 00:53:16.560 Just slightly to a tangent to this, 1031 00:53:16.660 --> 00:53:18.740 I know there's a study in Sydney 1032 00:53:18.740 --> 00:53:20.480 within the Jewish communities 1033 00:53:21.020 --> 00:53:23.360 where they work out that 1034 00:53:23.360 --> 00:53:25.640 some of the Jewish teenagers 1035 00:53:25.640 --> 00:53:26.960 carry a particular mutation 1036 00:53:27.480 --> 00:53:28.660 that is only a problem 1037 00:53:28.660 --> 00:53:30.400 if they marry someone else with the same mutation. 1038 00:53:30.800 --> 00:53:32.680 And rather than burden these teenagers 1039 00:53:32.680 --> 00:53:33.660 with this knowledge, 1040 00:53:34.280 --> 00:53:35.280 you know, 14, 1041 00:53:35.560 --> 00:53:37.640 they wait until they're about to partner 1042 00:53:37.640 --> 00:53:38.600 and then they release, 1043 00:53:38.780 --> 00:53:41.740 whether both of the partners have this mutation. 1044 00:53:42.060 --> 00:53:42.340 Oh. 1045 00:53:42.760 --> 00:53:43.320 Is that, 1046 00:53:44.160 --> 00:53:45.800 do you see that as a way of the future 1047 00:53:45.800 --> 00:53:48.240 that we perhaps could sequence everyone's genomes 1048 00:53:48.240 --> 00:53:49.020 but, you know, 1049 00:53:49.040 --> 00:53:51.280 keep it in a secret database 1050 00:53:51.280 --> 00:53:53.100 until it becomes a relevant issue 1051 00:53:53.100 --> 00:53:55.340 when procreation is about to happen? 1052 00:53:56.220 --> 00:53:56.620 Hmm. 1053 00:53:58.780 --> 00:53:59.860 Not one you've come across? 1054 00:53:59.940 --> 00:54:00.560 It's just, yeah. 1055 00:54:01.480 --> 00:54:04.100 I'm aware of the Tysex mutation. 1056 00:54:04.940 --> 00:54:06.580 That's the one that is terrible. 1057 00:54:06.740 --> 00:54:08.520 You know, children die by the age of five. 1058 00:54:09.880 --> 00:54:12.180 I think that's an interesting model. 1059 00:54:12.640 --> 00:54:13.260 Yeah. 1060 00:54:16.360 --> 00:54:17.620 I'm not quite sure. 1061 00:54:19.300 --> 00:54:19.920 Right. 1062 00:54:21.040 --> 00:54:22.540 Just, you mentioned before 1063 00:54:22.540 --> 00:54:25.240 how the cracking of the human genome 1064 00:54:25.240 --> 00:54:28.300 was very much a coordinated effort. 1065 00:54:28.840 --> 00:54:31.620 Is the same sort of coordination occurring 1066 00:54:31.620 --> 00:54:34.860 for, you know, the plethora of cancers 1067 00:54:34.860 --> 00:54:35.540 that are out there 1068 00:54:35.540 --> 00:54:38.580 or is it very much small groups, 1069 00:54:38.780 --> 00:54:41.260 doing their own thing to tackle it? 1070 00:54:41.640 --> 00:54:42.240 Yes. 1071 00:54:42.320 --> 00:54:45.480 So this project called the Cancer Genome Atlas 1072 00:54:45.480 --> 00:54:48.140 is very much a collaborative project. 1073 00:54:48.640 --> 00:54:54.120 So, cancer researchers all over the world 1074 00:54:54.120 --> 00:54:58.540 are getting samples of tumour tissue. 1075 00:54:58.840 --> 00:55:00.340 They're reading the genome 1076 00:55:00.340 --> 00:55:03.620 and then they're sharing what's called the bioinformatics, 1077 00:55:03.880 --> 00:55:05.840 trying to analyse, OK, you know, 1078 00:55:05.840 --> 00:55:07.940 there's thousands and thousands and thousands 1079 00:55:07.940 --> 00:55:10.560 of genes to sort through here. 1080 00:55:10.920 --> 00:55:13.940 What do we think are the driver mutations 1081 00:55:13.940 --> 00:55:15.820 as opposed to the passengers? 1082 00:55:16.320 --> 00:55:17.900 So that's an interesting concept 1083 00:55:17.900 --> 00:55:21.260 because one of the first things that happens in cancer 1084 00:55:21.260 --> 00:55:24.920 is it starts multiplying in a very reckless way 1085 00:55:24.920 --> 00:55:27.680 and starts accruing all sorts of damage. 1086 00:55:28.200 --> 00:55:33.160 And so it's kind of like evolution in overdrive. 