1 00:00:14,240 --> 00:00:16,959 Speaker 1: We're here to celebrate the completion of the first survey 2 00:00:17,480 --> 00:00:20,959 Speaker 1: of the entire human genome. Without a doubt, this is 3 00:00:21,000 --> 00:00:25,959 Speaker 1: the most important, most wondrous map ever produced by human kind. 4 00:00:28,480 --> 00:00:30,600 Speaker 1: The moment we are here to witness was brought about 5 00:00:31,280 --> 00:00:34,160 Speaker 1: brilliant and painstaking work of scientists all over the world, 6 00:00:34,159 --> 00:00:38,680 Speaker 1: including It was June two thousand. President Bill Clinton was 7 00:00:38,680 --> 00:00:42,199 Speaker 1: in the crowded White House East Room announcing a momentous achievement. 8 00:00:42,720 --> 00:00:46,199 Speaker 1: Government scientist had decoded nearly all three billion letters of 9 00:00:46,200 --> 00:00:50,520 Speaker 1: the human genetic blueprint. The excitement and the hype was intense. 10 00:00:51,200 --> 00:00:54,440 Speaker 1: President Clinton painted a tantalizing picture of the opening of 11 00:00:54,440 --> 00:00:58,600 Speaker 1: a new scientific frontier. With this profound new knowledge, human 12 00:00:58,680 --> 00:01:01,160 Speaker 1: kind is on the verge of gaining immense new power 13 00:01:01,240 --> 00:01:05,360 Speaker 1: to heal. Genome science will have a real impact on 14 00:01:05,520 --> 00:01:09,120 Speaker 1: all our lives, and even more on the lives of 15 00:01:09,160 --> 00:01:14,399 Speaker 1: our children. It will revolutionize the diagnosis, prevention, and treatment 16 00:01:14,400 --> 00:01:18,080 Speaker 1: of most, if not all, human diseases. In coming years, 17 00:01:18,120 --> 00:01:22,720 Speaker 1: doctors increasingly will be able to cure diseases like Alzheimer's, Parkinson's, diabetes, 18 00:01:23,080 --> 00:01:30,640 Speaker 1: and cancer by attacking their genetic roots. It didn't work 19 00:01:30,680 --> 00:01:35,480 Speaker 1: out that way at least not exactly. Welcome to Prognosis. 20 00:01:35,840 --> 00:01:41,760 Speaker 1: I'm your host, Michelle fay Cortes. This week, we're going 21 00:01:41,800 --> 00:01:44,520 Speaker 1: to tell you what happened after the press conference and 22 00:01:44,560 --> 00:01:47,680 Speaker 1: how one of the greatest undertakings in medical history, the 23 00:01:47,720 --> 00:01:51,000 Speaker 1: decoding of the human genome, was just the start of 24 00:01:51,040 --> 00:01:55,760 Speaker 1: an exhilarating, frustrating journey that's still far from over. Here's 25 00:01:55,760 --> 00:02:13,040 Speaker 1: Bloomberg's Bob Langrath with the story. Sitting next to Clinton 26 00:02:13,120 --> 00:02:16,720 Speaker 1: at the White House was Francis Collins. Cons is a geneticist, 27 00:02:16,840 --> 00:02:18,799 Speaker 1: and he led the international team that worked on the 28 00:02:18,840 --> 00:02:22,040 Speaker 1: genome project. Now he runs the National Institutes of Health. 29 00:02:22,880 --> 00:02:25,560 Speaker 1: I was both excited about the way in which the 30 00:02:25,600 --> 00:02:27,120 Speaker 1: world was going to find out that we had a 31 00:02:27,200 --> 00:02:30,560 Speaker 1: draft of the human genome sequence, the instruction book for 32 00:02:30,639 --> 00:02:33,880 Speaker 1: human biology. But I had also just spoken at the 33 00:02:33,919 --> 00:02:37,080 Speaker 1: funeral of my sister in law two days before, who 34 00:02:37,160 --> 00:02:40,800 Speaker 1: died from cancer and for whom this particular advance hadn't 35 00:02:40,800 --> 00:02:43,520 Speaker 1: come along soon enough. So I sort of put the 36 00:02:43,520 --> 00:02:47,000 Speaker 1: whole thing into focus of what we had and how 37 00:02:47,080 --> 00:02:49,720 Speaker 1: far we still needed to go for this to actually 38 00:02:49,760 --> 00:02:55,440 Speaker 1: benefit people who are waiting for answers. Actually the genome 39 00:02:55,440 --> 00:02:58,960 Speaker 1: wasn't done. There was only a first draft. The unveiling 40 00:02:59,080 --> 00:03:01,520 Speaker 1: was pushed out quickly, in part because the government was 41 00:03:01,600 --> 00:03:04,640 Speaker 1: raising a private group at the press conference, the teams 42 00:03:04,639 --> 00:03:08,160 Speaker 1: that only fully scanned about the genome. It would be 43 00:03:08,280 --> 00:03:11,640 Speaker 1: three years before the final version was published, and even 44 00:03:11,680 --> 00:03:14,120 Speaker 1: with the map, finding the causes of diseases in the 45 00:03:14,160 --> 00:03:18,200 Speaker 1: genetic code was elusive. Instead of a few key genes 46 00:03:18,280 --> 00:03:23,040 Speaker 1: driving common ailments like heart disease or diabetes, scientists found dozens, 47 00:03:23,280 --> 00:03:28,480 Speaker 1: if not hundreds. Human common disease is really complicated, more 48 00:03:28,520 --> 00:03:33,639 Speaker 1: complicated than we thought it was going to be less 49 00:03:33,639 --> 00:03:36,880 Speaker 1: than a decade ago. Despite the flood of new genome data, 50 00:03:37,160 --> 00:03:39,800 Speaker 1: there was a sense that drugs were getting harder to discover. 