1 00:00:00,090 --> 00:00:02,490 The following content is provided under a Creative 2 00:00:02,490 --> 00:00:04,030 Commons license. 3 00:00:04,030 --> 00:00:06,330 Your support will help MIT OpenCourseWare 4 00:00:06,330 --> 00:00:10,720 continue to offer high quality educational resources for free. 5 00:00:10,720 --> 00:00:13,320 To make a donation or view additional materials 6 00:00:13,320 --> 00:00:17,280 from hundreds of MIT courses, visit MIT OpenCourseWare 7 00:00:17,280 --> 00:00:18,450 at ocw.mit.edu. 8 00:00:26,130 --> 00:00:29,411 TYLER JACKS: OK, good morning everybody. 9 00:00:29,411 --> 00:00:29,910 Morning. 10 00:00:29,910 --> 00:00:32,970 Good morning, good morning. 11 00:00:32,970 --> 00:00:36,650 All right, we're going to continue our discussion 12 00:00:36,650 --> 00:00:40,100 about cancer today as well as on Friday. 13 00:00:40,100 --> 00:00:44,150 In between you have an exam on Wednesday. 14 00:00:44,150 --> 00:00:45,590 Partly in preparation for that I'm 15 00:00:45,590 --> 00:00:54,460 having office hours tomorrow between 3:00 and 4:00 in 76453. 16 00:00:54,460 --> 00:00:56,630 And as the note says, come with questions 17 00:00:56,630 --> 00:00:59,180 that you have about immunology, which I taught you, 18 00:00:59,180 --> 00:01:03,050 and the introductory cancer class that I taught you. 19 00:01:03,050 --> 00:01:04,886 If you have questions about other subjects 20 00:01:04,886 --> 00:01:06,260 that will be covered in this exam 21 00:01:06,260 --> 00:01:07,968 that Professor [? Sid ?] covered for you, 22 00:01:07,968 --> 00:01:10,880 it's best to go to her office hours, or to your TAs, 23 00:01:10,880 --> 00:01:13,730 or the other sections that will be held. 24 00:01:13,730 --> 00:01:16,760 All right so towards the end of last lecture 25 00:01:16,760 --> 00:01:19,100 we talked about smoking and cancer, 26 00:01:19,100 --> 00:01:21,270 and I warned you against the evils of smoking. 27 00:01:21,270 --> 00:01:23,660 And I hope you were paying attention. 28 00:01:23,660 --> 00:01:27,980 This slide shows you some pretty startling statistics 29 00:01:27,980 --> 00:01:32,090 that relate the increase in smoking, shown here, 30 00:01:32,090 --> 00:01:36,080 among men in this country, which began around 1900. 31 00:01:36,080 --> 00:01:38,240 And you can see it rapidly increased over 32 00:01:38,240 --> 00:01:40,800 the first part of the last century. 33 00:01:40,800 --> 00:01:43,880 And you can also see that about 20 years later lung cancer 34 00:01:43,880 --> 00:01:47,090 rates rose equally quickly. 35 00:01:47,090 --> 00:01:48,800 And this was some of the evidence 36 00:01:48,800 --> 00:01:51,170 that smoking caused lung cancer. 37 00:01:51,170 --> 00:01:53,600 And we now know, as I mentioned to you last time, 38 00:01:53,600 --> 00:01:57,980 that there are lots of carcinogens in cigarette smoke 39 00:01:57,980 --> 00:01:59,060 that cause lung cancer. 40 00:01:59,060 --> 00:02:00,980 Lots of mutagens. 41 00:02:00,980 --> 00:02:06,030 Either mutagens in their native form or promutagens 42 00:02:06,030 --> 00:02:09,680 that can be converted into mutagens, that we 43 00:02:09,680 --> 00:02:14,700 expose ourselves to through the process of tobacco smoking. 44 00:02:14,700 --> 00:02:16,410 That was men. 45 00:02:16,410 --> 00:02:20,470 But lung cancer has also increased in women. 46 00:02:20,470 --> 00:02:23,480 You can see this also precipitous increase 47 00:02:23,480 --> 00:02:26,940 in lung cancer among women in this country. 48 00:02:26,940 --> 00:02:29,910 And lung cancer has now passed breast cancer 49 00:02:29,910 --> 00:02:32,820 as the leading cause of cancer deaths among women 50 00:02:32,820 --> 00:02:34,620 in the United States. 51 00:02:34,620 --> 00:02:37,500 You can see that in the case of men, 52 00:02:37,500 --> 00:02:42,870 smoking levels actually started to drop quite some time ago. 53 00:02:42,870 --> 00:02:45,570 And coincident with that, lung cancer 54 00:02:45,570 --> 00:02:48,990 deaths among men in this country also have been dropping. 55 00:02:48,990 --> 00:02:53,010 It's a direct result of smoking cessation and people 56 00:02:53,010 --> 00:02:54,690 not starting to smoke. 57 00:02:54,690 --> 00:02:57,300 That had not happened in the case of women 58 00:02:57,300 --> 00:02:58,500 until very recently. 59 00:02:58,500 --> 00:03:01,020 In fact, just last month a study was 60 00:03:01,020 --> 00:03:04,710 published that showed that also for women lung cancer rates are 61 00:03:04,710 --> 00:03:06,009 now starting to go down. 62 00:03:06,009 --> 00:03:07,800 And that's a direct consequence of the fact 63 00:03:07,800 --> 00:03:09,390 that fewer women are smoking. 64 00:03:09,390 --> 00:03:12,630 It takes a few years to see that effect play out 65 00:03:12,630 --> 00:03:14,580 because people who were smoking 20 years ago 66 00:03:14,580 --> 00:03:17,550 are getting cancer based on that now. 67 00:03:17,550 --> 00:03:22,720 So examples of why smoking is bad for you. 68 00:03:25,380 --> 00:03:39,110 Cigarette smoke can be considered 69 00:03:39,110 --> 00:03:41,210 a environmental carcinogen, although it's one 70 00:03:41,210 --> 00:03:44,294 that we expose ourselves to. 71 00:03:44,294 --> 00:03:45,710 I talked to you about a variety of 72 00:03:45,710 --> 00:03:50,720 other environmental carcinogens that we get exposed to. 73 00:03:59,910 --> 00:04:02,640 I also described this phenomenon by which 74 00:04:02,640 --> 00:04:05,460 chemicals that are not in their native state, mutagenic, 75 00:04:05,460 --> 00:04:08,520 can become mutagenic through metabolism in our bodies. 76 00:04:08,520 --> 00:04:11,520 Promutagens can be converted to mutagens in our body. 77 00:04:11,520 --> 00:04:14,490 And I showed you the example of benzo [a] pyrene which 78 00:04:14,490 --> 00:04:17,910 is in cigarette smoke and gets converted into a mutagenic form 79 00:04:17,910 --> 00:04:19,800 in our bodies. 80 00:04:19,800 --> 00:04:22,960 And there are many other such. 81 00:04:22,960 --> 00:04:37,090 There are also examples, and I didn't say this explicitly, 82 00:04:37,090 --> 00:04:39,320 of nonmutagenic carcinogens. 83 00:04:39,320 --> 00:04:42,740 This goes against the rule that carcinogens are mutagens. 84 00:04:42,740 --> 00:04:45,470 These are actually nonmutagenic but they're 85 00:04:45,470 --> 00:04:48,860 cancer causing so we call them carcinogens. 86 00:04:48,860 --> 00:05:00,580 Examples of this would be alcohol and asbestos. 87 00:05:00,580 --> 00:05:04,660 These affect cancer rates, we think, 88 00:05:04,660 --> 00:05:06,460 because they cause tissue damage. 89 00:05:11,950 --> 00:05:14,090 Alcohol in the liver, for example, 90 00:05:14,090 --> 00:05:15,520 causes tissue damage in the liver. 91 00:05:15,520 --> 00:05:18,190 Asbestos, if you breathe it in, can cause tissue damage 92 00:05:18,190 --> 00:05:19,810 in the linings of the lungs. 93 00:05:19,810 --> 00:05:30,650 This tissue damage then results in increased proliferation. 94 00:05:30,650 --> 00:05:32,630 Cells are recruited to grow in order 95 00:05:32,630 --> 00:05:35,360 to repair the damage that was caused, 96 00:05:35,360 --> 00:05:43,690 and this can then indirectly result in mutations. 97 00:05:43,690 --> 00:05:46,270 Because as I mentioned to you, every time your cell 98 00:05:46,270 --> 00:05:48,820 divides there's a chance that a problem will happen, 99 00:05:48,820 --> 00:05:50,950 a chance that a replication error will occur. 100 00:05:57,596 --> 00:05:59,220 There's a chance that an important gene 101 00:05:59,220 --> 00:06:01,350 relevant to cancer will incur a mutation. 