1 00:00:01,413 --> 00:00:05,627 It was a Sunday afternoon back in April of this year, 2 00:00:05,651 --> 00:00:06,984 my phone was ringing. 3 00:00:07,524 --> 00:00:09,476 I picked it up, 4 00:00:09,500 --> 00:00:11,141 the voice said, 5 00:00:11,165 --> 00:00:12,394 "It's Rebecca. 6 00:00:12,847 --> 00:00:16,698 I'm just calling to invite you to my funeral." 7 00:00:18,339 --> 00:00:21,569 I said, "Rebecca, what are you talking about?" 8 00:00:21,593 --> 00:00:23,514 She said, "Joy, 9 00:00:23,538 --> 00:00:26,721 as my friend, you have to let me go. 10 00:00:27,235 --> 00:00:28,385 It's my time." 11 00:00:29,854 --> 00:00:32,179 The next day, she was dead. 12 00:00:34,021 --> 00:00:37,179 Rebecca was 31 years old when she died. 13 00:00:37,657 --> 00:00:41,506 She had an eight-year struggle with breast cancer, 14 00:00:41,530 --> 00:00:43,196 it came back three times. 15 00:00:43,879 --> 00:00:45,536 I failed her. 16 00:00:46,642 --> 00:00:49,042 The scientific community failed her. 17 00:00:49,579 --> 00:00:52,046 And the medical community failed her. 18 00:00:53,254 --> 00:00:55,054 And she's not the only one. 19 00:00:55,674 --> 00:00:57,569 Every five seconds, 20 00:00:57,593 --> 00:01:00,029 someone dies of cancer. 21 00:01:01,371 --> 00:01:05,659 Today, we, medical researchers are committed 22 00:01:05,683 --> 00:01:08,945 to having Rebecca and people like her 23 00:01:08,969 --> 00:01:11,769 be one of the last patients that we fail. 24 00:01:12,569 --> 00:01:17,049 The US government alone has spent over 100 billion 25 00:01:17,073 --> 00:01:18,613 on cancer research 26 00:01:18,637 --> 00:01:20,257 since the 1970s, 27 00:01:20,281 --> 00:01:23,882 with limited progress in regards to patient survival. 28 00:01:24,236 --> 00:01:28,036 Especially for certain types of very aggressive cancers. 29 00:01:28,950 --> 00:01:31,155 So we need a change, because clearly, 30 00:01:31,179 --> 00:01:35,193 what we've been doing so far has not been working. 31 00:01:36,679 --> 00:01:39,966 And what we do in medicine is to send out firefighters, 32 00:01:39,990 --> 00:01:42,257 because cancer is like a big fire. 33 00:01:42,784 --> 00:01:45,577 And these firefighters are the cancer drugs. 34 00:01:46,228 --> 00:01:49,815 But we're sending them out without a fire truck. 35 00:01:50,315 --> 00:01:53,482 So without transportation, without ladders, 36 00:01:53,506 --> 00:01:55,639 and without emergency equipment. 37 00:01:56,657 --> 00:02:00,871 And over 99 percent of these firefighters 38 00:02:00,895 --> 00:02:02,628 never make it to the fire. 39 00:02:03,553 --> 00:02:06,268 Over 99 percent of cancer drugs 40 00:02:06,292 --> 00:02:08,582 never make it to the tumor, 41 00:02:08,606 --> 00:02:12,836 because they lack transportation and tools 42 00:02:12,860 --> 00:02:16,463 to take them to the location they're aiming for. 43 00:02:17,999 --> 00:02:22,199 Turns out, it really is all about location, location, location. 44 00:02:23,063 --> 00:02:27,301 So we need a fire truck to get to the right location. 45 00:02:28,403 --> 00:02:29,974 And I'm here to tell you 46 00:02:29,998 --> 00:02:32,847 that nanoparticles are the fire trucks. 47 00:02:33,323 --> 00:02:37,405 We can load cancer drugs inside nanoparticles 48 00:02:37,429 --> 00:02:41,079 and nanoparticles can function as the carrier 49 00:02:41,103 --> 00:02:42,984 and necessary equipment 50 00:02:43,008 --> 00:02:46,579 to bring the cancer drugs to the heart of the tumor. 51 00:02:48,315 --> 00:02:49,817 So what are nanoparticles 52 00:02:49,841 --> 00:02:52,608 and what does it really mean to be nano-sized? 