1 00:00:00,410 --> 00:00:03,327 (mysterious music) 2 00:00:06,220 --> 00:00:08,870 Currently, scientists around the world 3 00:00:08,870 --> 00:00:11,560 are working on unraveling the last secrets 4 00:00:11,560 --> 00:00:12,693 of our human body. 5 00:00:13,720 --> 00:00:17,990 To do this, they need expertise, super computers, 6 00:00:17,990 --> 00:00:20,253 and a large dose of good ideas. 7 00:00:24,320 --> 00:00:27,680 The proteome comprises the basic building blocks of life. 8 00:00:27,680 --> 00:00:31,333 Worldwide, researchers are uncovering its secrets. 9 00:00:49,270 --> 00:00:53,300 Almost every new therapy and diagnostic, for that matter, 10 00:00:53,300 --> 00:00:56,820 that we're inventing in my laboratory, 11 00:00:56,820 --> 00:00:58,523 ultimately deals with a proteome. 12 00:01:10,271 --> 00:01:12,470 So we have a gained a lot of progress 13 00:01:12,470 --> 00:01:14,093 in genomic research. 14 00:01:15,504 --> 00:01:17,220 But in the end it's still protein. 15 00:01:17,220 --> 00:01:19,160 So if you can measure protein, 16 00:01:19,160 --> 00:01:21,930 you understand what protein does, 17 00:01:21,930 --> 00:01:25,053 then you can understand disease. 18 00:01:33,130 --> 00:01:35,190 Protein is the next generation 19 00:01:35,190 --> 00:01:37,170 because it's not just what could happen, 20 00:01:37,170 --> 00:01:39,070 it's what is happening. 21 00:01:39,070 --> 00:01:41,640 And throughout medicine we've always looked at disease 22 00:01:41,640 --> 00:01:43,100 after it happened. 23 00:01:43,100 --> 00:01:45,530 We didn't ever get to see that process, 24 00:01:45,530 --> 00:01:48,360 and the ability now of looking at the human proteome, 25 00:01:48,360 --> 00:01:52,672 which is new, is giving us a new window, a new dimension 26 00:01:52,672 --> 00:01:55,250 on each of us that really is moving science forward 27 00:01:55,250 --> 00:01:56,763 at an amazing clip. 28 00:02:05,148 --> 00:02:07,230 Can I decode the proteome? 29 00:02:07,230 --> 00:02:08,460 Can it be done? 30 00:02:08,460 --> 00:02:09,400 Yes. 31 00:02:09,400 --> 00:02:11,280 Imagine a car or any machine 32 00:02:11,280 --> 00:02:13,650 with the same complexity as a car. 33 00:02:13,650 --> 00:02:15,820 Is it possible to take a motor apart 34 00:02:15,820 --> 00:02:18,570 in order to understand how it worked? 35 00:02:18,570 --> 00:02:20,480 I believe we'll be able to do that 36 00:02:20,480 --> 00:02:21,830 with the proteome. 37 00:02:21,830 --> 00:02:23,780 But I can't say how long it might take. 38 00:02:28,580 --> 00:02:30,710 In conference calls and crisis units, 39 00:02:30,710 --> 00:02:32,410 medical doctors and scientists 40 00:02:32,410 --> 00:02:35,500 discuss the current ways to best utilize the information 41 00:02:35,500 --> 00:02:37,000 that has already been gleaned. 42 00:02:44,080 --> 00:02:46,810 What has changed since researchers worldwide 43 00:02:46,810 --> 00:02:50,220 began to focus on proteins in the human body? 44 00:02:50,220 --> 00:02:52,250 Above all, this. 45 00:02:52,250 --> 00:02:54,860 Scientists in large clinics throughout the world 46 00:02:54,860 --> 00:02:56,610 like the Charite in Berlin 47 00:02:56,610 --> 00:02:58,910 are increasingly gaining detailed insight 48 00:02:58,910 --> 00:03:00,600 into what happens in the body 49 00:03:00,600 --> 00:03:03,490 between genes and illnesses. 50 00:03:03,490 --> 00:03:05,410 In terms of protein analysis, 51 00:03:05,410 --> 00:03:07,780 researchers have been making enormous progress 52 00:03:07,780 --> 00:03:09,480 in recent years. 53 00:03:09,480 --> 00:03:11,080 The more progress they make, 54 00:03:11,080 --> 00:03:13,340 the more targeted and effective they will be 55 00:03:13,340 --> 00:03:16,450 in diagnosing the major illnesses like Alzheimer's 56 00:03:16,450 --> 00:03:17,283 and cancer. 57 00:03:21,740 --> 00:03:24,800 The Department of Pediatrics at the Charite. 58 00:03:24,800 --> 00:03:26,963 The case of the three year old, Joanna. 59 00:03:28,000 --> 00:03:29,610 Early on she had been diagnosed 60 00:03:29,610 --> 00:03:31,830 with leukemia by the doctors. 61 00:03:31,830 --> 00:03:34,180 Grueling chemotherapy followed 62 00:03:34,180 --> 00:03:36,860 until the family, on the advice of their doctor, 63 00:03:36,860 --> 00:03:38,950 decided to try a new therapy 64 00:03:38,950 --> 00:03:41,033 based on molecular analysis. 65 00:03:45,390 --> 00:03:48,510 It's no longer a trip into the unknown. 66 00:03:48,510 --> 00:03:49,820 In the early days no one knew 67 00:03:49,820 --> 00:03:51,850 where the journey would take us. 68 00:03:51,850 --> 00:03:53,700 But all that is now rather different. 69 00:03:58,888 --> 00:04:03,555 For us, it's simply that now there is an end in sight. 70 00:04:04,410 --> 00:04:06,150 A year ago we had no idea 71 00:04:06,150 --> 00:04:07,583 what we would be faced with. 72 00:04:08,520 --> 00:04:10,530 The therapy was bringing no progress 73 00:04:10,530 --> 00:04:12,770 and last spring things just wen downhill 74 00:04:12,770 --> 00:04:15,270 until we were able to change the therapy 75 00:04:15,270 --> 00:04:16,853 and things started to improve. 76 00:04:20,670 --> 00:04:23,910 Within the shortest time she had made real progress. 77 00:04:23,910 --> 00:04:25,960 Her blood levels were suddenly so good 78 00:04:25,960 --> 00:04:27,620 and the metabolic equivalence 79 00:04:27,620 --> 00:04:29,883 showed that at last things were looking up. 80 00:04:32,330 --> 00:04:34,100 The targeted treatment carried out 81 00:04:34,100 --> 00:04:36,410 on the basis of molecular analysis 82 00:04:36,410 --> 00:04:38,220 can bring decisive progress, 83 00:04:38,220 --> 00:04:40,923 says the director of the department of pediatrics. 84 00:04:43,060 --> 00:04:45,090 The traditional concept of chemotherapy 85 00:04:45,090 --> 00:04:47,110 is in effect misleading. 86 00:04:47,110 --> 00:04:48,670 Chemotherapy works everywhere 87 00:04:48,670 --> 00:04:50,960 where rapid cell division takes place, 88 00:04:50,960 --> 00:04:52,280 but it can't differentiate 89 00:04:52,280 --> 00:04:54,730 between healthy and cancerous cells. 90 00:04:54,730 --> 00:04:56,860 That means there are many side effects 91 00:04:56,860 --> 00:04:59,670 and we aren't able to target every aggressive cancer cell 92 00:04:59,670 --> 00:05:01,010 and kill it off. 93 00:05:01,010 --> 00:05:02,510 Where children are concerned, 94 00:05:02,510 --> 00:05:04,760 there's often regression and illness. 95 00:05:04,760 --> 00:05:06,330 And in children's cancer treatment, 96 00:05:06,330 --> 00:05:08,950 we have healing rates of 80%. 97 00:05:08,950 --> 00:05:11,830 That's gratifying but 20% dying from their illness 98 00:05:11,830 --> 00:05:14,050 is still 20% too much. 99 00:05:14,050 --> 00:05:15,330 And that is our aim. 100 00:05:15,330 --> 00:05:17,470 To reduce this figure and if possible, 101 00:05:17,470 --> 00:05:20,313 achieve a cure rate of 100%. 102 00:05:24,670 --> 00:05:27,708 The developments are based on a groundbreaking 103 00:05:27,708 --> 00:05:29,860 new understanding of the makeup of the human organism, 104 00:05:29,860 --> 00:05:32,330 to which the research team on under Bernhard Kuster 105 00:05:32,330 --> 00:05:34,940 has made an essential contribution. 106 00:05:34,940 --> 00:05:37,960 He was able to catalog more that 18,000 proteins 107 00:05:37,960 --> 00:05:41,040 in the human body, out of which around 20,000 108 00:05:41,040 --> 00:05:42,233 of the genes are built. 109 00:05:45,430 --> 00:05:47,490 The active agents in the living system 110 00:05:47,490 --> 00:05:49,540 are the proteins, because they provide 111 00:05:49,540 --> 00:05:51,240 the controlling elements. 112 00:05:51,240 --> 00:05:53,310 They also provide the structural elements 113 00:05:53,310 --> 00:05:54,830 of the cells and organs, 114 00:05:54,830 --> 00:05:57,610 as well as, in effect, regulating and controlling 115 00:05:57,610 --> 00:05:59,880 all the vital processes. 116 00:05:59,880 --> 00:06:02,830 In so far as the genome is the static structure, 117 00:06:02,830 --> 00:06:06,000 like an archive in which one can relocate information, 118 00:06:06,000 --> 00:06:08,093 the proteins are the active agents. 119 00:06:10,970 --> 00:06:13,420 At the Max Planck Institute of Biochemistry, 120 00:06:13,420 --> 00:06:16,470 Matthias Mann is one of the most influential scientists 121 00:06:16,470 --> 00:06:19,310 working in the field of protein research. 122 00:06:19,310 --> 00:06:21,450 We believe that proteins are more exciting 123 00:06:21,450 --> 00:06:23,460 because they're the ones that make things happen 124 00:06:23,460 --> 00:06:24,510 in the body. 125 00:06:24,510 --> 00:06:26,740 The genomic aspect is so to speak 126 00:06:26,740 --> 00:06:28,850 the blueprint that stores information, 127 00:06:28,850 --> 00:06:30,610 but everything that takes place in the body 128 00:06:30,610 --> 00:06:32,200 is carried out by proteins. 129 00:06:32,200 --> 00:06:33,860 They digest the food. 130 00:06:33,860 --> 00:06:35,450 They keep the structures in place 131 00:06:35,450 --> 00:06:37,700 and carry out all reactions in the body. 132 00:06:37,700 --> 00:06:40,000 In other words, everything that happens actively 133 00:06:40,000 --> 00:06:42,023 does so by means of proteins. 