102 00:06:01,350 --> 00:06:04,320 So more replication, more proliferation, the greater the 103 00:06:04,320 --> 00:06:09,060 chance that a problematic mutation will take place. 104 00:06:21,030 --> 00:06:23,430 I didn't say this explicitly, but likewise 105 00:06:23,430 --> 00:06:25,800 problems in chromosome segregation 106 00:06:25,800 --> 00:06:27,840 can occur every time a cell divides. 107 00:06:27,840 --> 00:06:31,350 We have intricate systems to ensure that chromosomes 108 00:06:31,350 --> 00:06:33,750 separate properly so that each daughter 109 00:06:33,750 --> 00:06:36,480 cell gets the right complement of chromosomes. 110 00:06:36,480 --> 00:06:38,310 But sometimes that breaks down. 111 00:06:38,310 --> 00:06:41,140 And sometimes cells get the wrong number of chromosomes. 112 00:06:41,140 --> 00:06:48,980 We talked about this in the context of meiosis, 113 00:06:48,980 --> 00:06:52,890 but non-disjunction events can occur in mitosis as well, 114 00:06:52,890 --> 00:06:55,520 leading to chromosome imbalances, which 115 00:06:55,520 --> 00:06:57,170 are also hallmarks of cancer. 116 00:06:57,170 --> 00:06:59,150 As I showed you last time, if you 117 00:06:59,150 --> 00:07:01,760 look at the chromosome content of a cancer cell 118 00:07:01,760 --> 00:07:04,730 it is often very, very abnormal. 119 00:07:04,730 --> 00:07:07,040 And these abnormal chromosome numbers 120 00:07:07,040 --> 00:07:10,490 occur due to defects in chromosome segregation, 121 00:07:10,490 --> 00:07:14,680 including non-disjunction events. 122 00:07:14,680 --> 00:07:19,780 OK, so various things that we expose ourselves to 123 00:07:19,780 --> 00:07:24,610 or that just go along with the normal process of cell division 124 00:07:24,610 --> 00:07:27,310 can lead to mutations. 125 00:07:27,310 --> 00:07:30,010 And as I emphasized in the last lecture, 126 00:07:30,010 --> 00:07:34,120 cancer is the consequence of the accumulation 127 00:07:34,120 --> 00:07:37,150 of mutations in critical genes. 128 00:07:37,150 --> 00:07:44,540 So to summarize what I told you about last time, 129 00:07:44,540 --> 00:07:46,970 we now think of the process of cancer development 130 00:07:46,970 --> 00:08:04,760 as going from a normal cell through multiple steps 131 00:08:04,760 --> 00:08:08,680 to the development of malignant cells. 132 00:08:08,680 --> 00:08:14,400 This process, for most types of cancer, 133 00:08:14,400 --> 00:08:17,490 will take years to accomplish. 134 00:08:17,490 --> 00:08:22,770 Cells acquire these alterations over multiple years. 135 00:08:22,770 --> 00:08:42,070 And these arrows represent mutations to cellular genes. 136 00:08:42,070 --> 00:08:45,460 Mutations in processes that are important in determining 137 00:08:45,460 --> 00:08:48,010 the normal behavior of these cells 138 00:08:48,010 --> 00:08:52,520 and allowing these cells to behave abnormally. 139 00:08:52,520 --> 00:08:56,660 This process unfolds over time, as I mentioned. 140 00:08:56,660 --> 00:08:58,370 And gives rise to this phenomenon, 141 00:08:58,370 --> 00:09:01,130 or this hypothesis really for which we have 142 00:09:01,130 --> 00:09:04,250 great evidence now, the so-called clonal evolution 143 00:09:04,250 --> 00:09:07,010 of cancer, which I drew on the board for you last time. 144 00:09:07,010 --> 00:09:09,410 This is a nice version of that same concept 145 00:09:09,410 --> 00:09:12,020 from a figure from a book from Bob Weinberg who teaches 146 00:09:12,020 --> 00:09:14,990 this same class in the fall. 147 00:09:14,990 --> 00:09:17,900 Here you have a row of normal cells. 148 00:09:17,900 --> 00:09:21,240 Within these cells a mutation arises. 149 00:09:21,240 --> 00:09:24,530 This mutation gives that cell the ability to expand, 150 00:09:24,530 --> 00:09:27,350 perhaps better than its neighbor cells. 151 00:09:27,350 --> 00:09:30,470 So a number of daughter cells carrying this mutation 152 00:09:30,470 --> 00:09:31,650 are born. 153 00:09:31,650 --> 00:09:35,570 Within this now clone of singly mutant cells, 154 00:09:35,570 --> 00:09:38,720 a second mutation can arise, say in this cell here. 155 00:09:38,720 --> 00:09:42,050 This mutation, likewise, confers upon these cells 156 00:09:42,050 --> 00:09:45,040 a greater ability to grow, divide, survive, out 157 00:09:45,040 --> 00:09:46,040 compete their neighbors. 158 00:09:46,040 --> 00:09:48,170 So you get a lot of these cells too. 159 00:09:48,170 --> 00:09:50,240 And then within that expanded clone of cells, 160 00:09:50,240 --> 00:09:52,970 a third mutation arises, and so on. 161 00:09:52,970 --> 00:09:59,390 Until one has enough patients to have a fully malignant cell. 162 00:09:59,390 --> 00:10:02,320 So what are the genes that are relevant here? 163 00:10:02,320 --> 00:10:04,000 Well, let's think about the processes 164 00:10:04,000 --> 00:10:06,880 that we know are important in cancer development, 165 00:10:06,880 --> 00:10:08,770 and those are listed in the bottom right. 166 00:10:08,770 --> 00:10:11,730 Proliferation is the most obvious one. 167 00:10:11,730 --> 00:10:14,880 Cells proliferate abnormally in cancer. 168 00:10:14,880 --> 00:10:17,280 So mutations in genes that regulate proliferation 169 00:10:17,280 --> 00:10:20,610 are likely to be important here. 170 00:10:20,610 --> 00:10:23,460 Cancer is a disease of cell number, too many cells. 171 00:10:23,460 --> 00:10:26,330 You can get that because you have too much proliferation, 172 00:10:26,330 --> 00:10:29,170 but you can also get it if you have too little cell death. 173 00:10:29,170 --> 00:10:31,890 So mutations in genes that regulate cell death processes 174 00:10:31,890 --> 00:10:33,930 are also found in cancer. 175 00:10:33,930 --> 00:10:36,060 I told you last time about angiogenesis, 176 00:10:36,060 --> 00:10:37,800 the process by which blood vessels are 177 00:10:37,800 --> 00:10:39,940 recruited into the tumor. 178 00:10:39,940 --> 00:10:42,270 These two are recruited by virtue of signals 179 00:10:42,270 --> 00:10:44,250 that the tumor sends, some of which 180 00:10:44,250 --> 00:10:46,500 other product of mutations. 181 00:10:46,500 --> 00:10:49,140 I told you that cancer cells move 182 00:10:49,140 --> 00:10:51,300 in the process of metastasis. 183 00:10:51,300 --> 00:10:56,475 They break their interactions with their neighbors 184 00:10:56,475 --> 00:10:58,350 and they begin to move throughout the tissue, 185 00:10:58,350 --> 00:10:59,808 and ultimately throughout the body. 186 00:10:59,808 --> 00:11:01,650 So they have increased cell motility. 187 00:11:01,650 --> 00:11:03,064 And they also can invade. 188 00:11:03,064 --> 00:11:04,980 They can invade through the basement membrane. 189 00:11:04,980 --> 00:11:06,960 They can invade into the local tissue. 190 00:11:06,960 --> 00:11:08,460 So they have increased invasiveness. 191 00:11:08,460 --> 00:11:13,600 And there are other changes that take place within cancer cells. 192 00:11:13,600 --> 00:11:21,400 And so these mutations then collectively 193 00:11:21,400 --> 00:11:32,820 increase proliferation, decrease cell death, 194 00:11:32,820 --> 00:11:46,200 increase angiogenesis, increase motility, 195 00:11:46,200 --> 00:11:47,610 and increase invasiveness. 196 00:11:52,160 --> 00:11:56,480 It's important to know about these because today we 197 00:11:56,480 --> 00:11:59,160 are able to target some of these mutations. 198 00:11:59,160 --> 00:12:01,700 We are able to target the gene products formed 199 00:12:01,700 --> 00:12:05,090 by these mutant genes and thereby create 200 00:12:05,090 --> 00:12:06,470 better therapies. 