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An analogy between the evolution of drug resistance in bacterial communities and malignant tissues

Abstract

Cancer cells rapidly evolve drug resistance through somatic evolution and, in order to continue growth in the metastatic phase, violate the organism-wide consensus of regulated growth and beneficial communal interactions. We suggest that there is a fundamental mechanistic connection between the rapid evolution of resistance to chemotherapy in cellular communities within malignant tissues and the rapid evolution of antibiotic resistance in bacterial communities. We propose that this evolution is the result of a programmed and collective stress response performed by interacting cells, and that, given this fundamental connection, studying bacterial communities can provide deeper insights into the dynamics of adaptation and the evolution of cells within tumours.

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Figure 1: An alternative view of cancer development.
Figure 2: Changes in microenvironments.
Figure 3: Proposed experimental approaches to investigate drug resistance using bacterial models.
Figure 4: Evolutionary aspects of biofilm development as a model of drug resistance in tumours.

References

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

    Article  CAS  PubMed  Google Scholar 

  2. Ellis, L. M. & Hicklin, D. J. VEGF-targeted therapy: mechanisms of anti-tumour activity. Nature Rev. Cancer 8, 579–591 (2008).

    CAS  Google Scholar 

  3. Weinstein, I. B. & Joe, A. Oncogene addiction. Cancer Res. 68, 3077–3080 (2008).

    CAS  PubMed  Google Scholar 

  4. Letai, A. G. Diagnosing and exploiting cancer's addiction to blocks in apoptosis. Nature Rev. Cancer 8, 121–132 (2008).

    CAS  Google Scholar 

  5. Kamb, A., Wee, S. & Lengauer, C. Why is cancer drug discovery so difficult? Nature Rev. Drug Discov. 6, 115–120 (2007).

    CAS  Google Scholar 

  6. Lage, H. An overview of cancer multidrug resistance: a still unsolved problem. Cell. Mol. Life Sci. 65, 3145–3167 (2008).

    CAS  PubMed  Google Scholar 

  7. Butler, M. T., Wang, Q. & Harshey, R. M. Cell density and mobility protect swarming bacteria against antibiotics. Proc. Natl Acad. Sci. USA 107, 3776–3781 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  8. Ahmed, N., Abubaker, K., Findlay, J. & Quinn, M. Epithelial mesenchymal transition and cancer stem cell-like phenotypes facilitate chemoresistance in recurrent ovarian cancer. Curr. Cancer Drug Targets 10, 268–278 (2010).

    CAS  PubMed  Google Scholar 

  9. Stewart, P. S. & Costerton, J. W. Antibiotic resistance of bacteria in biofilms. Lancet 358, 135–138 (2001).

    CAS  PubMed  Google Scholar 

  10. Tong, R. T. et al. Vascular normalization by vascular endothelial growth factor receptor 2 blockade induces a pressure gradient across the vasculature and improves drug penetration in tumors. Cancer Res. 64, 3731–3736 (2004).

    CAS  PubMed  Google Scholar 

  11. Bock, K. D., Cauwenberghs, S. & Carmeliet, P. Vessel abnormalization: another hallmark of cancer? Molecular mechanisms and therapeutic implications. Curr. Opin. Genet. Dev. 21, 73–79 (2011).

    PubMed  Google Scholar 

  12. Balaban, N. Q., Merrin, J., Chait, R., Kowalik, L. & Leibler, S. Bacterial persistence as a phenotypic switch. Science 305, 1622–1625 (2004).

    CAS  PubMed  Google Scholar 

  13. Sharma, S. V. et al. A Chromatin-mediated reversible drug-tolerant state in cancer cell subpopulations. Cell 141, 69–80 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Alonso, A., Campanario, E. & Martinez, J. L. Emergence of multidrug-resistant mutants is increased under antibiotic selective pressure in Pseudomonas aeruginosa. Microbiology 145, 2857–2862 (1999).

    CAS  PubMed  Google Scholar 

  15. Cirz, R. T. et al. Inhibition of mutation and combating the evolution of antibiotic resistance. PLoS Biol. 3, e176 (2005).

    PubMed  PubMed Central  Google Scholar 

  16. Schimke, R., Kaufman, R., Alt, F. & Kellems, R. Gene amplification and drug resistance in cultured murine cells. Science 202, 1051–1055 (1978).