134 00:06:45,290 --> 00:06:46,760 While most genes do nothing 135 00:06:46,760 --> 00:06:48,660 other than reproduce proteins, 136 00:06:48,660 --> 00:06:50,920 their production, protein synthesis, 137 00:06:50,920 --> 00:06:52,823 is an essential function of life. 138 00:06:54,850 --> 00:06:57,340 They ensure that the genome code of the DNA, 139 00:06:57,340 --> 00:06:59,010 our genetic information, 140 00:06:59,010 --> 00:07:02,130 becomes in the end flesh and blood. 141 00:07:02,130 --> 00:07:04,177 For a considerable time 142 00:07:04,177 --> 00:07:06,570 it was thought that one gene produced only one protein. 143 00:07:06,570 --> 00:07:09,310 But today we know that a gene can be the template 144 00:07:09,310 --> 00:07:11,023 for several different proteins. 145 00:07:12,520 --> 00:07:14,150 This diversity can come about 146 00:07:14,150 --> 00:07:16,470 during translation from the DNA, 147 00:07:16,470 --> 00:07:19,143 or through changes in the proteins themselves. 148 00:07:21,310 --> 00:07:23,040 The protein inventory of a cell 149 00:07:23,040 --> 00:07:25,800 is thus much larger than its genome. 150 00:07:25,800 --> 00:07:28,903 It is estimated that there are one million protein variants. 151 00:07:29,780 --> 00:07:31,510 They are life's kitchen, 152 00:07:31,510 --> 00:07:33,200 determining its structure, 153 00:07:33,200 --> 00:07:34,600 how its put together, 154 00:07:34,600 --> 00:07:37,310 which in turn, makes us what we are, 155 00:07:37,310 --> 00:07:39,650 and determines our state of health. 156 00:07:39,650 --> 00:07:41,940 It's the proteins that, for example, 157 00:07:41,940 --> 00:07:44,540 turn normal cells into tumorous ones, 158 00:07:44,540 --> 00:07:47,260 and as a result, determine the approach to be taken 159 00:07:47,260 --> 00:07:49,963 as far as therapies and medicines are concerned. 160 00:07:52,900 --> 00:07:55,583 The campus of the Technical University of Munich. 161 00:07:56,480 --> 00:07:58,690 In the faculty of bioinformatics, 162 00:07:58,690 --> 00:08:01,420 they're looking for a way through the protein labyrinth 163 00:08:01,420 --> 00:08:03,150 to help develop new tools 164 00:08:03,150 --> 00:08:05,853 for the use in the fight against diseases like cancer. 165 00:08:06,720 --> 00:08:08,570 In computer generated models, 166 00:08:08,570 --> 00:08:10,380 the team under professor Rost 167 00:08:10,380 --> 00:08:11,720 is attempting to find ways 168 00:08:11,720 --> 00:08:14,693 of predicting behavior of the structure of proteins. 169 00:08:17,450 --> 00:08:19,780 The first thing the people carrying out research 170 00:08:19,780 --> 00:08:21,560 into medicine wish to develop 171 00:08:21,560 --> 00:08:24,620 is an image of the protein they wish to target. 172 00:08:24,620 --> 00:08:28,000 What it looks like in its three dimensional form. 173 00:08:28,000 --> 00:08:29,540 That is then the first step. 174 00:08:29,540 --> 00:08:30,900 That can take a long, long time, 175 00:08:30,900 --> 00:08:33,140 in some cases up to 10 years. 176 00:08:33,140 --> 00:08:36,310 In the shortest case, it can take three months. 177 00:08:36,310 --> 00:08:38,320 But in the meantime, there are many that can be 178 00:08:38,320 --> 00:08:41,003 relatively quickly established within months. 179 00:08:44,320 --> 00:08:45,707 Back to the Charite. 180 00:08:45,707 --> 00:08:48,550 Joanna is being treated with a new therapy, 181 00:08:48,550 --> 00:08:50,740 a specific medicine that targets and attacks 182 00:08:50,740 --> 00:08:55,120 the cancer cells without resorting to chemotherapy at all. 183 00:08:55,120 --> 00:08:57,610 For the family, this is uncharted territory 184 00:08:57,610 --> 00:08:59,320 with many unknowns. 185 00:08:59,320 --> 00:09:00,790 Just as it is for the doctor 186 00:09:00,790 --> 00:09:02,203 administering the treatment. 187 00:09:05,010 --> 00:09:06,840 That's always the fundamental question 188 00:09:06,840 --> 00:09:09,930 with every patient undergoing this targeted therapy. 189 00:09:09,930 --> 00:09:12,560 A combination therapy would normally be more effective 190 00:09:12,560 --> 00:09:14,960 from an oncological perspective. 191 00:09:14,960 --> 00:09:16,600 So do you feel confident in saying 192 00:09:16,600 --> 00:09:18,900 in this case we're going for a monotherapy, 193 00:09:18,900 --> 00:09:20,420 we're stopping the chemotherapy, 194 00:09:20,420 --> 00:09:23,800 and we'll continue using only the targeted medicine. 195 00:09:23,800 --> 00:09:26,450 To be able to say this you need good arguments, 196 00:09:26,450 --> 00:09:27,850 and I've collected these arguments 197 00:09:27,850 --> 00:09:29,480 for the tumor conference as well. 198 00:09:29,480 --> 00:09:31,450 These are case histories. 199 00:09:31,450 --> 00:09:33,380 In the meantime, there is somewhat more literature 200 00:09:33,380 --> 00:09:34,570 on these patients, 201 00:09:34,570 --> 00:09:36,620 and when you have arguments to say, good, 202 00:09:36,620 --> 00:09:38,580 we see patients who are responding, 203 00:09:38,580 --> 00:09:40,913 then we can have confidence with Joanna too. 204 00:09:43,570 --> 00:09:46,560 You have to have the courage right from the beginning. 205 00:09:46,560 --> 00:09:48,210 For every therapy you use, 206 00:09:48,210 --> 00:09:49,310 from that moment on, 207 00:09:49,310 --> 00:09:52,210 when a doctor says, your child has a tumor, 208 00:09:52,210 --> 00:09:54,823 you need a lot of courage, strength, and stamina. 209 00:09:57,360 --> 00:09:59,020 And during the last year, 210 00:09:59,020 --> 00:10:01,740 taking the decision on that specific medicine 211 00:10:01,740 --> 00:10:04,650 was one that was not too difficult to take 212 00:10:04,650 --> 00:10:07,700 because we had tried various chemotherapy protocols 213 00:10:07,700 --> 00:10:09,140 for almost two years 214 00:10:09,140 --> 00:10:10,713 and none of them were working. 215 00:10:13,800 --> 00:10:16,330 For us, it was always clear that we wanted to avoid 216 00:10:16,330 --> 00:10:20,160 extreme chemotherapy treatments as much as possible. 217 00:10:20,160 --> 00:10:22,760 And that was the case with this new medicine, 218 00:10:22,760 --> 00:10:24,853 and we haven't regretted that decision. 219 00:10:30,960 --> 00:10:32,240 But it's not only Joanna 220 00:10:32,240 --> 00:10:34,440 who's benefiting from the new treatment. 221 00:10:34,440 --> 00:10:37,110 For research into molecular therapy as a whole, 222 00:10:37,110 --> 00:10:39,460 the experience gained with child tumors 223 00:10:39,460 --> 00:10:41,193 is of enormous significance. 224 00:10:44,220 --> 00:10:47,010 Child cancer cases do indeed provide advantages 225 00:10:47,010 --> 00:10:50,110 as models for such molecular targeted therapies 226 00:10:50,110 --> 00:10:51,150 because they're genetically 227 00:10:51,150 --> 00:10:52,863 not so complex in their structure. 228 00:10:54,409 --> 00:10:55,520 That can also be explained by the fact that 229 00:10:55,520 --> 00:10:57,880 with children, environmental factors 230 00:10:57,880 --> 00:11:00,680 have not yet had a long-term impact. 231 00:11:00,680 --> 00:11:02,870 In other words, we have genetic changes 232 00:11:02,870 --> 00:11:04,680 that have been there in the tissue of the tumor 233 00:11:04,680 --> 00:11:06,120 right from the start, 234 00:11:06,120 --> 00:11:08,160 and which have not been further complicated 235 00:11:08,160 --> 00:11:09,793 by environmental factors. 236 00:11:10,630 --> 00:11:13,210 That's why child tumors lend themselves much better 237 00:11:13,210 --> 00:11:15,160 to the study of such concepts, 238 00:11:15,160 --> 00:11:17,693 and to the creation of molecular profiles. 239 00:11:21,040 --> 00:11:22,170 At the same time, 240 00:11:22,170 --> 00:11:24,130 the protein composition of the cells 241 00:11:24,130 --> 00:11:26,320 is of great significance 242 00:11:26,320 --> 00:11:28,093 and it changes continuously. 243 00:11:28,980 --> 00:11:31,090 In contrast to the static genome, 244 00:11:31,090 --> 00:11:33,890 the proteome is dynamic and varies 245 00:11:33,890 --> 00:11:36,280 depending on the age, state of health, 246 00:11:36,280 --> 00:11:38,903 and on environmental factors throughout one's life. 247 00:11:40,170 --> 00:11:42,210 Thus the caterpillar and the butterfly 248 00:11:42,210 --> 00:11:45,710 that develops from it have the same genome. 249 00:11:45,710 --> 00:11:48,320 The difference in appearance is due entirely 250 00:11:48,320 --> 00:11:50,100 to the different proteome. 251 00:11:50,100 --> 00:11:52,523 The same applies to human beings. 252 00:11:55,850 --> 00:11:58,400 If we know the protein composition of the cells 253 00:11:58,400 --> 00:11:59,960 and the current changes, 254 00:11:59,960 --> 00:12:02,950 then that's the key to fighting the affected cells 255 00:12:02,950 --> 00:12:04,560 with targeted medicines, 256 00:12:04,560 --> 00:12:08,510 with new or simpler and smarter already licensed ones 257 00:12:08,510 --> 00:12:11,673 that contain a suitable combination of active agents. 258 00:12:13,600 --> 00:12:17,750 Meanwhile, cancer, neurological diseases, and diabetes, 259 00:12:17,750 --> 00:12:21,143 are no longer viewed as completely distinct illnesses. 260 00:12:36,852 --> 00:12:38,530 It's going more and more in the direction 261 00:12:38,530 --> 00:12:41,650 of no longer regarding illnesses in terms of problems 262 00:12:41,650 --> 00:12:43,320 with the affected organs, 263 00:12:43,320 --> 00:12:46,783 but rather as an irregularity of molecular processes. 