Cancer as an evolutionary and ecological process

Key Points

  • Neoplasms are composed of an ecosystem of evolving clones, competing and cooperating with each other and other cells in their microenvironment, and this has important implications for both neoplastic progression and therapy.

  • Selection at the different levels of genes, cells and organisms might conflict, and have resulted in a legacy of tumour-suppression mechanisms and vulnerability to oncogenesis in our genomes.

  • Most of the dynamics of evolution have not been measured in neoplasms, including mutation rates, fitness effects of mutations, generation times, population structure, the frequency of selective sweeps and the selective effects of our therapies.

  • Many of the genetic and epigenetic alterations observed in neoplasms are evolutionarily neutral.

  • Cancer therapies select for cancer stem cells with resistance mutations, although various evolutionary approaches have been suggested to overcome this problem, including selecting for benign or chemosensitive cells, altering the carrying capacity of the neoplasm and the competitive effects of neoplastic and normal cells on each other.

  • Dispersal theory suggests that high cell mortality and variation of resources and population densities across space might select for metastasis.

  • There is evidence of competition, predation, parasitism and mutualism between co-evolving clones in and around a neoplasm.

  • We will need to interfere with clonal evolution and alter the fitness landscapes of neoplastic cells to prevent or cure cancer. Evolutionary biology should be central to this endeavor.

Abstract

Neoplasms are microcosms of evolution. Within a neoplasm, a mosaic of mutant cells compete for space and resources, evade predation by the immune system and can even cooperate to disperse and colonize new organs. The evolution of neoplastic cells explains both why we get cancer and why it has been so difficult to cure. The tools of evolutionary biology and ecology are providing new insights into neoplastic progression and the clinical control of cancer.

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Figure 1: Intestinal tissue architecture and sub-population structure.
Figure 2: Asexual evolution in neoplastic progression.
Figure 3: Ecological interactions.
Figure 4: Evolution of a neoplastic population.

References

  1. 1

    Nowell, P. C. The clonal evolution of tumor cell populations. Science 194, 23–28 (1976). The seminal description of cancer as an evolutionary process. Predicts sequences of clonal expansions, individual variation in response to interventions and therapeutic resistance.

    CAS  Article  Google Scholar 

  2. 2

    Crespi, B. & Summers, K. Evolutionary Biology of Cancer. Trends Ecol. Evol. 20, 545–552 (2005).

    Article  Google Scholar 

  3. 3

    Heppner, G. & Miller, F. The cellular basis of tumor progression. Int. Rev. Cytol. 177, 1–56 (1998).

    CAS  PubMed  Google Scholar 

  4. 4

    Cairns, J. Mutation selection and the natural history of cancer. Nature 255, 197–200 (1975). Highlights the interaction between tissue architecture and clonal evolution. Also predicts the retention of a non-recombining, 'immortal' strand of DNA in stem cells.

    Article  CAS  Google Scholar 

  5. 5

    Tsao, J. L. et al. Genetic reconstruction of individual colorectal tumor histories. Proc. Natl Acad. Sci. USA 97, 1236–1241 (2000). Uses phylogenetic methods to trace the common ancestor of microsatellite-unstable clones in colorectal cancer back to a date before an adenoma was detected.

    Article  CAS  Google Scholar 

  6. 6

    Tsao, J. L. et al. Colorectal adenoma and cancer divergence. Evidence of multilineage progression. Am. J. Pathol. 154, 1815–1824 (1999).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. 7

    Michor, F., Iwasa, Y. & Nowak, M. A. Dynamics of cancer progression. Nature Rev. Cancer 4, 197–205 (2004).

    Article  CAS  Google Scholar 

  8. 8

    Maley, C. C. et al. Genetic clonal diversity predicts progression to esophageal adenocarcinoma. Nature Genet. 38, 468–473 (2006). Shows that genetic diversity measures from ecology and evolution predict progression to malignancy.

    Article  CAS  Google Scholar 

  9. 9

    Maley, C. C. & Reid, B. J. Natural selection in neoplastic progression of Barrett's esophagus. Semin. Cancer Biol. 15, 474–483 (2005).

    Article  CAS  Google Scholar 

  10. 10

    Maley, C. C., Reid, B. J. & Forrest, S. Cancer prevention strategies that address the evolutionary dynamics of neoplastic cells: simulating benign cell boosters and selection for chemosensitivity. Cancer Epidemiol. Biomarkers Prev. 13, 1375–1384 (2004). Uses computational models to develop prevention and therapeutic strategies for avoiding the evolution of resistance.

    PubMed  Google Scholar 

  11. 11

    Tomlinson, I. P. M. Game-theory models of interactions between tumour cells. Euro. J. Cancer 33, 1495–1500 (1997).

    Article  CAS  Google Scholar 

  12. 12

    Gatenby, R. A. & Vincent, T. L. Application of quantitative models from population biology and evolutionary game theory to tumor therapeutic strategies. Mol. Cancer Ther. 2, 919–927 (2003). Describes the use of evolutionary and ecological models to develop new approaches to therapy.

    CAS  PubMed  Google Scholar 

  13. 13

    Gonzalez-Garcia, I., Sole, R. V. & Costa, J. Metapopulation dynamics and spatial heterogeneity in cancer. Proc. Natl Acad. Sci. USA 99, 13085–13089 (2002). Shows genetic heterogeneity within a neoplasm, and how clones can be intertwined in complex patterns.

