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Evolutionary dynamics of carcinogenesis and why targeted therapy does not work

Abstract

All malignant cancers, whether inherited or sporadic, are fundamentally governed by Darwinian dynamics. The process of carcinogenesis requires genetic instability and highly selective local microenvironments, the combination of which promotes somatic evolution. These microenvironmental forces, specifically hypoxia, acidosis and reactive oxygen species, are not only highly selective, but are also able to induce genetic instability. As a result, malignant cancers are dynamically evolving clades of cells living in distinct microhabitats that almost certainly ensure the emergence of therapy-resistant populations. Cytotoxic cancer therapies also impose intense evolutionary selection pressures on the surviving cells and thus increase the evolutionary rate. Importantly, the principles of Darwinian dynamics also embody fundamental principles that can illuminate strategies for the successful management of cancer.

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Figure 1: A unifying model of carcinogenesis.

References

  1. Nowell, P. C. The clonal evolution of tumor cell populations. Science 194, 23–28 (1976).

    CAS  PubMed  Article  Google Scholar 

  2. Jones, S. et al. Comparative lesion sequencing provides insights into tumor evolution. Proc. Natl Acad. Sci. USA 105, 4283–4288 (2008).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  3. Gerlinger, M. et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N. Engl. J. Med. 366, 883–892 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  4. Gerlinger, M. & Swanton, C. How Darwinian models inform therapeutic failure initiated by clonal heterogeneity in cancer medicine. Br. J. Cancer 103, 1139–1143 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  5. Greaves, M. & Maley, C. C. Clonal evolution in cancer. Nature 481, 306–313 (2012).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  6. Gatenby, R. A., Gillies, R. J. & Brown, J. S. Of cancer and cave fish. Nature Rev. Cancer 11, 237–238 (2011).

    CAS  Article  Google Scholar 

  7. Gillies, R. J., Robey, I. & Gatenby, R. A. Causes and consequences of increased glucose metabolism of cancers. J. Nucl Med 49 Suppl 2, 24S–42S (2008).

    CAS  PubMed  Article  Google Scholar 

  8. Allred, D. C. et al. Ductal carcinoma in situ and the emergence of diversity during breast cancer evolution. Clin. Cancer Res. 14, 370–378 (2008).

    CAS  Article  PubMed  Google Scholar 

  9. Gatenby, R. A. & Gillies, R. J. A microenvironmental model of carcinogenesis. Nature Rev. Cancer 8, 56–61 (2008).

    CAS  Article  Google Scholar 

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

    CAS  Article  Google Scholar 

  11. Loeb, L. A. Mutator phenotype may be required for multistage carcinogenesis. Cancer Res. 51, 3075–3079 (1991).

    CAS  PubMed  Google Scholar 

  12. Cahill, D. P., Kinzler, K. W., Vogelstein, B. & Lengauer, C. Genetic instability and darwinian selection in tumours. Trends Cell Biol. 9, M57–M60 (1999).

    CAS  PubMed  Article  Google Scholar 

  13. Garber, J. E. & Offit, K. Hereditary cancer predisposition syndromes. J. Clin. Oncol. 23, 276–292 (2005).

    PubMed  Article  Google Scholar 

  14. Chung, C. C. & Chanock, S. J. Current status of genome-wide association studies in cancer. Hum. Genet. 130, 59–78 (2011).

    PubMed  Article  Google Scholar 

  15. Negrini, S., Gorgoulis, V. G. & Halazonetis, T. D. Genomic instability--an evolving hallmark of cancer. Nature Rev. Mol. Cell Biol. 11, 220–228 (2010).

    CAS  Article  Google Scholar 

  16. Podsypanina, K. et al. Mutation of Pten/Mmac1 in mice causes neoplasia in multiple organ systems. Proc. Natl Acad. Sci. USA 96, 1563–1568 (1999).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  17. Michiels, F. M. et al. Development of medullary thyroid carcinoma in transgenic mice expressing the RET protooncogene altered by a multiple endocrine neoplasia type 2A mutation. Proc. Natl Acad. Sci. USA 94, 3330–3335 (1997).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  18. Ferrara, N. et al. Heterozygous embryonic lethality induced by targeted inactivation of the VEGF gene. Nature 380, 439–442 (1996).

