Are the small and indolent cancers found in abundance in cancer screening normal variations, risk factors, or disease? Naturalists in philosophy of medicine turn to pathophysiological findings to decide such questions objectively. To understand the role of pathophysiological findings in disease definition, we must understand how they mislead in diagnostic reasoning. Participants on all sides of the definition of disease debate attempt to secure objectivity via reductionism. These reductivist routes to objectivity are inconsistent with the Bayesian nature of clinical reasoning; (...) when they appeal to the sciences, they are inconsistent with what philosophy of biology tells us about its natural kinds. Proposals that we narrow the scope of our claims in the disease definition debates are useful, but paradigms can still distort our reasoning in particular cases, even when we are self-conscious about their status. (shrink)

Cancer is typically spoken of as a “complex” disease. But, in what sense are cancers “complex”? Is there one sense, or several? What implications does this complexity have – both for how we study, and how we intervene upon cancers? The aim of this paper is first, to clarify the variety of senses in which cancer is spoken of as "complex" in the scientific literature, and second, to discover what explanatory and predictive roles such features play.

Philosophers sometimes refer to ‘moves’ made in the context of a philosophical debate. Once familiar with these recognizable tropes, we then possess them as tools – a suite of possible moves to make in novel contexts. In this paper, I outline three such philosophy moves, then demonstrate how moves can be combined. Examples of moves and some combinations feature throughout the paper.

Cancer is a paradigmatic case of a complex causal process; causes of cancer operate at a variety of temporal and spatial scales, and the respects in which these causes act and interact are diverse. There are, for instance, temporal order effects, organizational effects, structural effects, and dynamic relationships between causes operating at different temporal and spatial scales. Because of this complexity, models of cancer initiation and progression often involve deliberate choices to focus on one time scale, one causal pathway, or (...) one aspect of cancer’s dynamics. As in most of biology, modeling cancer involves simplification and idealization. At the same time, theoretical perspectives inform the construction of these models. Such perspectives might involve viewing cancer ‘as’ a genetic disease, metabolic disease, stem cell disease, an infectious disease, or a disease of tissue disorganization. This paper will argue that purportedly competing theoretical views of cancer are not at odds, but can be viewed as mutually informative. Models are most often developed in the service of asking very specific questions, and this requires limiting our view of the phenomena to a specific temporal or spatial scale, a particular cause, or a particular outcome, dynamic, or pattern. Thus, while some models may seem at odds, often they are simply concerned with different questions, or, they are complementary and mutually informative. I hope to bring this case to bear on debates among philosophers of science over perspectivism and realism, as well pluralism about the aims and scope of scientific theory. (shrink)

The question of the division of cognitive labor has given rise to various models characterizing the way scientists should distribute their efforts. These models often consider the scientific community as a self-governed sphere constituted by rational agents making choices on the basis of fixed rules. Such models have recently been criticized for not taking into account the real mechanisms of science funding. Hence, the question of the utility of the DCL models in guiding science policy remains an open one. In (...) this paper, we show that two unconsidered dimensions would have to be taken into account. First, DCL studies miss the existence of distinct levels of epistemic objectives organizing the research process. Indeed, the scientific field is structured as a system of hierarchical, interconnected practices which are defined both by their inherent purposes and by various superposed external functions. Second, I criticize the absence of ontological considerations, since the epistemological significance of pluralism is highly dependent on the nature of the object under study. Because of these missing dimensions, current DCL models might have a limited usefulness to identify good practices of research governance. (shrink)

In 2015, Tomasetti and Vogelstein published a paper in Science containing the following provocative statement: “… only a third of the variation in cancer risk among tissues is attributable to environmental factors or inherited predispositions. The majority is due to “bad luck,” that is, random mutations arising during DNA replication in normal, noncancerous stem cells.” The paper—and perhaps especially this rather coy reference to “bad luck”—became a flash point for a series of letters and reviews, followed by replies and yet (...) further counterpoints. In this paper, I critically assess Tomasetti and Vogelstein's argument, discuss the meaning of “luck” (or, better: “chance”) in the context of the debate, and use this case study to address larger questions about methodological criteria for causal explanations of population level patterns in biomedicine. (shrink)

Cancer has garnered increasing interest among philosophers. This chapter focuses on cancer medicine and precision oncology, an influential approach to cancer which seeks to individualize treatment on the basis of genetic or molecular features of disease. It reviews a range of ontological, epistemic, and ethical questions raised by precision oncology, relating developments in cancer medicine to broader issues in the philosophy of science and medicine.

Cancer—and scientific research on cancer—raises a variety of compelling philosophical questions. This entry will focus on four topics, which philosophers of science have begun to explore and debate. First, scientific classifications of cancer have as yet failed to yield a unified taxonomy. There is a diversity of classificatory schemes for cancer, and while some are hierarchical, others appear to be “cross-cutting,” or non-nested. This literature thus raises a variety of questions about the nature of the disease and disease classification. Second, (...) philosophers of science have historically taken the aim of science to be arriving at true theories. However, scientists studying cancer come from a variety of disciplines, with different scientific as well as practical aims. Perhaps it is not surprising, then, that historians and philosophers of science do not seem to agree on how best to characterize the aim and structure of cancer research; it is far from clear whether the appropriate characterization of the aim is arriving at true theories, or even whether the proper units of analysis are “theories”, or instead, “models”, “explanatory frameworks”, “research programs”, “paradigms”, or perhaps, “experimental traditions”. With the rise of “big data” science—such as the Cancer Genome Atlas Project (or TCGA)—and “systems” approaches to the study of disease, both philosophers and historians of science are rethinking how best to describe and explain these distinctive kinds of scientific inquiry. -/- Third, cancer is in part a byproduct of our developmental and life history, as well as our evolutionary history. Cancer progression can be compared to a reversion of development, or, to the evolution of multicellularity. Thus, cancer raises intriguing questions about how we conceive of “functions”, “development”, and the role of our evolutionary history and particularly, selective trade-offs, in vulnerability to disease. -/- Last but not least, cancer research provides a case study for consideration of the roles of values at the science-policy interface. Epidemiological and toxicological research on cancer’s causes informs toxics law and regulatory policy, which raises a variety of questions about the nature of evidence and inductive risk in such contexts. (shrink)