    Article  CAS  Google Scholar 

  14. 14

    Brash, D. E., Zhang, W., Grossman, D. & Takeuchi, S. Colonization of adjacent stem cell compartments by mutant keratinocytes. Semin. Cancer Biol. 15, 97–102 (2005).

    Article  CAS  Google Scholar 

  15. 15

    Braakhuis, B. J., Leemans, C. R. & Brakenhoff, R. H. Expanding fields of genetically altered cells in head and neck squamous carcinogenesis. Semin. Cancer Biol. 15, 113–120 (2005).

    Article  Google Scholar 

  16. 16

    Maley, C. C. et al. Selectively advantageous mutations and hitchhikers in neoplasms: p16 lesions are selected in Barrett's esophagus. Cancer Res. 64, 3414–3427 (2004).

    Article  CAS  Google Scholar 

  17. 17

    Franklin, W. A. et al. Widely dispersed p53 mutation in respiratory epithelium. A novel mechanism for field car-cinogenesis. J. Clin. Invest. 100, 2133–2137 (1997). Shows that neoplastic clones can spread over large surface areas.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. 18

    Castro, M. A., Onsten, T. T., de Almeida, R. M. & Moreira, J. C. Profiling cytogenetic diversity with entropy-based karyotypic analysis. J. Theor. Biol. 234, 487–495 (2005).

    Article  CAS  Google Scholar 

  19. 19

    Keller, L. K. Levels of Selection in Evolution (Princeton University Press, Princeton, New Jersey, 1999).

    Google Scholar 

  20. 20

    Leroi, A. M., Koufopanou, V. & Burt, A. Cancer selection. Nature Rev. Cancer 3, 226–231 (2003).

    Article  CAS  Google Scholar 

  21. 21

    Weinstein, B. S. & Ciszek, D. The reserve-capacity hypothesis: evolutionary origins and modern implications of the trade-off between tumor-suppression and tissue-repair. Exp. Gerontol. 37, 615–627 (2002).

    Article  CAS  Google Scholar 

  22. 22

    Frank, S. A. & Nowak, M. A. Problems of somatic mutation and cancer. Bioessays 26, 291–299 (2004).

    Article  CAS  Google Scholar 

  23. 23

    Campisi, J. Aging, tumor suppression and cancer: high wire-act! Mech. Ageing Dev. 126, 51–58 (2005).

    Article  CAS  Google Scholar 

  24. 24

    Summers, K., da Silva, J. & Farwell, M. Intragenomic conflict and cancer. Med. Hypotheses 59, 170–179 (2002).

    Article  CAS  Google Scholar 

  25. 25

    Roth, M. J. et al. Genetic progression and heterogeneity associated with the development of esophageal squamous cell carcinoma. Cancer Res. 61, 4098–4104 (2001).

    CAS  PubMed  Google Scholar 

  26. 26

    Hanahan, D. & Weinberg, R. A. The hallmarks of cancer. Cell 100, 57–70 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. 27

    Stoler, D. L. et al. The onset and extent of genomic instability in sporadic colorectal tumor progression. Proc. Natl Acad. Sci. USA 96, 15121–15126 (1999). Measures the frequency of genomic alterations in colorectal cancer at approximately 11,000 per clone.

    Article  CAS  Google Scholar 

  28. 28

    Sole, R. V. & Deisboeck, T. S. An error catastrophe in cancer? J. Theor. Biol. 228, 47–54 (2004).

    Article  Google Scholar 

  29. 29

    Breivik, J. The evolutionary origin of genetic instability in cancer development. Semin. Cancer Biol. 15, 51–60 (2005).

    Article  CAS  Google Scholar 

  30. 30

    Michor, F., Iwasa, Y., Vogelstein, B., Lengauer, C. & Nowak, M. A. Can chromosomal instability initiate tumorigenesis? Semin. Cancer Biol. 15, 43–49 (2005).

    Article  CAS  Google Scholar 

  31. 31

    Rajagopalan, H., Nowak, M. A., Vogelstein, B. & Lengauer, C. The significance of unstable chromosomes in colorectal cancer. Nature Rev. Cancer 3, 695–701 (2003).

    Article  CAS  Google Scholar 

  32. 32

    Gray, M. W., Burger, G. & Lang, B. F. Mitochondrial evolution. Science 283, 1476–1481 (1999).

    Article  CAS  Google Scholar 

  33. 33

    Baylin, S. B. & Herman, J. G. DNA hypermethylation in tumorigenesis- epigenetics joins genetics. Trends Genet. 16, 168–174 (2000).

    CAS  Google Scholar 

  34. 34

    Feinberg, A. P., Ohlsson, R. & Henikoff, S. The epigenetic progenitor origin of human cancer. Nature Rev. Genet. 7, 21–33 (2006).

    Article  CAS  Google Scholar 

  35. 35

    Weisenberger, D. J. et al. CpG island methylator phenotype underlies sporadic microsatellite instability and is tightly associated with BRAF mutation in colorectal cancer. Nature Genet. 38, 787–793 (2006).

    Article  CAS  Google Scholar 

  36. 36

    Horie-Inoue, K. & Inoue, S. Epigenetic and proteolytic inactivation of 14–3-3sigma in breast and prostate cancers. Semin. Cancer Biol. 16, 235–239 (2006).

