American Journal of Epidemiology © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: [email protected].
Vol. 181, No. 5
Letters to the Editor RE: “THE NEXT GENERATION OF LARGE-SCALE EPIDEMIOLOGIC RESEARCH: IMPLICATIONS FOR TRAINING CANCER EPIDEMIOLOGISTS”
ACKNOWLEDGMENTS Conflict of interest: none declared. REFERENCES 1. Spitz MR, Lam TK, Schully SD, et al. The next generation of large-scale epidemiologic research: implications for training cancer epidemiologists. Am J Epidemiol. 2014;180(10):964–967. 2. Nowell PC. The clonal evolution of tumor cell populations. Science. 1976;194(4260):23–28. 3. Hanahan D. Rethinking the war on cancer. Lancet. 2014; 383(9916):558–563. 4. Weinberg RA. Coming full circle-from endless complexity to simplicity and back again. Cell. 2014;157(1):267–271. 5. Galea S. An argument for a consequentialist epidemiology. Am J Epidemiol. 2013;178(8):1185–1191. 6. Jemal A, Thun MJ, Ries LAG, et al. Annual report to the nation on the status of cancer, 1975–2005, featuring trends in lung cancer, tobacco use, and tobacco control. J Natl Cancer Inst. 2008;100(23):1672–1694. 7. Ravdin PM, Cronin KA, Howlader N, et al. The decrease in breast-cancer incidence in 2003 in the United States. N Engl J Med. 2007;356(16):1670–1674. 8. Edwards BK, Noone AM, Mariotto AB, et al. Annual Report to the Nation on the status of cancer, 1975–2010, featuring prevalence of comorbidity and impact on survival among persons with lung, colorectal, breast, or prostate cancer. Cancer. 2014;120(9):1290–1314. 9. Sonnenschein C, Soto AM. Theories of carcinogenesis: an emerging perspective. Semin Cancer Biol. 2008;18(5):372–377. 10. Sonnenschein C, Soto AM. The aging of the 2000 and 2011 Hallmarks of Cancer reviews: a critique. J Biosci. 2013;38(3): 651–663.
Susan E. Carozza (e-mail: [email protected]) Epidemiology Program, School of Biological and Population Health Sciences, College of Public Health and Human Sciences, Oregon State University, Corvallis, OR DOI: 10.1093/aje/kwv022; Advance Access publication: February 18, 2015
360
Am J Epidemiol. 2015;181(5):360–361
Downloaded from http://aje.oxfordjournals.org/ at Stockholms Universitet on August 15, 2015
used in innovative ways. The decision of whether to train future (or retrain current) cancer epidemiologists as molecular geneticists and/or big data analysts should rest on personal preferences, because the record thus far shows that such efforts may not result in those big wins in the war on cancer that are our ultimate goal as cancer epidemiologists. Also, while we’re rethinking the whole paradigm, can we please stop talking about this effort in military terms? Perhaps gardening is the more accurate, realistic metaphor—find out what improves the “soil” of tissues and organs, favors their healthy growth and maintenance, and discourages the “weeds.”
I read with concern the recent commentary by Spitz et al. (1) in which they advocate training current and future cancer epidemiologists in the complexities of the “-omics” (i.e., genomics, proteomics, metabolomics, and epigenomics), with the corollary of advanced data management and analysis training to handle the reams of “big data” generated by these technologies. Essentially, in their view, cancer epidemiologists should be trained in computer science and molecular biology so that they will contribute meaningfully to moving epidemiology away from being considered a “soft” science. Implicit in their commentary is the foundational belief that molecular approaches to investigating the causes of cancer offer the most promise for preventing cancer incidence and mortality. Arguably, the current paradigm for cancer research rests within the somatic mutation theory, which characterizes cancer as a cell-based, genetic, molecular disease (2). The promise of the relentless, well-funded search of genetic evidence was that it would first provide a cogent explanation of the disease and then the means to prevent cancer incidence and mortality. Instead, judging by candid admissions made by leading cancer researchers reflecting on the so-called war on cancer (3, 4), those promises remain mostly unfulfilled. If the goal of epidemiology is to study the causes and distributions of diseases in human populations so as to identify ways to prevent and control disease (5), then cancer epidemiology has had several notable successes, including the decrease in the number of cases and deaths from smoking-related cancers (6) and the precipitous drop in breast cancer incidence that was likely an unintended consequence of women fleeing from their hormone treatments (7). The body of research driven by the somatic mutation theory is largely unrelated to these few measurable successes; no big “wins” in our field have been scored from decades of focusing on genetic mutations. Unfortunately, many cancer rates are increasing for unknown reasons (8), and for most cancers, there are still no robust prevention strategies. Treatments based on somatic mutation theory have, so far, been fleeting and temporary (3). It is perhaps time for cancer epidemiologists to explore alternative theories of cancer causation. The tissue organization field theory (9), which posits that cancer is a tissue-based rather than a cell-based disease, has great potential for reframing the way we think about cancer causation and the means to treat and even prevent cancers. Sonnenschein and Soto (10) compellingly refute the classic hallmarks of cancer and propose switching from the reductionist philosophy shadowing the somatic mutation theory to a more plausible and productive organicist approach. Exploring the potential of this theory in human populations will require cancer epidemiologists to think differently about which exposures to investigate, what new kinds of collaborators to recruit, and how epidemiologic methods might be