    CAS  Article  PubMed  Google Scholar 

  19. Zhang, Q. et al. Acceleration of emergence of bacterial antibiotic resistance in connected microenvironments. Science 333, 1764–1767 (2011).

    CAS  PubMed  Article  Google Scholar 

  20. Davies, P. C. & Lineweaver, C. H. Cancer tumors as Metazoa 1.0: tapping genes of ancient ancestors. Phys. Biol. 8, 015001 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  21. Goncharova, E. I., Nadas, A. & Rossman, T. G. Serum deprivation, but not inhibition of growth per se, induces a hypermutable state in Chinese hamster G12 cells. Cancer Res. 56, 752–756 (1996).

    CAS  PubMed  Google Scholar 

  22. Hanahan, D. & Weinberg, R. A. Hallmarks of cancer: the next generation. Cell 144, 646–674 (2011).

    CAS  Article  PubMed  Google Scholar 

  23. Grivennikov, S. I., Greten, F. R. & Karin, M. Immunity, inflammation, and cancer. Cell 140, 883–899 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  24. Aggarwal, B. B., Vijayalekshmi, R. V. & Sung, B. Targeting inflammatory pathways for prevention and therapy of cancer: short-term friend, long-term foe. Clin. Cancer Res. 15, 425–430 (2009).

    CAS  PubMed  Article  Google Scholar 

  25. Papp-Szabo, E., Josephy, P. D. & Coomber, B. L. Microenvironmental influences on mutagenesis in mammary epithelial cells. Int. J. Cancer 116, 679–685 (2005).

    CAS  PubMed  Article  Google Scholar 

  26. Reynolds, T. Y., Rockwell, S. & Glazer, P. M. Genetic instability induced by the tumor microenvironment. Cancer Res. 56, 5754–5757 (1996).

    CAS  PubMed  Google Scholar 

  27. Wilkinson, D., Sandhu, J. K., Breneman, J. W., Tucker, J. D. & Birnboim, H. C. Hprt mutants in a transplantable murine tumour arise more frequently in vivo than in vitro. Br. J. Cancer 72, 1234–1240 (1995).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  28. Scheffner, M., Werness, B. A., Huibregtse, J. M., Levine, A. J. & Howley, P. M. The E6 oncoprotein encoded by human papillomavirus types 16 and 18 promotes the degradation of p53. Cell 63, 1129–1136 (1990).

    CAS  PubMed  Article  Google Scholar 

  29. Brechot, C., Pourcel, C., Louise, A., Rain, B. & Tiollais, P. Presence of integrated hepatitis B virus DNA sequences in cellular DNA of human hepatocellular carcinoma. Nature 286, 533–535 (1980).

    CAS  PubMed  Article  Google Scholar 

  30. Anand, P. et al. Cancer is a preventable disease that requires major lifestyle changes. Pharm. Res. 25, 2097–2116 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  31. Minamoto, T., Mai, M. & Ronai, Z. Environmental factors as regulators and effectors of multistep carcinogenesis. Carcinogenesis 20, 519–527 (1999).

    CAS  PubMed  Article  Google Scholar 

  32. DeMarini, D. M. Genotoxicity of tobacco smoke and tobacco smoke condensate: a review. Mutat. Res. 567, 447–474 (2004).

    CAS  PubMed  Article  Google Scholar 

  33. Ikehata, H. & Ono, T. The mechanisms of UV mutagenesis. J. Radiat. Res. 52, 115–125 (2011).

    CAS  PubMed  Article  Google Scholar 

  34. Chitneni, S. K., Palmer, G. M., Zalutsky, M. R. & Dewhirst, M. W. Molecular imaging of hypoxia. J. Nucl. Med. 52, 165–168 (2011).

    CAS  PubMed  Article  Google Scholar 

  35. Wykoff, C. C. et al. Expression of the hypoxia-inducible and tumor-associated carbonic anhydrases in ductal carcinoma in situ of the breast. Am. J. Pathol. 158, 1011–1019 (2001).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  36. Gillies, R. J. & Gatenby, R. A. Adaptive landscapes and emergent phenotypes: why do cancers have high glycolysis? J. Bioenerg. Biomembr. 39, 251–257 (2007).