53 00:02:53,664 --> 00:02:57,037 Well, there are many different types of nanoparticles 54 00:02:57,061 --> 00:02:58,736 made out of various materials, 55 00:02:58,760 --> 00:03:02,133 such as metal-based nanoparticles 56 00:03:02,157 --> 00:03:04,529 or fat-based nanoparticles. 57 00:03:05,309 --> 00:03:08,880 But to really illustrate what it means to be nano-sized, 58 00:03:08,904 --> 00:03:11,658 I took one of my hair strands 59 00:03:11,682 --> 00:03:13,649 and placed it under the microscope. 60 00:03:14,094 --> 00:03:15,562 Now, I have very thin hair, 61 00:03:15,586 --> 00:03:20,632 so my hair is approximately 40,000 nanometers in diameter. 62 00:03:21,284 --> 00:03:24,268 So this means, if we take 400 of nanoparticles 63 00:03:24,292 --> 00:03:27,260 and we stack them on top of each other, 64 00:03:27,284 --> 00:03:30,855 we get the thickness of a single hair strand. 65 00:03:31,577 --> 00:03:34,243 So I lead a nanoparticle laboratory 66 00:03:34,267 --> 00:03:37,172 to fight cancer and other diseases 67 00:03:37,196 --> 00:03:39,596 at Mayo Clinic here in Jacksonville. 68 00:03:40,228 --> 00:03:41,394 And at Mayo Clinic, 69 00:03:41,418 --> 00:03:45,121 we really have the tools to make a difference for patients, 70 00:03:45,145 --> 00:03:49,978 thanks to the generous donations and grants to fund our research. 71 00:03:51,574 --> 00:03:55,981 And so, how do these nanoparticles manage to transport cancer drugs 72 00:03:56,005 --> 00:03:57,155 to the tumor? 73 00:03:57,807 --> 00:04:00,751 Well, they have an extensive toolbox. 74 00:04:01,982 --> 00:04:04,188 So cancer drugs without nanoparticles 75 00:04:04,212 --> 00:04:07,857 are quickly washed out of the body through the kidneys 76 00:04:07,881 --> 00:04:09,826 because they are so small. 77 00:04:09,850 --> 00:04:12,152 So it's like water going through a sieve. 78 00:04:12,628 --> 00:04:15,770 And so they don't really have time to reach the tumor, 79 00:04:15,794 --> 00:04:18,022 and here we see an illustration of this. 80 00:04:18,046 --> 00:04:20,252 We have the firefighters, the cancer drugs, 81 00:04:20,276 --> 00:04:22,387 they're circulating in the blood, 82 00:04:22,411 --> 00:04:24,434 but they're quickly washed out of the body 83 00:04:24,458 --> 00:04:27,592 and they don't really end up inside the tumor. 84 00:04:28,450 --> 00:04:33,077 But if we put these cancer drugs inside nanoparticles, 85 00:04:33,101 --> 00:04:35,188 they will not get washed out by the body, 86 00:04:35,212 --> 00:04:37,529 because the nanoparticles are too big. 87 00:04:37,553 --> 00:04:40,731 And they will continue to circulate in the blood, 88 00:04:40,755 --> 00:04:43,473 giving them more time to find the tumor. 89 00:04:44,252 --> 00:04:46,823 And here we see the cancer drugs, the firefighters, 90 00:04:46,847 --> 00:04:50,289 inside the fire truck, the nanoparticles. 91 00:04:50,313 --> 00:04:51,988 They're circulating in the blood, 92 00:04:52,012 --> 00:04:53,948 they don't get washed out, 93 00:04:53,972 --> 00:04:57,138 and they actually end up reaching the tumor. 94 00:04:59,480 --> 00:05:01,898 And so what other tools do nanoparticles have? 95 00:05:02,785 --> 00:05:06,428 Well, they can protect cancer drugs from getting destroyed 96 00:05:06,452 --> 00:05:07,602 inside the body. 97 00:05:08,293 --> 00:05:12,053 There are certain very important but sensitive drugs 98 00:05:12,077 --> 00:05:15,029 that are easily degraded by enzymes in the blood. 99 00:05:15,339 --> 00:05:18,625 So unless they have this nanoparticle protection, 100 00:05:18,649 --> 00:05:20,934 they will not be able to function. 