    Article  CAS  Google Scholar 

  37. 37

    Albertini, R. J., Nicklas, J. A., O'Neill, J. P. & Robison, S. H. In vivo somatic mutations in humans: measurement and analysis. Annu. Rev. Genet. 24, 305–326 (1990).

    Article  CAS  Google Scholar 

  38. 38

    Araten, D. J. et al. A quantitative measurement of the human somatic mutation rate. Cancer Res. 65, 8111–8117 (2005).

    Article  CAS  Google Scholar 

  39. 39

    Sniegowski, P. D., Gerrish, P. J., Johnson, T. & Shaver, A. The evolution of mutation rates: separating causes from consequences. Bioessays 22, 1057–1066 (2000).

    Article  CAS  Google Scholar 

  40. 40

    Sniegowski, P. D., Gerrish, P. J. & Lenski, R. E. Evolution of high mutation rates in experimental populations of E. coli. Nature 387, 703–705 (1997).

    Article  CAS  Google Scholar 

  41. 41

    Dyer, M. A. & Bremner, R. The search for the retinoblastoma cell of origin. Nature Rev. Cancer 5, 91–101 (2005).

    Article  Google Scholar 

  42. 42

    Renan, M. J. How many mutations are required for tumorigenesis? Implications from human cancer data. Mol. Carcinogenesis 7, 139–146 (1993).

    Article  CAS  Google Scholar 

  43. 43

    Nunney, L. The population genetics of multistage carcinogenesis. Proc. Biol. Sci. 270, 1183–1191 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. 44

    Loeb, L. A. Mutator phenotype may be required for multistage carcinogenesis. Cancer Res. 51, 3075–3079 (1991). Shows that the background mutation rate is not adequate to explain carcinogenesis, and proposes that genetic instability might be necessary for cancer to develop.

    CAS  Google Scholar 

  45. 45

    Tomlinson, I. & Bodmer, W. Selection, the mutation rate and cancer: ensuring that the tail does not wag the dog. Nature Med. 5, 11–12 (1999).

    Article  CAS  Google Scholar 

  46. 46

    Moolgavkar, S. H. & Luebeck, E. G. Multistage carcinogenesis and the incidence of human cancer. Genes Chromosomes Cancer 38, 302–306 (2003).

    Article  CAS  Google Scholar 

  47. 47

    Loeb, K. R. & Loeb, L. A. Significance of multiple muta-tions in cancer. Carcinogenesis 21, 379–385 (2000).

    Article  CAS  Google Scholar 

  48. 48

    Maley, C. C. et al. The combination of genetic instability and clonal expansion predicts progression to esophageal adenocarcinoma. Cancer Res. 64, 7629–7633 (2004).

    Article  CAS  Google Scholar 

  49. 49

    Ohta, T. Slightly deleterious mutant substitutions in evolution. Nature 246, 96–98 (1973).

    Article  CAS  Google Scholar 

  50. 50

    Huntly, B. J. & Gilliland, D. G. Leukaemia stem cells and the evolution of cancer-stem-cell research. Nature Rev. Cancer 5, 311–321 (2005).

    Article  CAS  Google Scholar 

  51. 51

    Al-Hajj, M., Wicha, M. S., Benito-Hernandez, A., Morrison, S. J. & Clarke, M. F. Prospective identification of tumorigenic breast cancer cells. Proc. Natl Acad. Sci. USA 100, 3983–3988 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. 52

    Collins, A. T., Berry, P. A., Hyde, C., Stower, M. J. & Maitland, N. J. Prospective identification of tumorigenic prostate cancer stem cells. Cancer Res. 65, 10946–10951 (2005).

    Article  CAS  Google Scholar 

  53. 53

    Sell, S. Cellular origin of cancer: dedifferentiation or stem cell maturation arrest? Environ. Health Perspect. 101, 15–26 (1993).

    Article  PubMed  PubMed Central  Google Scholar 

  54. 54

    Potten, C. S., Booth, C. & Pritchard, D. M. The intestinal epithelial stem cell: the mucosal governor. Int. J. Exp. Pathol. 78, 219–243 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. 55

    Michor, F., Frank, S. A., May, R. M., Iwasa, Y. & Nowak, M. A. Somatic selection for and against cancer. J. Theor. Biol. 225, 377–382 (2003).

    Article  CAS  Google Scholar 

  56. 56

    Frank, S. A. & Nowak, M. A. Cell biology: developmental predisposition to cancer. Nature 422, 494 (2003).

    Article  CAS  Google Scholar 

  57. 57

    Meza, R., Luebeck, E. G. & Moolgavkar, S. H. Gestational mutations and carcinogenesis. Math. Biosci. 197, 188–210 (2005).

    Article  CAS  Google Scholar 

  58. 58

    Maynard Smith, J. & Haigh, J. The hitch-hiking effect of a favorable gene. Genet. Res. 231, 1114–1116 (1974).

    Google Scholar 

  59. 59

    Lewontin, R. C. The Genetic Basis of Evolutionary Change (Columbia University Press, New York, 1970).

    Google Scholar 

  60. 60

    Braakhuis, B. J., Tabor, M. P., Kummer, J. A., Leemans, C. R. & Brakenhoff, R. H. A genetic explanation of Slaughter's concept of field cancerization: evidence and clinical implications. Cancer Res. 63, 1727–1730 (2003).