    CAS  PubMed  Article  Google Scholar 

  37. Bristow, R. G. & Hill, R. P. Hypoxia and metabolism. Hypoxia, DNA repair and genetic instability. Nature Rev. Cancer 8, 180–192 (2008).

    CAS  Article  Google Scholar 

  38. Klein, T. J. & Glazer, P. M. The tumor microenvironment and DNA repair. Semin. Radiat. Oncol. 20, 282–287 (2010).

    PubMed  PubMed Central  Article  Google Scholar 

  39. Lu, Y., Chu, A., Turker, M. S. & Glazer, P. M. Hypoxia-induced epigenetic regulation and silencing of the BRCA1 promoter. Mol. Cell. Biol. 31, 3339–3350 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  40. Mihaylova, V. T. et al. Decreased expression of the DNA mismatch repair gene Mlh1 under hypoxic stress in mammalian cells. Mol. Cell. Biol. 23, 3265–3273 (2003).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  41. Hammond, E. M., Dorie, M. J. & Giaccia, A. J. ATR/ATM targets are phosphorylated by ATR in response to hypoxia and ATM in response to reoxygenation. J. Biol. Chem. 278, 12207–12213 (2003).

    CAS  PubMed  Article  Google Scholar 

  42. Graeber, T. G. et al. Hypoxia-mediated selection of cells with diminished apoptotic potential in solid tumours. Nature 379, 88–91 (1996).

    CAS  PubMed  Article  Google Scholar 

  43. Shi, Q. et al. Constitutive and inducible interleukin 8 expression by hypoxia and acidosis renders human pancreatic cancer cells more tumorigenic and metastatic. Clin. Cancer Res. 5, 3711–3721 (1999).

    CAS  PubMed  Google Scholar 

  44. Bindra, R. S. & Glazer, P. M. Genetic instability and the tumor microenvironment: towards the concept of microenvironment-induced mutagenesis. Mutat. Res. 569, 75–85 (2005).

    CAS  PubMed  Article  Google Scholar 

  45. Young, S. D., Marshall, R. S. & Hill, R. P. Hypoxia induces DNA overreplication and enhances metastatic potential of murine tumor cells. Proc. Natl Acad. Sci. USA 85, 9533–9537 (1988).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  46. Rice, G. C., Hoy, C. & Schimke, R. T. Transient hypoxia enhances the frequency of dihydrofolate reductase gene amplification in Chinese hamster ovary cells. Proc. Natl Acad. Sci. USA 83, 5978–5982 (1986).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  47. Otsuka, J. The large-scale evolution by generating new genes from gene duplication; similarity and difference between monoploid and diploid organisms. J. Theor. Biol. 278, 120–126 (2011).

    PubMed  Article  Google Scholar 

  48. van Sluis, R. et al. In vivo imaging of extracellular pH using 1H MRSI. Magn. Reson. Med. 41, 743–750 (1999).

    CAS  PubMed  Article  Google Scholar 

  49. Gillies, R. J., Liu, Z. & Bhujwalla, Z. 31P-MRS measurements of extracellular pH of tumors using 3-aminopropylphosphonate. Am. J. Physiol. 267, C195–203 (1994).

    CAS  PubMed  Article  Google Scholar 

  50. Morita, T., Nagaki, T., Fukuda, I. & Okumura, K. Clastogenicity of low pH to various cultured mammalian cells. Mutat. Res. 268, 297–305 (1992).

    CAS  PubMed  Article  Google Scholar 

  51. Zhang, H. Y., Hormi-Carver, K., Zhang, X., Spechler, S. J. & Souza, R. F. In benign Barrett's epithelial cells, acid exposure generates reactive oxygen species that cause DNA double-strand breaks. Cancer Res. 69, 9083–9089 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  52. Xiao, H., Li, T. K., Yang, J. M. & Liu, L. F. Acidic pH induces topoisomerase II-mediated DNA damage. Proc. Natl Acad. Sci. USA 100, 5205–5210 (2003).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  53. Hashim, A. I., Zhang, X., Wojtkowiak, J. W., Martinez, G. V. & Gillies, R. J. Imaging pH and metastasis. NMR Biomed. 24, 582–591 (2011).