51 00:03:40,560 --> 00:03:42,920 Speaker 1: A two thousand and ten New York Times article called 52 00:03:42,920 --> 00:03:45,760 Speaker 1: the goal of finding the genetic roots of disease elusive. 53 00:03:46,320 --> 00:03:50,040 Speaker 1: It said that, quote geneticists are almost back to square 54 00:03:50,080 --> 00:03:52,440 Speaker 1: one and knowing where to look for the roots of 55 00:03:52,480 --> 00:03:58,400 Speaker 1: common disease unquote, but behind the scenes, something important was happening. 56 00:03:59,680 --> 00:04:02,360 Speaker 1: It took thirteen years and costs three billion dollars to 57 00:04:02,400 --> 00:04:06,160 Speaker 1: decode the first genome, and fo million dollars of that 58 00:04:06,320 --> 00:04:09,680 Speaker 1: went just to the sequencing itself. According to Dr Collins, 59 00:04:10,960 --> 00:04:13,760 Speaker 1: the sequencing machines that did most of the work for 60 00:04:13,840 --> 00:04:17,200 Speaker 1: sequencing that first human genome or the size of phone booths, 61 00:04:17,680 --> 00:04:20,479 Speaker 1: and it took a warehouse full of them to have 62 00:04:20,560 --> 00:04:23,559 Speaker 1: the kind of throughtput you needed to achieve this. DNA 63 00:04:23,680 --> 00:04:28,119 Speaker 1: sequencing needed to get faster, cheaper, and smaller. It needed 64 00:04:28,200 --> 00:04:32,240 Speaker 1: a revolution. If you look over the history of science, 65 00:04:32,920 --> 00:04:37,000 Speaker 1: the thing that has been profoundly game changing in a 66 00:04:37,080 --> 00:04:41,599 Speaker 1: scientific area is major technical innovations. You know, whether it 67 00:04:41,720 --> 00:04:45,840 Speaker 1: was inventing the telescope, what it did to astronomy, inventing 68 00:04:45,839 --> 00:04:49,800 Speaker 1: a microscope, what it did for microbiology and cell biology, 69 00:04:50,160 --> 00:04:52,120 Speaker 1: and look at that first cat scan, what it did 70 00:04:52,120 --> 00:04:55,680 Speaker 1: for radiology. That's Eric Greene, who is now director of 71 00:04:55,680 --> 00:04:59,279 Speaker 1: the National Human Genome Research Institute. He was an early 72 00:04:59,320 --> 00:05:02,160 Speaker 1: genome research or at the ni H. I think we 73 00:05:02,240 --> 00:05:06,120 Speaker 1: recognize that the technologies that were used for sequence in 74 00:05:06,120 --> 00:05:09,400 Speaker 1: that first human genome were good enough, but we needed 75 00:05:09,440 --> 00:05:12,359 Speaker 1: something far better. The trick was to take billions of 76 00:05:12,440 --> 00:05:15,280 Speaker 1: letters in a person's DNA and process them all at 77 00:05:15,279 --> 00:05:18,200 Speaker 1: the same time, like a computer circuit with billions of 78 00:05:18,200 --> 00:05:22,480 Speaker 1: transistors all firing at once. As newer and faster machines 79 00:05:22,520 --> 00:05:26,560 Speaker 1: were introduced, costs sank rapidly. In two thousand and five, 80 00:05:26,680 --> 00:05:29,000 Speaker 1: the cost of scanning a human genome ran to about 81 00:05:29,040 --> 00:05:33,320 Speaker 1: ten million dollars. By two fifteen, raw scanning costs plummeted 82 00:05:33,440 --> 00:05:37,039 Speaker 1: to below dollars. And in two thousand three, did I 83 00:05:37,040 --> 00:05:39,720 Speaker 1: believe it was going to happen this quickly? Absolutely not. 84 00:05:39,880 --> 00:05:42,080 Speaker 1: I'm sure any of us would have gotten it wrong, 85 00:05:42,279 --> 00:05:44,719 Speaker 1: probably by toothfold. We probably would have said it would 86 00:05:44,760 --> 00:05:46,840 Speaker 1: have taken, you know, thirty years to get down to 87 00:05:46,880 --> 00:05:50,719 Speaker 1: a thousand dollar human genome sequence. Room fulls of machines 88 00:05:50,800 --> 00:05:54,400 Speaker 1: were no longer needed. Dr Collins says, now on the 89 00:05:54,440 --> 00:05:57,200 Speaker 1: sequencing machines sit on the desktop, or in the most 90 00:05:57,240 --> 00:06:00,760 Speaker 1: dramatic example, they're about the size of a cell phone 91 00:06:01,080 --> 00:06:10,040 Speaker 1: that attaches directly to your laptop. That's when DNA sequencing 92 00:06:10,200 --> 00:06:13,960 Speaker 1: went from being a research tool and became medicine. In 93 00:06:14,040 --> 00:06:17,080 Speaker 1: two thousand and nine, doctors in Wisconsin were treating four 94 00:06:17,120 --> 00:06:20,919 Speaker 1: year old Nicholas Voker for a mysterious disease that produced 95 00:06:20,920 --> 00:06:25,960 Speaker 1: holes and his intestine. In desperation, his doctor's convinced genesis 96 00:06:26,040 --> 00:06:29,320 Speaker 1: at the Medical College of Wisconsin to sequence all his genes. 