201 00:12:06,470 --> 00:12:09,800 So our goal is to understand these processes such 202 00:12:09,800 --> 00:12:12,860 that we can ultimately control them more effectively 203 00:12:12,860 --> 00:12:16,460 in the context of treatment. 204 00:12:16,460 --> 00:12:20,380 OK well, that then leads us to what are the genes? 205 00:12:28,660 --> 00:12:31,620 What amongst the 22,000 genes in your genome 206 00:12:31,620 --> 00:12:33,670 get mutated in the development of cancer? 207 00:12:37,520 --> 00:12:38,480 How can we find them? 208 00:12:43,280 --> 00:12:45,290 Nowadays, we sequence the genomes 209 00:12:45,290 --> 00:12:47,407 of cancer cells, that's how we find them. 210 00:12:47,407 --> 00:12:48,740 But that's not always been true. 211 00:12:48,740 --> 00:12:50,907 It's actually been true for only the last few years. 212 00:12:50,907 --> 00:12:52,614 And so I'll give you some examples of how 213 00:12:52,614 --> 00:12:53,940 they were found previously. 214 00:13:02,050 --> 00:13:03,120 And why do we care? 215 00:13:03,120 --> 00:13:04,494 Well, I've already indicated some 216 00:13:04,494 --> 00:13:06,950 of this a few minutes ago, but the reason we care 217 00:13:06,950 --> 00:13:09,190 to understand the disease at the molecular level. 218 00:13:20,000 --> 00:13:21,750 Ultimately we'll be able to provide, 219 00:13:21,750 --> 00:13:25,270 in very accurate detail, improved diagnostic 220 00:13:25,270 --> 00:13:28,927 information, improved prognostic information. 221 00:13:28,927 --> 00:13:30,760 We'll be able to tell that an individual has 222 00:13:30,760 --> 00:13:35,200 cancer by detecting abnormal genes in their blood. 223 00:13:35,200 --> 00:13:38,830 Circulating DNA in their blood carrying specific mutations 224 00:13:38,830 --> 00:13:40,770 associated with particular cancers. 225 00:13:40,770 --> 00:13:42,520 We'll be able to diagnose the disease 226 00:13:42,520 --> 00:13:44,350 at an earlier stage that way. 227 00:13:44,350 --> 00:13:46,540 We'll be able to figure out exactly what mutations 228 00:13:46,540 --> 00:13:49,180 are present in the cancer cell to know whether that's 229 00:13:49,180 --> 00:13:51,700 a tumor that's going to go on to kill the patient, 230 00:13:51,700 --> 00:13:53,470 or sit there and do nothing. 231 00:13:53,470 --> 00:13:55,660 Should we treat the patient aggressively? 232 00:13:55,660 --> 00:13:57,730 Or should we leave them alone? 233 00:13:57,730 --> 00:13:59,790 Only with this molecular information will be 234 00:13:59,790 --> 00:14:02,110 will be able to figure that out in detail. 235 00:14:17,700 --> 00:14:20,460 We will, and we already, use this information 236 00:14:20,460 --> 00:14:24,030 to make better cancer drugs, molecularly targeted 237 00:14:24,030 --> 00:14:28,300 therapies that will replace conventional chemotherapy, 238 00:14:28,300 --> 00:14:30,480 which I'll teach you about on Friday. 239 00:14:30,480 --> 00:14:33,632 Chemotherapy can work, but it's highly, highly toxic 240 00:14:33,632 --> 00:14:35,340 and we'd like to be able to get rid of it 241 00:14:35,340 --> 00:14:38,310 and replace it with drugs that are much more specific, much 242 00:14:38,310 --> 00:14:42,000 more selective, and much less harmful except for the cancer 243 00:14:42,000 --> 00:14:43,440 cells. 244 00:14:43,440 --> 00:14:54,570 And this will usher in a new era, which 245 00:14:54,570 --> 00:14:57,270 I would argue is already here in some small way, called 246 00:14:57,270 --> 00:15:00,210 personalized medicine. 247 00:15:00,210 --> 00:15:02,040 The individual's disease will be diagnosed 248 00:15:02,040 --> 00:15:04,680 at the molecular level and a specific therapy 249 00:15:04,680 --> 00:15:08,290 will be designed for them based on those alterations. 250 00:15:08,290 --> 00:15:12,240 We'll dial up the right therapy based on that information. 251 00:15:12,240 --> 00:15:17,250 And again, hopefully, hopefully, yield better results 252 00:15:17,250 --> 00:15:19,380 and less toxic side effects. 253 00:15:19,380 --> 00:15:21,120 Cancer is leading the way, actually, 254 00:15:21,120 --> 00:15:22,740 in personalized medicine. 255 00:15:22,740 --> 00:15:24,750 But it will be true for lots of diseases 256 00:15:24,750 --> 00:15:28,250 in the not too distant future. 257 00:15:28,250 --> 00:15:30,530 OK, so what are the genes? 258 00:15:30,530 --> 00:15:33,140 Well, I'm going to introduce you to two broad classes of genes 259 00:15:33,140 --> 00:15:34,670 today. 260 00:15:34,670 --> 00:15:36,950 The first of which are called oncogenes. 261 00:15:43,610 --> 00:15:45,760 Onco for mass, genes. 262 00:15:45,760 --> 00:15:49,220 Oncogenes, cancer genes, cancer causing 263 00:15:49,220 --> 00:15:50,600 genes of one sort or another. 264 00:15:54,390 --> 00:15:58,190 The first of these oncogenes was identified in the context 265 00:15:58,190 --> 00:15:59,360 of oncogenic viruses. 266 00:16:15,330 --> 00:16:18,770 For example, rous sarcoma virus, which is a retrovirus. 267 00:16:22,290 --> 00:16:25,230 We'll learn more about those next week. 268 00:16:25,230 --> 00:16:28,170 Retroviruses are viruses with an RNA genome. 269 00:16:28,170 --> 00:16:31,470 HIV falls into the same class. 270 00:16:31,470 --> 00:16:34,260 Rous sarcoma virus, or RSV, has been 271 00:16:34,260 --> 00:16:38,670 studied since about 1910 or so. 272 00:16:38,670 --> 00:16:41,010 It was discovered by a virologist 273 00:16:41,010 --> 00:16:44,260 at Rockefeller University by the name of Peyton Rous. 274 00:16:44,260 --> 00:16:50,370 Peyton Rous was a virologist and a Long Island chicken farmer 275 00:16:50,370 --> 00:16:55,500 came to Peyton Rous with a prize hen from his collection. 276 00:16:55,500 --> 00:16:57,780 A prize hen that had a tumor mass growing 277 00:16:57,780 --> 00:16:59,970 on its breast muscle. 278 00:16:59,970 --> 00:17:02,683 And the farmer brought this hen to Peyton Rous 279 00:17:02,683 --> 00:17:04,349 and asked him to cure the hen because it 280 00:17:04,349 --> 00:17:05,790 was very valuable to him 281 00:17:05,790 --> 00:17:07,410 Peyton Rous took the hen. 282 00:17:07,410 --> 00:17:08,550 The farmer said, thank you. 283 00:17:08,550 --> 00:17:09,490 The farmer went away. 284 00:17:09,490 --> 00:17:14,910 Peyton Rous then promptly killed the hen and isolated the tumor. 285 00:17:14,910 --> 00:17:18,270 And was able to isolate from the tumor a virus. 286 00:17:18,270 --> 00:17:22,290 A virus that could infect another bird and cause 287 00:17:22,290 --> 00:17:24,089 cancer in that bird. 288 00:17:24,089 --> 00:17:27,329 So this was the first example of a virus associated 289 00:17:27,329 --> 00:17:28,950 with tumor development. 290 00:17:28,950 --> 00:17:30,750 There have since been many examples 291 00:17:30,750 --> 00:17:35,400 of viruses associated with tumor development in animal species. 292 00:17:35,400 --> 00:17:38,730 A few examples in people, but relatively few. 293 00:17:38,730 --> 00:17:42,870 Most cancers in humans are not virus associated but some are, 294 00:17:42,870 --> 00:17:45,540 like human papilloma virus associated cervical cancer 295 00:17:45,540 --> 00:17:47,050 as an example. 296 00:17:47,050 --> 00:17:49,980 But these viruses studied in laboratory animals 297 00:17:49,980 --> 00:17:52,620 were extremely important in teaching us about how 298 00:17:52,620 --> 00:17:54,885 cancers arise normally. 