WEBVTT 1 00:00:00.720 --> 00:00:02.670 Hello, and welcome to the second part 2 00:00:02.670 --> 00:00:05.703 of our lecture on breast cancer epidemiology. 3 00:00:06.720 --> 00:00:07.553 In this lecture, 4 00:00:07.553 --> 00:00:10.560 we're going to turn to breast cancer prevention. 5 00:00:10.560 --> 00:00:15.560 So to begin with, we see where we'll discuss tamoxifen. 6 00:00:17.460 --> 00:00:20.681 So a key aspect of breast cancer 7 00:00:20.681 --> 00:00:24.030 is that breast cancer specimens 8 00:00:24.030 --> 00:00:26.130 or tissues that are collected 9 00:00:26.130 --> 00:00:29.010 via biopsy or surgical procedures like mastectomy 10 00:00:29.010 --> 00:00:31.620 are routinely subjected to laboratory analysis 11 00:00:31.620 --> 00:00:34.770 of estrogen receptors and progesterone receptors. 12 00:00:34.770 --> 00:00:37.290 Again, estrogen and progesterone being two key hormones 13 00:00:37.290 --> 00:00:41.193 that may play a role in breast cancer risk or prevention. 14 00:00:42.210 --> 00:00:44.070 Breast tumors, which are positive 15 00:00:44.070 --> 00:00:46.080 for estrogen receptors may respond 16 00:00:46.080 --> 00:00:47.760 to hormone therapy by the administration 17 00:00:47.760 --> 00:00:50.520 of selective estrogen receptor modulators 18 00:00:50.520 --> 00:00:53.280 or sSERMs like tamoxifen. 19 00:00:53.280 --> 00:00:55.290 Tamoxifen is now being offered to women treated 20 00:00:55.290 --> 00:00:57.600 for early stage breast cancer for protection 21 00:00:57.600 --> 00:01:00.030 against the development of second primary cancer 22 00:01:00.030 --> 00:01:03.153 in the contralateral breast or the other breast. 23 00:01:03.990 --> 00:01:05.010 In the US, 24 00:01:05.010 --> 00:01:07.860 the Food and Drug Administration has also approved tamoxifen 25 00:01:07.860 --> 00:01:10.773 for use as a preventive agent in high-risk women. 26 00:01:11.771 --> 00:01:15.750 And the use of tamoxifen really came from the results 27 00:01:15.750 --> 00:01:18.450 of four randomized clinical trials that looked 28 00:01:18.450 --> 00:01:20.800 at the possibility of breast cancer prevention. 29 00:01:21.780 --> 00:01:24.210 Of these trials, one of them performed 30 00:01:24.210 --> 00:01:28.560 in the US showed beneficial effects, and also, 31 00:01:28.560 --> 00:01:30.810 there were two European trials 32 00:01:30.810 --> 00:01:33.360 that did not find any effects. 33 00:01:33.360 --> 00:01:35.970 In a fourth trial conducted in European centers, 34 00:01:35.970 --> 00:01:37.410 tamoxifen reduced the incidence 35 00:01:37.410 --> 00:01:40.530 of breast cancer by 32% compared to a placebo 36 00:01:40.530 --> 00:01:42.240 but there was a significant excess 37 00:01:42.240 --> 00:01:44.283 of deaths in the tamoxifen group. 38 00:01:45.622 --> 00:01:48.360 So there's several adverse side effects 39 00:01:48.360 --> 00:01:51.750 of tamoxifen as well, including endometrial cancer, 40 00:01:51.750 --> 00:01:54.600 estrogen receptor negative breast cancer, colon cancer, 41 00:01:54.600 --> 00:01:57.753 pulmonary embolism, and other thrombotic events. 42 00:02:01.860 --> 00:02:03.420 The appearance of the breast 43 00:02:03.420 --> 00:02:05.220 on a mammogram facilitates the partition 44 00:02:05.220 --> 00:02:10.220 of tissues into different areas, looking at zones 45 00:02:11.760 --> 00:02:13.590 that are primarily composed of adipose 46 00:02:13.590 --> 00:02:16.200 or fat tissue and zones that are made mostly 47 00:02:16.200 --> 00:02:19.320 of fibrous and glandular tissue. 