    CAS  PubMed  Google Scholar 

  61. 61

    Chao, E. C. & Lipkin, S. M. Molecular models for the tissue specificity of DNA mismatch repair-deficient carcinogenesis. Nucleic Acids Res. 34, 840–852 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. 62

    Fearon, E. R. & Vogelstein, B. A genetic model for colorectal tumorigenesis. Cell 61, 759–767 (1990).

    Article  CAS  Google Scholar 

  63. 63

    Desper, R. et al. Inferring tree models for oncogenesis from comparative genome hybridization data. J. Comput. Biol. 37–51 (1999).

  64. 64

    Smith, G. et al. Mutations in APC, Kirsten-ras, and p53 — alternative genetic pathways to colorectal cancer. Proc. Natl Acad. Sci. USA 99, 9433–9438 (2002).

    Article  CAS  Google Scholar 

  65. 65

    Kobayashi, S. et al. EGFR mutation and resistance of non-small-cell lung cancer to gefitinib. N. Engl. J. Med. 352, 786–792 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. 66

    Gorre, M. E. et al. Clinical resistance to STI-571 cancer therapy caused by BCR-ABL gene mutation or amplification. Science 293, 876–880 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. 67

    Wang, T. L. et al. Digital karyotyping identifies thymidylate synthase amplification as a mechanism of resistance to 5-fluorouracil in metastatic colorectal cancer patients. Proc. Natl Acad. Sci. USA 101, 3089–3094 (2004).

    Article  CAS  Google Scholar 

  68. 68

    Donnenberg, V. S. & Donnenberg, A. D. Multiple drug resistance in cancer revisited: the cancer stem cell hypothesis. J. Clin. Pharmacol. 45, 872–877 (2005).

    Article  CAS  Google Scholar 

  69. 69

    Michor, F. et al. Dynamics of chronic myeloid leukaemia. Nature 435, 1267–1270 (2005).

    Article  CAS  Google Scholar 

  70. 70

    Luria, S. E. & Delbruck, M. Mutations of bacteria from virus sensitivity to virus resistance. Genetics 28, 491–511 (1943).

    CAS  PubMed  PubMed Central  Google Scholar 

  71. 71

    Komarova, N. Stochastic modeling of drug resistance in cancer. J. Theor. Biol. 239, 351–366 (2006).

    Article  CAS  Google Scholar 

  72. 72

    Roche-Lestienne, C. & Preudhomme, C. Mutations in the ABL kinase domain pre-exist the onset of imatinib treatment. Semin. Hematol. 40, 80–82 (2003).

    Article  CAS  Google Scholar 

  73. 73

    Iwasa, Y., Nowak, M. A. & Michor, F. Evolution of resistance during clonal expansion. Genetics 172, 2557–2566 (2006).

    Article  PubMed  PubMed Central  Google Scholar 

  74. 74

    Knudson, A. G. Jr. Mutation and cancer: statistical study of retinoblastoma. Proc. Natl Acad. Sci. USA 68, 820–823 (1971). Uses a Poisson model to deduce the requirement of two mutations to generate retinoblastoma.

    Article  Google Scholar 

  75. 75

    Etzioni, R. et al. The case for early detection. Nature Rev. Cancer 3, 1–10 (2003).

    Article  CAS  Google Scholar 

  76. 76

    Chabner, B. A. & Roberts, T. G. Jr. Timeline: chemotherapy and the war on cancer. Nature Rev. Cancer 5, 65–72 (2005).

    Article  CAS  Google Scholar 

  77. 77

    Komarova, N. L. & Wodarz, D. Evolutionary dynamics of mutator phenotypes in cancer: implications for chemotherapy. Cancer Res. 63, 6635–6642 (2003).

    CAS  PubMed  Google Scholar 

  78. 78

    Suiter, A. M., Banziger, O. & Dean, A. M. Fitness consequences of a regulatory polymorphism in a seasonal environment. Proc. Natl Acad. Sci. USA 100, 12782–12786 (2003).

    Article  CAS  Google Scholar 

  79. 79

    Kim, J. J. & Tannock, I. F. Repopulation of cancer cells during therapy: an important cause of treatment failure. Nature Rev. Cancer 5, 516–525 (2005).

    Article  CAS  Google Scholar 

  80. 80

    Kern, W. & Estey, E. H. High-dose cytosine arabinoside in the treatment of acute myeloid leukemia: review of three randomized trials. Cancer 107, 116–124 (2006).

    Article  CAS  Google Scholar 

  81. 81

    Dolken, G. Detection of minimal residual disease. Adv. Cancer Res. 82, 133–185 (2001).

    Article  CAS  Google Scholar 

  82. 82

    Rubin, C. E. et al. DNA aneuploidy in colonic biopsies predicts future development of dysplasia in ulcerative colitis. Gastroenterology 103, 1611–1620 (1992).

    Article  CAS  Google Scholar 

  83. 83

    Brentnall, T. A. et al. Mutations in the p53 gene: an early marker of neoplastic progression in ulcerative colitis. Gastroenterology 107, 369–378 (1994).