299 00:17:58,140 --> 00:18:05,720 It was known using rous sarcoma virus 300 00:18:05,720 --> 00:18:07,920 that if you took a normal chicken cell, 301 00:18:07,920 --> 00:18:12,570 fibroblasts from a chicken and infected it with rous sarcoma 302 00:18:12,570 --> 00:18:18,480 virus, it would cause those cells to round up and begin 303 00:18:18,480 --> 00:18:21,530 to proliferate abnormally. 304 00:18:21,530 --> 00:18:24,940 And these cells were given a term called being transformed. 305 00:18:29,360 --> 00:18:32,675 Transformed cells that had the appearance of cancer cells. 306 00:18:35,630 --> 00:18:39,050 After that work, a great deal of effort 307 00:18:39,050 --> 00:18:42,050 went into figuring out what were the genes of rous sarcoma 308 00:18:42,050 --> 00:18:45,920 virus that allowed the virus to cause those cells to become 309 00:18:45,920 --> 00:18:47,085 transformed. 310 00:18:58,127 --> 00:18:59,960 And it was determined that the virus carries 311 00:18:59,960 --> 00:19:04,880 a single gene called SRC, S-R-C, for sarcoma, 312 00:19:04,880 --> 00:19:07,790 which is responsible for this transformation process. 313 00:19:07,790 --> 00:19:09,710 You could basically just add the SRC gene 314 00:19:09,710 --> 00:19:11,300 and the same process would occur. 315 00:19:19,120 --> 00:19:21,840 Trying to understand the origins of the SRC, 316 00:19:21,840 --> 00:19:25,840 two investigators at UCSF, Mike Bishop and Harold Varmus 317 00:19:25,840 --> 00:19:32,890 in around 1975, determined that the SRC gene had a homologue, 318 00:19:32,890 --> 00:19:35,380 a related copy, in chicken cells. 319 00:19:47,560 --> 00:19:49,960 And they went on to hypothesize correctly 320 00:19:49,960 --> 00:19:54,280 that rous sarcoma virus stole this gene from the chicken 321 00:19:54,280 --> 00:19:58,880 cells that it was infecting and incorporated into its genome. 322 00:19:58,880 --> 00:20:03,340 So the SRC gene, this cancer gene, had a cellular origin. 323 00:20:03,340 --> 00:20:07,540 Moreover, they were able to show that SRC exists in human cells. 324 00:20:10,980 --> 00:20:12,890 And this was quite shocking. 325 00:20:12,890 --> 00:20:18,060 This cancer associated gene was present in our DNA. 326 00:20:18,060 --> 00:20:19,940 This discovery led Bishop and Varmus 327 00:20:19,940 --> 00:20:22,950 to win the Nobel Prize in 1989. 328 00:20:22,950 --> 00:20:24,890 And a funny story happened that day. 329 00:20:24,890 --> 00:20:25,800 This is a true story. 330 00:20:25,800 --> 00:20:27,930 I actually worked for Varmus as a PhD student, 331 00:20:27,930 --> 00:20:30,040 so I heard it from the horse's mouth. 332 00:20:30,040 --> 00:20:33,110 Varmus's sister-in-law was standing in a cafeteria line 333 00:20:33,110 --> 00:20:35,070 at Berkeley waiting to get her lunch 334 00:20:35,070 --> 00:20:37,490 and two guys were standing in front of her. 335 00:20:37,490 --> 00:20:39,200 And one guy said to the other what 336 00:20:39,200 --> 00:20:40,000 are you going to have today? 337 00:20:40,000 --> 00:20:41,500 And the guy said, I don't really know. 338 00:20:41,500 --> 00:20:43,640 And the first guy said, well don't get the chicken 339 00:20:43,640 --> 00:20:45,860 because two guys just won the Nobel Prize for showing 340 00:20:45,860 --> 00:20:48,791 that chicken causes cancer. 341 00:20:48,791 --> 00:20:53,122 This is sometimes how the public perceives what we do. 342 00:20:53,122 --> 00:20:54,830 But anyway, they went on to win the Nobel 343 00:20:54,830 --> 00:20:56,670 Prize for this important work. 344 00:21:06,730 --> 00:21:08,230 And they proposed that there were 345 00:21:08,230 --> 00:21:10,780 genes in our DNA, which they referred 346 00:21:10,780 --> 00:21:14,740 to as proto-oncogenes, which could undergo 347 00:21:14,740 --> 00:21:22,500 mutation and become oncogenes. 348 00:21:22,500 --> 00:21:24,300 In the case of RSV, the mutation was 349 00:21:24,300 --> 00:21:26,730 to take the gene out of the genome 350 00:21:26,730 --> 00:21:30,810 and stick it in the genome of a virus. 351 00:21:30,810 --> 00:21:34,990 But as we'll see today, there are other ways to do that too. 352 00:21:34,990 --> 00:21:37,390 Now, what the heck are we doing with proto-oncogenes 353 00:21:37,390 --> 00:21:38,860 in our genomes? 354 00:21:38,860 --> 00:21:40,450 What are these genes doing there? 355 00:21:40,450 --> 00:21:42,010 Why do we have the SRC gene? 356 00:21:42,010 --> 00:21:44,770 Why do we have other such genes? 357 00:21:44,770 --> 00:21:47,670 Who can tell me? 358 00:21:47,670 --> 00:21:51,900 Why is it beneficial to have a cancer causing gene in our DNA? 359 00:21:56,670 --> 00:21:58,961 What might these genes be doing? 360 00:21:58,961 --> 00:22:01,460 AUDIENCE: They might be just for normal metabolic processes. 361 00:22:01,460 --> 00:22:03,376 TYLER JACKS: Yeah, normal metabolic processes. 362 00:22:03,376 --> 00:22:05,220 Or perhaps normal proliferation. 363 00:22:05,220 --> 00:22:06,290 Our cells divide too. 364 00:22:06,290 --> 00:22:09,870 You go from a single cell when you're at fertilization to 10 365 00:22:09,870 --> 00:22:10,910 to the 13 cells. 366 00:22:10,910 --> 00:22:12,140 It's a lot of cell division. 367 00:22:12,140 --> 00:22:13,350 That's a controlled process. 368 00:22:13,350 --> 00:22:15,540 There's lots of genes that are devoted 369 00:22:15,540 --> 00:22:17,070 to teaching your cells what to do 370 00:22:17,070 --> 00:22:18,480 when they're supposed to do it. 371 00:22:18,480 --> 00:22:21,480 And these genes are presumably involved in those normal cell 372 00:22:21,480 --> 00:22:24,840 division processes but they get corrupted 373 00:22:24,840 --> 00:22:26,220 in the context of cancer. 374 00:22:26,220 --> 00:22:28,380 They get altered so they don't work properly. 375 00:22:28,380 --> 00:22:29,010 OK. 376 00:22:29,010 --> 00:22:33,230 So RSV was the first example, SRC was the first example. 377 00:22:33,230 --> 00:22:36,950 But it still led to some skepticism, some concern that 378 00:22:36,950 --> 00:22:39,740 in fact what was seen in the context of these viruses 379 00:22:39,740 --> 00:22:42,297 might not be relevant to real human cancer. 380 00:22:42,297 --> 00:22:43,880 Which as I told you a few minutes ago, 381 00:22:43,880 --> 00:22:47,360 rarely involves viral infection. 382 00:22:47,360 --> 00:23:00,380 And so along came Bob Weinberg who was, and is still, at MIT. 383 00:23:00,380 --> 00:23:03,320 His lab is in the Whitehead Institute. 384 00:23:03,320 --> 00:23:05,348 And Weinberg did a critical experiment. 385 00:23:08,340 --> 00:23:09,780 He started with an individual. 386 00:23:13,021 --> 00:23:14,641 [LAUGHTER] 387 00:23:14,641 --> 00:23:17,070 Sorry about that. 388 00:23:17,070 --> 00:23:20,171 This is a person. 389 00:23:20,171 --> 00:23:20,670 Sort of. 390 00:23:29,346 --> 00:23:30,970 And this individual had bladder cancer. 391 00:23:46,090 --> 00:23:57,770 Weinberg isolated the DNA from the bladder cancer 392 00:23:57,770 --> 00:24:00,265 to ask the question, were there cancer genes in there? 393 00:24:00,265 --> 00:24:02,570 Were there oncogenes in there? 394 00:24:02,570 --> 00:24:06,170 Were there mutationally altered genes 395 00:24:06,170 --> 00:24:10,514 which the reason that this tumor arose? 396 00:24:10,514 --> 00:24:11,680 And so he did an experiment. 397 00:24:11,680 --> 00:24:17,320 He took this isolated DNA and he introduced it into some cells 398 00:24:17,320 --> 00:24:20,720 in the laboratory. 399 00:24:20,720 --> 00:24:26,960 These were immortalized mouse cells. 400 00:24:30,520 --> 00:24:33,580 Immortalize meaning that they would grow in the lab forever. 401 00:24:33,580 --> 00:24:34,960 Which by the way, is not normal. 