    PubMed  PubMed Central  Google Scholar 

  54. Webb, B. A., Chimenti, M., Jacobson, M. P. & Barber, D. L. Dysregulated pH: a perfect storm for cancer progression. Nature Rev. Cancer 11, 671–677 (2011).

    CAS  Article  Google Scholar 

  55. Radu, C. G., Nijagal, A., McLaughlin, J., Wang, L. & Witte, O. N. Differential proton sensitivity of related G protein-coupled receptors T cell death-associated gene 8 and G2A expressed in immune cells. Proc. Natl Acad. Sci. USA 102, 1632–1637 (2005).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  56. Leffler, A., Monter, B. & Koltzenburg, M. The role of the capsaicin receptor TRPV1 and acid-sensing ion channels (ASICS) in proton sensitivity of subpopulations of primary nociceptive neurons in rats and mice. Neuroscience 139, 699–709 (2006).

    CAS  PubMed  Article  Google Scholar 

  57. Dong, X. et al. Expression of acid-sensing ion channels in intestinal epithelial cells and their role in the regulation of duodenal mucosal bicarbonate secretion. Acta Physiol. (Oxf.) 201, 97–107 (2011).

    CAS  Article  Google Scholar 

  58. Yun, J. et al. Glucose deprivation contributes to the development of KRAS pathway mutations in tumor cells. Science 325, 1555–1559 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  59. Rose, C. J. et al. Quantifying spatial heterogeneity in dynamic contrast-enhanced MRI parameter maps. Magn. Reson. Med. 62, 488–499 (2009).

    PubMed  Article  Google Scholar 

  60. Kawata, Y. et al. Quantitative classification based on CT histogram analysis of non-small cell lung cancer: Correlation with histopathological characteristics and recurrence-free survival. Med. Phys. 39, 988 (2012).

    PubMed  Article  Google Scholar 

  61. Drew, P. J. et al. Dynamic contrast enhanced magnetic resonance imaging of the breast is superior to triple assessment for the pre-operative detection of multifocal breast cancer. Ann. Surg. Oncol. 6, 599–603 (1999).

    CAS  PubMed  Article  Google Scholar 

  62. Knopp, M. V., Giesel, F. L., Marcos, H., von Tengg-Kobligk, H. & Choyke, P. Dynamic contrast-enhanced magnetic resonance imaging in oncology. Top. Magn. Reson. Imag. 12, 301–308 (2001).

    CAS  Article  Google Scholar 

  63. Lamer, S. et al. Radiologic assessment of intranodal vascularity in head and neck squamous cell carcinoma. Correlation with histologic vascular density. Invest. Radiol 31, 673–679 (1996).

    CAS  PubMed  Article  Google Scholar 

  64. Venkatasubramanian, R., Arenas, R. B., Henson, M. A. & Forbes, N. S. Mechanistic modelling of dynamic MRI data predicts that tumour heterogeneity decreases therapeutic response. Br. J. Cancer 103, 486–497 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  65. Helmlinger, G., Yuan, F., Dellian, M. & Jain, R. K. Interstitial pH and pO2 gradients in solid tumors in vivo: high-resolution measurements reveal a lack of correlation. Nature Med. 3, 177–182 (1997).

    CAS  PubMed  Article  Google Scholar 

  66. Kimura, H. et al. Fluctuations in red cell flux in tumor microvessels can lead to transient hypoxia and reoxygenation in tumor parenchyma. Cancer Res. 56, 5522–5528 (1996).

    CAS  PubMed  Google Scholar 

  67. Costouros, N. G. et al. Microarray gene expression analysis of murine tumor heterogeneity defined by dynamic contrast-enhanced MRI. Mol. Imag. 1, 301–308 (2002).