97 00:06:29,920 --> 00:06:32,920 Speaker 1: Here's next doctor reaching out to the geneticist with an 98 00:06:33,080 --> 00:06:37,680 Speaker 1: unprecedented request. Dear Howard, I hope you are well. I'm 99 00:06:37,720 --> 00:06:40,240 Speaker 1: writing to get your thoughts on a patient of mine 100 00:06:40,320 --> 00:06:44,320 Speaker 1: that might benefit from a high throughput sequencing of his genome. 101 00:06:45,279 --> 00:06:49,039 Speaker 1: This is a unique situation. This patients is very ill 102 00:06:49,480 --> 00:06:53,920 Speaker 1: and has been in the hospital since January. It worked. 103 00:06:54,720 --> 00:06:58,000 Speaker 1: They found an unexpected mutation and it pointed to a treatment, 104 00:06:58,520 --> 00:07:02,719 Speaker 1: a bone marrow transplant. The case exploded into the headlines 105 00:07:02,760 --> 00:07:05,960 Speaker 1: with the Milwaukee, Wisconsin Journal Sentinel wrote a Pulitzer Prize 106 00:07:06,000 --> 00:07:10,000 Speaker 1: winning series about the success. Around the same time, researcher 107 00:07:10,040 --> 00:07:13,400 Speaker 1: Stephen Kingsmore helped perform a highly detailed genome of a 108 00:07:13,480 --> 00:07:18,160 Speaker 1: Korean person. The medical potential was becoming clearer. We kind 109 00:07:18,200 --> 00:07:21,280 Speaker 1: of as a team had a Eureka moment when we said, 110 00:07:21,320 --> 00:07:24,160 Speaker 1: ah ha, there's a huge amount of information in here 111 00:07:24,200 --> 00:07:28,200 Speaker 1: that's of practical usefulness to people, and this really changed 112 00:07:28,240 --> 00:07:31,720 Speaker 1: the trajectory of my career. Maybe want to go from 113 00:07:31,720 --> 00:07:37,080 Speaker 1: a basic research institute back into a hospital environment where 114 00:07:37,080 --> 00:07:39,640 Speaker 1: we could start to apply this and understand what it 115 00:07:39,720 --> 00:07:43,080 Speaker 1: might mean for the future of medicine. By two thousan twelve, 116 00:07:43,240 --> 00:07:46,720 Speaker 1: Dr Kingsmore was testing out a new ultra fast sequencing 117 00:07:46,720 --> 00:07:51,160 Speaker 1: machine on sick babies. We started to use it in 118 00:07:51,280 --> 00:07:55,600 Speaker 1: our neonatal intensive care unit, where decisions had to be 119 00:07:55,720 --> 00:07:58,760 Speaker 1: made within minutes or ours. There was no time to 120 00:07:58,960 --> 00:08:02,920 Speaker 1: lose in making it diagnosis, and so we published a 121 00:08:03,000 --> 00:08:07,880 Speaker 1: paper in October twelve saying that we could decode a 122 00:08:07,960 --> 00:08:11,800 Speaker 1: baby's genome in forty eight hours and return those results 123 00:08:11,840 --> 00:08:15,080 Speaker 1: back to the ne anatologists and showed that it would 124 00:08:15,200 --> 00:08:20,120 Speaker 1: change the management. That was truly a breakthrough. Dr Kingsmore 125 00:08:20,200 --> 00:08:22,680 Speaker 1: is now at the forefront of using genome testing to 126 00:08:22,840 --> 00:08:26,400 Speaker 1: diagnose and treat infants with unknown genetic diseases at the 127 00:08:26,480 --> 00:08:30,000 Speaker 1: RADI Children's Institute for Genomic Medicine in San Diego. It 128 00:08:30,040 --> 00:08:33,400 Speaker 1: turns out to be an ideal application for genome sequencing. 129 00:08:33,800 --> 00:08:36,160 Speaker 1: Tens of thousands of babies are born each year with 130 00:08:36,280 --> 00:08:40,960 Speaker 1: unknown genetic diseases. There are ten thousand genetic diseases, and 131 00:08:41,000 --> 00:08:43,679 Speaker 1: no physician on planet Earth has ever seen them all, 132 00:08:44,000 --> 00:08:48,240 Speaker 1: so picking which of those to test for is incredibly difficult. 