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The evolution of failure: explaining cancer as an evolutionary process

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A Commentary to this article was published on 08 December 2016

“Through failure we understand design.” Frank, 2007.

Abstract

One of the major developments in cancer research in recent years has been the construction of models that treat cancer as a cellular population subject to natural selection. We expand on this idea, drawing upon multilevel selection theory. Cancer is best understood in our view from a multilevel perspective, as both a by-product of selection at other levels of organization, and as subject to selection (and drift) at several levels of organization. Cancer is a by-product in two senses. First, cancer cells co-opt signaling pathways that are otherwise adaptive at the organismic level. Second, cancer is also a by-product of features distinctive to the metazoan lineage: cellular plasticity and modularity. Applying the multilevel perspective in this way permits one to explain transitions in complexity and individuality in cancer progression. Our argument is a reply to Germain’s (2012) scepticism towards the explanatory relevance of natural selection for cancer. The extent to which cancer fulfills the conditions for being a paradigmatic Darwinian population depends on the scale of analysis, and the details of the purported selective scenario. Taking a multilevel perspective clarifies some of the complexities surrounding how to best understand the relevance of evolutionary thinking in cancer progression.

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Notes

  1. For a history of evolutionary perspectives on cancer, see, Morange (2012).

  2. A reviewer asks whether the lineage of cells in a clonal population is a “population.” We grant that it is an atypical population, in that the population is all descended from a clone. But, if clonal populations of bacteria such as Lenski’s E. coli are populations, we don’t see why clonal populations in a tumor would not be.

  3. A ‘r’ selection population is one with a high growth rate, seeding many individuals. ‘R’ selection is often associated with populations which gain from dispersing over hostile environments. In contrast ‘k’ selection population have low growth rates due to the population living in an environment near carrying capacity. See Macarthur and Wilson (1967).

  4. A reviewer comments: “There is no denying that the success of metastasis depends on many evolved features and interactions (including cells other than the colonizing cells) and, as the author points out, that features such as heterogeneity are tumor-level property… However, in order to show that tumours have complex adaptations, it is insufficient to show that tumours have developed complex traits, or that these promote progression, and one must also show that these traits were selected at this level, rather than for the benefit of single cells.” This is an excellent comment and central concern worth addressing. In our view, a trait that promotes relative survival and reproductive success of an entity at some level need not be (initially) selected for survival and reproductive success at that particular level. As long as it (currently) promotes survival and reproductive success of entities at that level, the trait is selected for at that level. We believe that we have shown this to be the case, and, the following references provide further elaboration of examples (Gatenby et al. 2007; Gavert and Ben-Ze’ev 2010; Egeblad et al. 2010; Mueller and Fuesnig 2004). Ruling out selection on a given level by arguing that a trait was not initially selected for to benefit that level would rule out all selection on all coopted traits, which would (potentially) rule out a good deal of selection even at the level of individual cells or organisms. See, e.g., Lloyd (2012) for discussion.

  5. In Hanahan and Weinberg (2000) they claim cancer is a population of cells with the following features (1) Self stimulation of growth (2) resist inhibitory signals (3) apoptosis avoidance (4) angiogenesis (5) unlimited replication (6) metastasis.

References

  • Aktipis CA, Boddy AM, Jansen G, Hibner U, Hochberg ME, Maley CC, Wilkinson GS (2015) Cancer across the tree of life: cooperation and cheating in multicellularity. Phil Trans R Soc B 370(1673):20140219

    Article  Google Scholar 

  • Anderson A, Weaver A, Cummings PT, Quaranta V (2006) Tumor morphology and phenotypic evolution driven by selective pressure from the microenvironment. Cell 127(5):905–915

    Article  Google Scholar 

  • Bissell M, Hines WC (2011) Why don’t we get more cancer? A proposed role of the microenvironment in restraining cancer progression. Nat Med 17(3):320–329

    Article  Google Scholar 

  • Cairns J (1975) Mutation selection and the natural history of cancer. Nature 255:197–200

    Article  Google Scholar 

  • Cairns J (1978) Cancer science and society. Freeman and Co, San Francisco

    Google Scholar 

  • Crespi B, Summers K (2006) Evolutionary biology of cancer. Trends Ecol Evol 20(10):545–551

    Article  Google Scholar 

  • Damuth J, Heisler IL (1988) Alternative formulations of multilevel selection. Biol Phil 3(4):407–430

    Article  Google Scholar 

  • Egeblad M, Nakasone ES, Werb Z (2010) “Tumors as organs: complex tissues that interface with the entire organism”. Dev Cell 18:884–901