264 00:12:48,100 --> 00:12:50,300 And whether we're talking about the heart, the lungs, 265 00:12:50,300 --> 00:12:52,140 or perhaps the bowels or brain, 266 00:12:52,140 --> 00:12:55,090 the symptoms are, irrespective of where they occur, 267 00:12:55,090 --> 00:12:57,453 an expression of the mechanisms behind them. 268 00:12:59,970 --> 00:13:02,570 At least with cancer illnesses they're often the same, 269 00:13:02,570 --> 00:13:05,510 and when we know that, we can develop a therapy end 270 00:13:05,510 --> 00:13:08,693 to treating patients individually for their specific tumors. 271 00:13:14,300 --> 00:13:16,180 Los Angeles. 272 00:13:16,180 --> 00:13:17,890 David Agus has his institute 273 00:13:17,890 --> 00:13:20,300 at the University of Southern California. 274 00:13:20,300 --> 00:13:22,800 He's one of the most renowned cancer specialists 275 00:13:22,800 --> 00:13:23,773 in the USA. 276 00:13:26,470 --> 00:13:30,042 Often enough, he has had to convey devastating diagnosis. 277 00:13:30,042 --> 00:13:32,040 For him and his colleagues, 278 00:13:32,040 --> 00:13:35,660 this molecular analysis, the exploration of proteins, 279 00:13:35,660 --> 00:13:37,690 offers a completely new approach 280 00:13:37,690 --> 00:13:40,363 and the opportunity for a medical revolution. 281 00:13:42,060 --> 00:13:44,400 It's nothing more and nothing less 282 00:13:44,400 --> 00:13:47,040 than a new orientation of our understanding 283 00:13:47,040 --> 00:13:48,837 of illness and health. 284 00:13:51,945 --> 00:13:52,980 A trial happened in breast cancer a decade ago, 285 00:13:52,980 --> 00:13:54,800 which is very emblematic, 286 00:13:54,800 --> 00:13:57,450 is they took women, premenopausal breast cancer, 287 00:13:57,450 --> 00:13:59,790 and normally we treat them and then we stop 288 00:13:59,790 --> 00:14:01,070 and we wait for them to recur, 289 00:14:01,070 --> 00:14:02,330 and we treat again. 290 00:14:02,330 --> 00:14:04,290 Well in this case, after treatment, 291 00:14:04,290 --> 00:14:06,525 half of the women were given a drug 292 00:14:06,525 --> 00:14:09,060 that builds bone, a drug that was meant for osteoporosis. 293 00:14:09,060 --> 00:14:10,840 And half were given placebo. 294 00:14:10,840 --> 00:14:14,540 And they reduced recurrence of the cancer by 40%. 295 00:14:14,540 --> 00:14:15,373 Why? 296 00:14:15,373 --> 00:14:17,450 Because breast cancer goes to bone. 297 00:14:17,450 --> 00:14:19,500 So if you change the soil, 298 00:14:19,500 --> 00:14:21,080 the seed doesn't grow. 299 00:14:21,080 --> 00:14:22,970 That's such a powerful statement, 300 00:14:22,970 --> 00:14:25,490 that my job as a cancer doctor for example, 301 00:14:25,490 --> 00:14:27,800 isn't to target the cancer cell, 302 00:14:27,800 --> 00:14:29,460 it's to change the body. 303 00:14:29,460 --> 00:14:32,690 To me, cancer is a verb and not a noun. 304 00:14:32,690 --> 00:14:33,763 You're cancering. 305 00:14:34,630 --> 00:14:38,360 You don't get cancer, it's something the body does. 306 00:14:38,360 --> 00:14:41,410 And so that's a radically different way of thinking about 307 00:14:41,410 --> 00:14:42,963 disease and health. 308 00:14:45,680 --> 00:14:47,680 Birmingham, Alabama. 309 00:14:47,680 --> 00:14:49,870 This is where Professor Austad and his team 310 00:14:49,870 --> 00:14:53,240 carry out their research on extremely long-living animals, 311 00:14:53,240 --> 00:14:55,880 like mussels, in order to identify targets 312 00:14:55,880 --> 00:14:57,053 for new medicines. 313 00:14:58,450 --> 00:15:01,800 He is convinced that the key to delaying the aging process 314 00:15:01,800 --> 00:15:04,270 and with it, the avoidance of illness, 315 00:15:04,270 --> 00:15:07,763 lies in the protection of the proteins in our cells. 316 00:15:11,630 --> 00:15:13,760 It's the biology of the cell. 317 00:15:13,760 --> 00:15:15,540 If you just thought of this room 318 00:15:15,540 --> 00:15:19,350 with a bunch of folded paper figures 319 00:15:19,350 --> 00:15:20,920 that had a certain function 320 00:15:20,920 --> 00:15:23,360 and they were bashing into one another all the time 321 00:15:23,360 --> 00:15:26,690 you could see how they could slightly start to get out. 322 00:15:26,690 --> 00:15:28,110 Well if that happens to a protein, 323 00:15:28,110 --> 00:15:30,020 it doesn't function anymore. 324 00:15:30,020 --> 00:15:31,580 Not only does it not function, 325 00:15:31,580 --> 00:15:35,180 sometimes it actually becomes toxic, it becomes poisonous 326 00:15:35,180 --> 00:15:37,320 just because it's taking up room 327 00:15:37,320 --> 00:15:39,570 and it may actually cause things to happen 328 00:15:39,570 --> 00:15:40,543 that it shouldn't. 329 00:15:44,360 --> 00:15:47,790 From Alabama, back to Berlin into the Charite. 330 00:15:49,200 --> 00:15:52,010 This is the story of Sabina Grossman. 331 00:15:52,010 --> 00:15:55,070 Six years ago she was diagnosed with cancer. 332 00:15:55,070 --> 00:15:57,720 It was the beginning of a long and difficult journey. 333 00:15:58,580 --> 00:16:00,220 Because for most cancer patients 334 00:16:00,220 --> 00:16:03,360 the dangers of dying lie not in the initial illness, 335 00:16:03,360 --> 00:16:06,350 but from the cancer cells and protein combinations 336 00:16:06,350 --> 00:16:08,723 that elude the initial therapy and return. 337 00:16:10,100 --> 00:16:12,363 That was what happened to Sabina Grossman. 338 00:16:20,588 --> 00:16:23,860 And then came a diagnosis of uterine cancer, 339 00:16:23,860 --> 00:16:26,820 which I had had, or the precondition for it. 340 00:16:26,820 --> 00:16:30,270 And then, yes, I lived in hope that after a small operation 341 00:16:30,270 --> 00:16:31,720 everything would be okay. 342 00:16:31,720 --> 00:16:33,130 But ultimately since then, 343 00:16:33,130 --> 00:16:34,423 nothing has been okay. 344 00:16:36,910 --> 00:16:39,680 Time and again she had to undergo operations 345 00:16:39,680 --> 00:16:41,860 and was given chemotherapy. 346 00:16:41,860 --> 00:16:44,060 She spent months in hospital. 347 00:16:44,060 --> 00:16:46,033 But the recidivous tumors returned. 348 00:16:47,522 --> 00:16:50,322 Since then, her life has been determined by her illness. 349 00:16:53,150 --> 00:16:56,020 And that was very difficult at the beginning. 350 00:16:56,020 --> 00:16:57,770 I really suffered and struggled 351 00:16:57,770 --> 00:17:01,500 and wanted to return to my previous state of fitness. 352 00:17:01,500 --> 00:17:04,400 And then at some stage you come to terms with it. 353 00:17:04,400 --> 00:17:06,390 At least I learnt that at some stage 354 00:17:06,390 --> 00:17:07,920 I would have to live with it, 355 00:17:07,920 --> 00:17:10,135 and that that is the way it is 356 00:17:10,135 --> 00:17:12,020 and that I can somehow manage. 357 00:17:12,020 --> 00:17:13,970 It is now part of my daily life 358 00:17:13,970 --> 00:17:15,810 and I plan my day accordingly 359 00:17:15,810 --> 00:17:17,163 so that I can manage it. 360 00:17:20,340 --> 00:17:22,500 The Benjamin Franklin University Clinic 361 00:17:22,500 --> 00:17:24,950 is part of the Charite in Berlin. 362 00:17:24,950 --> 00:17:26,320 This is where Sabina Grossman 363 00:17:26,320 --> 00:17:28,470 has been treated over the years. 364 00:17:28,470 --> 00:17:30,950 In agreement with the director of the cancer center, 365 00:17:30,950 --> 00:17:33,100 her doctor presented her difficult case 366 00:17:33,100 --> 00:17:34,523 to the tumor conference. 367 00:17:39,560 --> 00:17:42,560 I've certainly spent a lot of time here 368 00:17:42,560 --> 00:17:45,223 and sometimes I feel much too much at home here. 369 00:17:46,240 --> 00:17:48,210 I know my way around too well. 370 00:17:48,210 --> 00:17:50,060 Sometimes I wish it weren't that way. 371 00:17:53,040 --> 00:17:54,800 That's basically the protein we're facing 372 00:17:54,800 --> 00:17:56,580 with your tumor cells. 373 00:17:56,580 --> 00:17:57,890 Quite a high mutation rate 374 00:17:57,890 --> 00:18:00,333 that's affecting various signal pathways. 375 00:18:04,680 --> 00:18:05,790 What that now means 376 00:18:05,790 --> 00:18:09,400 is that we once again see different pathways represented 377 00:18:09,400 --> 00:18:12,810 in which the genetic changes in your ovarian carcinomas 378 00:18:12,810 --> 00:18:13,793 have played a role. 379 00:18:15,120 --> 00:18:17,510 We're able to draw conclusions from that 380 00:18:17,510 --> 00:18:20,193 and recommend certain targeted therapies. 381 00:18:24,480 --> 00:18:26,900 In principle, that would be chemo with tablets 382 00:18:26,900 --> 00:18:28,063 or what exactly? 383 00:18:30,960 --> 00:18:33,220 Well it's not really a real chemo. 384 00:18:33,220 --> 00:18:35,180 These are targeted therapies, 385 00:18:35,180 --> 00:18:37,110 which attack your tumor cells 386 00:18:37,110 --> 00:18:39,633 along these specifically changed pathways. 387 00:18:42,209 --> 00:18:43,620 What's special with these new therapy options 388 00:18:43,620 --> 00:18:46,180 is that we can basically attack the points of weakness 389 00:18:46,180 --> 00:18:47,690 in the tumor cells 390 00:18:47,690 --> 00:18:50,220 and intervene there where these genetic changes 391 00:18:50,220 --> 00:18:53,970 lead to the pathways being highly regulated. 392 00:18:53,970 --> 00:18:56,720 And if we can manage to switch them off again, 393 00:18:56,720 --> 00:18:58,813 we can slow the growth of the tumor. 