402 00:24:34,960 --> 00:24:36,626 Normally you take cells out of your body 403 00:24:36,626 --> 00:24:38,300 or out of a mouse, put them in the lab, 404 00:24:38,300 --> 00:24:39,250 they'll grow for a while but they'll 405 00:24:39,250 --> 00:24:40,690 stop growing eventually. 406 00:24:40,690 --> 00:24:42,490 These cells were immortal. 407 00:24:42,490 --> 00:24:44,247 They could continue to grow. 408 00:24:44,247 --> 00:24:46,080 But they were otherwise pretty well-behaved. 409 00:24:46,080 --> 00:24:47,920 They laid flat on the dish. 410 00:24:47,920 --> 00:24:51,130 They had normal boundaries between cells. 411 00:24:51,130 --> 00:24:53,302 They were non-transformed. 412 00:24:53,302 --> 00:24:54,760 They didn't look like cancer cells. 413 00:24:59,920 --> 00:25:01,360 And they were non-tumorigenic. 414 00:25:06,850 --> 00:25:10,630 If he introduced these cells into an experimental animal 415 00:25:10,630 --> 00:25:12,344 they wouldn't cause a tumor, OK. 416 00:25:12,344 --> 00:25:14,260 They were immortalized but they were otherwise 417 00:25:14,260 --> 00:25:16,340 pretty well-behaved. 418 00:25:16,340 --> 00:25:19,280 He introduced the isolated DNA from the tumor cell 419 00:25:19,280 --> 00:25:27,380 through a process call transfection, 420 00:25:27,380 --> 00:25:30,260 where basically the DNA gets sheared up and introduced 421 00:25:30,260 --> 00:25:39,460 into the cells such that, roughly speaking 422 00:25:39,460 --> 00:25:44,920 each cell is getting individual genes spread out 423 00:25:44,920 --> 00:25:46,810 amongst this population of mouse cells. 424 00:25:46,810 --> 00:25:49,450 And then he waited. 425 00:25:49,450 --> 00:25:52,210 And what he found was that at low frequency, 426 00:25:52,210 --> 00:25:59,590 whereas most of the cells state in their normal morphology, 427 00:25:59,590 --> 00:26:00,940 occasionally he got this. 428 00:26:09,922 --> 00:26:13,430 [PHONE RINGING] 429 00:26:13,430 --> 00:26:15,940 Can somebody get that? 430 00:26:15,940 --> 00:26:18,440 A transformed colony of cells. 431 00:26:18,440 --> 00:26:21,590 And he assumed, correctly, that this colony 432 00:26:21,590 --> 00:26:24,650 arose because one of these genes was 433 00:26:24,650 --> 00:26:30,460 a cancer gene that allowed these cells to divide abnormally. 434 00:26:30,460 --> 00:26:33,010 He further could show that if he took those cells 435 00:26:33,010 --> 00:26:35,790 and introduced them into an animal 436 00:26:35,790 --> 00:26:37,890 they would now cause a tumor. 437 00:26:37,890 --> 00:26:39,330 So they were not just transformed, 438 00:26:39,330 --> 00:26:40,710 they were also tumorigenic. 439 00:26:45,190 --> 00:26:46,960 He went on to isolate the human gene. 440 00:26:51,950 --> 00:26:55,460 Which was not difficult to do because the cells themselves 441 00:26:55,460 --> 00:26:58,625 were mouse, so he's looking for the human DNA sequence. 442 00:27:02,250 --> 00:27:04,790 And he found, eventually, that it was a mutant version 443 00:27:04,790 --> 00:27:07,942 of a gene called RAS. 444 00:27:07,942 --> 00:27:10,400 A gene that you've actually learned about already in class. 445 00:27:10,400 --> 00:27:13,850 And I'll tell you more about in a second. 446 00:27:13,850 --> 00:27:15,890 This discovery made by Weinberg's lab 447 00:27:15,890 --> 00:27:19,340 and a few other labs at the same time in the early 1980's is 448 00:27:19,340 --> 00:27:22,070 the reason I'm standing before you. 449 00:27:22,070 --> 00:27:26,270 When I was your age Weinberg came to my college 450 00:27:26,270 --> 00:27:28,830 and gave a lecture on this work. 451 00:27:28,830 --> 00:27:30,890 And I was so excited about the potential 452 00:27:30,890 --> 00:27:33,650 of learning about cancer at the molecular level 453 00:27:33,650 --> 00:27:35,480 that I decided right then and there 454 00:27:35,480 --> 00:27:38,930 to start working on cancer, and have been doing ever since. 455 00:27:38,930 --> 00:27:41,210 So sometimes the things you learn in class 456 00:27:41,210 --> 00:27:42,770 actually change your life. 457 00:27:42,770 --> 00:27:44,570 Not to say that's going to happen today, 458 00:27:44,570 --> 00:27:45,590 but sometimes it does. 459 00:27:50,290 --> 00:27:55,590 OK, so Weinberg isolates the RAS oncogene 460 00:27:55,590 --> 00:27:59,010 from these bladder cancer Cells. 461 00:27:59,010 --> 00:28:01,020 They went on to sequence the gene 462 00:28:01,020 --> 00:28:03,900 to determine how it was different from the normal copy 463 00:28:03,900 --> 00:28:04,590 of RAS. 464 00:28:04,590 --> 00:28:06,480 And that's illustrated here. 465 00:28:06,480 --> 00:28:09,540 Here's the normal RAS sequence. 466 00:28:09,540 --> 00:28:10,870 This is now not working. 467 00:28:15,150 --> 00:28:17,130 Here's the normal RAS sequence. 468 00:28:17,130 --> 00:28:19,170 It's a version of RAS called H-RAS. 469 00:28:19,170 --> 00:28:21,810 That's insignificant. 470 00:28:21,810 --> 00:28:26,320 You can see the codons, the encoded amino acids. 471 00:28:26,320 --> 00:28:30,000 Here's the change that has taken place within the cancer cells. 472 00:28:30,000 --> 00:28:32,770 They didn't have a G in this position, 473 00:28:32,770 --> 00:28:35,640 instead they had a T in this position. 474 00:28:35,640 --> 00:28:38,400 This gene wouldn't encode glycine like it's supposed to 475 00:28:38,400 --> 00:28:42,670 but instead valene at codon position number 12. 476 00:28:42,670 --> 00:28:45,300 This change, this single nucleotide change, 477 00:28:45,300 --> 00:28:47,850 this single amino acid substitution 478 00:28:47,850 --> 00:28:52,530 caused this signaling protein to go from a regulatable state 479 00:28:52,530 --> 00:28:53,299 as shown here. 480 00:28:53,299 --> 00:28:54,840 And hopefully this is familiar to you 481 00:28:54,840 --> 00:28:57,750 because you learned about it already in the signaling part 482 00:28:57,750 --> 00:28:59,650 of cell biology. 483 00:28:59,650 --> 00:29:02,680 RAS is a GTP binding protein, which normally 484 00:29:02,680 --> 00:29:08,230 cycles between an active GTP bound state and an inactive GDP 485 00:29:08,230 --> 00:29:09,490 bound state. 486 00:29:09,490 --> 00:29:14,500 It goes from on to off through this hydrolysis of GTP. 487 00:29:14,500 --> 00:29:18,530 In the context of this mutation the GDP hydrolysis 488 00:29:18,530 --> 00:29:20,040 is inhibited. 489 00:29:20,040 --> 00:29:23,960 So the protein stays in its GTP bound active state. 490 00:29:23,960 --> 00:29:26,430 It gets stuck on. 491 00:29:26,430 --> 00:29:28,670 And rather than signaling in a regulated fashion, 492 00:29:28,670 --> 00:29:30,890 signals constitutively. 493 00:29:30,890 --> 00:29:33,350 Rather than telling the cells to divide when they should, 494 00:29:33,350 --> 00:29:36,410 it tells the cells to divide always. 495 00:29:36,410 --> 00:29:38,270 And that's presumably why this mutation 496 00:29:38,270 --> 00:29:44,510 is selected for in this type of cancer and many, many others. 497 00:29:44,510 --> 00:29:51,720 OK, I remind you that RAS is a signal transduction pathway. 498 00:29:51,720 --> 00:29:53,730 Here's RAS itself. 499 00:29:53,730 --> 00:29:57,750 RAS interacts with upstream receptor molecules and growth 500 00:29:57,750 --> 00:29:58,840 factors. 501 00:29:58,840 --> 00:30:02,820 There are intermediary adapter proteins 502 00:30:02,820 --> 00:30:04,510 that help that interaction. 503 00:30:04,510 --> 00:30:08,850 There are downstream signaling proteins, like kinases. 504 00:30:08,850 --> 00:30:11,940 And ultimately there are nuclear transcription factors 505 00:30:11,940 --> 00:30:13,680 and target genes that they regulate. 