1087 00:55:33.160 --> 00:55:35.600 All these new mutations are then available 1088 00:55:35.600 --> 00:55:37.840 for selection to say, 1089 00:55:37.840 --> 00:55:40.680 OK, wow, this is going to help the cancer cell 1090 00:55:41.260 --> 00:55:43.740 grow in a different part of the body. 1091 00:55:44.220 --> 00:55:49.700 So when you look at a cancer cell or a tumour, 1092 00:55:49.720 --> 00:55:52.520 it's just full of DNA mutations. 1093 00:55:53.080 --> 00:55:55.120 And then you have to sort of figure out, 1094 00:55:55.180 --> 00:55:58.180 well, which of those mutations are just mistakes 1095 00:55:58.180 --> 00:56:02.080 and which of them are actually giving that cancer cell 1096 00:56:02.080 --> 00:56:04.200 an advantage, a Darwinian advantage? 1097 00:56:04.660 --> 00:56:06.900 So it's by this collaborative approach 1098 00:56:06.900 --> 00:56:09.660 where they look through all this data 1099 00:56:09.660 --> 00:56:12.040 from thousands and thousands of cancer samples 1100 00:56:12.040 --> 00:56:14.400 that they try to tease that out and say, 1101 00:56:14.540 --> 00:56:17.120 ah, these are the driver mutations. 1102 00:56:17.220 --> 00:56:19.220 We see these over and over again. 1103 00:56:19.280 --> 00:56:20.560 They're statistically significant. 1104 00:56:20.720 --> 00:56:22.960 These ones are probably just passengers. 1105 00:56:23.040 --> 00:56:24.880 They're just junk that's coming along. 1106 00:56:25.840 --> 00:56:27.860 This is a little bit off topic, 1107 00:56:28.680 --> 00:56:31.880 but do you know the state of US patent law 1108 00:56:31.880 --> 00:56:36.880 with regard to genes in non-human organs, 1109 00:56:36.900 --> 00:56:39.140 so plants and other animals? 1110 00:56:41.120 --> 00:56:46.100 I think there would be lots and lots of patents 1111 00:56:46.100 --> 00:56:48.360 that have already been granted. 1112 00:56:48.420 --> 00:56:52.000 We went through a huge phase of granting patents, 1113 00:56:52.360 --> 00:56:55.360 and what we might see now going forward 1114 00:56:55.360 --> 00:56:57.520 is the testing of those patents. 1115 00:56:57.780 --> 00:57:00.500 But yes, there are certainly a lot... 1116 00:57:00.500 --> 00:57:04.380 And it causes a big problem when it comes to biotechnology, 1117 00:57:04.400 --> 00:57:06.880 because when you want to do some genetic testing, 1118 00:57:06.900 --> 00:57:07.460 genetic engineering, 1119 00:57:07.780 --> 00:57:09.940 you have to really find your way 1120 00:57:09.940 --> 00:57:11.620 through this thicket of patents. 1121 00:57:12.060 --> 00:57:14.500 So yes, it is a problem, definitely, 1122 00:57:15.200 --> 00:57:18.660 and one that will be interesting to look at going forward 1123 00:57:18.660 --> 00:57:20.280 given the Supreme Court decision. 1124 00:57:20.760 --> 00:57:21.420 All right. 1125 00:57:21.480 --> 00:57:24.040 I think it's time we ought to wind up. 1126 00:57:24.300 --> 00:57:26.940 So I'd like to thank you all as an audience 1127 00:57:26.940 --> 00:57:29.480 for being very attentive and interested 1128 00:57:29.480 --> 00:57:30.600 and some good questions, 1129 00:57:30.780 --> 00:57:32.560 and particularly like to thank Elizabeth 1130 00:57:32.560 --> 00:57:34.520 for steering us through this maze, 1131 00:57:35.580 --> 00:57:37.820 explaining where we're at at the moment 1132 00:57:37.820 --> 00:57:40.220 and some models of where we might be going 1133 00:57:40.220 --> 00:57:41.780 in the very near future. 1134 00:57:41.960 --> 00:57:44.060 So if you could join with me to thank Elizabeth 1135 00:57:44.060 --> 00:57:45.680 very much for this talk. 1136 00:57:45.720 --> 00:57:45.980 Thank you. 1137 00:57:46.760 --> 00:57:47.300 APPLAUSE 1138 00:57:52.400 --> 00:57:56.640 This session of the 2013 Adelaide Festival of Ideas 1139 00:57:56.640 --> 00:57:58.700 was recorded by Radio Adelaide. 1140 00:57:58.780 --> 00:58:00.720 Through the support of the Bar Smith Library, 1141 00:58:01.080 --> 00:58:02.300 University of Adelaide, 1142 00:58:02.420 --> 00:58:04.320 the University of South Australia Library, 1143 00:58:04.520 --> 00:58:06.300 and Flinders University Library.