    Article  Google Scholar 

  • Fisher R (1930) The genetical theory of natural selection. Clarendon, Oxford

    Book  Google Scholar 

  • Frank SA (2007) Dynamics of cancer: incidence, inheritance and evolution. Princeton, New Jersey

    Google Scholar 

  • Frank SA, Nowak MA (2004) Problems of somatic mutation and cancer. BioEssays 26(3):291–299

    Article  Google Scholar 

  • Gatenby RA et al (2006) Acid-mediated tumor invasion: a multidisciplinary study. Cancer Res 66:5216–5223

    Article  Google Scholar 

  • Gatenby RA et al (2007) Cellular adaptations to hypoxia and acidosis during somatic evolution of breast cancer. Br J Cancer 97(5):646–653

    Article  Google Scholar 

  • Gause GF (1966) Aspects of antibiotic research. Chem Ind 36:1506–1513

    Google Scholar 

  • Gavert N, Ben-Ze’ev A (2010) Coordinating changes in cell adhesion and phenotype during EMT-like processes in cancer. F1000 Biol Rep 8(2):86

    Google Scholar 

  • Gerlinger M, Rowan AJ, Horswell S, Larkin J, Endesfelder D, Gronroos E, Swanton C (2012) Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. New Eng J Med 366(10):883–892

    Article  Google Scholar 

  • Germain PL (2012) Cancer cells and adaptive explanations. Biol Phil 27(6):785–810

    Article  Google Scholar 

  • Godfrey-Smith P (2009) Darwinian populations and natural selection, vol 22. Oxford University Press, Oxford

    Book  Google Scholar 

  • Greaves M, Maley CC (2012) Clonal evolution in cancer. Nature 481(7381):306–313

    Article  Google Scholar 

  • Gupta PB, Chaffer CL, Weinberg RA (2009) Cancer stem cells: mirage or reality? Nat Med 15(9):1010–1012

    Article  Google Scholar 

  • Hanahan D, Weinberg RA (2000) The hallmarks of cancer. Cell 100(1):57–70

    Article  Google Scholar 

  • Hausman DM (2012) Health, naturalism, and functional efficiency. Phil Sci 79(4):519–541

    Article  Google Scholar 

  • Jordan CT, Guzman ML, Noble M (2006) Cancer stem cells. New Eng J Med 355(12):1253–1261

    Article  Google Scholar 

  • Karamysheva AF (2008) Mechanisms of angiogenesis. Biochemistry (Moscow) 73(7):751–762

    Article  Google Scholar 

  • Klein CA, Blankenstein TJ, Schmidt-Kittler O, Petronio M, Polzer B, Stoecklein NH, Riethmüller G (2002) Genetic heterogeneity of single disseminated tumour cells in minimal residual cancer. Lancet 360(9334):683–689

    Article  Google Scholar 

  • Komarova NL, Wodarz D (2004) The optimal rate of chromosome loss for the inactivation of tumor suppressor genes in cancer. Proc Natl Acad Sci USA 101(18):7017–7021

    Article  Google Scholar 

  • Komarova NL, Wodarz D (2005) Drug resistance in cancer: principles of emergence and prevention. Proc Natl Acad Sci 102(7):9714–9719

    Article  Google Scholar 

  • Lewontin RC (1970) The units of selection. Ann Rev Ecol Syst 1:1–18

    Article  Google Scholar 

  • Lloyd E (2012) Units and levels of selection. In: Edward NZ (ed) The stanford encyclopedia of philosophy. URL = <http://plato.stanford.edu/archives/win2012/entries/selection-units/>

  • MacArthur RH, Wilson EO (1967) The theory of island biogeography. Princeton University Press, New Jersey

    Google Scholar 

  • Martincorena I et al (2015) High burden and pervasive positive selection of somatic mutations in normal human skin. Science 348(6237):880–886

    Article  Google Scholar 

  • Merlo LMF, Pepper JW, Reid BJ, Maley CC (2006) Cancer as an evolutionary and ecological process. Nat Rev Cancer 6(12):924–935

    Article  Google Scholar 

  • Michod RE (1997) Evolution of the individual. Am Nat 150(S1):S5–S21

    Article  Google Scholar 

  • Michod RE, Herron MD (2006) Cooperation and conflict during evolutionary transitions in individuality. J Evol Biol 19:1406–1409

    Article  Google Scholar 

  • Michor F, Iwasa Y, Nowak MA (2004) Dynamics of cancer progression. Nat Rev Cancer 4(3):197–205

    Article  Google Scholar 

  • Morange M (2012) What history tells us XXVIII. What is really new in the current evolutionary theory of cancer? J Biosci 37(4):609–612