Vol. 181, No. 5
Letters to the Editor RE: “THE NEXT GENERATION OF LARGE-SCALE EPIDEMIOLOGIC RESEARCH: IMPLICATIONS FOR TRAINING CANCER EPIDEMIOLOGISTS”
ACKNOWLEDGMENTS Conflict of interest: none declared. REFERENCES 1. Spitz MR, Lam TK, Schully SD, et al. The next generation of large-scale epidemiologic research: implications for training cancer epidemiologists. Am J Epidemiol. 2014;180(10):964–967. 2. Nowell PC. The clonal evolution of tumor cell populations. Science. 1976;194(4260):23–28. 3. Hanahan D. Rethinking the war on cancer. Lancet. 2014; 383(9916):558–563. 4. Weinberg RA. Coming full circle-from endless complexity to simplicity and back again. Cell. 2014;157(1):267–271. 5. Galea S. An argument for a consequentialist epidemiology. Am J Epidemiol. 2013;178(8):1185–1191. 6. Jemal A, Thun MJ, Ries LAG, et al. Annual report to the nation on the status of cancer, 1975–2005, featuring trends in lung cancer, tobacco use, and tobacco control. J Natl Cancer Inst. 2008;100(23):1672–1694. 7. Ravdin PM, Cronin KA, Howlader N, et al. The decrease in breast-cancer incidence in 2003 in the United States. N Engl J Med. 2007;356(16):1670–1674. 8. Edwards BK, Noone AM, Mariotto AB, et al. Annual Report to the Nation on the status of cancer, 1975–2010, featuring prevalence of comorbidity and impact on survival among persons with lung, colorectal, breast, or prostate cancer. Cancer. 2014;120(9):1290–1314. 9. Sonnenschein C, Soto AM. Theories of carcinogenesis: an emerging perspective. Semin Cancer Biol. 2008;18(5):372–377. 10. Sonnenschein C, Soto AM. The aging of the 2000 and 2011 Hallmarks of Cancer reviews: a critique. J Biosci. 2013;38(3): 651–663.
Susan E. Carozza (e-mail: [email protected]) Epidemiology Program, School of Biological and Population Health Sciences, College of Public Health and Human Sciences, Oregon State University, Corvallis, OR DOI: 10.1093/aje/kwv022; Advance Access publication: February 18, 2015
360
Am J Epidemiol. 2015;181(5):360–361
Downloaded from http://aje.oxfordjournals.org/ at Stockholms Universitet on August 15, 2015
used in innovative ways. The decision of whether to train future (or retrain current) cancer epidemiologists as molecular geneticists and/or big data analysts should rest on personal preferences, because the record thus far shows that such efforts may not result in those big wins in the war on cancer that are our ultimate goal as cancer epidemiologists. Also, while we’re rethinking the whole paradigm, can we please stop talking about this effort in military terms? Perhaps gardening is the more accurate, realistic metaphor—find out what improves the “soil” of tissues and organs, favors their healthy growth and maintenance, and discourages the “weeds.”
I read with concern the recent commentary by Spitz et al. (1) in which they advocate training current and future cancer epidemiologists in the complexities of the “-omics” (i.e., genomics, proteomics, metabolomics, and epigenomics), with the corollary of advanced data management and analysis training to handle the reams of “big data” generated by these technologies. Essentially, in their view, cancer epidemiologists should be trained in computer science and molecular biology so that they will contribute meaningfully to moving epidemiology away from being considered a “soft” science. Implicit in their commentary is the foundational belief that molecular approaches to investigating the causes of cancer offer the most promise for preventing cancer incidence and mortality. Arguably, the current paradigm for cancer research rests within the somatic mutation theory, which characterizes cancer as a cell-based, genetic, molecular disease (2). The promise of the relentless, well-funded search of genetic evidence was that it would first provide a cogent explanation of the disease and then the means to prevent cancer incidence and mortality. Instead, judging by candid admissions made by leading cancer researchers reflecting on the so-called war on cancer (3, 4), those promises remain mostly unfulfilled. If the goal of epidemiology is to study the causes and distributions of diseases in human populations so as to identify ways to prevent and control disease (5), then cancer epidemiology has had several notable successes, including the decrease in the number of cases and deaths from smoking-related cancers (6) and the precipitous drop in breast cancer incidence that was likely an unintended consequence of women fleeing from their hormone treatments (7). The body of research driven by the somatic mutation theory is largely unrelated to these few measurable successes; no big “wins” in our field have been scored from decades of focusing on genetic mutations. Unfortunately, many cancer rates are increasing for unknown reasons (8), and for most cancers, there are still no robust prevention strategies. Treatments based on somatic mutation theory have, so far, been fleeting and temporary (3). It is perhaps time for cancer epidemiologists to explore alternative theories of cancer causation. The tissue organization field theory (9), which posits that cancer is a tissue-based rather than a cell-based disease, has great potential for reframing the way we think about cancer causation and the means to treat and even prevent cancers. Sonnenschein and Soto (10) compellingly refute the classic hallmarks of cancer and propose switching from the reductionist philosophy shadowing the somatic mutation theory to a more plausible and productive organicist approach. Exploring the potential of this theory in human populations will require cancer epidemiologists to think differently about which exposures to investigate, what new kinds of collaborators to recruit, and how epidemiologic methods might be