133 00:08:48,880 --> 00:08:52,760 Speaker 1: The second thing is that in newborns, the genetic diseases 134 00:08:52,960 --> 00:08:56,520 Speaker 1: really don't look like their textbook description. When you put 135 00:08:56,520 --> 00:08:59,920 Speaker 1: those two reasons together, it means that without the ability 136 00:09:00,040 --> 00:09:04,040 Speaker 1: to just survey the entire genome and examine all ten 137 00:09:04,160 --> 00:09:08,760 Speaker 1: thows and genetic diseases at once, the likelihood of a 138 00:09:08,800 --> 00:09:14,040 Speaker 1: physician making the correct diagnosis is almost zero. His lab 139 00:09:14,120 --> 00:09:16,200 Speaker 1: has three of the top of the line geno i'm 140 00:09:16,200 --> 00:09:19,600 Speaker 1: scanning machines from a company called a Lumina. The machines 141 00:09:19,600 --> 00:09:23,479 Speaker 1: are roughly the size of a washing machine. In urgent situations, 142 00:09:23,520 --> 00:09:26,400 Speaker 1: his team can decode a baby genome in about two days. 143 00:09:27,240 --> 00:09:33,400 Speaker 1: We receive blood samples and medical records from about fifteen 144 00:09:33,440 --> 00:09:38,080 Speaker 1: children's hospitals all around North America, and so they will 145 00:09:38,120 --> 00:09:40,280 Speaker 1: contact us and let us know that they have a 146 00:09:40,360 --> 00:09:43,640 Speaker 1: kid who they believe they might need a genome sequence on, 147 00:09:44,200 --> 00:09:47,200 Speaker 1: and the following morning the sample will arrive. Will then 148 00:09:47,280 --> 00:09:50,720 Speaker 1: put that into our batch for the day, and our 149 00:09:50,760 --> 00:09:56,559 Speaker 1: goal is to deliver a diagnostic result as quickly as 150 00:09:56,600 --> 00:10:01,160 Speaker 1: as humanly possible back to that physician, with a goal 151 00:10:01,200 --> 00:10:05,520 Speaker 1: obviously of giving treatment guidance that will either save a 152 00:10:05,600 --> 00:10:11,280 Speaker 1: child's life or prevent complications of that disease. In three 153 00:10:11,360 --> 00:10:13,959 Speaker 1: years at Rady, Dr Kingsmore's team is the code of 154 00:10:14,000 --> 00:10:16,920 Speaker 1: the genomes of hundreds of sick babies, and it is 155 00:10:17,000 --> 00:10:20,800 Speaker 1: making a difference. So one and two or one in three, 156 00:10:21,120 --> 00:10:24,360 Speaker 1: we will make a diagnosis. A figure that's completely consistent 157 00:10:24,440 --> 00:10:29,120 Speaker 1: is that of those diagnoses will resultant changes in how 158 00:10:29,160 --> 00:10:33,440 Speaker 1: the baby is managed in the intensive care unit. And 159 00:10:33,480 --> 00:10:36,320 Speaker 1: then about one and four has a change in outcome. 160 00:10:36,960 --> 00:10:41,280 Speaker 1: Sometimes it has life saving There are some extraordinary saves. 161 00:10:41,360 --> 00:10:45,720 Speaker 1: There are some children who undoubtedly would die, and we 162 00:10:45,800 --> 00:10:48,800 Speaker 1: make a phone call with a diagnosis. There's a treatment 163 00:10:48,880 --> 00:10:59,280 Speaker 1: that's given promptly, and the child does well, faster, cheaper. 164 00:10:59,400 --> 00:11:02,959 Speaker 1: DNA toton was beginning to revolutionize medical care by two 165 00:11:04,120 --> 00:11:09,200 Speaker 1: Then in two two things happened, one in Washington and 166 00:11:09,240 --> 00:11:12,480 Speaker 1: the other in Hollywood. The Supreme Court said that jeans 167 00:11:12,600 --> 00:11:16,559 Speaker 1: couldn't be someone's intellectual property, and one of the world's 168 00:11:16,600 --> 00:11:19,320 Speaker 1: biggest movie stars made a start medical choice based on 169 00:11:19,400 --> 00:11:25,199 Speaker 1: her DNA. A few years ago, a blood test revealed 170 00:11:25,200 --> 00:11:27,959 Speaker 1: that Angeline had carried a mutation of the b r 171 00:11:28,040 --> 00:11:31,880 Speaker 1: c A one gene, giving her an estimated eighty seven 172 00:11:31,960 --> 00:11:36,920 Speaker 1: percent risk of breast cancer of fifty risk of ovarian cancer. 173 00:11:37,400 --> 00:11:43,320 Speaker 1: So in she had both brushed removed and underwent reconstructive surgery, 174 00:11:43,800 --> 00:11:46,480 Speaker 1: emerging as a beacon of hope for women when she 175 00:11:46,640 --> 00:11:49,760 Speaker 1: told the world, I feel wonderful. I'm very, very grateful. 176 00:11:56,600 --> 00:11:59,560 Speaker 1: Ellen Mattlof at the time was a cancer genetic counselor 177 00:11:59,600 --> 00:12:03,320 Speaker 1: at Yeah University. She helped patients and their families understand 178 00:12:03,360 --> 00:12:06,600 Speaker 1: their risk, what are the correct tests, and interpret complex 179 00:12:06,679 --> 00:12:11,240 Speaker 1: DNA results. When I was the director of the cancer 180 00:12:11,280 --> 00:12:15,600 Speaker 1: Genetic Counseling program at Yale, I saw several things shifting, 181 00:12:15,760 --> 00:12:20,720 Speaker 1: and they were seismic shifts. First, Angelina Jolie came out 182 00:12:20,800 --> 00:12:23,640 Speaker 1: with her New York Times editorial that she was a 183 00:12:23,720 --> 00:12:27,800 Speaker 1: b r C A one carrier, and overnight our referrals 184 00:12:27,920 --> 00:12:33,200 Speaker 1: increased by fort and they never returned to baseline. There 185 00:12:33,280 --> 00:12:37,080 Speaker 1: was a huge change. Then a few weeks later, the 186 00:12:37,120 --> 00:12:40,880 Speaker 1: Supreme Court issued its ruling that meant companies, including the 187 00:12:40,880 --> 00:12:43,720 Speaker 1: one that had a monopoly in the test Angelina Jolie used, 188 00:12:43,840 --> 00:12:47,480 Speaker 1: couldn't own the patents on Jeanes Here's Dr Collins again. 