The aim of this paper is to assess the relevance of somatic evolution by natural selection to our understanding of cancer development. I do so in two steps. In the first part of the paper, I ask to what extent cancer cells meet the formal requirements for evolution by natural selection, relying on Godfrey-Smith’s (2009) framework of Darwinian populations. I argue that although they meet the minimal requirements for natural selection, cancer cells are not paradigmatic Darwinian populations. In the second (...) part of the paper, I examine the most important examples of adaptation in cancer cells. I argue that they are not significant accumulations of evolutionary changes, and that as a consequence natural selection plays a lesser role in their explanation. Their explanation, I argue, is best sought in the previously existing wiring of the healthy cells. (shrink)

The book presents a new way of understanding Darwinism and evolution by natural selection, combining work in biology, philosophy, and other fields.

The probability that the fitter of two alleles will increase in frequency in a population goes up as the product of N (the effective population size) and s (the selection coefficient) increases. Discovering the distribution of values for this product across different alleles in different populations is a very important biological task. However, biologists often use the product Ns to define a different concept; they say that drift “dominates” selection or that drift is “stronger than” selection when Ns is much (...) smaller than some threshold quantity (e.g., ½) and that the reverse is true when Ns is much larger than that threshold. We argue that the question of whether drift dominates selection for a single allele in a single population makes no sense. Selection and drift are causes of evolution, but there is no fact of the matter as to which cause is stronger in the evolution of any given allele. (shrink)

In response to Germain argument that evolution by natural selection has a limited explanatory power in cancer, Lean and Plutynski have recently argued that many adaptations in cancer only make sense at the tumor level, and that cancer progression mirrors the major evolutionary transitions. While we agree that selection could potentially act at various levels of organization in cancers, we argue that tumor-level selection is unlikely to actually play a relevant role in our understanding of the somatic evolution of human (...) cancers. (shrink)

Clatterbuck et al. (Biol Philos 28: 577–592, 2013) argue that there is no fact of the matter whether selection dominates drift or vice versa in any particular case of evolution. Their reasons are not empirically based; rather, they are purely conceptual. We show that their conceptual presuppositions are unmotivated, unnecessary and overly complex. We also show that their conclusion runs contrary to current biological practice. The solution is to recognize that evolution involves a probabilistic sampling process, and that drift is (...) a deviation from probabilistic expectation. We conclude that conceptually, there are no problems with distinguishing drift from selection, and empirically—as modern science illustrates—when drift does occur, there is a quantifiable fact of the matter to be discovered. (shrink)

A new therapeutic strategy could break the stalemate in the war on cancer by targeting not all cancerous cells but the small fraction that lie at the root of cancers. Lucie Laplane offers a comprehensive analysis of cancer stem cell theory, based on an original interdisciplinary approach that combines biology, biomedical history, and philosophy.

Reprogramming technologies show that cellular identity can be reprogrammed, challenging the classical conception of cell differentiation as an irreversible process. If non-stem cells can be reprogrammed into stem cells, then what is it to be a stem cell, and what kind of property is stemness? This article addresses this question both philosophically and biologically, states the different possibilities, and illustrates their potential consequences for science with the example of anti-cancer therapies.