394 00:19:05,720 --> 00:19:07,560 With the new analytical possibilities 395 00:19:07,560 --> 00:19:10,360 we can now, for the first time characterize 396 00:19:10,360 --> 00:19:12,763 these tumors biologically in a much better way. 397 00:19:13,710 --> 00:19:15,970 And we can also see what, in all likelihood, 398 00:19:15,970 --> 00:19:19,040 lies behind them, which genetic changes determine 399 00:19:19,040 --> 00:19:21,050 the characteristics of the tumor, 400 00:19:21,050 --> 00:19:22,760 and how we can then attempt to target 401 00:19:22,760 --> 00:19:24,343 the weak points of the tumor. 402 00:19:28,620 --> 00:19:30,830 It was in fact my hope from the beginning 403 00:19:30,830 --> 00:19:33,050 that the research would progress rapidly 404 00:19:33,050 --> 00:19:34,323 and deliver results. 405 00:19:35,340 --> 00:19:37,390 Because it was quite clear that we were stumbling 406 00:19:37,390 --> 00:19:39,010 around in the dark, 407 00:19:39,010 --> 00:19:40,720 and that we were trying out therapies 408 00:19:40,720 --> 00:19:42,870 in the hope that they would hit the target. 409 00:19:44,390 --> 00:19:46,460 And the only things that we knew would hit home 410 00:19:46,460 --> 00:19:48,840 were the operations and everything else, 411 00:19:48,840 --> 00:19:51,560 namely what Miss Letsch has already explained, 412 00:19:51,560 --> 00:19:53,453 had been tried out on other cancers. 413 00:19:58,770 --> 00:20:00,250 And all the time I lived in hope 414 00:20:00,250 --> 00:20:03,940 that by some chance, the research would find something 415 00:20:03,940 --> 00:20:05,350 and that there would be new options 416 00:20:05,350 --> 00:20:08,050 because otherwise it becomes pretty clear 417 00:20:08,050 --> 00:20:09,203 where it will lead. 418 00:20:18,160 --> 00:20:20,240 Targeted therapy fights tumor cells 419 00:20:20,240 --> 00:20:21,483 at the molecular level. 420 00:20:22,780 --> 00:20:25,440 Proteins are responsible for the growth of tumor cells 421 00:20:25,440 --> 00:20:28,343 by sending out too many growth signals to the cells. 422 00:20:30,190 --> 00:20:33,193 This is where many of the newly developed medicines start. 423 00:20:34,050 --> 00:20:35,790 They stop the growth signals, 424 00:20:35,790 --> 00:20:38,540 which encourages the tumor to regress. 425 00:20:38,540 --> 00:20:42,233 Almost all tumor medicines are aimed at the cell proteins. 426 00:20:49,550 --> 00:20:52,080 On the way to the Comprehensive Cancer Center 427 00:20:52,080 --> 00:20:52,913 at the Charite. 428 00:20:56,010 --> 00:20:58,350 This is where experts from the various disciplines 429 00:20:58,350 --> 00:21:00,953 come together to discuss a combined strategy. 430 00:21:06,770 --> 00:21:09,940 It is the clinical and molecular tumor conference, 431 00:21:09,940 --> 00:21:12,863 a kind of task force in the battle against cancer. 432 00:21:17,990 --> 00:21:20,820 Doctors, biologists, and computer scientists 433 00:21:20,820 --> 00:21:22,280 make up a team. 434 00:21:22,280 --> 00:21:24,560 Together they discuss new therapy models 435 00:21:24,560 --> 00:21:26,863 in the case of complicated illnesses. 436 00:21:28,250 --> 00:21:31,833 Models based on continuously changing protein systems. 437 00:21:40,140 --> 00:21:41,800 Not only do we have to understand 438 00:21:41,800 --> 00:21:43,990 how complex it is, but also what makes 439 00:21:43,990 --> 00:21:46,530 the tumor cells metastasize and grow. 440 00:21:46,530 --> 00:21:49,140 That's what we have to try and prevent. 441 00:21:49,140 --> 00:21:52,370 While the old domain was to eradicate the tumor cell, 442 00:21:52,370 --> 00:21:55,130 we know that in many cases that doesn't work, 443 00:21:55,130 --> 00:21:57,430 so it's a question of hindering the tumor cells 444 00:21:57,430 --> 00:22:01,110 from growing, reproducing and metastasizing. 445 00:22:01,110 --> 00:22:03,540 It could be that many of us carry tumor cells 446 00:22:03,540 --> 00:22:05,210 within us without becoming ill. 447 00:22:05,210 --> 00:22:08,203 And our aim is to recreate that situation. 448 00:22:11,160 --> 00:22:12,440 It is in fact the case 449 00:22:12,440 --> 00:22:14,520 that a tumor cell is intelligent, 450 00:22:14,520 --> 00:22:16,470 in so far as it can learn very quickly 451 00:22:16,470 --> 00:22:19,390 how to repel whatever we use to attack it. 452 00:22:19,390 --> 00:22:20,993 We learned that already in the 60's 453 00:22:20,993 --> 00:22:24,580 when in the beginning, we only had one single simple therapy 454 00:22:24,580 --> 00:22:28,520 to treat cancers, and this very soon resulted in relapses, 455 00:22:28,520 --> 00:22:31,500 simply because the tumor cells find mechanisms. 456 00:22:31,500 --> 00:22:34,420 For instance, they can activate pumps in their cells 457 00:22:34,420 --> 00:22:37,216 which are able to filter out the chemotherapy medicines, 458 00:22:37,216 --> 00:22:40,080 and in this way, ensure they're no longer vulnerable 459 00:22:40,080 --> 00:22:41,513 to these chemotherapies. 460 00:22:42,400 --> 00:22:44,533 And there are numerous such mechanisms. 461 00:22:48,362 --> 00:22:49,940 We have to understand what the proteins 462 00:22:49,940 --> 00:22:52,400 in the tumor cells do on the working level, 463 00:22:52,400 --> 00:22:54,740 and look specifically at what sort of intervention 464 00:22:54,740 --> 00:22:57,680 we can initiate that won't damage the body, 465 00:22:57,680 --> 00:23:00,070 but at the same time will neutralize this program 466 00:23:00,070 --> 00:23:02,900 of the tumor cells which allows them to grow unhindered 467 00:23:02,900 --> 00:23:04,233 and metastasize. 468 00:23:10,640 --> 00:23:14,300 I can see clearly here that this is normal mucosal tissue. 469 00:23:14,300 --> 00:23:17,280 And here a tumor nodule is growing inside 470 00:23:17,280 --> 00:23:18,450 the healthy tissue. 471 00:23:18,450 --> 00:23:20,520 And then you see that the cell nuclei 472 00:23:20,520 --> 00:23:21,870 look very different. 473 00:23:21,870 --> 00:23:24,538 That tells us that the cells are not healthy. 474 00:23:24,538 --> 00:23:26,410 While here in the normal tissue 475 00:23:26,410 --> 00:23:29,820 they appear to be uniform and have specific characteristics, 476 00:23:29,820 --> 00:23:31,550 and these areas of tissue, 477 00:23:31,550 --> 00:23:33,240 we analyze them at the protein 478 00:23:33,240 --> 00:23:35,800 and molecular biological levels. 479 00:23:35,800 --> 00:23:37,040 I can only put it that way 480 00:23:37,040 --> 00:23:39,103 but a pathologist will understand it. 481 00:23:41,640 --> 00:23:42,473 The basis for that is, 482 00:23:42,473 --> 00:23:46,520 as it has always been, a classic tissue analysis. 483 00:23:46,520 --> 00:23:50,090 On our way to the Charite's Pathological Institute, 484 00:23:50,090 --> 00:23:53,132 this is where they are attempting to identify 485 00:23:53,132 --> 00:23:54,532 and understand cancer cells. 486 00:23:55,480 --> 00:23:57,600 In Professor Klauschen's laboratories, 487 00:23:57,600 --> 00:24:01,340 they're examining and preparing patient tissue samples. 488 00:24:01,340 --> 00:24:04,150 The aim of the scientists and laboratory assistants 489 00:24:04,150 --> 00:24:06,620 is to be able to recognize the cancer cells 490 00:24:06,620 --> 00:24:08,170 and make an assessment of them. 491 00:24:11,240 --> 00:24:13,210 It's absolutely essential that the colleague 492 00:24:13,210 --> 00:24:15,330 who takes the tissue sample of the lung 493 00:24:15,330 --> 00:24:18,330 recognizes clearly which area contains the tumor 494 00:24:18,330 --> 00:24:20,650 or the pathologically relevant lesion 495 00:24:20,650 --> 00:24:23,440 so that he can cut out a sample precisely there 496 00:24:23,440 --> 00:24:25,283 to undergo further procedures. 497 00:24:29,870 --> 00:24:32,170 In the Charite's pathological department, 498 00:24:32,170 --> 00:24:34,520 the tissue samples are prepared. 499 00:24:34,520 --> 00:24:36,680 They are finely sliced and died 500 00:24:36,680 --> 00:24:39,080 so that a morphological assessment of the tumor 501 00:24:39,080 --> 00:24:40,070 can be made. 502 00:24:40,070 --> 00:24:42,963 That is, in terms of their form and structure. 503 00:24:48,977 --> 00:24:52,430 Here we can see the cells that look, we can say, 504 00:24:52,430 --> 00:24:54,000 very pleomorphic. 505 00:24:54,000 --> 00:24:56,700 That means that the nuclei all look very different 506 00:24:56,700 --> 00:24:59,270 in terms of their form and size. 507 00:24:59,270 --> 00:25:00,680 Here we have tumor cells 508 00:25:00,680 --> 00:25:03,070 and they're surrounded by lymphatic tissue. 509 00:25:03,070 --> 00:25:05,850 That means we have here a lymph node metastasis 510 00:25:05,850 --> 00:25:06,963 of a carcinoma. 511 00:25:11,340 --> 00:25:13,710 The classic laboratory analysis is, 512 00:25:13,710 --> 00:25:14,960 as it has always been, 513 00:25:14,960 --> 00:25:16,550 the basis and reference point 514 00:25:16,550 --> 00:25:18,513 for the new molecular analysis. 515 00:25:21,070 --> 00:25:22,940 The samples are processed further 516 00:25:24,100 --> 00:25:25,500 so they can be evaluated 517 00:25:25,500 --> 00:25:27,803 during the histopathological examination. 518 00:25:31,044 --> 00:25:33,287 Are the tumors malignant or benign? 519 00:25:39,010 --> 00:25:42,410 This is the last stop in terms of classical tissue analysis 520 00:25:42,410 --> 00:25:45,080 as it has traditionally been done. 521 00:25:45,080 --> 00:25:47,410 The new part comes next. 522 00:25:47,410 --> 00:25:49,100 The cancer cells are examined 523 00:25:49,100 --> 00:25:53,350 in molecular analysis as to their specific characteristics. 524 00:25:53,350 --> 00:25:55,830 Where has the DNA undergone change? 525 00:25:55,830 --> 00:25:59,190 And which proteins produce the cancer cells? 