    Article  CAS  Google Scholar 

  84. 84

    van Oijen, M. G. & Slootweg, P. J. Oral field cancerization: carcinogen-induced independent events or micrometastatic deposits? Cancer Epidemiol. Biomarkers Prev. 9, 249–256 (2000).

    CAS  PubMed  Google Scholar 

  85. 85

    Hunter, K. W. Allelic diversity in the host genetic background may be an important determinant in tumor metastatic dissemination. Cancer Lett. 200, 97–105 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  86. 86

    Bernards, R. & Weinberg, R. A. A progression puzzle. Nature 418, 823 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. 87

    Bernards, R. & Weinberg, R. A. Bernards and Weinberg reply. Nature 419, 560 (2002).

    Article  CAS  Google Scholar 

  88. 88

    Fidler, I. J. & Kripke, M. L. Metastasis results from preexisting variant cells within a malignant tumor. Science 197, 893–895 (1977).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. 89

    Kirkwood, T. B. Evolution of ageing. Mech. Ageing Dev. 123, 737–745 (2002).

    Article  Google Scholar 

  90. 90

    Futuyma, D. J. Evolutionary Biology (Sinauer Associates Inc., Sunderland, Massachusetts, 1998).

    Google Scholar 

  91. 91

    Paszek, M. J. et al. Tensional homeostasis and the malignant phenotype. Cancer Cell 8, 241–254 (2005).

    Article  CAS  Google Scholar 

  92. 92

    Vaupel, P. & Mayer, A. Hypoxia and anemia: effects on tumor biology and treatment resistance. Transfus. Clin. Biol. 12, 5–10 (2005).

    Article  Google Scholar 

  93. 93

    Cadet, C., Ferriere, R., Metz, J. A. & van Baalen, M. The evolution of dispersal under demographic stochasticity. Am. Nat. 162, 427–441 (2003).

    Article  Google Scholar 

  94. 94

    Fidler, I. J. The pathogenesis of cancer metastasis: the 'seed and soil' hypothesis revisited. Nature Rev. Cancer 3, 453–458 (2003).

    Article  CAS  Google Scholar 

  95. 95

    Kolar, C. S. & Lodge, D. M. Progress in invasion biology: predicting invaders. Trends Ecol. Evol. 16, 199–204 (2001).

    Article  Google Scholar 

  96. 96

    Peterson, A. T. Predicting the geography of species' invasions via ecological niche modeling. Q. Rev. Biol. 78, 419–433 (2003).

    Article  Google Scholar 

  97. 97

    Shea, K. & Chesson, P. Community ecology theory as a framework for biological invasions. Trends Ecol. Evol. 17, 170–176 (2002).

    Article  Google Scholar 

  98. 98

    Mable, B. K. Breaking down taxonomic barriers in polyploidy research. Trends Plant Sci. 8, 582–590 (2003).

    Article  CAS  Google Scholar 

  99. 99

    Otto, S. P. & Whitton, J. Polyploid incidence and evolution. Annu. Rev. Genet. 34, 401–437 (2000).

    Article  CAS  Google Scholar 

  100. 100

    Imhof, M. & Schlotterer, C. E. coli microcosms indicate a tight link between predictability of ecosystem dynamics and diversity. PLoS Genet. 2, e103 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. 101

    Heppner, G., Miller, B., Cooper, D. N. & Miller, F. R. in Cell Biology of Breast Cancer (eds McGrath, C. M., Brennan, M. J. & Rich, M. A.) 161–172 (Academic Press, New York, 1980).

    Google Scholar 

  102. 102

    Guba, M. et al. A primary tumor promotes dormancy of solitary tumor cells before inhibiting angiogenesis. Cancer Res. 61, 5575–5579 (2001).

    CAS  PubMed  Google Scholar 

  103. 103

    Miller, B. E., Miller, F. R., Leith, J. & Heppner, G. H. Growth interaction in vivo between tumor subpopulations derived from a single mouse mammary tumor. Cancer Res. 40, 3977–3981 (1980). Shows that different clones in a neoplasm can affect each other's growth in complex ways.

    CAS  PubMed  Google Scholar 

  104. 104

    Caignard, A., Martin, M. S., Michel, M. F. & Martin, F. Interaction between two cellular subpopulations of a rat colonic carcinoma when inoculated to the syngeneic host. Int. J. Cancer 36, 273–279 (1985).

    Article  CAS  Google Scholar 

  105. 105

    Bach, L. A., Bentzen, S. M., Alsner, J. & Christiansen, F. B. An evolutionary-game model of tumour-cell interactions: possible relevance to gene therapy. Eur. J. Cancer 37, 2116–2120 (2001).

    Article  CAS  Google Scholar 

  106. 106

    Gatenby, R. A. & Vincent, T. L. An evolutionary model of carcinogenesis. Cancer Res. 63, 6212–6220 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  107. 107

    Nagy, J. D. Competition and natural selection in a mathematical model of cancer. Bull. Math. Biol. 66, 663–687 (2004).

    Article  Google Scholar 

  108. 108

    Seliger, B. Strategies of tumor immune evasion. BioDrugs 19, 347–354 (2005).

    Article  CAS  Google Scholar 

  109. 109

    Uhr, J. W., Scheuermann, R. H., Street, N. E. & Vitetta, E. S. Cancer dormancy: opportunities for new therapeutic approaches. Nature Med. 3, 505–509 (1997).