    CAS  PubMed  Google Scholar 

  17. Longley, D. B. & Johnston, P. G. Molecular mechanisms of drug resistance. J. Pathol. 205, 275–292 (2005).

    CAS  PubMed  Google Scholar 

  18. Sniegowski, P. D. & Murphy, H. A. Evolvability. Curr. Biol. 16, R831–R834 (2006).

    CAS  PubMed  Google Scholar 

  19. Bielas, J. H., Loeb, K. R., Rubin, B. P., True, L. D. & Loeb, L. A. Human cancers express a mutator phenotype. Proc. Natl Acad. Sci. USA 103, 18238–18242 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Bjedov, I. et al. Stress-induced mutagenesis in bacteria. Science 300, 1404–1409 (2003).

    CAS  PubMed  Google Scholar 

  21. Earl, D. J. & Deem, M. W. Evolvability is a selectable trait. Proc. Natl Acad. Sci. USA 101, 11531–11536 (2004).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Draghi, J. A., Parsons, T. L., Wagner, G. P. & Plotkin, J. B. Mutational robustness can facilitate adaptation. Nature 463, 353–355 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 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).

    CAS  PubMed  Google Scholar 

  24. Giraud, A. et al. Costs and benefits of high mutation rates: adaptive evolution of bacteria in the mouse gut. Science 291, 2606–2608 (2001).

    CAS  PubMed  Google Scholar 

  25. Ponder, R. G., Fonville, N. C. & Rosenberg, S. M. A switch from high-fidelity to error-prone DNA double-strand break repair underlies stress-induced mutation. Mol. Cell 19, 791–804 (2005).

    CAS  PubMed  Google Scholar 

  26. Gonzalez, C. et al. Mutability and importance of a hypermutable cell subpopulation that produces stress-induced mutants in Escherichia coli. PLoS Genet. 4, e1000208 (2008).

    PubMed  PubMed Central  Google Scholar 

  27. Drlica, K. & Zhao, X. DNA gyrase, topoisomerase IV, and the 4-quinolones. Microbiol. Mol. Biol. Rev. 61, 377–392 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Viswanathan, A., You, H. & Doetsch, P. Phenotypic change caused by transcriptional bypass of uracil in nondividing cells. Science 284, 159–162 (1999).

    CAS  PubMed  Google Scholar 

  29. Lengauer, C., Kinzler, K. W. & Vogelstein, B. Genetic instabilities in human cancers. Nature 396, 643–649 (1998).

    CAS  PubMed  Google Scholar 

  30. Saxowsky, T. T., Meadows, K. L., Klungland, A. & Doetsch, P. W. 8-oxoguanine-mediated transcriptional mutagenesis causes ras activation in mammalian cells. Proc. Natl Acad. Sci. USA 105, 18877–18882 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Ma, L. et al. Assembly and development of the Pseudomonas aeruginosa biofilm matrix. PLoS Pathog. 5, e1000354 (2009).

    PubMed  PubMed Central  Google Scholar 

  32. Stewart, P. S. Diffusion in biofilms. J. Bacteriol. 185, 1485–1491 (2003).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Rani, S. A. et al. Spatial patterns of DNA replication, protein synthesis, and oxygen concentration within bacterial biofilms reveal diverse physiological states. J. Bacteriol. 189, 4223–4233 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  34. Driffield, K., Miller, K., Bostock, J. M., O.' Neill, A. J. & Chopra, I. Increased mutability of Pseudomonas aeruginosa in biofilms. J. Antimicrob. Chemother. 61, 1053–1056 (2008).

    CAS  PubMed  Google Scholar 

  35. Oliver, A., Canton, R., Campo, P., Baquero, F. & Blazquez, J. High frequency of hypermutable Pseudomonas aeruginosa in cystic fibrosis lung infection. Science 288, 1251–1253 (2000).

    CAS  PubMed  Google Scholar 

  36. Boles, B. R. & Singh, P. K. Endogenous oxidative stress produces diversity and adaptability in biofilm communities. Proc. Natl Acad. Sci. USA 105, 12503–12508 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  37. Macia, M. D. et al. Hypermutation is a key factor in development of multiple-antimicrobial resistance in Pseudomonas aeruginosa strains causing chronic lung infections. Antimicrob. Agents Chemother. 49, 3382–3386 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Taddei, F. et al. Role of mutator alleles in adaptive evolution. Nature 387, 700–702 (1997).