189 00:12:48,600 --> 00:12:51,880 Speaker 1: It was a wonderful day, indeed, when the Supreme Court, 190 00:12:52,120 --> 00:12:55,720 Speaker 1: in a nine to nothing decision, came out with their 191 00:12:56,080 --> 00:13:00,480 Speaker 1: conclusion that gene patenting ought not to be a ouabol 192 00:13:00,559 --> 00:13:02,840 Speaker 1: that it didn't fit with the original goals of the 193 00:13:02,880 --> 00:13:06,960 Speaker 1: patent system, and I think that has opened up diagnostics 194 00:13:07,200 --> 00:13:10,120 Speaker 1: in a much broader way, which has been a very 195 00:13:10,160 --> 00:13:13,760 Speaker 1: good thing for the whole field and has accelerated the 196 00:13:13,800 --> 00:13:16,960 Speaker 1: possibilities of many of us having that kind of information 197 00:13:17,200 --> 00:13:20,440 Speaker 1: now or in the future. For years, one company had 198 00:13:20,440 --> 00:13:22,240 Speaker 1: the patent on b r C A one and b 199 00:13:22,360 --> 00:13:25,439 Speaker 1: r C A two, the most common causes of hereditary 200 00:13:25,480 --> 00:13:29,079 Speaker 1: breast cancer. That meant that hospitals and companies not holding 201 00:13:29,080 --> 00:13:33,560 Speaker 1: the patent couldn't combine them into broader tests. Gene patenting 202 00:13:34,559 --> 00:13:38,200 Speaker 1: was a serious threat on the view of many of 203 00:13:38,320 --> 00:13:43,239 Speaker 1: us to progress in this field, and yet it continued 204 00:13:43,320 --> 00:13:46,280 Speaker 1: for quite a few years after that. At the time 205 00:13:46,320 --> 00:13:49,800 Speaker 1: of the Supreme Court ruling, BRCA testing costs as much 206 00:13:49,800 --> 00:13:53,199 Speaker 1: as four thousand dollars. Within days of the decision, new 207 00:13:53,240 --> 00:13:55,680 Speaker 1: companies that have been barred from the market started offering 208 00:13:55,760 --> 00:14:00,280 Speaker 1: their own tests. Cost plummeted. Ellen matt Loff, who now 209 00:14:00,320 --> 00:14:02,760 Speaker 1: runs a startup called My Gene Council, was a plaint 210 00:14:02,760 --> 00:14:05,719 Speaker 1: different the Supreme Court case. She saw the impact on 211 00:14:05,800 --> 00:14:10,320 Speaker 1: patients firsthand. And today we have some testing companies that 212 00:14:10,400 --> 00:14:12,600 Speaker 1: have offered b r C A one and two testing 213 00:14:12,679 --> 00:14:16,559 Speaker 1: from time to time for a hundred or two hundred dollars, 214 00:14:16,559 --> 00:14:20,600 Speaker 1: so it's changed dramatically. Of course, cost isn't the only 215 00:14:20,640 --> 00:14:24,520 Speaker 1: problem that geneticists were grappling with, and the easy diagnoses 216 00:14:24,560 --> 00:14:27,760 Speaker 1: and freely flowing data envisioned years ago haven't quite come 217 00:14:27,760 --> 00:14:31,160 Speaker 1: to pass. I can remember fifteen years ago when the 218 00:14:31,200 --> 00:14:34,720 Speaker 1: genome was sequenced that everyone was saying that first of all, 219 00:14:34,760 --> 00:14:37,480 Speaker 1: you would carry around your genome like a flash drive 220 00:14:38,160 --> 00:14:39,960 Speaker 1: and it would be a piece of cake. You just 221 00:14:40,000 --> 00:14:42,280 Speaker 1: bring it to your doctor's office, plug it in, and 222 00:14:42,320 --> 00:14:46,360 Speaker 1: that every doctor would be so educated on genomics that 223 00:14:46,480 --> 00:14:49,600 Speaker 1: they would be able to interpret it. None of that 224 00:14:49,760 --> 00:14:53,920 Speaker 1: has been as simple as it sounded. But where the 225 00:14:53,960 --> 00:14:59,880 Speaker 1: failure has come is helping consumers and healthcare providers under 226 00:15:00,080 --> 00:15:04,400 Speaker 1: stand and use the data. Also, as genetic tests become 227 00:15:04,440 --> 00:15:08,240 Speaker 1: more common, the risk of misinterpretation by doctors untrained in 228 00:15:08,280 --> 00:15:11,640 Speaker 1: the complex world of genetics is growing. This is especially 229 00:15:11,640 --> 00:15:14,040 Speaker 1: true in the high stakes area of cancer. We're ordering 230 00:15:14,040 --> 00:15:16,480 Speaker 1: the wrong tests or misinterpreting the result