    Article  CAS  Google Scholar 

  110. 110

    Mitteldorf, J. Chaotic population dynamics and the evolution of aging. Evol. Ecol. Res. 8, 561–574 (2006).

    Google Scholar 

  111. 111

    Rundhaug, J. E. Matrix metalloproteinases and angiogenesis. J. Cell. Mol. Med. 9, 267–285 (2005).

    Article  CAS  Google Scholar 

  112. 112

    Travisano, M. & Velicer, G. J. Strategies of microbial cheater control. Trends Microbiol. 12, 72–78 (2004).

    Article  CAS  Google Scholar 

  113. 113

    Turner, P. E. Parasitism between co-infecting bacteriophages. Adv. Ecol. Res. 37, 309–332 (2005).

    Article  Google Scholar 

  114. 114

    Velicer, G. J., Kroos, L. & Lenski, R. E. Developmental cheating in the social bacterium Myxococcus xanthus. Nature 404, 598–601 (2000).

    Article  CAS  Google Scholar 

  115. 115

    Jouanneau, J., Moens, G., Bourgeois, Y., Poupon, M. F. & Thiery, J. P. A minority of carcinoma cells producing acidic fibroblast growth factor induces a community effect for tumor progression. Proc. Natl Acad. Sci. USA 91, 286–290 (1994).

    Article  CAS  Google Scholar 

  116. 116

    Axelrod, R., Axelrod, D. E. & Pienta, K. J. Evolution of cooperation among tumor cells. Proc. Natl Acad. Sci. USA 103, 13474–13479 (2006).

    Article  CAS  Google Scholar 

  117. 117

    Mueller, M. M. & Fusenig, N. E. Friends or foes- bipolar effects of the tumour stroma in cancer. Nature Rev. Cancer 4, 839–849 (2004).

    Article  CAS  Google Scholar 

  118. 118

    Shao, Z. M., Nguyen, M. & Barsky, S. H. Human breast carcinoma desmoplasia is PDGF initiated. Oncogene 19, 4337–4345 (2000).

    Article  CAS  Google Scholar 

  119. 119

    Tlsty, T. D. Stromal cells can contribute oncogenic signals. Semin. Cancer Biol. 11, 97–104 (2001).

    Article  CAS  Google Scholar 

  120. 120

    Fukino, K. et al. Combined total genome loss of heterozygosity scan of breast cancer stroma and epithelium reveals multiplicity of stromal targets. Cancer Res. 64, 7231–7236 (2004). Shows that tumour stroma also has genetic lesions, and so must be co-evolving with the epithelium.

    Article  CAS  Google Scholar 

  121. 121

    Paterson, R. F. et al. Molecular genetic alterations in the laser-capture-microdissected stroma adjacent to bladder carcinoma. Cancer 98, 1830–1836 (2003).

    Article  CAS  Google Scholar 

  122. 122

    Ishiguro, K., Yoshida, T., Yagishita, H., Numata, Y. & Okayasu, T. Epithelial and stromal genetic instability contributes to genesis of colorectal adenomas. Gut 55, 695–702 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  123. 123

    Kenny, P. A. & Bissell, M. J. Tumor reversion: correction of malignant behavior by microenvironmental cues. Int. J. Cancer 107, 688–695 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  124. 124

    Mintz, B. & Illmensee, K. Normal genetically mosaic mice produced from malignant teratocarcinoma cells. Proc. Natl Acad. Sci. USA 72, 3585–3589 (1975).

    Article  CAS  Google Scholar 

  125. 125

    Miller, F. R. & Heppner, G. H. Cellular interactions in metastasis. Cancer Metastasis Rev. 9, 21–34 (1990).

    Article  CAS  Google Scholar 

  126. 126

    Kuperwasser, C. et al. Reconstruction of functionally normal and malignant human breast tissues in mice. Proc. Natl Acad. Sci. USA 101, 4966–4971 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  127. 127

    Bhowmick, N. A. et al. TGF-β signaling in fibroblasts modulates the oncogenic potential of adjacent epithelia. Science 303, 848–851 (2004).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  128. 128

    Orimo, A. et al. Stromal fibroblasts present in invasive human breast carcinomas promote tumor growth and angiogenesis through elevated SDF-1/CXCL12 secretion. Cell 121, 335–348 (2005).

    Article  CAS  Google Scholar 

  129. 129

    Roxburgh, S. H., Shea, K. & Wilson, J. B. The intermediate disturbance hypothesis: patch dynamics and mechanisms of species coexistence. Ecology 85, 359–371 (2004).

    Article  Google Scholar 

  130. 130

    Bjerkvig, R., Tysnes, B. B., Aboody, K. S., Najbauer, J. & Terzis, A. J. Opinion: the origin of the cancer stem cell: current controversies and new insights. Nature Rev. Cancer 5, 899–904 (2005).

    Article  CAS  Google Scholar 

  131. 131

    Boyer, B., Valles, A. M. & Edme, N. Induction and regulation of epithelial-mesenchymal transitions. Biochem. Pharmacol. 60, 1091–1099 (2000).

    Article  CAS  Google Scholar 

  132. 132

    Elena, S. F. & Lenski, R. E. Evolution experiments with microorganisms: the dynamics and genetic bases of adaptation. Nature Rev. Genet. 4, 457–469 (2003).