526 00:25:59,190 --> 00:26:01,030 Each patient's specific tumor 527 00:26:01,030 --> 00:26:02,833 is given a molecular profile. 528 00:26:04,340 --> 00:26:07,383 This tumor profile is what has to be counted. 529 00:26:13,240 --> 00:26:14,630 The starting point of our work 530 00:26:14,630 --> 00:26:16,440 is the questioning by the clinician 531 00:26:16,440 --> 00:26:19,750 who has a patient with a suspected lung carcinoma 532 00:26:19,750 --> 00:26:21,470 for which there is possibly a good 533 00:26:21,470 --> 00:26:23,423 and tailor made therapy available. 534 00:26:24,270 --> 00:26:26,520 That's why they send the patient's tissue sample 535 00:26:26,520 --> 00:26:28,890 to the pathology department. 536 00:26:28,890 --> 00:26:31,340 We can then sequence the tumor's DNA 537 00:26:31,340 --> 00:26:33,710 and check it for relevant modifications 538 00:26:33,710 --> 00:26:37,370 that are known to us from scientific and clinical studies. 539 00:26:37,370 --> 00:26:40,913 After that, our work is tailor made to the case at hand. 540 00:26:44,073 --> 00:26:45,940 With exactitude, the extent and depth 541 00:26:45,940 --> 00:26:49,030 of this analysis, our knowledge of detailed life 542 00:26:49,030 --> 00:26:50,990 within the tumor increases. 543 00:26:50,990 --> 00:26:53,923 As a result, we receive a mass of data. 544 00:26:58,000 --> 00:27:00,530 When you examine these tumorous cells in depth, 545 00:27:00,530 --> 00:27:02,350 every patient is different. 546 00:27:02,350 --> 00:27:04,830 Each tumor in each patient is different, 547 00:27:04,830 --> 00:27:08,360 and with that many patients, each metastasis is different 548 00:27:08,360 --> 00:27:10,153 and we can't work with that. 549 00:27:11,350 --> 00:27:13,680 We need big data, that is we need to note 550 00:27:13,680 --> 00:27:15,090 all these changes. 551 00:27:15,090 --> 00:27:17,680 In some tumors there are thousands of mutations 552 00:27:17,680 --> 00:27:19,333 at the genetic and protein level. 553 00:27:20,280 --> 00:27:22,330 We have to feed all that into the computer 554 00:27:22,330 --> 00:27:25,020 in order to discover underlying principles, 555 00:27:25,020 --> 00:27:27,432 and then again recognize commonalities 556 00:27:27,432 --> 00:27:30,216 and be able to create computer simulations. 557 00:27:30,216 --> 00:27:33,330 What happens if we neutralize a protein? 558 00:27:33,330 --> 00:27:35,870 What happens in this network? 559 00:27:35,870 --> 00:27:37,950 That's really advanced mathematics 560 00:27:37,950 --> 00:27:40,890 that requires much bigger and faster computers 561 00:27:40,890 --> 00:27:43,693 and people who understand them and can program them. 562 00:27:47,190 --> 00:27:48,410 Berkhard Rost is a pioneer 563 00:27:48,410 --> 00:27:50,393 in the field of bioinformatics. 564 00:27:51,280 --> 00:27:53,370 Without specialists in computing, 565 00:27:53,370 --> 00:27:56,373 developments in research in medicine would be impossible. 566 00:27:57,240 --> 00:27:59,830 If researchers attempted to discover possible 567 00:27:59,830 --> 00:28:02,990 protein-binding partners by experimenting, 568 00:28:02,990 --> 00:28:06,000 they would be fully occupied for decades. 569 00:28:06,000 --> 00:28:08,260 That's why it's essential to develop 570 00:28:08,260 --> 00:28:09,853 an automated procedure. 571 00:28:13,190 --> 00:28:14,630 During the last 10 years 572 00:28:14,630 --> 00:28:17,010 biology has been transformed. 573 00:28:17,010 --> 00:28:19,660 Biology was a science in which the experimenter 574 00:28:19,660 --> 00:28:22,000 would have a particular hypothesis, 575 00:28:22,000 --> 00:28:24,220 and then they deliberated as to how best 576 00:28:24,220 --> 00:28:26,330 they could set up an experiment 577 00:28:26,330 --> 00:28:29,350 in order to established whether it was true or not. 578 00:28:29,350 --> 00:28:31,010 All energy was channeled into that 579 00:28:31,010 --> 00:28:33,800 to try and prove whether the answer was yes or no 580 00:28:33,800 --> 00:28:35,283 to a particular question. 581 00:28:36,430 --> 00:28:37,740 During the last 10 years 582 00:28:37,740 --> 00:28:40,660 that method is being increasingly replaced 583 00:28:40,660 --> 00:28:43,540 by these high through put experiments. 584 00:28:43,540 --> 00:28:45,550 There are experiments that provide me 585 00:28:45,550 --> 00:28:49,190 with a mass of data, but none of these items of data 586 00:28:49,190 --> 00:28:51,563 enables me to say yes or no. 587 00:28:52,550 --> 00:28:55,900 All in all, they may give me something of an idea 588 00:28:55,900 --> 00:28:58,530 how it could be, and that is a context 589 00:28:58,530 --> 00:29:02,030 in which it would be impossible without bioinformatics, 590 00:29:02,030 --> 00:29:05,073 because none of these experiments gives a clear answer. 591 00:29:07,920 --> 00:29:09,450 Without enormous computing 592 00:29:09,450 --> 00:29:12,193 and storage capacity it would be impossible. 593 00:29:13,081 --> 00:29:15,530 And the flood of data is expanding continuously 594 00:29:15,530 --> 00:29:18,080 and exponentially worldwide. 595 00:29:18,080 --> 00:29:20,550 An incredible amount that has to be converted 596 00:29:20,550 --> 00:29:23,290 into useful information if we wish to develop 597 00:29:23,290 --> 00:29:25,497 suitable therapies and medicines. 598 00:29:25,497 --> 00:29:28,043 But the data alone will tell us nothing. 599 00:29:31,490 --> 00:29:34,420 It immediately goes back to bioinformatics. 600 00:29:34,420 --> 00:29:36,860 To the question of what the data means. 601 00:29:36,860 --> 00:29:38,570 What is its significance? 602 00:29:38,570 --> 00:29:41,300 How can I link the data that already exists, 603 00:29:41,300 --> 00:29:43,940 turn it round a little so that it becomes relevant 604 00:29:43,940 --> 00:29:45,163 to my experiment? 605 00:29:53,700 --> 00:29:55,960 In the Swiss Institute of Bioinformatics 606 00:29:55,960 --> 00:29:59,310 in Geneva, they are attempting to master the data. 607 00:29:59,310 --> 00:30:01,310 It is one of the most renowned institutes 608 00:30:01,310 --> 00:30:04,840 in the world working on bioinformatic issues. 609 00:30:04,840 --> 00:30:07,860 Here, for the first time, computers have been used 610 00:30:07,860 --> 00:30:10,170 that are normally employed by Echelon, 611 00:30:10,170 --> 00:30:12,260 the global US spy network, 612 00:30:12,260 --> 00:30:14,830 that has scanned enormous amounts of information 613 00:30:14,830 --> 00:30:16,580 in the search for suspicious words. 614 00:30:22,050 --> 00:30:24,620 Immense quantity of data is too big 615 00:30:24,620 --> 00:30:28,440 to look at it just like people used to do in experiment. 616 00:30:28,440 --> 00:30:30,971 Look at the results with their eyes 617 00:30:30,971 --> 00:30:32,560 and extract conclusion from it. 618 00:30:32,560 --> 00:30:35,660 When you do any type of, for example, 619 00:30:35,660 --> 00:30:39,640 of proteomic studies, you generate a massive amount of data 620 00:30:39,640 --> 00:30:42,330 and you need computers to analyze this data, 621 00:30:42,330 --> 00:30:45,100 to get from this massive data, 622 00:30:45,100 --> 00:30:47,319 what are the important points 623 00:30:47,319 --> 00:30:49,800 for the scientists to look at? 624 00:30:49,800 --> 00:30:52,640 And that requires bioinformatics. 625 00:30:52,640 --> 00:30:55,550 You go from a mass of data, it's like a pyramid, 626 00:30:55,550 --> 00:30:58,370 and at the top of the pyramid you've got knowledge. 627 00:30:58,370 --> 00:31:00,060 And getting from data to knowledge 628 00:31:00,060 --> 00:31:02,650 means computing, extracting things, 629 00:31:02,650 --> 00:31:05,490 throwing out things which are not interesting, 630 00:31:05,490 --> 00:31:09,540 and getting to the gold nuggets, 631 00:31:09,540 --> 00:31:13,273 which are the important knowledge items. 632 00:31:14,510 --> 00:31:16,830 For the research, the Swiss Prot Group 633 00:31:16,830 --> 00:31:18,950 is of existential significance 634 00:31:18,950 --> 00:31:21,200 and forms the UniProt centerpiece, 635 00:31:21,200 --> 00:31:23,610 the largest bioinformatic data bank 636 00:31:23,610 --> 00:31:26,123 for the proteins of all livings organisms. 637 00:31:27,340 --> 00:31:30,370 150 biologists and computer experts 638 00:31:30,370 --> 00:31:32,700 are working continuously on the maintenance 639 00:31:32,700 --> 00:31:35,530 of this unique protein data bank. 640 00:31:35,530 --> 00:31:38,320 It encompasses not only information on the composition 641 00:31:38,320 --> 00:31:41,540 of specific proteins, but also what is known 642 00:31:41,540 --> 00:31:43,233 about their biological function. 643 00:31:44,710 --> 00:31:47,820 If I want to know which protein does what 644 00:31:48,658 --> 00:31:51,867 in a disease, you will actually come to UniProt. 645 00:31:51,867 --> 00:31:53,210 You can come to this database 646 00:31:53,210 --> 00:31:54,970 to understand how it works. 647 00:31:54,970 --> 00:31:57,910 Because it's a reference, it becomes like 648 00:31:57,910 --> 00:31:59,370 an encyclopedia, as I said before, 649 00:31:59,370 --> 00:32:02,120 which sets pretty much the ground. 650 00:32:02,120 --> 00:32:03,920 Now if you have certain type of mutation 651 00:32:03,920 --> 00:32:06,300 that you might see for a genetic disease, 652 00:32:06,300 --> 00:32:07,580 you might actually relate that 653 00:32:07,580 --> 00:32:09,790 to the information that we capture. 