    CAS  PubMed  Google Scholar 

  39. Liotta, L. A. & Kohn, E. C. The microenvironment of the tumour–host interface. Nature 411, 375–379 (2001).

    CAS  PubMed  Google Scholar 

  40. Joyce, J. A. & Pollard, J. W. Microenvironmental regulation of metastasis. Nature Rev. Cancer 9, 239–252 (2009).

    CAS  Google Scholar 

  41. Kalluri, R. & Zeisberg, M. Fibroblasts in cancer. Nature Rev. Cancer 6, 392–401 (2006).

    CAS  Google Scholar 

  42. Sethi, T. et al. Extracellular matrix proteins protect small cell lung cancer cells against apoptosis: a mechanism for small cell lung cancer growth and drug resistance in vivo. Nature Med. 5, 662–668 (1999).

    CAS  PubMed  Google Scholar 

  43. Rintoul, R. & Sethi, T. Extracellular matrix regulation of drug resistance in small-cell lung cancer. Clin. Sci. 102, 417–424 (2002).

    CAS  Google Scholar 

  44. Tredan, O., Galmarini, C. M., Patel, K. & Tannock, I. F. Drug resistance and the solid tumor microenvironment. J. Natl Cancer Inst. 99, 1441–1454 (2007).

    CAS  PubMed  Google Scholar 

  45. Gatenby, R. A. & Gillies, R. J. Why do cancers have high aerobic glycolysis? Nature Rev. Cancer 4, 891–899 (2004).

    CAS  Google Scholar 

  46. Tlsty, T. D. & Coussens, L. M. Tumor stroma and regulation of cancer development. Annu. Rev. Pathol. 1, 119–150 (2006).

    CAS  PubMed  Google Scholar 

  47. Koukourakis, M. I., Giatromanolaki, A., Harris, A. L. & Sivridis, E. Comparison of metabolic pathways between cancer cells and stromal cells in colorectal carcinomas: a metabolic survival role for tumor-associated stroma. Cancer Res. 66, 632–637 (2006).

    CAS  PubMed  Google Scholar 

  48. Kansal, A. R., Torquato, S., Chiocca, E. A. & Deisboeck, T. S. Emergence of a subpopulation in a computational model of tumor growth. J. Theoret. Biol. 207, 431–441 (2000).

    CAS  Google Scholar 

  49. Bellomo, N., Li, N. & Maini, P. On the foundations of cancer modelling: selected topics, speculations, and perspectives. Math. Models Meth. Appl. Sci. 18, 593–646 (2008).

    Google Scholar 

  50. Kim, M. et al. Tumor self-seeding by circulating cancer cells. Cell 139, 1315–1326 (2009).

    PubMed  PubMed Central  Google Scholar 

  51. Tourovskaia, A., Figueroa-Masot, X. & Folch, A. Differentiation-on-a-chip: a microfluidic platform for long-term cell culture studies. Lab. Chip 5, 14–19 (2005).

    CAS  PubMed  Google Scholar 

  52. Kimura, H., Yamamoto, T., Sakai, H., Sakai, Y. & Fujii, T. An integrated microfluidic system for long-term perfusion culture and on-line monitoring of intestinal tissue models. Lab. Chip 8, 741–746 (2008).

    CAS  PubMed  Google Scholar 

  53. Liu, L. et al. A microfluidic device for continuous cancer cell culture and passage with hydrodynamic forces. Lab. Chip 10, 1807–1813 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. Groisman, A. et al. A microfluidic chemostat for experiments with bacterial and yeast cells. Nature Meth. 2, 685–689 (2005).

    CAS  Google Scholar 

  55. Balagadde, F. K., You, L., Hansen, C. L., Arnold, F. H. & Quake, S. R. Long-term monitoring of bacteria undergoing programmed population control in a microchemostat. Science 309, 137–140 (2005).

    CAS  PubMed  Google Scholar 

  56. Austin, R. H., Tung, C. K., Lambert, G., Liao, D. & Gong, X. An introduction to micro-ecology patches. Chem. Soc. Rev. 39, 1049–1059 (2010).

    CAS  PubMed  Google Scholar 

  57. Hermsen, R. & Hwa, T. Sources and sinks: a stochastic model of evolution in heterogeneous environments. Phys. Rev. Lett. 105, 248104 (2010).

    PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  59. Maley, C. C. et al. Genetic clonal diversity predicts progression to esophageal adenocarcinoma. Nature Genet. 38, 468–473 (2006).