can lead to 231 00:15:16,520 --> 00:15:20,000 Speaker 1: a fatal illness or unnecessary surgery. It's a problem that 232 00:15:20,080 --> 00:15:24,240 Speaker 1: some say is getting worse, we're finding that genetic test 233 00:15:24,320 --> 00:15:28,160 Speaker 1: results are being misinterpreted more often now than ever before, 234 00:15:29,080 --> 00:15:33,320 Speaker 1: and the reason for that is that fewer patients are 235 00:15:33,400 --> 00:15:37,240 Speaker 1: seeing certified genetic counselors to order their tests and to 236 00:15:37,360 --> 00:15:42,040 Speaker 1: interpret them after. And also the tests have grown in complexity, 237 00:15:42,560 --> 00:15:53,120 Speaker 1: so it's easier to misinterpret them now. In terms of drugs, 238 00:15:53,200 --> 00:15:55,640 Speaker 1: Dr Collins says cancer is one area that seen a 239 00:15:55,720 --> 00:16:00,440 Speaker 1: direct impact from the Genome project. Cancer is fundamentally genetic disease, 240 00:16:00,680 --> 00:16:03,800 Speaker 1: and understanding gene abnormalities and patient tumors has led to 241 00:16:03,920 --> 00:16:07,120 Speaker 1: powerful new treatments for leukemia, certain types of lung cancer, 242 00:16:07,120 --> 00:16:10,320 Speaker 1: and breast cancer. If you want to take an area 243 00:16:10,520 --> 00:16:14,440 Speaker 1: we're having access to genome sequence has been revolutionary, it's cancer. 244 00:16:15,200 --> 00:16:17,760 Speaker 1: If I had cancer today, or if anybody I know 245 00:16:17,840 --> 00:16:21,680 Speaker 1: had cancer today, I would want their tumor to undergo 246 00:16:21,720 --> 00:16:26,400 Speaker 1: a complete DNA sequencing in order to identify what mutations 247 00:16:26,480 --> 00:16:29,480 Speaker 1: have happened in that cancer to cause those good cells 248 00:16:29,520 --> 00:16:33,520 Speaker 1: to go bad. Increasingly, cancer centers are scanning patients DNA 249 00:16:33,640 --> 00:16:35,680 Speaker 1: to match them to the treatment most likely to work 250 00:16:35,720 --> 00:16:38,800 Speaker 1: for them, and biotech companies are working on developing a 251 00:16:38,920 --> 00:16:41,920 Speaker 1: liquid biopsy that which detect signs of cancer in the blood. 252 00:16:42,240 --> 00:16:44,280 Speaker 1: So far this year, there have been about a dozen 253 00:16:44,280 --> 00:16:47,840 Speaker 1: new cancer drugs approved by the FDA, and so the 254 00:16:47,960 --> 00:16:54,880 Speaker 1: list of targeted drug treatments for cancer is growing almost daily. Nevertheless, 255 00:16:55,320 --> 00:16:57,720 Speaker 1: many tumors have turned out to have a complicated array 256 00:16:57,720 --> 00:17:01,360 Speaker 1: of mutations and we don't always know how to arget them. 257 00:17:01,400 --> 00:17:03,280 Speaker 1: But there may be another reason why there aren't more 258 00:17:03,360 --> 00:17:07,480 Speaker 1: gene based drugs. Louise am All, who studies complex systems 259 00:17:07,520 --> 00:17:10,960 Speaker 1: at Northwestern University That's found that risk averse researchers have 260 00:17:11,040 --> 00:17:13,359 Speaker 1: been concentrating most of their attention on genes that have 261 00:17:13,400 --> 00:17:16,639 Speaker 1: been known for years. They are ignoring unknown genes, some 262 00:17:16,760 --> 00:17:19,960 Speaker 1: of which could lead to medical breakthroughs. One of the 263 00:17:20,080 --> 00:17:22,520 Speaker 1: numbers that I think is important is this idea that 264 00:17:22,720 --> 00:17:28,040 Speaker 1: five of the genes are accounting for about fifty of 265 00:17:28,160 --> 00:17:32,879 Speaker 1: the publications. Very little attention is really being given to 266 00:17:33,040 --> 00:17:36,879 Speaker 1: a very large fraction of the of the genes. In fact, 267 00:17:37,280 --> 00:17:39,879 Speaker 1: in the five years between twous and eleven and two fifteen, 268 00:17:39,960 --> 00:17:44,080 Speaker 1: Dr Amroll and as research partner Thomas Stutgart found only 269 00:17:44,080 --> 00:17:46,520 Speaker 1: a handful of new genes broke out from obscurity to 270 00:17:46,560 --> 00:17:51,040 Speaker 1: become objects of intensive scientific research. Everybody is becoming more 271 00:17:51,080 --> 00:17:54,639 Speaker 1: and more conservative, which means that the way in which 272 00:17:54,720 --> 00:17:58,359 Speaker 1: we are exploring the known is less and less efficient. 