101 00:05:22,362 --> 00:05:25,363 Another nanoparticle tool are the surface extensions 102 00:05:25,387 --> 00:05:30,506 that are like tiny hands with fingers that grab on to the tumor, 103 00:05:30,530 --> 00:05:32,117 and fit exactly onto it, 104 00:05:32,141 --> 00:05:34,426 so that when the nanoparticles are circulating, 105 00:05:34,450 --> 00:05:37,006 they can attach onto the cancer cells, 106 00:05:37,030 --> 00:05:40,591 buying the cancer drugs more time to do their job. 107 00:05:41,887 --> 00:05:44,133 And these are just some of the many tools 108 00:05:44,157 --> 00:05:46,023 that nanoparticles can have. 109 00:05:46,585 --> 00:05:47,760 And today, 110 00:05:47,784 --> 00:05:51,974 we have more than 10 clinically approved nanoparticles for cancer 111 00:05:51,998 --> 00:05:55,164 that are given to patients all over the world. 112 00:05:56,069 --> 00:06:00,362 Yet, we have patients like Rebecca, who die. 113 00:06:01,362 --> 00:06:05,275 So what are the major challenges and limitations 114 00:06:05,299 --> 00:06:08,088 with currently approved nanoparticles? 115 00:06:09,501 --> 00:06:12,938 Well, a major challenge is the liver, 116 00:06:12,962 --> 00:06:16,033 because the liver is the body's filtration system, 117 00:06:16,057 --> 00:06:20,969 and the liver recognizes and destroys foreign objects, such as viruses 118 00:06:20,993 --> 00:06:23,731 bacteria and also nanoparticles. 119 00:06:24,231 --> 00:06:27,580 And the immune cells in the liver eat the nanoparticles, 120 00:06:27,604 --> 00:06:30,961 preventing them from reaching the tumor. 121 00:06:33,367 --> 00:06:37,136 And here we see an illustration where the kidney is no longer a problem, 122 00:06:37,160 --> 00:06:39,580 but these fire trucks, the nanoparticles, 123 00:06:39,604 --> 00:06:41,267 get stuck in the liver, 124 00:06:41,291 --> 00:06:45,589 and actually, less of them end up reaching the tumor. 125 00:06:47,164 --> 00:06:50,462 So a future strategy to improve nanoparticles 126 00:06:50,486 --> 00:06:54,708 is to temporarily disarm the immune cells in the liver. 127 00:06:55,399 --> 00:06:57,532 So how do we disarm these cells? 128 00:06:57,883 --> 00:07:01,515 Well, we looked at drugs that were already clinically approved 129 00:07:01,539 --> 00:07:03,395 for other indications 130 00:07:03,419 --> 00:07:06,196 to see if any of them could stop the immune cells 131 00:07:06,220 --> 00:07:08,815 from eating the nanoparticles. 132 00:07:09,776 --> 00:07:11,307 And unexpectedly, 133 00:07:11,331 --> 00:07:13,942 in one of our preclinical studies, 134 00:07:13,966 --> 00:07:18,104 we found that a 70-year-old malaria drug 135 00:07:18,128 --> 00:07:20,826 was able to stop the immune cells 136 00:07:20,850 --> 00:07:22,958 from internalizing the nanoparticles 137 00:07:22,982 --> 00:07:25,212 so that they could escape the liver 138 00:07:25,236 --> 00:07:29,196 and continue their journey to their goal, the tumor. 139 00:07:30,538 --> 00:07:33,689 And here we see the illustration of blocking the liver. 140 00:07:33,713 --> 00:07:35,546 The nanoparticles don't go there, 141 00:07:35,570 --> 00:07:38,037 and they instead end up in the tumor. 142 00:07:39,141 --> 00:07:42,030 So, sometimes, unexpected connections 143 00:07:42,054 --> 00:07:43,831 are made in science, 144 00:07:43,855 --> 00:07:46,132 that lead to new solutions. 145 00:07:47,919 --> 00:07:51,630 Another strategy for preventing nanoparticles 146 00:07:51,654 --> 00:07:54,196 from getting stuck in the liver 147 00:07:54,220 --> 00:07:57,450 is to use the body's own nanoparticles. 