    CAS  PubMed  Google Scholar 

  60. Conibear, T. C. R., Collins, S. L. & Webb, J. S. Role of mutation in Pseudomonas aeruginosa biofilm development. PLoS ONE 4, e6289 (2009).

    PubMed  PubMed Central  Google Scholar 

  61. West, S. A., Griffin, A. S., Gardner, A. & Diggle, S. P. Social evolution theory for microorganisms. Nature Rev. Microbiol. 4, 597–607 (2006).

    CAS  Google Scholar 

  62. Lee, H. H., Molla, M. N., Cantor, C. R. & Collins, J. J. Bacterial charity work leads to population-wide resistance. Nature 467, 82–85 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  63. Fordyce, C. et al. DNA damage drives an activin A-dependent induction of cyclooxygenase-2 in premalignant cells and lesions. Cancer Prev. Res. 3, 190–201 (2010).

    CAS  Google Scholar 

  64. Hickson, J. et al. Societal interactions in ovarian cancer metastasis: a quorum-sensing hypothesis. Clin. Exp. Metastasis 26, 67–76 (2008).

    PubMed  Google Scholar 

  65. Miller, M. B. & Bassler, B. L. Quorum sensing in bacteria. Annu. Rev. Microbiol. 55, 165–199 (2001).

    CAS  PubMed  Google Scholar 

  66. Smith, J. M. Evolution and the Theory of Games 1st edn (Cambridge Univ. Press, Cambridge, UK,1982).

    Google Scholar 

  67. Hahn, W. C. & Weinberg, R. A. Modelling the molecular circuitry of cancer. Nature Rev. Cancer 2, 331–341 (2002).

    CAS  Google Scholar 

  68. Loewen, P. C. & Hengge-Aronis, R. The role of the sigma factor sigmas (KatF) in bacterial global regulation. Annu. Rev. Microbiol. 48, 53–80 (1994).

    CAS  PubMed  Google Scholar 

  69. Zambrano, M., Siegele, D., Almiron, M., Tormo, A. & Kolter, R. Microbial competition: Escherichia coli mutants that take over stationary phase cultures. Science 259, 1757–1760 (1993).

    CAS  PubMed  Google Scholar 

  70. Keymer, J. E., Galajda, P., Lambert, G., Liao, D. & Austin, R. H. Computation of mutual fitness by competing bacteria. Proc. Natl Acad. Sci. USA 105, 20269–20273 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  71. Feist, A. M., Herrgard, M. J., Thiele, I., Reed, J. L. & Palsson, B. O. Reconstruction of biochemical networks in microorganisms. Nature Rev. Microbiol. 7, 129–143 (2009).

    CAS  Google Scholar 

  72. Lewis, N. E. et al. Large-scale in silico modeling of metabolic interactions between cell types in the human brain. Nature Biotech. 28, 1279–1285 (2010).

    CAS  Google Scholar 

  73. Moynahan, M. E., Chiu, J. W., Koller, B. H. & Jasin, M. Brca1 controls homology-directed DNA repair. Mol. Cell 4, 511–518 (1999).

    CAS  PubMed  Google Scholar 

  74. Walker, G. C. Inducible DNA repair systems. Annu. Rev. Biochem. 54, 425–457 (1985).

    CAS  PubMed  Google Scholar 

  75. Fernández De Henestrosa, A. R. et al. Identification of additional genes belonging to the LexA regulon in Escherichia coli. Mol. Microbiol. 35, 1560–1572 (2000).

    PubMed  Google Scholar 

  76. Goodman, M. F. Error-prone repair, DNA polymerases in prokaryotes and eukaryotes. Annu. Rev. Biochem. 71, 17–50 (2002).

    CAS  PubMed  Google Scholar 

  77. Hicks, W. M., Kim, M. & Haber, J. E. Increased mutagenesis and unique mutation signature associated with mitotic gene conversion. Science 329, 82–85 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  78. Oliver, A. & Mena, A. Bacterial hypermutation in cystic fibrosis, not only for antibiotic resistance. Clin. Microbiol. Infect. 16, 798–808 (2010).

    CAS  PubMed  Google Scholar 

  79. Jensen, R. B., Carreira, A. & Kowalczykowski, S. C. Purified human BRCA2 stimulates RAD51-mediated recombination. Nature 467, 678–683 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Patel, K. J. et al. Involvement of Brca2 in DNA repair. Mol. Cell 1, 347–357 (1998).