    CAS  Article  Google Scholar 

  68. Guccione, S. et al. Functional genomics guided with MR imaging: mouse tumor model study. Radiology 228, 560–568 (2003).

    PubMed  Article  Google Scholar 

  69. Hobbs, S. K. et al. Magnetic resonance image-guided proteomics of human glioblastoma multiforme. J. Magn. Reson. Imag. 18, 530–536 (2003).

    Article  Google Scholar 

  70. Winge, O. Zytologische untersuchungen uber die natur maligner tumoren. II. Teerkarzinome bei mausen. Z. Zellforsch. Mikrosk. Anat. 10, 683–735 (1930).

    Article  Google Scholar 

  71. Sandberg, A. A. & Hossfeld, D. K. Chromosomal abnormalities in human neoplasia. Annu. Rev. Med. 21, 379–408 (1970).

    CAS  PubMed  Article  Google Scholar 

  72. Bakhoum, S. F., Danilova, O. V., Kaur, P., Levy, N. B. & Compton, D. A. Chromosomal instability substantiates poor prognosis in patients with diffuse large B-cell lymphoma. Clin. Cancer Res. 17, 7704–7711 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  73. Loeb, L. A. Human cancers express mutator phenotypes: origin, consequences and targeting. Nature Rev. Cancer 11, 450–457 (2011).

    CAS  Article  Google Scholar 

  74. Yachida, S. et al. Distant metastasis occurs late during the genetic evolution of pancreatic cancer. Nature 467, 1114–1117 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  75. Araujo, R. P., Liotta, L. A. & Petricoin, E. F. Proteins, drug targets and the mechanisms they control: the simple truth about complex networks. Nature Rev. Drug Discov. 6, 871–880 (2007).

    CAS  Article  Google Scholar 

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

    CAS  PubMed  Article  Google Scholar 

  77. Marty, M. et al. Randomized phase II trial of the efficacy and safety of trastuzumab combined with docetaxel in patients with human epidermal growth factor receptor 2-positive metastatic breast cancer administered as first-line treatment: the M77001 study group. J. Clin. Oncol. 23, 4265–4274 (2005).

    CAS  PubMed  Article  Google Scholar 

  78. Mahtani, R. L. & Vogel, C. L. Pleomorphic lobular carcinoma of the breast: four long-term responders to trastuzumab--coincidence or hint? J. Clin. Oncol. 26, 5823–5824 (2008).

    PubMed  Article  Google Scholar 

  79. Untch, M. et al. Pathologic complete response after neoadjuvant chemotherapy plus trastuzumab predicts favorable survival in human epidermal growth factor receptor 2-overexpressing breast cancer: results from the TECHNO trial of the AGO and GBG study groups. J. Clin. Oncol. 29, 3351–3357 (2011).

    CAS  PubMed  Article  Google Scholar 

  80. Druker, B. J. et al. Five-year follow-up of patients receiving imatinib for chronic myeloid leukemia. N. Engl. J. Med. 355, 2408–2417 (2006).

    CAS  PubMed  Article  Google Scholar 

  81. Engelman, J. A. & Settleman, J. Acquired resistance to tyrosine kinase inhibitors during cancer therapy. Curr. Opin. Genet. Dev. 18, 73–79 (2008).

    CAS  PubMed  Article  Google Scholar 

  82. Aktipis, C. A., Kwan, V. S., Johnson, K. A., Neuberg, S. L. & Maley, C. C. Overlooking evolution: a systematic analysis of cancer relapse and therapeutic resistance research. PLoS ONE 6, e26100 (2011).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  83. O'Hare, T., Corbin, A. S. & Druker, B. J. Targeted CML therapy: controlling drug resistance, seeking cure. Curr. Opin. Genet. Dev. 16, 92–99 (2006).

    CAS  PubMed  Article  Google Scholar 

  84. Blackwell, K. L. et al. Randomized study of Lapatinib alone or in combination with trastuzumab in women with ErbB2-positive, trastuzumab-refractory metastatic breast cancer. J. Clin. Oncol. 28, 1124–1130 (2010).