48 00:02:19.320 --> 00:02:23.220 In 1976, John Wolfe, a radiologist in Detroit, Michigan 49 00:02:23.220 --> 00:02:24.810 was the first to describe differences 50 00:02:24.810 --> 00:02:27.720 in breast cancer risk associated with variations 51 00:02:27.720 --> 00:02:30.363 in the mammographic appearances of the breast. 52 00:02:31.200 --> 00:02:32.670 And here we see 53 00:02:32.670 --> 00:02:36.630 that one's breast cancer risk increases 54 00:02:36.630 --> 00:02:40.233 when someone has a higher percentage of dense breast tissue. 55 00:02:41.670 --> 00:02:44.670 Next, looking at NSAIDs or again, 56 00:02:44.670 --> 00:02:47.280 these anti-inflammatory drugs, 57 00:02:47.280 --> 00:02:49.110 we see that many epidemiologic studies 58 00:02:49.110 --> 00:02:50.940 have noted a significant preventive effect 59 00:02:50.940 --> 00:02:53.100 of non-steroidal anti-inflammatory drugs 60 00:02:53.100 --> 00:02:55.680 or NSAIDs against breast cancer. 61 00:02:55.680 --> 00:02:59.490 A meta-analysis of these investigations, which is depicted 62 00:02:59.490 --> 00:03:02.880 on this slide, comparing all these many different studies, 63 00:03:02.880 --> 00:03:04.530 suggests that the risk of breast cancer 64 00:03:04.530 --> 00:03:06.780 is reduced by approximately 25% 65 00:03:06.780 --> 00:03:09.720 with regular use of common over-the-counter NSAIDs, 66 00:03:09.720 --> 00:03:11.523 like aspirin and ibuprofen. 67 00:03:12.450 --> 00:03:14.490 Studies in molecular epidemiology 68 00:03:14.490 --> 00:03:17.460 in animals suggest this effect is manifest primarily due 69 00:03:17.460 --> 00:03:22.460 to blockade of Cyclooxygenase-2 or the COX-2 enzyme, 70 00:03:22.950 --> 00:03:25.200 which is a rate-limiting inducible enzyme 71 00:03:25.200 --> 00:03:26.883 of the inflammatory cascade. 72 00:03:30.150 --> 00:03:32.550 As mentioned before, some of the key findings 73 00:03:32.550 --> 00:03:34.290 about breast cancer risk 74 00:03:34.290 --> 00:03:35.970 and breast cancer prevention were drawn 75 00:03:35.970 --> 00:03:40.140 from the Women's Health Initiative Observational Cohort. 76 00:03:40.140 --> 00:03:45.060 In this study, 80,741 women took part 77 00:03:45.060 --> 00:03:47.640 without cancer at baseline. 78 00:03:47.640 --> 00:03:49.980 These women were 50 to 79 years of age 79 00:03:49.980 --> 00:03:52.653 and baseline data on NSAID use was collected. 80 00:03:53.640 --> 00:03:56.340 When collecting four years of follow-up data 81 00:03:56.340 --> 00:03:59.070 or nearly 300,000 person years, 82 00:03:59.070 --> 00:04:03.600 1,392 cases of breast cancer were detected. 83 00:04:03.600 --> 00:04:05.700 This showed that there was an annual breast cancer rate 84 00:04:05.700 --> 00:04:08.223 of 481 per 105. 85 00:04:09.540 --> 00:04:11.100 Conclusions from the study found 86 00:04:11.100 --> 00:04:13.980 that NSAIDs reduced breast cancer risk by 28% 87 00:04:13.980 --> 00:04:18.980 and ibuprofen or taking ibuprofen reduced the risk by 49%. 88 00:04:19.440 --> 00:04:22.860 But at the same time, acetaminophen had no effect. 89 00:04:22.860 --> 00:04:24.540 The key mechanism of action 90 00:04:24.540 --> 00:04:28.563 was blocking the COX-2 inflammatory cascade. 