654 00:32:09,790 --> 00:32:11,830 So basically in the big data field 655 00:32:11,830 --> 00:32:13,820 you need to have reference sets. 656 00:32:13,820 --> 00:32:17,493 And those reference sets is what we provide in UniProt. 657 00:32:20,340 --> 00:32:21,630 Berlin. 658 00:32:21,630 --> 00:32:23,920 Hans Lehrach carries out his research here 659 00:32:23,920 --> 00:32:27,350 at the Max Planck Institute for Molecular Genetics. 660 00:32:27,350 --> 00:32:29,050 It is one of the leaders in the area 661 00:32:29,050 --> 00:32:31,030 of personalized medicine 662 00:32:31,030 --> 00:32:32,850 because the logical next step 663 00:32:32,850 --> 00:32:35,600 leads to the situation of new therapy models 664 00:32:35,600 --> 00:32:38,643 on the basis of this data and new insights. 665 00:32:48,950 --> 00:32:52,950 The battle against tumors is a very difficult problem. 666 00:32:52,950 --> 00:32:56,260 But one of the tools that we are now trying to create 667 00:32:56,260 --> 00:32:59,590 is the use of exact molecular characterization 668 00:32:59,590 --> 00:33:02,850 of each tumor and of the patient 669 00:33:02,850 --> 00:33:05,680 so that we can try out every treatment. 670 00:33:05,680 --> 00:33:08,563 Every treatment option on a computer model. 671 00:33:15,230 --> 00:33:18,120 Whereas we can only try out very few medicines 672 00:33:18,120 --> 00:33:19,930 on the actual patient, 673 00:33:19,930 --> 00:33:22,560 on a computer model of the patient of course, 674 00:33:22,560 --> 00:33:26,360 we can try out 10,000 different medicines, 675 00:33:26,360 --> 00:33:28,480 and medicine combinations 676 00:33:28,480 --> 00:33:31,293 without damaging the patient in any way. 677 00:33:32,751 --> 00:33:35,223 And at the same time avoid incurring huge costs. 678 00:33:39,850 --> 00:33:41,933 On our way to Alacris Theranostics, 679 00:33:41,933 --> 00:33:45,790 Hans Lehrach's firm analyzes the genes and proteins 680 00:33:45,790 --> 00:33:46,840 of patients. 681 00:33:46,840 --> 00:33:49,810 From each one, computer models of the cancer cells 682 00:33:49,810 --> 00:33:53,660 are created, including all individual molecular changes 683 00:33:53,660 --> 00:33:55,173 and peculiarities. 684 00:33:58,670 --> 00:34:01,490 Here in the laboratory the DNA samples arrive 685 00:34:01,490 --> 00:34:04,180 and we isolate the genetic material. 686 00:34:04,180 --> 00:34:06,920 Then the next technical step is that in practice 687 00:34:06,920 --> 00:34:09,213 we split this DNA into small fragments. 688 00:34:11,550 --> 00:34:14,060 Once the DNA has been prepared we load it into 689 00:34:14,060 --> 00:34:15,710 the sequencing apparatus 690 00:34:15,710 --> 00:34:17,800 so that we can decipher the changes 691 00:34:17,800 --> 00:34:19,350 or the changes in the sequence. 692 00:34:27,210 --> 00:34:28,810 In order to build the models 693 00:34:28,810 --> 00:34:30,120 we have to have the data 694 00:34:30,120 --> 00:34:32,343 that's then incorporated into the model. 695 00:34:33,690 --> 00:34:35,890 And the data is obtained from a rough analysis 696 00:34:35,890 --> 00:34:37,380 of the sequences. 697 00:34:37,380 --> 00:34:38,890 We can then transplant this 698 00:34:38,890 --> 00:34:43,220 into the network model and look for functional consequences 699 00:34:43,220 --> 00:34:46,180 or test out medicines, which, in this model, 700 00:34:46,180 --> 00:34:49,190 could have a potential effect or not. 701 00:34:49,190 --> 00:34:52,050 Or combinations of medicines that either have 702 00:34:52,050 --> 00:34:54,083 or don't have the desired impact. 703 00:34:56,690 --> 00:34:58,270 The perspective is to create 704 00:34:58,270 --> 00:35:02,090 the whole personal avatar on a molecular level. 705 00:35:02,090 --> 00:35:04,280 In the near future, we could have a simulated 706 00:35:04,280 --> 00:35:06,863 model like this of every individual. 707 00:35:09,660 --> 00:35:11,110 The challenge that faces us, 708 00:35:11,110 --> 00:35:13,210 especially in the field of oncology, 709 00:35:13,210 --> 00:35:16,500 is the fact that with cancers, every tumor is different, 710 00:35:16,500 --> 00:35:17,950 every individual is different, 711 00:35:17,950 --> 00:35:20,360 has a different genetic background. 712 00:35:20,360 --> 00:35:23,440 The changes in the tumor vary considerably. 713 00:35:23,440 --> 00:35:26,040 When we look at a lung cancer or a brain cancer, 714 00:35:26,040 --> 00:35:28,800 the variations between patients are so wide 715 00:35:28,800 --> 00:35:31,200 that each patient in essence needs their own 716 00:35:31,200 --> 00:35:32,463 specific treatment. 717 00:35:36,450 --> 00:35:39,150 With the computer model we depict the biochemistry 718 00:35:39,150 --> 00:35:41,030 that takes place in the cell 719 00:35:41,030 --> 00:35:44,670 and basically depict each single step of a reaction, 720 00:35:44,670 --> 00:35:46,730 how a particular gene is synthesized 721 00:35:46,730 --> 00:35:48,720 into a particular protein, 722 00:35:48,720 --> 00:35:51,950 and how this protein later, together with other proteins, 723 00:35:51,950 --> 00:35:55,353 is able to interact and construct the cell signal network. 724 00:35:57,060 --> 00:35:59,850 The model we have at the moment is a cellular model, 725 00:35:59,850 --> 00:36:01,910 but we can already visualize complex 726 00:36:01,910 --> 00:36:04,910 multi-cellular systems as in a cancer. 727 00:36:04,910 --> 00:36:08,390 We can do this because we have several parallel models. 728 00:36:08,390 --> 00:36:11,460 We can envisage that we'll have a physiological model, 729 00:36:11,460 --> 00:36:14,260 or a whole body model of a patient. 730 00:36:14,260 --> 00:36:16,800 However, to reach that point it'll be a long road 731 00:36:16,800 --> 00:36:19,310 and an enormous amount of work. 732 00:36:19,310 --> 00:36:21,420 It'll be the result of a cumulative effort 733 00:36:21,420 --> 00:36:23,553 by many working groups and many firms. 734 00:36:30,490 --> 00:36:31,840 One of the pioneers involved 735 00:36:31,840 --> 00:36:35,600 in the tracing of proteins was Professor Matthias Mann. 736 00:36:35,600 --> 00:36:37,750 His team works at the Max Planck Institute 737 00:36:37,750 --> 00:36:39,363 of Biochemistry in Munich. 738 00:36:42,730 --> 00:36:46,550 His methods have revolutionized protein research. 739 00:36:46,550 --> 00:36:49,530 Without his fundamental research, proteomics wouldn't be 740 00:36:49,530 --> 00:36:51,120 where it is today. 741 00:36:51,120 --> 00:36:53,900 Above all, it was the developments he initiated 742 00:36:53,900 --> 00:36:56,370 in the field of mass spectrometry 743 00:36:56,370 --> 00:36:59,493 that made the mass measurements of proteins at all possible. 744 00:37:01,090 --> 00:37:03,990 The methods he devised are used worldwide today 745 00:37:03,990 --> 00:37:08,173 as standard procedures in Los Angeles as well as in Beijing. 746 00:37:11,090 --> 00:37:13,090 The big problem for proteomics was that 747 00:37:13,090 --> 00:37:15,690 it was very slow and not very sensitive. 748 00:37:15,690 --> 00:37:19,330 We couldn't detect the existence of many proteins. 749 00:37:19,330 --> 00:37:21,420 With these developments it became possible 750 00:37:21,420 --> 00:37:22,730 to detect lots of proteins, 751 00:37:22,730 --> 00:37:24,630 and this in turn provides us 752 00:37:24,630 --> 00:37:28,260 with the biological information, the medical information. 753 00:37:28,260 --> 00:37:29,870 If we only had 10 proteins, 754 00:37:29,870 --> 00:37:32,030 then we wouldn't learn a great deal from that. 755 00:37:32,030 --> 00:37:35,030 But today we can determine 10,000 proteins. 756 00:37:35,030 --> 00:37:36,810 Matt gives us a global overview 757 00:37:36,810 --> 00:37:39,473 about the exact condition of the cell or patient. 758 00:37:43,580 --> 00:37:44,800 Bernhard Kuster's team, 759 00:37:44,800 --> 00:37:47,360 with the identification of more than 18,000 760 00:37:47,360 --> 00:37:49,190 genetically coded proteins, 761 00:37:49,190 --> 00:37:52,840 has achieved another significantly important step. 762 00:37:52,840 --> 00:37:54,900 Investigation has shown that around 763 00:37:54,900 --> 00:37:57,360 10,000 different proteins are to be found 764 00:37:57,360 --> 00:38:00,540 in cells and organs, which control and represent 765 00:38:00,540 --> 00:38:04,503 all vital functions, and are therefore like life's kitchen. 766 00:38:07,240 --> 00:38:09,810 In the meantime, we are now able to identify 767 00:38:09,810 --> 00:38:12,673 the central proteome of various types of cancer. 768 00:38:16,920 --> 00:38:20,800 We know more or less exactly how many proteins there are. 769 00:38:20,800 --> 00:38:23,510 But at the same time, we don't know what thousands 770 00:38:23,510 --> 00:38:25,330 of them do exactly. 771 00:38:25,330 --> 00:38:27,350 That's why we are in the first instance 772 00:38:27,350 --> 00:38:29,460 interested in compiling a map 773 00:38:29,460 --> 00:38:32,350 in order to see which proteins there are all together, 774 00:38:32,350 --> 00:38:34,080 where they're found in the organism, 775 00:38:34,080 --> 00:38:36,130 and how many of them there are. 776 00:38:36,130 --> 00:38:38,710 And ideally that would lead us to an understanding 777 00:38:38,710 --> 00:38:40,740 of what needs to be done. 778 00:38:40,740 --> 00:38:43,620 Some of these proteins have already been well-researched. 779 00:38:43,620 --> 00:38:45,393 Thousands of them not at all. 780 00:38:48,360 --> 00:38:50,890 Time is of the essence. 