    CAS  PubMed  Google Scholar 

  81. Roca, A. & Cox, M. RecA protein: structure, function, and role in recombinational DNA repair. Prog. Nucleic Acid Res. Mol. Biol. 56, 129–223 (1997).

    CAS  PubMed  Google Scholar 

  82. Levine, A. J. p53, the cellular gatekeeper for growth and division. Cell 88, 323–331 (1997).

    CAS  PubMed  Google Scholar 

  83. Hollstein, M. et al. Database of p53 gene somatic mutations in human tumors and cell lines. Nucleic Acids Res. 22, 3551–3555 (1994).

    CAS  PubMed  PubMed Central  Google Scholar 

  84. Branda, S. S., Vik, A., Friedman, L. & Kolter, R. Biofilms: the matrix revisited. Trends Microbiol. 13, 20–26 (2005).

    CAS  PubMed  Google Scholar 

  85. Monds, R. D. & O.'Toole, G. A. The developmental model of microbial biofilms: ten years of a paradigm up for review. Trends Microbiol. 17, 73–87 (2009).

    CAS  PubMed  Google Scholar 

  86. Stewart, P. S. & Franklin, M. J. Physiological heterogeneity in biofilms. Nature Rev. Microbiol. 6, 199–210 (2008).

    CAS  Google Scholar 

  87. Costerton, J. W., Stewart, P. S. & Greenberg, E. P. Bacterial biofilms: a common cause of persistent infections. Science 284, 1318–1322 (1999).

    CAS  PubMed  Google Scholar 

  88. Donlan, R. M. & Costerton, J. W. Biofilms: survival mechanisms of clinically relevant microorganisms. Clin. Microbiol. Rev. 15, 167–193 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  89. Stoodley, P. et al. Growth and detachment of cell clusters from mature mixed-species biofilms. Appl. Environ. Microbiol. 67, 5608–5613 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

We wish to thank D. Coffey and A. Barker for their helpful comments. The research described was supported by award U54CA143803 from the US National Cancer Institute. The content is solely the responsibility of the authors and does not necessarily represent the official views of the US National Cancer Institute or the US National Institutes of Health.

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Correspondence to Thea D. Tlsty or Robert H. Austin.

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Glossary

Altruism

Behaviours that benefit another individual while incurring a cost to oneself.

Biofilm

A multicellular aggregate of bacteria and its associated proteinaceous matrix formed in response to external stress.

Cheating

A strategy in which individuals do not cooperate but still benefit from the positive interactions with cooperating individuals.

Clonal expansion

Population growth that is mainly carried out by a single genotype.

Cooperation

Actions or behaviours that are beneficial to other individuals.

Cystic fibrosis

An inherited disease that causes thick mucus to build up in the lungs and the digestive tract.

Cytocidal agent

A molecule or drug causing cell death.

Exopolymer matrix

A polysaccharide-based extracellular matrix collectively secreted by bacteria in biofilms. The matrix links cells together and acts as a protective microenvironment.

Game theory

A mathematical theory describing the costs and benefits associated with the interactions among individuals of a group. This theory is most often used in economics and evolutionary biology.

Genetic drift

A process through which the frequency of genes in populations fluctuates because selection occurs mainly by chance.

Growth advantage under stationary phase

(GASP). A phenotype that allows certain bacterial cells to outcompete wild-type cells by maintaining a proliferative state while the wild-type cells cease to grow and enter stationary phase.

Phenotypic switching

The ability of organisms to alternate between two distinct states in order to adapt to fluctuating environments.

Retromutagenesis

A process whereby DNA damage that causes changes to base pairing becomes incorporated into the genome. This may occur if a mutant protein resulting from transcriptional mutagenesis causes the rapid restart of DNA replication, thus resulting in a genetic lesion that alters base pairing being copied by a DNA polymerase before the lesion is repaired and thereby altering the DNA sequence.

SOS response

A global DNA damage response in bacteria that involves cell cycle arrest and mutagenic DNA repair and recombination.

Source–sink ecology

A theoretical model used to describe the dynamics of a population inside habitats that either promote growth (source) or induce death (sink).

Transcriptional mutagenesis

A process by which proteins with altered functions are translated because RNA polymerases transcribe mRNA from a template containing DNA damage.

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Lambert, G., Estévez-Salmeron, L., Oh, S. et al. An analogy between the evolution of drug resistance in bacterial communities and malignant tissues. Nat Rev Cancer 11, 375–382 (2011). https://doi.org/10.1038/nrc3039

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