    CAS  PubMed  Article  Google Scholar 

  85. Massarweh, S. & Schiff, R. Resistance to endocrine therapy in breast cancer: exploiting estrogen receptor/growth factor signaling crosstalk. Endocr. Relat. Cancer 13 Suppl. 1, 15–24 (2006).

    Article  CAS  Google Scholar 

  86. Baselga, J. et al. Everolimus in postmenopausal hormone-receptor-positive advanced breast cancer. N. Engl. J. Med. 366, 520–529 (2012).

    CAS  PubMed  Article  Google Scholar 

  87. Komarova, N. L. & Wodarz, D. Drug resistance in cancer: principles of emergence and prevention. Proc. Natl Acad. Sci. USA 102, 9714–9719 (2005).

    CAS  PubMed  Article  PubMed Central  Google Scholar 

  88. Chmielecki, J. et al. Optimization of dosing for EGFR-mutant non-small cell lung cancer with evolutionary cancer modeling. Sci Transl Med 3, 90ra59 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  89. Gatenby, R. A., Brown, J. & Vincent, T. Lessons from applied ecology: cancer control using an evolutionary double bind. Cancer Res. 69, 7499–7502 (2009).

    CAS  PubMed  Article  Google Scholar 

  90. Gatenby, R. A., Silva, A. S., Gillies, R. J. & Frieden, B. R. Adaptive therapy. Cancer Res. 69, 4894–4903 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  91. Mirski, S. E., Gerlach, J. H. & Cole, S. P. Multidrug resistance in a human small cell lung cancer cell line selected in adriamycin. Cancer Res. 47, 2594–2598 (1987).

    CAS  PubMed  Google Scholar 

  92. Abrahamsson, P. A. Potential benefits of intermittent androgen suppression therapy in the treatment of prostate cancer: a systematic review of the literature. Eur. Urol. 57, 49–59 (2010).

    CAS  PubMed  Article  Google Scholar 

  93. Beex, L. et al. Continuous versus intermittent tamoxifen versus intermittent/alternated tamoxifen and medroxyprogesterone acetate as first line endocrine treatment in advanced breast cancer: an EORTC phase III study (10863). Eur. J. Cancer 42, 3178–3185 (2006).

    CAS  PubMed  Article  Google Scholar 

  94. Farber, S. & Diamond, L. K. Temporary remissions in acute leukemia in children produced by folic acid antagonist, 4-aminopteroyl-glutamic acid. N. Engl. J. Med. 238, 787–793 (1948).

    CAS  PubMed  Article  Google Scholar 

  95. De Bock, K., Mazzone, M. & Carmeliet, P. Antiangiogenic therapy, hypoxia, and metastasis: risky liaisons, or not? Nature Rev. Clin. Oncol. 8, 393–404 (2011).

    CAS  Article  Google Scholar 

  96. Iwamoto, F. M. et al. Patterns of relapse and prognosis after bevacizumab failure in recurrent glioblastoma. Neurology 73, 1200–1206 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  97. Jain, R. K. Lessons from multidisciplinary translational trials on anti-angiogenic therapy of cancer. Nature Rev. Cancer 8, 309–316 (2008).

    CAS  Article  Google Scholar 

  98. Goel, S. et al. Normalization of the vasculature for treatment of cancer and other diseases. Physiol. Rev. 91, 1071–1121 (2011).

    CAS  PubMed  Article  Google Scholar 

  99. Chan, D. A. et al. Targeting GLUT1 and the Warburg effect in renal cell carcinoma by chemical synthetic lethality. Sci Transl Med 3, 94ra70 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  100. Ganapathy-Kanniappan, S. et al. 3-bromopyruvate: a new targeted antiglycolytic agent and a promise for cancer therapy. Curr. Pharm. Biotechnol. 11, 510–517 (2010).

    CAS  PubMed  Article  Google Scholar 

  101. Michelakis, E. D., Webster, L. & Mackey, J. R. Dichloroacetate (DCA) as a potential metabolic-targeting therapy for cancer. Br. J. Cancer 99, 989–994 (2008).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  102. Le, A. et al. Inhibition of lactate dehydrogenase A induces oxidative stress and inhibits tumor progression. Proc. Natl Acad. Sci. USA 107, 2037–2042 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  103. Gatenby, R. A., Gawlinski, E. T., Gmitro, A. F., Kaylor, B. & Gillies, R. J. Acid-mediated tumor invasion: a multidisciplinary study. Cancer Res. 66, 5216–5223 (2006).