506 00:30:13,680 --> 00:30:16,200 This is a signaling cascade. 507 00:30:16,200 --> 00:30:17,880 And actually what we learn in cancer 508 00:30:17,880 --> 00:30:21,780 is that many of these genes, not just RAS, 509 00:30:21,780 --> 00:30:25,170 but many of these genes can be mutated in the development 510 00:30:25,170 --> 00:30:26,880 of one or more cancers. 511 00:30:26,880 --> 00:30:30,990 For example, some genes like these are amplified. 512 00:30:30,990 --> 00:30:33,000 And I'll tell you more about that in a second. 513 00:30:33,000 --> 00:30:35,280 Others are the product of translocation 514 00:30:35,280 --> 00:30:37,380 so that they're expressed abnormally. 515 00:30:37,380 --> 00:30:40,500 Others have structural mutations like deletions. 516 00:30:40,500 --> 00:30:42,570 And others have very subtle mutations. 517 00:30:42,570 --> 00:30:44,550 The RAS mutation is a subtle mutation. 518 00:30:44,550 --> 00:30:48,450 It's a single nucleotide change that allows this gene 519 00:30:48,450 --> 00:30:51,460 to function abnormally. 520 00:30:51,460 --> 00:31:08,010 OK, so importantly oncogenes dominantly transform cells. 521 00:31:13,590 --> 00:31:16,350 Weinberg added a single mutant oncogene 522 00:31:16,350 --> 00:31:18,600 and it transformed those mouse cells. 523 00:31:26,600 --> 00:31:34,240 The mutations are a gain of function mutations. 524 00:31:34,240 --> 00:31:35,860 They're dominant mutations. 525 00:31:35,860 --> 00:31:37,270 Gain of function mutations. 526 00:31:39,980 --> 00:31:43,310 There are now about 300 or so, and the number 527 00:31:43,310 --> 00:31:46,040 is growing, known oncogenes. 528 00:31:46,040 --> 00:31:50,120 Within the 22,000 genes in your genomes, about 300 of them 529 00:31:50,120 --> 00:31:55,140 can be converted to an oncogenic form through mutation. 530 00:31:55,140 --> 00:31:57,410 What types of mutations do we find? 531 00:31:57,410 --> 00:31:59,060 Well I've listed them on that slide 532 00:31:59,060 --> 00:32:01,460 but I'll just write it down as well. 533 00:32:01,460 --> 00:32:11,610 Subtle mutations, RAS is the classic example. 534 00:32:11,610 --> 00:32:14,370 A single amino acid change will convert the protein 535 00:32:14,370 --> 00:32:17,500 to an oncogenic form. 536 00:32:17,500 --> 00:32:20,160 We can also find gene amplifications. 537 00:32:26,860 --> 00:32:30,410 Your genes are present at two per cell, one from mom, 538 00:32:30,410 --> 00:32:30,990 one from dad. 539 00:32:30,990 --> 00:32:32,590 You're supposed to have two. 540 00:32:32,590 --> 00:32:35,350 Sometimes in cancer amplification 541 00:32:35,350 --> 00:32:37,540 of regions of the DNA occur. 542 00:32:37,540 --> 00:32:41,800 So you go from having not two, but four, eight, 50, 100 543 00:32:41,800 --> 00:32:43,210 copies of the gene. 544 00:32:43,210 --> 00:32:45,610 And you can imagine having too many copies, leading 545 00:32:45,610 --> 00:32:48,430 to too much protein product, would actually lead 546 00:32:48,430 --> 00:32:50,110 to inappropriate signaling. 547 00:32:50,110 --> 00:32:53,200 So here the structural gene may not be mutated, 548 00:32:53,200 --> 00:32:55,029 the amino acid sequence may be the same. 549 00:32:55,029 --> 00:32:56,320 You've just got too much of it. 550 00:33:10,880 --> 00:33:12,890 Also, genes can be rearranged. 551 00:33:12,890 --> 00:33:14,090 Gene rearrangements. 552 00:33:22,590 --> 00:33:24,000 For example, translocations. 553 00:33:24,000 --> 00:33:26,550 And I showed you some pictures of translocations. 554 00:33:26,550 --> 00:33:29,310 Chromosomes that get joined inappropriately together. 555 00:33:29,310 --> 00:33:32,400 This can break two genes and form a new gene 556 00:33:32,400 --> 00:33:34,080 in the context of the translocation. 557 00:33:34,080 --> 00:33:37,900 Perhaps a gene is expressed from a weakly acting promoter, 558 00:33:37,900 --> 00:33:38,950 normally. 559 00:33:38,950 --> 00:33:40,890 But because of a translocation event 560 00:33:40,890 --> 00:33:42,750 a very strongly acting promoter gets 561 00:33:42,750 --> 00:33:44,980 stuck in front of that gene by mistake. 562 00:33:44,980 --> 00:33:47,160 And now the gene is expressed at very high levels, 563 00:33:47,160 --> 00:33:47,920 inappropriately. 564 00:33:47,920 --> 00:33:51,070 It's not unlike the consequences of gene amplification. 565 00:33:51,070 --> 00:33:53,620 So translocations, likewise, occur frequently. 566 00:33:53,620 --> 00:33:56,890 And we'll hear about consequences of amplification 567 00:33:56,890 --> 00:34:02,310 and re-arrangement next time when we talk about therapies. 568 00:34:02,310 --> 00:34:06,810 OK, so oncogenes act dominantly. 569 00:34:06,810 --> 00:34:12,260 They can transform cells all by themselves. 570 00:34:12,260 --> 00:34:18,610 But this should be in your minds creating confusion. 571 00:34:18,610 --> 00:34:25,254 Because I've also told you that cancer is a multi-step process. 572 00:34:25,254 --> 00:34:26,920 And if cancer were a multi-step process, 573 00:34:26,920 --> 00:34:30,250 how could it be that single mutations can transform cells? 574 00:34:30,250 --> 00:34:33,550 But in fact, we now know that single mutations 575 00:34:33,550 --> 00:34:45,154 are typically and maybe never sufficient to produce 576 00:34:45,154 --> 00:34:45,654 true cancer. 577 00:34:49,940 --> 00:34:51,770 So given that, can somebody explain how 578 00:34:51,770 --> 00:34:54,170 the Weinberg experiment worked? 579 00:34:54,170 --> 00:34:58,250 How was it that Weinberg was able to transfer a single gene 580 00:34:58,250 --> 00:35:02,720 into these cells and cause them to become transformed 581 00:35:02,720 --> 00:35:06,701 and tumorigenic if single mutations aren't enough? 582 00:35:06,701 --> 00:35:07,450 Why did this work? 583 00:35:10,520 --> 00:35:13,740 Anybody? 584 00:35:13,740 --> 00:35:17,170 The key is that they weren't normal cells. 585 00:35:17,170 --> 00:35:19,930 The cells he started with are already abnormal. 586 00:35:19,930 --> 00:35:21,410 They were already immortalized. 587 00:35:21,410 --> 00:35:23,284 They'd already been growing in the laboratory 588 00:35:23,284 --> 00:35:24,950 dish for a long time. 589 00:35:24,950 --> 00:35:26,980 So they were sensitive to a single mutation 590 00:35:26,980 --> 00:35:30,040 but normal cells in your body are not. 591 00:35:30,040 --> 00:35:31,390 And that's a good thing. 592 00:35:31,390 --> 00:35:33,850 Because as you sit there today you probably 593 00:35:33,850 --> 00:35:38,600 have about a million RAS mutant cells in your body, 594 00:35:38,600 --> 00:35:39,710 scattered around. 595 00:35:39,710 --> 00:35:42,770 And that's just based on the normal mutation frequency. 596 00:35:42,770 --> 00:35:44,480 The likelihood is that we all have 597 00:35:44,480 --> 00:35:48,410 about a million or more RAS mutant cells in our body. 598 00:35:48,410 --> 00:35:50,390 But because RAS mutations are not 599 00:35:50,390 --> 00:35:54,080 sufficient to drive cancer formation, that 600 00:35:54,080 --> 00:35:57,890 may be in a tumor initiated cell but it's not yet a full cancer, 601 00:35:57,890 --> 00:36:00,740 other mutations have to take place thereafter. 602 00:36:00,740 --> 00:36:02,300 We now believe that there's probably 603 00:36:02,300 --> 00:36:17,930 something like three to 20 mutations 604 00:36:17,930 --> 00:36:20,270 are required to make a full blown cancer. 