781 00:38:50,890 --> 00:38:53,670 Precisely in emerging societies like China, 782 00:38:53,670 --> 00:38:56,110 the synthesis between fundamental research, 783 00:38:56,110 --> 00:38:58,300 big data, and the experimental testing 784 00:38:58,300 --> 00:39:01,090 of active agents and active agent combinations 785 00:39:01,090 --> 00:39:04,030 is essential if we are not to lose control 786 00:39:04,030 --> 00:39:06,543 over the so-called diseases of civilization. 787 00:39:08,810 --> 00:39:12,620 China's population is, with 1.3 billion people, 788 00:39:12,620 --> 00:39:16,060 60 times bigger than that of Germany's. 789 00:39:16,060 --> 00:39:19,810 If there are annually around 500,000 new cancer patients 790 00:39:19,810 --> 00:39:22,880 in Germany, then in China, by comparison, 791 00:39:22,880 --> 00:39:25,000 it would be 30 million. 792 00:39:25,000 --> 00:39:28,570 For that reason also, 2.3 billion dollars 793 00:39:28,570 --> 00:39:32,080 have been invested in a new scientific complex. 794 00:39:32,080 --> 00:39:35,320 We have this five year plan. 795 00:39:35,320 --> 00:39:39,900 So now is the 13th five years plan. 796 00:39:39,900 --> 00:39:42,210 So you will notice the first floor 797 00:39:42,210 --> 00:39:45,400 are the mass spectrometers on the first floor. 798 00:39:45,400 --> 00:39:47,960 The second floor, the third floor 799 00:39:47,960 --> 00:39:52,950 are all for wet biology, cell biology, 800 00:39:52,950 --> 00:39:55,230 molecular biology, those type. 801 00:39:55,230 --> 00:39:59,350 And the fourth floor is the bioinformatics. 802 00:39:59,350 --> 00:40:04,350 So our super computer is in the fourth floor. 803 00:40:06,300 --> 00:40:08,710 At the Beijing Protein Research Center, 804 00:40:08,710 --> 00:40:10,930 they're concentrating on resources, 805 00:40:10,930 --> 00:40:13,340 personnel as well as technical. 806 00:40:13,340 --> 00:40:15,500 And today we are globally networked 807 00:40:15,500 --> 00:40:17,960 because the problems are too big to be solved 808 00:40:17,960 --> 00:40:19,860 at a national level. 809 00:40:19,860 --> 00:40:23,440 One of the particular project I work on 810 00:40:23,440 --> 00:40:25,470 is gastric cancer. 811 00:40:25,470 --> 00:40:29,830 Gastric cancer is the number one, 812 00:40:29,830 --> 00:40:32,390 or number two killer in China. 813 00:40:32,390 --> 00:40:35,473 It's a big problem in East Asia. 814 00:40:37,970 --> 00:40:40,730 Proteomics in combination with big data 815 00:40:40,730 --> 00:40:42,860 has become a new standard worldwide 816 00:40:42,860 --> 00:40:45,930 in the researching of all major diseases. 817 00:40:45,930 --> 00:40:47,740 In this way, scientists are coming 818 00:40:47,740 --> 00:40:50,190 to completely new insights, 819 00:40:50,190 --> 00:40:53,913 even concerning the most complex human organ, the brain. 820 00:40:55,310 --> 00:40:58,750 Edinburgh in Seth Grant's Institute. 821 00:40:58,750 --> 00:41:00,990 He's looking at the proteins that are responsible 822 00:41:00,990 --> 00:41:03,550 for some of the more common and devastating illnesses 823 00:41:03,550 --> 00:41:04,383 of the brain. 824 00:41:07,240 --> 00:41:11,510 Here is on the post-synaptic side of the synapse. 825 00:41:11,510 --> 00:41:16,230 And inside there, I would have these molecular machines 826 00:41:16,230 --> 00:41:19,040 situated inside and there is 827 00:41:20,150 --> 00:41:23,830 actually hundreds of those molecular machines 828 00:41:23,830 --> 00:41:26,890 inside this post-synaptic side of the synapse. 829 00:41:26,890 --> 00:41:30,460 So we have a hierarchy from genes to the RNA, 830 00:41:30,460 --> 00:41:33,250 which then makes the protein, which then makes the complexes 831 00:41:33,250 --> 00:41:36,870 and the super complexes, and those are then packed inside 832 00:41:36,870 --> 00:41:40,190 the synapses, and it's those molecular machines 833 00:41:40,190 --> 00:41:42,550 that are controlling innate behaviors, 834 00:41:42,550 --> 00:41:46,740 learned behaviors, and they go wrong in different diseases. 835 00:41:46,740 --> 00:41:48,750 And it's quite simple to explain how they go wrong 836 00:41:48,750 --> 00:41:51,500 in different diseases because many diseases 837 00:41:51,500 --> 00:41:53,713 cause a mutation in a gene, 838 00:41:54,850 --> 00:41:58,020 which causes this protein to malfunction 839 00:41:58,020 --> 00:41:59,840 or not be built properly, 840 00:41:59,840 --> 00:42:02,450 which means that complex now malfunctions, 841 00:42:02,450 --> 00:42:04,690 and that super complex now malfunctions, 842 00:42:04,690 --> 00:42:07,470 and now the synapse malfunctions. 843 00:42:07,470 --> 00:42:10,930 And that's why people with those mutations 844 00:42:10,930 --> 00:42:13,843 end up with psychiatric and neurological disorders. 845 00:42:18,840 --> 00:42:22,600 The understanding that the synapse 846 00:42:22,600 --> 00:42:25,300 has a large number of proteins 847 00:42:25,300 --> 00:42:29,900 and that there is organized into molecular machines 848 00:42:29,900 --> 00:42:33,310 has caused a transformation in the way 849 00:42:33,310 --> 00:42:35,470 we think about brain diseases. 850 00:42:35,470 --> 00:42:39,040 Now, we know all of the proteins in the synapses. 851 00:42:39,040 --> 00:42:41,430 And in the year 2011, 852 00:42:41,430 --> 00:42:45,320 when we characterized all the proteins in the human synapses 853 00:42:46,280 --> 00:42:49,100 we found to our great surprise 854 00:42:49,100 --> 00:42:51,560 that there were gene mutations 855 00:42:51,560 --> 00:42:53,160 that are responsible for more than 856 00:42:53,160 --> 00:42:57,410 130 different brain diseases 857 00:42:57,410 --> 00:43:00,120 that encode these synapse proteins 858 00:43:00,120 --> 00:43:02,130 and these molecular machines. 859 00:43:02,130 --> 00:43:04,840 And when those mutations interfere 860 00:43:04,840 --> 00:43:06,360 with the function of the gene, 861 00:43:06,360 --> 00:43:08,620 it interferes with the function of the proteins 862 00:43:08,620 --> 00:43:13,620 in the molecular machines and causes these 130 diseases. 863 00:43:15,850 --> 00:43:18,150 No longer isolated observations, 864 00:43:18,150 --> 00:43:21,680 only a comprehensive approach promises success. 865 00:43:21,680 --> 00:43:23,620 We have to imagine the human organism 866 00:43:23,620 --> 00:43:25,993 as a very complex processing system. 867 00:43:27,950 --> 00:43:31,080 You can tinker with a single gene 868 00:43:31,080 --> 00:43:36,080 and increase their longevity by as much as 50, 60%. 869 00:43:36,602 --> 00:43:38,330 We understand some of that 870 00:43:38,330 --> 00:43:40,010 but one of the things we're realizing 871 00:43:40,010 --> 00:43:42,690 is that what goes on inside of a cell 872 00:43:42,690 --> 00:43:45,140 is a complicated network. 873 00:43:45,140 --> 00:43:48,240 It really needs to be addressed as a system 874 00:43:48,240 --> 00:43:52,370 because like any intricate system, 875 00:43:52,370 --> 00:43:54,920 like inside of a radio or a computer, 876 00:43:54,920 --> 00:43:58,090 if you remove one thing, you have many, many effects. 877 00:43:58,090 --> 00:44:01,370 Or if you add something else you have many, many effects. 878 00:44:01,370 --> 00:44:02,820 So what we really need, 879 00:44:02,820 --> 00:44:06,400 we really need what they call a systems approach. 880 00:44:06,400 --> 00:44:07,940 An approach to understanding 881 00:44:07,940 --> 00:44:11,293 the entire molecular network inside the cell. 882 00:44:11,293 --> 00:44:14,710 There is one thing of paramount importance. 883 00:44:14,710 --> 00:44:16,950 Proteins are exactly like humans. 884 00:44:16,950 --> 00:44:18,910 They are not isolated beings. 885 00:44:18,910 --> 00:44:21,110 They work, they live in networks, 886 00:44:21,110 --> 00:44:22,890 function within networks, 887 00:44:22,890 --> 00:44:25,170 and if I wish to understand a protein, 888 00:44:25,170 --> 00:44:28,090 then I have to understand how the protein cooperates, 889 00:44:28,090 --> 00:44:30,493 with whom, how the networks are formed. 890 00:44:31,710 --> 00:44:35,580 And networks are something that I can look at experimentally 891 00:44:35,580 --> 00:44:37,640 and on the computer. 892 00:44:37,640 --> 00:44:41,940 But the experimental methods provide uncertain testimony, 893 00:44:41,940 --> 00:44:45,143 so that I have to combine this with computer models. 894 00:44:48,740 --> 00:44:49,720 Boston. 895 00:44:49,720 --> 00:44:53,190 The location of the famous Harvard University. 896 00:44:53,190 --> 00:44:55,260 This is where George Church works, 897 00:44:55,260 --> 00:44:58,730 one of the most famous of today's geneticists. 898 00:44:58,730 --> 00:45:00,870 He is renowned for his research in the field 899 00:45:00,870 --> 00:45:02,840 of synthetic biology, 900 00:45:02,840 --> 00:45:05,060 a biology that combines in new ways 901 00:45:05,060 --> 00:45:06,560 the building bricks of life, 902 00:45:06,560 --> 00:45:08,343 or constructs them artificially. 903 00:45:09,240 --> 00:45:12,200 The human being as a protein construction kit 904 00:45:12,200 --> 00:45:15,143 and the researcher and doctor as the necessary engineer. 905 00:45:20,260 --> 00:45:22,910 We're now composing an atlas 906 00:45:22,910 --> 00:45:25,290 of all the different kinds of cells in the body 907 00:45:25,290 --> 00:45:27,510 and where they are, how they're connected. 908 00:45:27,510 --> 00:45:31,000 Essentially producing not just a road map 909 00:45:31,000 --> 00:45:33,990 but a recipe book that tells us how to make 910 00:45:33,990 --> 00:45:37,193 any cell in any organ on demand. 