    CAS  PubMed  Article  Google Scholar 

  104. Ibrahim Hashim, A. et al. Reduction of metastasis using a non-volatile buffer. Clin. Exp. Metastasis 28, 841–849 (2011).

    PubMed  PubMed Central  Article  CAS  Google Scholar 

  105. Hashim, A. I. et al. Sytemic buffers inhibit carcinogenesis in TRAMP mice. J. Urology (2012). (in press Jan, </pub>2012).

  106. Ibrahim Hashim, A. et al. Reduction of metastasis using a non-volatile buffer. Clin Exp Metastasis (2011).

  107. Wojtkowiak, J. W., Verduzco, D., Schramm, K. J. & Gillies, R. J. Drug resistance and cellular adaptation to tumor acidic pH microenvironment. Mol. Pharm. 8, 2032–2038 (2011).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  108. Ghobrial, I. M., Witzig, T. E. & Adjei, A. A. Targeting apoptosis pathways in cancer therapy. CA Cancer J. Clin. 55, 178–194 (2005).

    PubMed  Article  Google Scholar 

  109. Ludwig, H., Khayat, D., Giaccone, G. & Facon, T. Proteasome inhibition and its clinical prospects in the treatment of hematologic and solid malignancies. Cancer 104, 1794–1807 (2005).

    CAS  PubMed  Article  Google Scholar 

  110. Madhok, B. M., Yeluri, S., Perry, S. L., Hughes, T. A. & Jayne, D. G. Dichloroacetate induces apoptosis and cell-cycle arrest in colorectal cancer cells. Br. J. Cancer 102, 1746–1752 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  111. Holoch, P. A. & Griffith, T. S. TNF-related apoptosis-inducing ligand (TRAIL): a new path to anti-cancer therapies. Eur. J. Pharmacol. 625, 63–72 (2009).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  112. Smolewski, P. Recent developments in targeting the mammalian target of rapamycin (mTOR) kinase pathway. Anticancer Drugs 17, 487–494 (2006).

    CAS  PubMed  Article  Google Scholar 

  113. Agulnik, M. New developments in mammalian target of rapamycin inhibitors for the treatment of sarcoma. Cancer 118, 1486–1497 (2012).

    CAS  PubMed  Article  Google Scholar 

  114. Houghton, P. J. Everolimus. Clin. Cancer Res. 16, 1368–1372 (2010).

    CAS  PubMed  PubMed Central  Article  Google Scholar 

  115. Pouget, J. P. et al. Clinical radioimmunotherapy--the role of radiobiology. Nature Rev. Clin. Oncol. 8, 720–734 (2011).

    CAS  Article  Google Scholar 

  116. Richman, C. M. et al. High-dose radioimmunotherapy combined with fixed, low-dose paclitaxel in metastatic prostate and breast cancer by using a MUC-1 monoclonal antibody, m170, linked to indium-111/yttrium-90 via a cathepsin cleavable linker with cyclosporine to prevent human anti-mouse antibody. Clin. Cancer Res. 11, 5920–5927 (2005).

    CAS  PubMed  Article  Google Scholar 

  117. Behr, T. M. et al. High-linear energy transfer (LET) alpha versus low-LET beta emitters in radioimmunotherapy of solid tumors: therapeutic efficacy and dose-limiting toxicity of 213Bi- versus 90Y-labeled CO17-1A Fab' fragments in a human colonic cancer model. Cancer Res. 59, 2635–2643 (1999).

    CAS  PubMed  Google Scholar 

  118. Chatal, J. F., Davodeau, F., Cherel, M. & Barbet, J. Different ways to improve the clinical effectiveness of radioimmunotherapy in solid tumors. J. Cancer Res. Ther. 5 Suppl. 1, S36–40 (2009).