605 00:36:22,860 --> 00:36:27,450 OK, so I've told you about oncogenes 606 00:36:27,450 --> 00:36:31,170 and I've related their function to normal cell division, 607 00:36:31,170 --> 00:36:32,430 and that's appropriate to do. 608 00:36:32,430 --> 00:36:36,150 Normal cells do get signals to divide, 609 00:36:36,150 --> 00:36:37,890 make more of themselves. 610 00:36:37,890 --> 00:36:41,160 And moreover, they get signals to stop dividing 611 00:36:41,160 --> 00:36:42,470 when it's time to stop. 612 00:36:42,470 --> 00:36:45,150 In embryogenesis once you form the liver 613 00:36:45,150 --> 00:36:47,970 you want to stop cell division within the liver cells. 614 00:36:47,970 --> 00:36:51,540 When you wound yourself you recruit cells to divide, 615 00:36:51,540 --> 00:36:55,170 but once the wound is healed you want it to stop dividing. 616 00:36:55,170 --> 00:36:58,620 And so there's complimentary signals, stop signals, 617 00:36:58,620 --> 00:37:02,010 that come into play to cause the cells to stop. 618 00:37:02,010 --> 00:37:04,530 Cancer cells have defects in both 619 00:37:04,530 --> 00:37:07,110 of these classes of signals. 620 00:37:07,110 --> 00:37:09,750 We've been talking now about the oncogene signals. 621 00:37:09,750 --> 00:37:10,980 They are the go Signals. 622 00:37:10,980 --> 00:37:14,110 The signals to tell the cell to divide. 623 00:37:14,110 --> 00:37:17,190 And because of these alterations like in RAS 624 00:37:17,190 --> 00:37:20,590 the cells are more capable of dividing. 625 00:37:20,590 --> 00:37:22,930 They make more of themselves. 626 00:37:22,930 --> 00:37:28,030 Moreover, the brakes on this process, the stop signals, 627 00:37:28,030 --> 00:37:32,470 are also typically lost in the development of cancer. 628 00:37:32,470 --> 00:37:35,830 Such that now the cells lacking the breaking signals 629 00:37:35,830 --> 00:37:38,590 will continue to divide still more. 630 00:37:38,590 --> 00:37:41,890 And these two classes of genes are 631 00:37:41,890 --> 00:37:45,100 called oncogenes, that we've been discussing already, 632 00:37:45,100 --> 00:37:48,250 and tumor suppressor genes that we'll discuss from now 633 00:37:48,250 --> 00:37:49,930 to the end of the lecture. 634 00:37:49,930 --> 00:37:51,520 Tumor suppressor genes. 635 00:38:05,687 --> 00:38:07,520 There are a number of tumor suppressor genes 636 00:38:07,520 --> 00:38:16,980 now as well, more than 200 known. 637 00:38:16,980 --> 00:38:21,240 So that's 500 or so known cancer genes already. 638 00:38:21,240 --> 00:38:25,070 The first one, the very first one 639 00:38:25,070 --> 00:38:29,330 described occurred in this type of tumor. 640 00:38:29,330 --> 00:38:32,980 This is a child with a tumor of the eye. 641 00:38:32,980 --> 00:38:34,840 The tumor is called retinoblastoma. 642 00:38:45,280 --> 00:38:49,660 And based on the examination of the genes within those tumor 643 00:38:49,660 --> 00:38:53,680 cells, it was hypothesized that the retinoblastoma gene that 644 00:38:53,680 --> 00:38:55,840 was responsible for this disease was 645 00:38:55,840 --> 00:38:58,150 one of these tumor suppressor genes before any of them 646 00:38:58,150 --> 00:38:59,081 were actually known. 647 00:39:01,970 --> 00:39:05,510 That led ultimately to the cloning of the RB gene, 648 00:39:05,510 --> 00:39:08,505 the retinoblastoma susceptibility gene called RB. 649 00:39:11,120 --> 00:39:12,500 Also in Bob Weinberg's lab. 650 00:39:15,520 --> 00:39:17,540 Which encodes a protein called pRB. 651 00:39:22,670 --> 00:39:25,370 And further work in Weinberg's lab and many others 652 00:39:25,370 --> 00:39:29,150 showed why cells get rid of the RB gene 653 00:39:29,150 --> 00:39:31,970 in the development of that cancer as well 654 00:39:31,970 --> 00:39:35,320 as other cancers. 655 00:39:35,320 --> 00:39:37,990 The RB gene is now-- or the protein that it encodes-- 656 00:39:37,990 --> 00:39:42,040 is now known to be an important regulator of the cell cycle. 657 00:39:42,040 --> 00:39:44,470 We learned about the cell cycle. 658 00:39:44,470 --> 00:39:50,590 Cells go from my mitosis G1, into S phase, and then G2, 659 00:39:50,590 --> 00:39:53,200 and then into mitosis again. 660 00:39:53,200 --> 00:39:55,120 This is a regulated process. 661 00:39:55,120 --> 00:39:59,500 And the RB gene or protein is important in controlling it. 662 00:40:03,170 --> 00:40:08,720 The RB protein acts here by blocking the transition from G1 663 00:40:08,720 --> 00:40:10,490 into S, and I'll tell you a bit more 664 00:40:10,490 --> 00:40:13,320 how it does so in a moment. 665 00:40:13,320 --> 00:40:15,610 This is when the protein is in its active state. 666 00:40:18,740 --> 00:40:22,220 It can be inactivated through phosphorylation. 667 00:40:31,540 --> 00:40:33,900 A phosphate group, actually many phosphate groups, 668 00:40:33,900 --> 00:40:36,360 can be transferred onto the RB gene 669 00:40:36,360 --> 00:40:40,061 through kinases, which are stimulated by growth promoting 670 00:40:40,061 --> 00:40:40,560 signals. 671 00:40:52,190 --> 00:40:54,440 Growth factor binding to a cell will ultimately 672 00:40:54,440 --> 00:40:57,190 result in the stimulation of these kinases 673 00:40:57,190 --> 00:40:59,990 to phosphorylate the RB protein, taking it 674 00:40:59,990 --> 00:41:06,380 from this active state to its phosphorylated state, which 675 00:41:06,380 --> 00:41:07,250 is inactive. 676 00:41:12,360 --> 00:41:16,430 So the break is released because the kinases inactivate 677 00:41:16,430 --> 00:41:18,650 the break, OK. 678 00:41:18,650 --> 00:41:20,690 Just a little bit more detail about RB. 679 00:41:24,860 --> 00:41:28,260 A lot is known about this process now. 680 00:41:28,260 --> 00:41:33,120 This transition from G1 into S requires 681 00:41:33,120 --> 00:41:36,865 some transcription factors called E2F transcription 682 00:41:36,865 --> 00:41:37,365 factors. 683 00:41:45,720 --> 00:41:50,887 And RB binds and inactivates the RB transcription factors, 684 00:41:50,887 --> 00:41:51,720 keeping them silent. 685 00:41:56,450 --> 00:42:01,610 When it's an active state RB has a little pocket 686 00:42:01,610 --> 00:42:05,060 to which the E2F transcription factors bind. 687 00:42:05,060 --> 00:42:10,010 Here's pRB, and here are the E2F transcription factors 688 00:42:10,010 --> 00:42:12,350 and they are sequestered by the RB protein 689 00:42:12,350 --> 00:42:14,810 and can't otherwise do their job. 690 00:42:14,810 --> 00:42:20,510 But when RB gets phosphorylated by those kinases 691 00:42:20,510 --> 00:42:25,670 these phosphate groups interfere with the binding of E2F, 692 00:42:25,670 --> 00:42:29,780 and E2F is then liberated to carry out its normal function 693 00:42:29,780 --> 00:42:32,110 driving this transition. 694 00:42:32,110 --> 00:42:33,110 OK. 695 00:42:33,110 --> 00:42:35,120 So this is how the break functions and it's 696 00:42:35,120 --> 00:42:36,380 a very, very important break. 697 00:42:36,380 --> 00:42:41,030 RB is mutated in a very high percentage of cancer cells, 698 00:42:41,030 --> 00:42:43,670 not just retinoblastomas but many others as well. 699 00:42:43,670 --> 00:42:46,460 And the pathway that it is controlled by 700 00:42:46,460 --> 00:42:48,830 is likewise mutated in a high frequency. 701 00:42:51,580 --> 00:42:56,130 Tumor suppressor genes, like RB, are the breaks. 702 00:42:56,130 --> 00:42:59,290 They negatively regulate proliferation. 703 00:43:11,060 --> 00:43:15,350 As such, are these genes normally hyper 704 00:43:15,350 --> 00:43:17,760 activated or inactivated in cancer? 705 00:43:20,420 --> 00:43:23,180 Hyper activated or inactivated? 706 00:43:23,180 --> 00:43:24,400 Inactivated. 