148 00:07:57,474 --> 00:07:58,942 Yes, surprise, surprise, 149 00:07:58,966 --> 00:08:02,544 you, and you and you, and all of us 150 00:08:02,568 --> 00:08:05,940 have a lot of nanoparticles circulating in our bodies. 151 00:08:06,434 --> 00:08:09,069 And because they're part of our bodies, 152 00:08:09,093 --> 00:08:13,018 the liver is less likely to label them as foreign. 153 00:08:14,998 --> 00:08:16,958 And these biological nanoparticles 154 00:08:16,982 --> 00:08:18,712 can be found in the saliva, 155 00:08:18,736 --> 00:08:21,958 in the blood, in the urine, in pancreatic juice, 156 00:08:21,982 --> 00:08:23,975 and we can collect them from the body 157 00:08:23,999 --> 00:08:27,846 and use them as fire trucks for cancer drugs. 158 00:08:28,855 --> 00:08:30,093 And in this case, 159 00:08:30,117 --> 00:08:33,283 the immune cells in the liver are less likely to eat 160 00:08:33,307 --> 00:08:35,241 the biological nanoparticles. 161 00:08:35,691 --> 00:08:38,619 So we're using a Trojan horse-based concept 162 00:08:38,643 --> 00:08:40,230 to fool the liver. 163 00:08:40,921 --> 00:08:43,278 And here we see the biological nanoparticles 164 00:08:43,302 --> 00:08:44,881 circulating in the blood, 165 00:08:44,905 --> 00:08:47,301 they don't get recognized by the liver, 166 00:08:47,325 --> 00:08:49,259 and they end up in the tumor. 167 00:08:50,413 --> 00:08:51,849 And in the future, 168 00:08:51,873 --> 00:08:55,396 we want to exploit nature's own nanoparticles 169 00:08:55,420 --> 00:08:58,363 for cancer drug delivery, 170 00:08:58,387 --> 00:09:01,323 to reduce side effects and save lives, 171 00:09:01,347 --> 00:09:06,267 by preventing the cancer drugs from being in the wrong location. 172 00:09:07,762 --> 00:09:09,952 However, a major problem has been 173 00:09:09,976 --> 00:09:14,270 how do we isolate these biological nanoparticles 174 00:09:14,294 --> 00:09:17,500 in large quantities, without damaging them? 175 00:09:18,915 --> 00:09:21,787 My lab has developed an efficient method for doing this. 176 00:09:21,811 --> 00:09:26,248 We can process large quantities of liquids from the body 177 00:09:26,272 --> 00:09:31,057 to produce a highly concentrated, high-quality formulation 178 00:09:31,081 --> 00:09:32,948 of biological nanoparticles. 179 00:09:34,136 --> 00:09:38,279 And these nanoparticles are not yet in clinical use, 180 00:09:38,303 --> 00:09:41,315 because it takes an average of 12 years 181 00:09:41,339 --> 00:09:43,775 to get something from the lab 182 00:09:43,799 --> 00:09:45,791 to your medicine cabinet. 183 00:09:48,093 --> 00:09:50,434 And this is the type of challenge 184 00:09:50,458 --> 00:09:55,958 that requires team work from scientists and physicians, 185 00:09:55,982 --> 00:09:58,910 who dedicate their lives to this battle. 186 00:10:00,149 --> 00:10:01,585 And we keep going 187 00:10:01,609 --> 00:10:04,762 thanks to inspiration from patients. 188 00:10:05,532 --> 00:10:09,691 And I believe that if we keep working on these nanomedicines, 189 00:10:09,715 --> 00:10:13,537 we will be able to reduce harm to healthy organs, 190 00:10:13,561 --> 00:10:15,307 improve quality of life, 191 00:10:15,331 --> 00:10:17,783 and save future patients. 192 00:10:20,363 --> 00:10:22,593 I like to imagine 193 00:10:22,617 --> 00:10:27,745 that if these treatments had been available for Rebecca, 194 00:10:27,769 --> 00:10:29,761 that call from her 195 00:10:29,785 --> 00:10:32,492 could have been an invitation, 196 00:10:32,516 --> 00:10:34,182 not to her funeral, 197 00:10:34,206 --> 00:10:35,372 but her wedding. 198 00:10:35,396 --> 00:10:36,761 Thank you. 199 00:10:36,785 --> 00:10:40,020 (Applause)