273 00:17:58,640 --> 00:18:02,000 Speaker 1: But if we keep having at attitudes we are never 274 00:18:02,200 --> 00:18:04,840 Speaker 1: I mean, it's going to be you know, a new 275 00:18:04,920 --> 00:18:09,280 Speaker 1: gene understood per per year, and at that rate it 276 00:18:09,280 --> 00:18:13,119 Speaker 1: would only take about another fifteen thousand years to understand 277 00:18:13,160 --> 00:18:17,080 Speaker 1: every single gene in the human geno. One method that 278 00:18:17,119 --> 00:18:19,760 Speaker 1: has proven useful for finding new drugs has been looking 279 00:18:19,760 --> 00:18:24,000 Speaker 1: for people with certain genetic abnormalities, but instead of hurting them, 280 00:18:24,240 --> 00:18:27,960 Speaker 1: their mutations help and a robust constructor in Texas with 281 00:18:28,160 --> 00:18:31,600 Speaker 1: super low cholesterol had a rare mutation in a gene 282 00:18:31,680 --> 00:18:36,360 Speaker 1: called PCSK nine. That discovery has led to two powerful 283 00:18:36,400 --> 00:18:40,359 Speaker 1: new cholesterol lowering medications into US and fifteen here's Dr 284 00:18:40,400 --> 00:18:44,280 Speaker 1: Collins again finding individuals who are rare examples where they're 285 00:18:44,280 --> 00:18:47,679 Speaker 1: protected against disease. You could call them superhumans. Um is 286 00:18:48,400 --> 00:18:51,040 Speaker 1: very much part of what anybody who thinks about genetics 287 00:18:51,080 --> 00:18:53,399 Speaker 1: would hope to find, and that's what we found with 288 00:18:53,480 --> 00:18:57,320 Speaker 1: PCSK nine. It's one of those really amazing success stories 289 00:18:57,359 --> 00:19:00,800 Speaker 1: of the last decade. To help find more vision treatments, 290 00:19:00,880 --> 00:19:03,680 Speaker 1: the NAH set up a giant new research program that 291 00:19:03,720 --> 00:19:06,880 Speaker 1: will track the health information of one million American residents, 292 00:19:07,240 --> 00:19:10,600 Speaker 1: eventually sequencing the genomes of all of them. That all 293 00:19:10,640 --> 00:19:13,280 Speaker 1: of us project will cost one point five billion over 294 00:19:13,359 --> 00:19:17,480 Speaker 1: ten years. If we really want to understand how effectively 295 00:19:17,560 --> 00:19:22,320 Speaker 1: to apply precision medicine to the average person in this country, 296 00:19:22,400 --> 00:19:24,880 Speaker 1: we need a very large pilot study to find out 297 00:19:24,960 --> 00:19:28,560 Speaker 1: how that works. This will be the largest, most powerful 298 00:19:28,640 --> 00:19:32,440 Speaker 1: research database ever contemplated in this country, and it will 299 00:19:32,440 --> 00:19:36,520 Speaker 1: teach us whether such things as knowing your genome sequence 300 00:19:36,560 --> 00:19:43,600 Speaker 1: is going to make you healthier. So what's next? George Church, 301 00:19:44,040 --> 00:19:47,240 Speaker 1: the genetics professor at Harvard Medical School, thinks the state 302 00:19:47,320 --> 00:19:50,080 Speaker 1: of DNA testing and scanning it's like the Internet in 303 00:19:50,119 --> 00:19:55,439 Speaker 1: the early nineties. So I was using computer network type 304 00:19:55,440 --> 00:19:58,520 Speaker 1: of things around, which is about the time that the 305 00:19:58,560 --> 00:20:04,440 Speaker 1: Internet started, and it was pretty sleepy until around when 306 00:20:04,480 --> 00:20:08,000 Speaker 1: suddenly everybody saw that there was a web browser, and 307 00:20:08,119 --> 00:20:12,120 Speaker 1: then within a year there was millions of web pages. 308 00:20:12,440 --> 00:20:15,679 Speaker 1: From almost a standstill, we have all the infrastructure in 309 00:20:15,680 --> 00:20:19,440 Speaker 1: place to sequence millions of human genos possibly billions, with 310 00:20:19,480 --> 00:20:21,560 Speaker 1: a little effort, but people are not aware of it. 311 00:20:21,600 --> 00:20:24,240 Speaker 1: They don't realize that the killer apps are already some 312 00:20:24,320 --> 00:20:27,320 Speaker 1: of them are already there. In October, the Food and 313 00:20:27,359 --> 00:20:30,560 Speaker 1: Drug Administration approved the first direct to consumer tests to 314 00:20:30,600 --> 00:20:34,400 Speaker 1: spot genetic variations and how people's bodies interact with different medicines, 315 00:20:35,000 --> 00:20:37,359 Speaker 1: but warned that people shouldn't use it to make medical 316 00:20:37,400 --> 00:20:40,560 Speaker 1: decisions by themselves. But while most people don't need it, 317 00:20:40,640 --> 00:20:43,320 Speaker 1: the potential for greater use of genetic testing is enormous. 318 00:20:43,840 --> 00:20:47,240 Speaker 1: Here's Dr Collins again. We now know that probably two 319 00:20:47,359 --> 00:20:51,840 Speaker 1: or three percent of us are walking around with significant 320 00:20:52,000 --> 00:20:56,000 Speaker 1: DNA mistakes that would be actionable right now if we 321 00:20:56,119 --> 00:20:59,920 Speaker 1: knew about it that we have one of those misspelled 322 00:21:00,000 --> 00:21:02,960 Speaker 1: things that places us at risk maybe for heart disease 323 00:21:03,560 --> 00:21:08,560 Speaker 1: or cancer, or some clotting problem or some neurologic difficulty. 