707 00:43:39,110 --> 00:43:42,620 That's in contrast to the oncogenes which get activated, 708 00:43:42,620 --> 00:43:44,630 hyper activated. 709 00:43:44,630 --> 00:43:46,515 These get inactivated or lost. 710 00:43:58,250 --> 00:44:02,930 These inactivating mutations are recessive. 711 00:44:02,930 --> 00:44:08,910 They are loss of function, again, 712 00:44:08,910 --> 00:44:11,910 in contrast to the situation with oncogenes 713 00:44:11,910 --> 00:44:16,420 which are dominant mutations, gain of function. 714 00:44:16,420 --> 00:44:19,327 And this actually creates an interesting challenge for us. 715 00:44:22,530 --> 00:44:25,620 If these are recessive mutations and a cell 716 00:44:25,620 --> 00:44:28,890 acquires a mutation in one copy of the RB gene-- 717 00:44:28,890 --> 00:44:33,240 and I'll just show the chromosomes on which RB exists. 718 00:44:33,240 --> 00:44:35,790 Happens to be chromosome 13. 719 00:44:35,790 --> 00:44:39,720 We have a normal cell, say it's a normal cell in the developing 720 00:44:39,720 --> 00:44:41,070 retina. 721 00:44:41,070 --> 00:44:42,720 And that cell incurs a mutation. 722 00:44:47,620 --> 00:44:50,230 Random chance, cigarette smoking, 723 00:44:50,230 --> 00:44:54,430 probably not in this child, but random chance. 724 00:44:54,430 --> 00:44:58,990 Leads to the inactivation of one copy of the RB gene. 725 00:44:58,990 --> 00:45:00,410 What's the phenotype of this cell? 726 00:45:03,930 --> 00:45:04,610 It's normal. 727 00:45:07,570 --> 00:45:09,670 These are recessive mutations. 728 00:45:09,670 --> 00:45:13,060 Having one normal copy is sufficient to provide 729 00:45:13,060 --> 00:45:17,300 RB protein, to provide control of the cell cycle. 730 00:45:17,300 --> 00:45:19,270 So the cell is normal but the cell 731 00:45:19,270 --> 00:45:26,290 is predisposed because now it only 732 00:45:26,290 --> 00:45:29,582 has one functional copy left. 733 00:45:29,582 --> 00:45:31,165 We could call this the first mutation. 734 00:45:34,350 --> 00:45:37,100 And now within this clone of cells 735 00:45:37,100 --> 00:45:42,080 if a second mutation occurs then we're in trouble. 736 00:45:42,080 --> 00:45:44,360 And the second mutation can occur in one 737 00:45:44,360 --> 00:45:45,780 of a couple of different ways. 738 00:45:45,780 --> 00:45:55,340 For example, it could be that by random chance, bad luck 739 00:45:55,340 --> 00:45:57,995 the normal copy on the other chromosome gets mutated. 740 00:46:00,850 --> 00:46:03,940 Or it could be, and it's actually more frequent, 741 00:46:03,940 --> 00:46:06,085 that a chromosomal event takes place. 742 00:46:08,840 --> 00:46:12,940 For example, a cell arises which only has one chromosome 13 743 00:46:12,940 --> 00:46:15,740 through chromosomal non-disjunction. 744 00:46:15,740 --> 00:46:18,820 And it's the one with the mutant copy. 745 00:46:18,820 --> 00:46:21,960 These are functionally equivalent. 746 00:46:21,960 --> 00:46:24,442 Both of these cells are RB deficient. 747 00:46:28,220 --> 00:46:33,810 And they are on their way to becoming cancers. 748 00:46:33,810 --> 00:46:36,960 Tumor suppressor genes therefore require two hits. 749 00:46:45,430 --> 00:46:48,970 Two hits, two mutational events to inactivate the two 750 00:46:48,970 --> 00:46:50,560 normal copies of the gene. 751 00:46:50,560 --> 00:46:53,179 They can be two mutations within the gene 752 00:46:53,179 --> 00:46:54,970 or they can be one mutation within the gene 753 00:46:54,970 --> 00:46:56,350 plus some chromosomal event. 754 00:46:56,350 --> 00:46:58,800 And I've shown you one example here, there are others. 755 00:47:02,080 --> 00:47:04,010 OK. 756 00:47:04,010 --> 00:47:05,450 So that looks good. 757 00:47:05,450 --> 00:47:07,775 Everybody gets it right, no problems? 758 00:47:07,775 --> 00:47:10,150 Let me show you this picture, which I actually showed you 759 00:47:10,150 --> 00:47:12,220 on the first day of class. 760 00:47:12,220 --> 00:47:16,780 This is a child who has bilateral, 761 00:47:16,780 --> 00:47:20,170 multi-focal retinoblastoma. 762 00:47:20,170 --> 00:47:25,900 This child has 12 different retinoblastoma tumors 763 00:47:25,900 --> 00:47:29,070 affecting both eyes. 764 00:47:29,070 --> 00:47:32,880 Not only that, this child comes from a family 765 00:47:32,880 --> 00:47:34,740 in which retinoblastoma is passing 766 00:47:34,740 --> 00:47:37,590 through the generations. 767 00:47:37,590 --> 00:47:40,800 The grandfather had it, he passed on the predisposition 768 00:47:40,800 --> 00:47:44,100 to multiple of his children, who passed on the predisposition 769 00:47:44,100 --> 00:47:47,000 to multiple of their children. 770 00:47:47,000 --> 00:47:50,360 This is an example of a familial cancer syndrome. 771 00:48:07,180 --> 00:48:09,430 Familial predisposition to cancer. 772 00:48:09,430 --> 00:48:12,670 Most cancers don't have this kind of pedigree. 773 00:48:12,670 --> 00:48:16,210 Most cancers are sporadic, but about 10% of cancers 774 00:48:16,210 --> 00:48:19,090 look like this with a clear family history. 775 00:48:19,090 --> 00:48:22,630 Familial retinoblastoma, familial breast cancer, 776 00:48:22,630 --> 00:48:26,110 familial colon cancer, and there are others. 777 00:48:26,110 --> 00:48:29,551 These are caused by mutations in genes like this. 778 00:48:29,551 --> 00:48:31,270 This individual that I showed you, 779 00:48:31,270 --> 00:48:34,000 the individuals in this family have 780 00:48:34,000 --> 00:48:40,980 inherited a defective copy of the gene 781 00:48:40,980 --> 00:48:43,310 from one of their parents. 782 00:48:43,310 --> 00:48:46,010 And as such they have this genotype. 783 00:48:46,010 --> 00:48:49,400 They are heterozygous for an RB mutation. 784 00:48:49,400 --> 00:48:52,580 Heterozygous for an RB mutation. 785 00:48:52,580 --> 00:48:55,580 And because they're heterozygous for an RB mutation 786 00:48:55,580 --> 00:48:59,420 they are highly predisposed to developing retinoblastoma. 787 00:48:59,420 --> 00:49:02,750 And the reason is that within their cells, 788 00:49:02,750 --> 00:49:06,040 within the developing retinal cells in their body 789 00:49:06,040 --> 00:49:08,870 two mutational events are not required. 790 00:49:08,870 --> 00:49:19,200 Instead in them, all of their cells look like this. 791 00:49:19,200 --> 00:49:24,650 All of their cells are in that heterozygous predisposed state. 792 00:49:24,650 --> 00:49:28,820 And therefore in them, a single hit 793 00:49:28,820 --> 00:49:34,430 is required to give rise to a cell that is lacking 794 00:49:34,430 --> 00:49:37,900 the function of RB altogether. 795 00:49:37,900 --> 00:49:39,910 And that's why they're predisposed. 796 00:49:39,910 --> 00:49:43,810 And that's why BRCA1 patients get breast cancer, 797 00:49:43,810 --> 00:49:47,980 and why APC patients get familial colon cancer. 798 00:49:47,980 --> 00:49:51,220 This slide also raises for you some interesting questions 799 00:49:51,220 --> 00:49:53,290 and we'll talk about them next time. 800 00:49:53,290 --> 00:49:55,870 Here's a person who has the right genotype 801 00:49:55,870 --> 00:49:57,520 but he didn't get the disease. 802 00:49:57,520 --> 00:49:58,930 Why not? 803 00:49:58,930 --> 00:50:00,850 And another question, what would happen 804 00:50:00,850 --> 00:50:04,330 if two individuals who were heterozygous for the mutation 805 00:50:04,330 --> 00:50:08,200 were to marry, have a child who was homozygous for an RB gene 806 00:50:08,200 --> 00:50:09,290 mutation? 807 00:50:09,290 --> 00:50:10,840 What would happen then? 808 00:50:10,840 --> 00:50:13,260 We'll talk about that next time.