    Article  Google Scholar 

  • Mori H et al (2002) Chromosome translocations and covert leukemic clones are generated during normal fetal development. Proc Natl Acad Sci 99(12):8242–8247

    Article  Google Scholar 

  • Mueller M, Fuesnig NE (2004) “Friends or foes – bipolar effects of the tumor stroma in cancer. Nat Rev Cancer 4:839–849

    Article  Google Scholar 

  • Navin N, Kendall J, Troge J, Andrews P, Rodgers L, McIndoo J, Wigler M (2011) Tumour evolution inferred by single-cell sequencing. Nature 472(7341):90–94

    Article  Google Scholar 

  • Nguyen LV, Vanner R, Dirks P, Eaves CJ (2010) Cancer stem cells: an evolving concept. Nat Rev Cancer 12(2):220–228

    Google Scholar 

  • Nowak MA (2006) Evolutionary dynamics: exploring the equations of life. Harvard University Press, Massachusetts

    Google Scholar 

  • Nowell PC (1976) The clonal evolution of tumor cell populations. Science 194:23–28

    Article  Google Scholar 

  • Odling-Smee FJ, Laland K, Feldman M (2003) Niche construction: a neglected process in evolution. Princeton University Press, New Jersey

    Google Scholar 

  • Okasha S (2005) Multi-level selection and the major transitions in evolution. Phil Sci Proc 72:1013–1025

    Article  Google Scholar 

  • Okasha S (2006) Evolution and the levels of selection. Oxford University Press, Oxford

    Book  Google Scholar 

  • Olumi AF, Grossfeld GD, Hayward SW, Carroll PR, Tlsty TD, Cunha GR (1999) Carcinoma-associated fibroblasts direct tumor progression of initiated human prostatic epithelium. Cancer Res 59(19):5002–5011

    Google Scholar 

  • Pepper JW, Sprouffske K, Maley CC (2007) Animal cell differentiation patterns suppress somatic evolution. PLoS Comput Biol 3(12):e250

    Article  Google Scholar 

  • Psaila B, Lyden D (2009) The metastatic niche: adapting the foreign soil. Nat Rev Cancer 9(4):285–293

    Article  Google Scholar 

  • Queller D, Strassman J (2009) Beyond society: the evolution of organismality. Phil Trans R Soc B 364:3143–3155

    Article  Google Scholar 

  • Redfield RJ (2002) Is quorum sensing a side effect of diffusion sensing? Trends Microbiol 10:365–370

    Article  Google Scholar 

  • Sakr WA et al (1993) The frequency of carcinoma and intraepithelial neoplasia of the prostate in young male patients. J Urol 150(2 Pt 1):379–385

    Google Scholar 

  • Sober E, Wilson DS (1999) Unto others: the evolution and psychology of unselfish behaviour. Harvard University Press, Massachusetts

    Google Scholar 

  • Sterelny KR, Joyce B, Calcott B, Fraser B (2014) Cooperation and its evolution. MIT Press, Massachusetts

    Google Scholar 

  • Turner JR (1977) Butterfly mimicry: the genetical evolution of an adaptation. Evol Biol 10:163–206

    Google Scholar 

  • Weigelt B, Glas AM, Wessels LF, Witteveen AT, Peterse JL, van’t Veer LJ (2003) Gene expression profiles of primary breast tumors maintained in distant metastases. Proc Natl Acad Sci 100(26):15901–15905

    Article  Google Scholar 

  • Weinberg RA (2014) The biology of cancer, 2nd (edn.). Garland Science, NY

    Google Scholar 

  • West S, Diggle SP, Buckling A, Gardner A, Griffin AS (2007) The social lives of microbes. Ann Rev Ecol Evol Syst 38:53–77

    Article  Google Scholar 

  • Williams P, Winzer K, Chan W, C´amara M (2007) Look who’s talking: communication and quorum sensing in the bacterial world. Philos Trans R Soc Lond, Ser B 362(1483):1119–1134

    Article  Google Scholar 

  • Wilson DS (1975) A theory of group selection. Proc Natl Acad Sci 72(1):143–146

    Article  Google Scholar 

  • Wodarz D, Komarova NL (2014) Dynamics of cancer: mathematical foundations of oncology. World Scientific Publishing Co, Singapore

    Book  Google Scholar 

  • Yachida S et al (2010) Distant metastasis occurs late during the genetic evolution of pancreatic cancer. Nature 467:1114

    Article  Google Scholar 

Download references

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Lean, C., Plutynski, A. The evolution of failure: explaining cancer as an evolutionary process. Biol Philos 31, 39–57 (2016). https://doi.org/10.1007/s10539-015-9511-1

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