    Article  CAS  Google Scholar 

  133. 133

    Spencer, S. L., Gerety, R. A., Pienta, K. J. & Forrest, S. Modeling somatic evolution in tumorigenesis. PLoS Comput. Biol. 2, e108 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  134. 134

    Drummond, A., Forsberg, R. & Rodrigo, A. G. The inference of stepwise changes in substitution rates using serial sequence samples. Mol. Biol. Evol. 18, 1365–1371 (2001).

    Article  CAS  Google Scholar 

  135. 135

    Harper, D. M. et al. Sustained efficacy up to 4.5 years of a bivalent L1 virus-like particle vaccine against human papillomavirus types 16 and 18: follow-up from a randomised control trial. Lancet 367, 1247–1255 (2006).

    Article  CAS  Google Scholar 

  136. 136

    Jakobisiak, M., Lasek, W. & Golab, J. Natural mechanisms protecting against cancer. Immunol. Lett. 90, 103–122 (2003).

    Article  CAS  Google Scholar 

  137. 137

    Sherr, C. J. Tumor surveillance via the ARF-p53 pathway. Genes Dev. 12, 2984–2991 (1998).

    Article  CAS  Google Scholar 

  138. 138

    Michor, F., Nowak, M. A., Frank, S. A. & Iwasa, Y. Stochastic elimination of cancer cells. Proc. Biol. Sci. 270, 2017–2024 (2003).

    Article  PubMed  PubMed Central  Google Scholar 

  139. 139

    Torres-Montaner, A. & Hughes, D. A hypothetical anti-neoplastic mechanism associated to reserve cells. J. Theor. Biol. 231, 239–248 (2004).

    Article  Google Scholar 

  140. 140

    Frank, S. A., Iwasa, Y. & Nowak, M. A. Patterns of cell division and the risk of cancer. Genetics 163, 1527–1532 (2003).

    PubMed  PubMed Central  Google Scholar 

  141. 141

    Komarova, N. L. & Cheng, P. Epithelial tissue architecture protects against cancer. Math. Biosci. 200, 90–117 (2006).

    Article  Google Scholar 

  142. 142

    Nowak, M. A., Michor, F. & Iwasa, Y. The linear process of somatic evolution. Proc. Natl Acad. Sci. USA 100, 14966–14969 (2003). Uses a mathematical model to analyse the evolutionary dynamics of cells in structured tissues.

    Article  CAS  Google Scholar 

  143. 143

    Frank, S. A. Genetic predisposition to cancer — insights from population genetics. Nature Rev. Genet. 5, 764–772 (2004).

    Article  CAS  Google Scholar 

  144. 144

    Fleming, M. A., Potter, J. D., Ramirez, C. J., Ostrander, G. K. & Ostrander, E. A. Understanding missense mutations in the BRCA1 gene: an evolutionary approach. Proc. Natl Acad. Sci. USA 100, 1151–1156 (2003).

    Article  CAS  Google Scholar 

  145. 145

    Slatkin, M. & Rannala, B. Estimating allele age. Annu. Rev. Genomics Hum. Genet. 1, 225–249 (2000).

    Article  CAS  Google Scholar 

  146. 146

    Deng, C. X. BRCA1: cell cycle checkpoint, genetic instability, DNA damage response and cancer evolution. Nucleic Acids Res. 34, 1416–1426 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  147. 147

    Jernstrom, H., Johannsson, O., Borg, A., Ivarsson, H. & Olsson, H. BRCA1-positive patients are small for gestational age compared with their unaffected relatives. Eur. J. Cancer 34, 368–371 (1998).

    Article  CAS  Google Scholar 

  148. 148

    Smith, T. M. et al. Complete genomic sequence and analysis of 117 kb of human DNA containing the gene BRCA1. Genome Res. 6, 1029–1049 (1996).

    Article  CAS  Google Scholar 

  149. 149

    Pavlicek, A. et al. Evolution of the tumor suppressor BRCA1 locus in primates: implications for cancer pre-disposition. Hum. Mol. Genet. 13, 2737–2751 (2004).

    Article  CAS  Google Scholar 

  150. 150

    Summers, K. & Crespi, B. Cadherins in maternal–foetal interactions: red queen with a green beard? Proc. Biol. Sci. 272, 643–649 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  151. 151

    Nielsen, R. et al. A scan for positively selected genes in the genomes of humans and chimpanzees. PLoS Biol. 3, e170 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  152. 152

    Crespi, B. J. & Summers, K. Positive selection in the evolution of cancer. Biol. Rev. Camb. Philos. Soc. 81, 407–424 (2006).

    Article  Google Scholar 

  153. 153

    Hernandez, L., Kozlov, S., Piras, G. & Stewart, C. L. Paternal and maternal genomes confer opposite effects on proliferation, cell-cycle length, senescence, and tumor formation. Proc. Natl Acad. Sci. USA 100, 13344–13349 (2003).

    Article  CAS  Google Scholar 

  154. 154

    Moran, P. A. P. Random processes in genetics. Proc. Camb. Phil. Soc. 54, 60–71 (1958).

    Article  Google Scholar 

  155. 155

    Ewens, W. J. Mathematical Population Genetics (Springer-Verlag, New York, 2004).