911 00:45:38,450 --> 00:45:41,900 We can make proteins in a laboratory and then deliver them 912 00:45:41,900 --> 00:45:45,003 to people, or we can make them in the person, 913 00:45:46,850 --> 00:45:50,070 essentially make the manufacturing of the proteins 914 00:45:50,070 --> 00:45:53,993 occur within the person typically through gene therapy. 915 00:45:55,660 --> 00:45:57,500 But do we want all this? 916 00:45:57,500 --> 00:45:59,570 The manufacture of exchangeable parts 917 00:45:59,570 --> 00:46:02,290 on demand for man, the machine. 918 00:46:02,290 --> 00:46:04,910 The Medical Institute at the University of Vienna 919 00:46:04,910 --> 00:46:06,570 where Professor Markus Hengstschlager 920 00:46:06,570 --> 00:46:09,310 works and teaches as a geneticist. 921 00:46:09,310 --> 00:46:12,020 He is a member of the Elite Scientific Advisory Group 922 00:46:12,020 --> 00:46:14,140 appointed by the pope and is today 923 00:46:14,140 --> 00:46:16,340 a member of the Austrian Ethical Commission. 924 00:46:18,060 --> 00:46:20,810 I foresee a situation in which nano technology 925 00:46:20,810 --> 00:46:23,630 will lead to micro machines coursing through our veins 926 00:46:23,630 --> 00:46:27,120 and arteries that can provide us daily, by the minute, 927 00:46:27,120 --> 00:46:30,490 with a picture of our complete physiological condition. 928 00:46:30,490 --> 00:46:31,537 What's our cholesterol level? 929 00:46:31,537 --> 00:46:33,520 What's the general situation 930 00:46:33,520 --> 00:46:35,980 as far as our fat metabolism is concerned? 931 00:46:35,980 --> 00:46:38,660 How is our liver working, etc. 932 00:46:38,660 --> 00:46:40,300 That's the first step. 933 00:46:40,300 --> 00:46:42,500 And then it'll be possible to look at our watch 934 00:46:42,500 --> 00:46:45,750 to register when a heart attack is about to take place. 935 00:46:45,750 --> 00:46:48,250 And this watch will simultaneously pre-book 936 00:46:48,250 --> 00:46:50,723 a bed in the hospital and call the ambulance. 937 00:46:51,740 --> 00:46:55,500 As the next step, I foresee perhaps a few decades later 938 00:46:55,500 --> 00:46:57,710 that these machines will also carry out 939 00:46:57,710 --> 00:46:59,450 the appropriate therapy 940 00:46:59,450 --> 00:47:01,760 if the therapy can be concentrated to the point 941 00:47:01,760 --> 00:47:03,700 of being transportable. 942 00:47:03,700 --> 00:47:05,530 Then we can entertain the idea, 943 00:47:05,530 --> 00:47:07,110 and now I'm being a visionary, 944 00:47:07,110 --> 00:47:08,690 I'm imagining the future, 945 00:47:08,690 --> 00:47:10,600 that this watch will be able to tell you 946 00:47:10,600 --> 00:47:13,620 that you'll possibly have a headache in the next 10 minutes, 947 00:47:13,620 --> 00:47:16,120 but we'll add that if you allow it to dispense 948 00:47:16,120 --> 00:47:18,830 a certain medicine at a particular location, 949 00:47:18,830 --> 00:47:22,210 then it can make sure you won't have a heart attack at all. 950 00:47:22,210 --> 00:47:24,090 There'll be many things I can think of 951 00:47:24,090 --> 00:47:27,320 that will be technologically possible, I'm sure of that. 952 00:47:27,320 --> 00:47:29,650 The question is whether we as human beings 953 00:47:29,650 --> 00:47:30,710 will benefit from this, 954 00:47:30,710 --> 00:47:33,260 or whether, and this is again an ethical question, 955 00:47:33,260 --> 00:47:35,760 there are good reasons for saying we don't want that. 956 00:47:35,760 --> 00:47:39,010 It'll only create more problems rather than benefits. 957 00:47:39,010 --> 00:47:41,100 Will we be able to come to a consensus 958 00:47:41,100 --> 00:47:42,360 about what we wish to have 959 00:47:42,360 --> 00:47:43,923 and what we will not allow? 960 00:47:47,325 --> 00:47:50,492 (curious piano music) 961 00:47:56,200 --> 00:47:58,180 One thing is clear. 962 00:47:58,180 --> 00:48:01,460 As a result of worldwide exploration, research, 963 00:48:01,460 --> 00:48:04,530 and medicine have virtually in real time 964 00:48:04,530 --> 00:48:07,833 achieved insight into the complex system of the body. 965 00:48:10,560 --> 00:48:14,550 How complex is revealed by looking at the protein profile 966 00:48:14,550 --> 00:48:15,563 of a drop of blood. 967 00:48:19,850 --> 00:48:22,790 Proteins are conversation or words. 968 00:48:22,790 --> 00:48:24,710 So this is the conversation in the body 969 00:48:24,710 --> 00:48:26,360 and for the first time ever, 970 00:48:26,360 --> 00:48:28,437 we can visualize this data, the system, 971 00:48:28,437 --> 00:48:30,343 or the conversation in the body. 972 00:48:31,600 --> 00:48:34,034 Through the collection of increasingly 973 00:48:34,034 --> 00:48:36,000 more exact knowledge, we will be able to intervene 974 00:48:36,000 --> 00:48:39,530 more rapidly and effectively when any irregularity, 975 00:48:39,530 --> 00:48:41,623 a disease, threatens the body. 976 00:48:43,330 --> 00:48:45,360 So before, we were looking at DNA. 977 00:48:45,360 --> 00:48:47,030 DNA was the root of everything. 978 00:48:47,030 --> 00:48:49,560 It's the only thing in science we ever got right. 979 00:48:49,560 --> 00:48:51,660 Protein is the next generation 980 00:48:51,660 --> 00:48:53,640 because it's not just what could happen, 981 00:48:53,640 --> 00:48:54,963 it's what is happening. 982 00:48:59,320 --> 00:49:01,410 It is absolutely necessary 983 00:49:01,410 --> 00:49:04,530 in the interest of the survival of society 984 00:49:04,530 --> 00:49:07,730 to develop more intelligent and more secure 985 00:49:07,730 --> 00:49:11,313 model-driven medical and preventative policies. 986 00:49:17,120 --> 00:49:19,750 I can predict that a disposition exists 987 00:49:19,750 --> 00:49:23,360 that can lead to a certain disease like for example cancer. 988 00:49:23,360 --> 00:49:24,900 Then I can perhaps predict 989 00:49:24,900 --> 00:49:27,930 where I could intervene in this protein circulation, 990 00:49:27,930 --> 00:49:29,270 in the protein network, 991 00:49:29,270 --> 00:49:32,310 to regulate it and avoid the disease happening. 992 00:49:32,310 --> 00:49:33,500 And I do believe this. 993 00:49:33,500 --> 00:49:35,473 It would be a positive outcome. 994 00:49:38,150 --> 00:49:40,780 Today we have a large scale global map. 995 00:49:40,780 --> 00:49:43,787 We see the rough picture, the countries and the continents. 996 00:49:43,787 --> 00:49:47,570 Where we want to go is to create a very detailed map 997 00:49:47,570 --> 00:49:49,920 in which every house, every tree, every road 998 00:49:49,920 --> 00:49:51,570 is clearly recognizable, 999 00:49:51,570 --> 00:49:53,420 and that should definitely be achievable 1000 00:49:53,420 --> 00:49:54,793 within the next 10 years. 1001 00:49:56,116 --> 00:49:59,283 (curious piano music) 1002 00:50:01,159 --> 00:50:03,930 I do believe that we'll make quicker progress, 1003 00:50:03,930 --> 00:50:05,280 and I would say cautiously 1004 00:50:05,280 --> 00:50:07,250 that every five years we'll have control 1005 00:50:07,250 --> 00:50:09,523 over a higher percentage of these tumors. 1006 00:50:11,390 --> 00:50:13,010 We can see that it's engaging 1007 00:50:13,010 --> 00:50:15,310 and that we are having increasing success, 1008 00:50:15,310 --> 00:50:17,060 and then the following will happen. 1009 00:50:17,060 --> 00:50:18,880 We will start to see the mechanisms 1010 00:50:18,880 --> 00:50:20,870 in other patients, and that will lead 1011 00:50:20,870 --> 00:50:23,310 to the introduction of completely new impulses 1012 00:50:23,310 --> 00:50:24,723 into classical medicine. 1013 00:50:26,490 --> 00:50:28,560 In the project to decode the proteome, 1014 00:50:28,560 --> 00:50:31,500 scientists worldwide have taken the road together 1015 00:50:31,500 --> 00:50:33,150 and worked to better comprehend 1016 00:50:33,150 --> 00:50:34,470 the complex building blocks 1017 00:50:34,470 --> 00:50:36,450 that make up the human being. 1018 00:50:36,450 --> 00:50:39,330 And through the necessary symbiosis of protein research 1019 00:50:39,330 --> 00:50:41,370 and big data we will perhaps 1020 00:50:41,370 --> 00:50:43,810 be better prepared for diseases. 1021 00:50:43,810 --> 00:50:46,240 With model therapies, new medicines, 1022 00:50:46,240 --> 00:50:48,030 perhaps to the point of even achieving 1023 00:50:48,030 --> 00:50:50,600 a deceleration of aging itself. 1024 00:50:50,600 --> 00:50:53,980 Discovery that maintaining the proteome 1025 00:50:53,980 --> 00:50:56,640 is a key component of aging, 1026 00:50:56,640 --> 00:50:59,020 is the most exciting work that's going on 1027 00:50:59,020 --> 00:50:59,990 in my lab right now. 1028 00:50:59,990 --> 00:51:03,210 At the same time there are diseases like Alzheimer's 1029 00:51:03,210 --> 00:51:05,860 where we're making critical understandings of. 1030 00:51:05,860 --> 00:51:07,590 So we're gonna be able to prevent 1031 00:51:07,590 --> 00:51:09,320 and reverse those diseases. 1032 00:51:09,320 --> 00:51:11,660 So whether dementia be from vascular 1033 00:51:11,660 --> 00:51:13,510 or whether it be from Alzheimer's, 1034 00:51:13,510 --> 00:51:15,840 we're gonna be able to make an enormous impact 1035 00:51:15,840 --> 00:51:17,950 in the relatively near future. 1036 00:51:17,950 --> 00:51:19,390 So it's a new era in medicine 1037 00:51:19,390 --> 00:51:22,793 and I truly believe we're all lucky to live now. 1038 00:51:24,004 --> 00:51:26,754 (mystical music)