International Society for History, Philosophy, and Social Studies of Biology

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MONDAY, JULY 6  /  15:30 - 17:00  /  DS-R510
Organized session / standard talks
Cancer causation and explanation

Katherine Liu (University of Minnesota, United States); Anya Plutynski (Washington University in St Louis, United States)

Cancer presents a fascinating case study for exploring a variety of questions about demarcating biological processes and entities, and the complimentary roles of molecular genetics, evolution and development in explaining disease. In this session, longstanding issues in philosophy of biology surrounding the unit or level of organization, the demarcation of biological kinds, the theoretical and practical relationships between molecular biology, evolution, and development, and the scope and limits of methodological reductionism overlap with longstanding issues in philosophy of medicine concerning disease classification and debates about how best to move from "bench to bedside." Some questions we investigate are: Is cancer a process or product? How is cancer a product or by-product of developmental processes? What are the scope and limits of molecular genetic explanations of cancer initiation and progression? How can evolutionary and developmental perspectives on cancer be integrated? This session will explore these questions, drawing upon current research in the sciences, situating the discussion vis-a-vis current philosophical work on the metaphysics and epistemology of the biomedical sciences.

Rethinking cancer through modularity

Katherine Liu (University of Minnesota, United States)

Cancer research is guided by two main conceptual models: (1) a molecular, biomarker approach focused on individuals; and (2) an evolutionary approach based in populations. In both cases, these models are meant to inform us about causal relationships in cancer such that researchers can develop clinical interventions. I argue that these conceptual models are not sufficient for cancer translational research, even when considered jointly. This is because they fall along the proximate-ultimate distinction, and it has been shown that maintaining this distinction is problematic. Taking a more integrated approach gives a more thorough causal picture. I offer a novel conceptual model for understanding cancer that based in modularity – the relationships between parts and wholes. This model helps us to understand the evolutionary dynamics of cancer by emphasizing changes in the degree of modularity over time as a major causal factor. This model helps bridge the proximate-ultimate distinction since modularity is about the relationships between hierarchical levels. I will end with a plan for how we can study this using microbial experimental evolution. Together this conceptual model and experimental approach will help clarify the complexity of causal factors in cancer and hopefully lead to the successful development of new clinical interventions.

Cancer as a process

John Dupré (University of Exeter, United Kingdom); Marta Bertolaso (Università Campus Bio-Medico, Italy)

Everyone knows that the idea of seeking ‘the cause’ of cancer is a mistake, since cancers are diverse and different cancers have different etiologies. A more unified perspective on the subject can nonetheless be discerned by taking seriously the fact that cancer is a process rather than a thing. Cancer is, indeed, a malfunction of a quite normal process, cell division or even, more broadly, development. This simple distinction has at least two significant implications. First, there is no reason to expect there to be any essential difference between cancerous and non-cancerous parts of an organism. There may be distinctive cancer cells or cancer genes in some or all cancers, but this cannot be assumed. Second, our understanding of development remains quite limited. In particular, we need a deep understanding of the exquisite regulation of cell development that allows particular cell lineages within an organism to reach and maintain a functional size. Without such an understanding the fundamental question that we need to address is not why we sometimes develop cancer (misregulation of cell division), but why we so often fail to develop cancer.

Sexual conflict or genial genes? The seductive temptations of evolutionary explanations of gender disparities in cancer

Anya Plutynski (Washington University in St Louis, United States)

Is better science necessarily sexist science? Epidemiologists have long known that there are significant differences in cancer susceptibility between males and females even in early childhood, males have a higher incidence of cancer, and higher mortality (Dorak, et. al., 2012). This has led some advocates of evolutionary medicine to argue that there are sex-specific genetic, developmental and evolutionary causes of this difference. For instance, short repeats of the CAG region of the androgen receptor are associated with increased transactivation of the receptor and increased body size, but also increased risk of prostate cancer, and more aggressive forms of disease. This has led to the suggestion that differential susceptibility to cancer could be driven by antagonistic pleiotropy enhanced reproductive success early in life at the expense of reduced survivorship later in life (Summers Crespi, 2008). Genes associated with antagonistic pleiotropy are expected to drive sexual conflict, where sexual conflict is when aspects of one sex's behavior, physiology, or phenotypic traits enhance that sex's fitness but impose a cost on the fitness of the opposite sex. Sexual conflict, it's argued, is expected because the sexes maximize their fitness via different and mutually incompatible strategies. Sex-specific optimization of reproductive strategies could result in different life spans and aging rates, and this could cause sexually antagonistic selection on shared genetic architecture. Is the disparity in cancer incidence and mortality driven by sexual conflict? This paper considers a variety of evidence and alternative explanatory strategies (e.g., immune surveillance differences, and/or differences due to the laboratory environment and gene x phenotype interactive effects in resource rich environments). In addition, I consider the broader import of such work for cancer treatment and prevention. How, if at all, does the study of sex difference in causes of cancer enhance our understanding of how to intervene on the disease?