    Google Scholar 

  156. 156

    Reid, B. J. et al. Barrett's esophagus: ordering the events that lead to cancer. Euro. J. Cancer Prev. 5 (Suppl. 2), 57–65 (1996). Shows how spatial information can be used to infer dependencies between genetic alterations in carcinogenesis.

    Article  Google Scholar 

  157. 157

    Wang, G. Q. et al. Histological precursors of oesophageal squamous cell carcinoma: results from a 13 year prospective follow up study in a high risk population. Gut 54, 187–192 (2005).

    Article  PubMed  PubMed Central  Google Scholar 

  158. 158

    Reid, B. J. et al. Predictors of progression in Barrett's esophagus II: baseline 17p (p53) loss of heterozygosity identifies a patient subset at increased risk for neoplastic progression. Am. J. Gastroenterol. 96, 2839–2848 (2001).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  159. 159

    Dolan, K., Morris, A. I., Gosney, J. R., Field, J. K. & Sutton, R. Loss of heterozygosity on chromosome 17p predicts neoplastic progression in Barrett's esophagus. J. Gastroenterol. Hepatol. 18, 683–689 (2003).

    Article  CAS  Google Scholar 

  160. 160

    Teodori, L. et al. DNA/protein flow cytometry as a predictive marker of malignancy in dysplasia-free Barrett's esophagus: thirteen-year follow-up study on a cohort of patients. Cytometry 34, 257–263 (1998).

    Article  CAS  Google Scholar 

  161. 161

    Lee, J. J. et al. Predicting cancer development in oral leukoplakia: ten years of translational research. Clin. Cancer Res. 6, 1702–1710 (2000).

    CAS  PubMed  Google Scholar 

  162. 162

    Rosin, M. P. et al. Use of allelic loss to predict malignant risk for low-grade oral epithelial dysplasia. Clin. Cancer Res. 6, 357–362 (2000).

    CAS  PubMed  Google Scholar 

  163. 163

    Befrits, R., Hammarberg, C., Rubio, C., Jaramillo, E. & Tribukait, B. DNA aneuploidy and histologic dysplasia in long-standing ulcerative colitis. A 10-year follow-up study. Dis. Colon. Rectum 37, 313–319; discussion 319–320 (1994).

    Article  CAS  Google Scholar 

  164. 164

    Lofberg, R., Brostrom, O., Karlen, P., Tribukait, B. & Ost, A. Colonoscopic surveillance in long-standing total ulcerative colitis-a 15-year follow-up study. Gastroenterology 4, 1021–1021 (1990).

    Article  Google Scholar 

  165. 165

    Wong, B. C. et al. Helicobacter pylori eradication to prevent gastric cancer in a high-risk region of China: a randomized controlled trial. JAMA 291, 187–194 (2004).

    Article  CAS  Google Scholar 

  166. 166

    Thompson, I. M. et al. The influence of finasteride on the development of prostate cancer. N. Engl. J. Med. 349, 215–224 (2003).

    Article  CAS  Google Scholar 

  167. 167

    Abrams, P. A. On classifying interactions between populations. Oecologia 73, 272–281 (1987).

    Article  CAS  Google Scholar 

  168. 168

    Heppner, G. H., Miller, B. E. & Miller, F. R. Tumor subpopulation interactions in neoplasms. Biochim. Biophys. Acta 695, 215–226 (1983).

    CAS  PubMed  Google Scholar 

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Acknowledgements

This work was supported by the US National Institutes of Health, the Commonwealth of Pennsylvania, and the Pew Charitable Trust, and initiated by the Santa Fe Institute. We thank W. Ewens, M. Carroll and J. Radich for helpful comments. We apologize to our peers whose work we were unable to cite owing to space limitations.

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Correspondence to Carlo C. Maley.

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Glossary

Clone

A set of cells that share a common genotype owing to descent from a common ancestor. In some contexts a clone is more restrictively defined as a set of genetically identical cells.

Fitness

The average contribution of a genotype to future generations. Fitness is generally a function of both survival and reproduction.

Genetic drift

Random changes in allele frequencies over generations. This dynamic of random sampling has a greater effect in smaller populations.

Neutral mutation

A mutation that has no fitness effect (survival or reproductive effect).

Fixation

When an allele (or in this case a clone) reaches 100% frequency in a population.

Hitchhiker mutation

An effectively neutral mutation that expands in a population because it is linked to a selectively advantageous allele. Sometimes called a 'passenger mutation' in cancer biology.

Molecular clock

When mutations occur at a constant rate, the number of mutations that have accumulated between two different lineages is representative of the time since the lineages diverged.

Selective sweep

The process of an adaptive mutation spreading through a population, typically ending in fixation.

Amensal

An interaction between individuals that decreases the fitness of one party but has no effect on the other.

Lotka–Volterra competition equations

The Lotka–Volterra model of competition is based on logistic growth equations of two populations that negatively affect each other's growth.

Mutualistic

An interaction between individuals that increases the fitness of both parties.

Commensal

An interaction between individuals that increases the fitness of one party and has no fitness effect on the other.

Fitness landscape

A multi-dimensional space in which every point represents the genotype or phenotype of a cell and its fitness value. Points are connected if a mutational event can transform one genotype (or phenotype) into the other.

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Merlo, L., Pepper, J., Reid, B. et al. Cancer as an evolutionary and ecological process. Nat Rev Cancer 6, 924–935 (2006). https://doi.org/10.1038/nrc2013

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