324 00:21:08,720 --> 00:21:11,560 Speaker 1: Two or three percent, well goodness six If they're three 325 00:21:11,960 --> 00:21:15,479 Speaker 1: million people just in this country, we're talking about somewhere 326 00:21:15,520 --> 00:21:18,840 Speaker 1: between six to nine million people right now that if 327 00:21:18,840 --> 00:21:21,960 Speaker 1: they had that information, their medical care would change for 328 00:21:22,119 --> 00:21:25,879 Speaker 1: their benefit. George Church thinks that genome scanning could directly 329 00:21:25,920 --> 00:21:28,600 Speaker 1: help at least one percent of people and more are 330 00:21:28,600 --> 00:21:31,600 Speaker 1: walking around with genetic variants and might put their children 331 00:21:31,640 --> 00:21:34,400 Speaker 1: at risk. But that would be my guess is ten 332 00:21:34,440 --> 00:21:38,120 Speaker 1: years from now, we could have everybody who has any 333 00:21:38,280 --> 00:21:43,679 Speaker 1: reasonable health care plan, maybe a billion people sequenced, and 334 00:21:43,720 --> 00:21:46,600 Speaker 1: then five of those that are at risk for having 335 00:21:46,880 --> 00:21:50,280 Speaker 1: children that have a severe genet disease will avoid that. 336 00:21:51,040 --> 00:21:53,320 Speaker 1: The key, he says, is getting people to do it. 337 00:21:53,520 --> 00:21:56,400 Speaker 1: I think it's analogous to seat belts, where the seat 338 00:21:56,400 --> 00:21:59,000 Speaker 1: belts were free, but people still didn't use them and 339 00:21:59,040 --> 00:22:02,080 Speaker 1: you had to had to have some public health strategy. 340 00:22:02,359 --> 00:22:05,960 Speaker 1: We've come a long way. Francis Collins's career shows how 341 00:22:06,040 --> 00:22:09,639 Speaker 1: much the technology has advanced. When he and other scientists 342 00:22:09,680 --> 00:22:12,040 Speaker 1: were trying to find the gene for cystic fibrosis in 343 00:22:12,080 --> 00:22:16,560 Speaker 1: the nineteen eighties, it was agonizingly slow going. It was 344 00:22:16,720 --> 00:22:21,280 Speaker 1: horrendously difficult. There was no genome project. There was very 345 00:22:21,320 --> 00:22:25,320 Speaker 1: little knowledge about anything about the DNA of the human 346 00:22:25,359 --> 00:22:28,600 Speaker 1: except little tiny islands that people had worked on. It 347 00:22:28,680 --> 00:22:32,560 Speaker 1: took years, but now, thanks to their groundwork, there finally 348 00:22:32,560 --> 00:22:37,600 Speaker 1: our treatments today. If you gave me DNA samples from 349 00:22:37,640 --> 00:22:41,280 Speaker 1: a few families with cystic fibrosis and a DNA sequencer, 350 00:22:41,760 --> 00:22:44,320 Speaker 1: a decent graduate student would have this answer in about 351 00:22:44,359 --> 00:22:48,600 Speaker 1: two days. That's the way it's happened. That's the that's 352 00:22:48,640 --> 00:22:52,320 Speaker 1: a great example of just what it has meant to 353 00:22:52,520 --> 00:22:55,919 Speaker 1: cross into this new territory where these technologies are so 354 00:22:56,000 --> 00:22:59,400 Speaker 1: powerful and so widely available. So if anybody tries to say, well, 355 00:22:59,440 --> 00:23:01,520 Speaker 1: you know, general Mix was sort of a fizzle that 356 00:23:01,560 --> 00:23:06,359 Speaker 1: didn't get us anywhere, boy, just look at what's now feasible. 357 00:23:12,800 --> 00:23:15,600 Speaker 1: And that's it for this week's prognosis. Thanks for listening. 358 00:23:16,119 --> 00:23:18,040 Speaker 1: Do you have a story about healthcare in the US 359 00:23:18,240 --> 00:23:20,440 Speaker 1: or around the world. We want to hear from you. 360 00:23:21,080 --> 00:23:24,000 Speaker 1: You can email me m Cortes at Bloomberg dot net 361 00:23:24,400 --> 00:23:27,359 Speaker 1: or find me on Twitter at the Cortes. If you 362 00:23:27,400 --> 00:23:29,560 Speaker 1: are a fan of this episode, please take a moment 363 00:23:29,560 --> 00:23:32,200 Speaker 1: to rate and review us. It helps new listeners find 364 00:23:32,240 --> 00:23:35,520 Speaker 1: the show. This episode was produced by Liz Smith. Our 365 00:23:35,520 --> 00:23:38,000 Speaker 1: story editor was Tim and Ette. Thanks also that Drew 366 00:23:38,080 --> 00:23:42,320 Speaker 1: Armstrong Francesco Levie is head of Bloomberg Podcasts. We'll see 367 00:23:42,320 --> 00:23:42,880 Speaker 1: you next week.