91 00:04:31.260 --> 00:04:33.120 So again, circling back 92 00:04:33.120 --> 00:04:36.210 to prostaglandins and estrogens one last time, 93 00:04:36.210 --> 00:04:38.790 we see the u pregulation of prostaglandins by induction 94 00:04:38.790 --> 00:04:42.150 of the COX-2 gene, stimulates estrogen biosynthesis 95 00:04:42.150 --> 00:04:45.870 by activation of the promoter II region of the CYP-19, 96 00:04:45.870 --> 00:04:47.790 our aromatase gene, 97 00:04:47.790 --> 00:04:50.820 and the key names of the CYP-19 gene 98 00:04:50.820 --> 00:04:53.910 and the promoter II region are not as important 99 00:04:53.910 --> 00:04:55.500 as remembering that prostaglandins 100 00:04:55.500 --> 00:04:57.870 and estrogens play a key role 101 00:04:57.870 --> 00:04:59.640 in the development of breast cancer. 102 00:04:59.640 --> 00:05:04.560 And that COX-2 is an intermediate element of that cascade. 103 00:05:04.560 --> 00:05:07.530 So as noted in the WHI study, 104 00:05:07.530 --> 00:05:11.790 blocking that COX-2 mode of action has the potential 105 00:05:11.790 --> 00:05:15.810 to lower one's risk for breast cancer. 106 00:05:15.810 --> 00:05:18.840 And some of that is depicted here in this figure 107 00:05:18.840 --> 00:05:19.950 that has a lot going on 108 00:05:19.950 --> 00:05:22.590 and it's certainly not important to know all 109 00:05:22.590 --> 00:05:26.940 of these different steps that may take part 110 00:05:26.940 --> 00:05:28.290 in mammary carcinogenesis. 111 00:05:28.290 --> 00:05:31.500 But this model is depicting some 112 00:05:31.500 --> 00:05:33.532 of the relationships between key players 113 00:05:33.532 --> 00:05:38.532 in the carcinogenesis of the mammary glands of the breast. 114 00:05:39.000 --> 00:05:42.270 We see some key players, the epithelial tissues, 115 00:05:42.270 --> 00:05:46.230 the adipose tissues, the role of chronic inflammation, 116 00:05:46.230 --> 00:05:50.400 including cyclooxygenase 1 and 2. 117 00:05:50.400 --> 00:05:52.293 We also see, as noted before, 118 00:05:53.224 --> 00:05:58.224 that the CYP-19 gene leads to production of estrogen, 119 00:05:58.530 --> 00:06:03.180 which will lead to mitogenesis and cell replication, 120 00:06:03.180 --> 00:06:07.053 potentially leading to more mutations in cancer. 121 00:06:09.630 --> 00:06:13.470 Finally, I just wanna remind everyone that a lot 122 00:06:13.470 --> 00:06:14.670 of these findings were found 123 00:06:14.670 --> 00:06:17.520 using the Hill's criteria of judgment. 124 00:06:17.520 --> 00:06:21.000 So these criteria, as we'll recall, 125 00:06:21.000 --> 00:06:23.276 are used to look at epidemiologic studies 126 00:06:23.276 --> 00:06:28.050 and really weigh the strength of their conclusions. 127 00:06:28.050 --> 00:06:31.650 So as you noted before, there may be times 128 00:06:31.650 --> 00:06:33.850 when different studies find different things 129 00:06:33.850 --> 00:06:37.380 or some studies find significant relationships 130 00:06:37.380 --> 00:06:41.160 while others find no significant relationships. 131 00:06:41.160 --> 00:06:42.750 It's important to use this criteria 132 00:06:42.750 --> 00:06:46.350 for assessing the strength of any given study 133 00:06:46.350 --> 00:06:50.223 and of the findings that that study might produce.