    CAS  PubMed  Article  Google Scholar 

  119. Wilson, W. R. & Hay, M. P. Targeting hypoxia in cancer therapy. Nature Rev. Cancer 11, 393–410 (2011).

    CAS  Article  Google Scholar 

  120. Duan, J. X. et al. Potent and highly selective hypoxia-activated achiral phosphoramidate mustards as anticancer drugs. J. Med. Chem. 51, 2412–2420 (2008).

    CAS  PubMed  Article  Google Scholar 

  121. Meng, F. et al. Molecular and cellular pharmacology of the hypoxia-activated prodrug TH-302. Mol. Cancer Ther. 6, 6 (2011).

    Google Scholar 

  122. Sun, J. D. et al. Selective tumor hypoxia targeting by hypoxia-activated prodrug TH-302 inhibits tumor growth in preclinical models of cancer. Clin. Cancer Res. 18, 758–770 (2011).

    PubMed  Article  Google Scholar 

  123. Tian, L. & Bae, Y. H. Cancer nanomedicines targeting tumor extracellular pH. Colloids Surf B Biointerfaces DOI colsurfb.2011.10.039 (2011).

  124. Kaminskas, L. M. et al. Doxorubicin-conjugated PEGylated dendrimers show similar tumoricidal activity but lower systemic toxicity when compared to PEGylated liposome and solution formulations in mouse and rat tumor models. Mol. Pharm. 9, 422–432 (2012).

    CAS  PubMed  Article  Google Scholar 

  125. 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).

    CAS  PubMed  Google Scholar 

  126. Casanueva, M. O., Burga, A. & Lehner, B. Fitness trade-offs and environmentally induced mutation buffering in isogenic C. elegans. Science 335, 82–85 (2012).

    CAS  PubMed  Article  Google Scholar 

  127. Jacob, F. Evolution and Tinkering. Science 196, 1161–1166 (1977).

    CAS  PubMed  Article  Google Scholar 

Download references

Acknowledgements

The authors would like to thank Z. Bhujwalla, K. Brindle, J. Brown, J. Evelhoch, A. Giuliano, P. Glazer, C. Hart, L. Loeb, T. Sellers, B. Vogelstein and J. Zhang for their insightful and helpful comments. Supported by a grant from the McDonnell Foundation and US NIH grants U54 CA143970 (“Physical Sciences in Oncology”) and R01 CA077575 (“Causes and Consequences of Acid pH in Tumors”) to R.A.G. and R.J.G.

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Speaking honorarium $500, Threshold Pharmaceuticals (RJG) Consultancy $1000, Intenzyne Corporation (RJG)

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Glossary

Atavistic

Reverting to or suggesting the characteristics of a remote ancestor or primitive type. In the current context, atavism is the expression of behaviours in cancer cells that are not normally observed in normal metazoan cells, but that are observed in prokaryotes and/or protozoa.

Clades

A taxonomic group of organisms classified together on the basis of homologous features traced to a common ancestor. In the current context, groups of cancer cells evolve in physically distinct niches, and exhibit local genetic homogeneity.

Nuclear grade

Breast cancers are assessed for the appearance of nuclei within the tumour cells and assigned a grade from 1 (small uniform cells) to 3 (marked nuclear variation).

Supervene

Describes a mathematical and philosophical formalism that characterizes the relationship between two sets — in this case phenotype (or more broadly adaptive strategies) and genotypes. In the subvenient set (genetics) each point will map to a point in the phenotype set, and in the supervenient set (phenotypes) each adaptive strategy can map too many different points in the genotype set.

Teleological

Describes a doctrine that final causes exist, and thus that purpose is a part of nature. In the current context, teleology dictates that cancers exist for a (self-serving) purpose. Thus, we ask why, and not how, cancers behave the way they do.

Theory

A coherent group of general propositions that can be used as principles of explanation and prediction for a class of phenomena. A proposed explanation the status of which is still conjectural and subject to experimentation.

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Gillies, R., Verduzco, D. & Gatenby, R. Evolutionary dynamics of carcinogenesis and why targeted therapy does not work. Nat Rev Cancer 12, 487–493 (2012). https://doi.org/10.1038/nrc3298

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