Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Opinion
  • Published:

Plasticity of tumour and immune cells: a source of heterogeneity and a cause for therapy resistance?

Abstract

Immunotherapies, signal transduction inhibitors and chemotherapies can successfully achieve remissions in advanced stage cancer patients, but durable responses are rare. Using malignant melanoma as a paradigm, we propose that therapy-induced injury to tumour tissue and the resultant inflammation can activate protective and regenerative responses that represent a shared resistance mechanism to different treatments. Inflammation-driven phenotypic plasticity alters the antigenic landscape of tumour cells, rewires oncogenic signalling networks, protects against cell death and reprogrammes immune cell functions. We propose that the successful combination of cancer treatments to tackle resistance requires an interdisciplinary understanding of these resistance mechanisms, supported by mathematical models.

This is a preview of subscription content, access via your institution

Access options

Buy this article

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Tumour evolution, therapy-induced tumour tissue damage and development of therapy resistance.
Figure 2: Interdisciplinary treatment approaches in melanoma.
Figure 3: Inflammation-induced phenotypic plasticity of tumour cells and immune cells.
Figure 4: Reconciling plasticity and clonal selection using ecology models.
Figure 5: Mouse and human co-clinical trials to facilitate the establishment of effective combination therapy protocols.

Similar content being viewed by others

References

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

    Article  CAS  PubMed  Google Scholar 

  2. Tsao, H., Atkins, M. B. & Sober, A. J. Management of cutaneous melanoma. N. Engl. J. Med. 351, 998–1012 (2004).

    Article  CAS  PubMed  Google Scholar 

  3. Bollag, G. et al. Clinical efficacy of a RAF inhibitor needs broad target blockade in BRAF-mutant melanoma. Nature 467, 596–599 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Chapman, P. B. et al. Improved survival with vemurafenib in melanoma with BRAF V600E mutation. N. Engl. J. Med. 364, 2507–2516 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Flaherty, K. T. et al. Improved survival with MEK inhibition in BRAF-mutated melanoma. N. Engl. J. Med. 367, 107–114 (2012).

    Article  CAS  PubMed  Google Scholar 

  6. Tsao, H., Chin, L., Garraway, L. A. & Fisher, D. E. Melanoma: from mutations to medicine. Genes Dev. 26, 1131–1155 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Hodi, F. S. et al. Improved survival with ipilimumab in patients with metastatic melanoma. N. Engl. J. Med. 363, 711–723 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Robert, C. et al. Ipilimumab plus dacarbazine for previously untreated metastatic melanoma. N. Engl. J. Med. 364, 2517–2526 (2011).

    Article  CAS  PubMed  Google Scholar 

  9. Brahmer, J. R. et al. Safety and activity of anti-PD-L1 antibody in patients with advanced cancer. N. Engl. J. Med. 366, 2455–2465 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Topalian, S. L. et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N. Engl. J. Med. 366, 2443–2454 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Paez, J. G. et al. EGFR mutations in lung cancer: correlation with clinical response to gefitinib therapy. Science 304, 1497–1500 (2004).

    Article  CAS  PubMed  Google Scholar 

  12. Lynch, T. J. et al. Activating mutations in the epidermal growth factor receptor underlying responsiveness of non-small-cell lung cancer to gefitinib. N. Engl. J. Med. 350, 2129–2139 (2004).

    Article  CAS  PubMed  Google Scholar 

  13. Maemondo, M. et al. Gefitinib or chemotherapy for non-small-cell lung cancer with mutated EGFR. N. Engl. J. Med. 362, 2380–2388 (2010).

    Article  CAS  PubMed  Google Scholar 

  14. Marusyk, A., Almendro, V. & Polyak, K. Intra-tumour heterogeneity: a looking glass for cancer? Nature Rev. Cancer 12, 323–334 (2012).

    Article  CAS  Google Scholar 

  15. Merlo, L. M., Pepper, J. W., Reid, B. J. & Maley, C. C. Cancer as an evolutionary and ecological process. Nature Rev. Cancer 6, 924–935 (2006).

    Article  CAS  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Gillies, R. J., Verduzco, D. & Gatenby, R. A. Evolutionary dynamics of carcinogenesis and why targeted therapy does not work. Nature Rev. Cancer 12, 487–493 (2012).

    Article  CAS  Google Scholar 

  19. Zhou, B. B. et al. Tumour-initiating cells: challenges and opportunities for anticancer drug discovery. Nature Rev. Drug Discov. 8, 806–823 (2009).

    Article  CAS  Google Scholar 

  20. Frank, N. Y., Schatton, T. & Frank, M. H. The therapeutic promise of the cancer stem cell concept. J. Clin. Invest. 120, 41–50 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Clevers, H. The cancer stem cell: premises, promises and challenges. Nature Med. 17, 313–319 (2011).

    Article  CAS  PubMed  Google Scholar 

  22. Magee, J. A., Piskounova, E. & Morrison, S. J. Cancer stem cells: impact, heterogeneity, and uncertainty. Cancer Cell 21, 283–296 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Ossowski, L. & Aguirre-Ghiso, J. A. Dormancy of metastatic melanoma. Pigment Cell Melanoma Res. 23, 41–56 (2010).

    Article  PubMed  Google Scholar 

  24. Singh, A. & Settleman, J. EMT, cancer stem cells and drug resistance: an emerging axis of evil in the war on cancer. Oncogene 29, 4741–4751 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Baylin, S. B. Resistance, epigenetics and the cancer ecosystem. Nature Med. 17, 288–289 (2011).

    Article  CAS  PubMed  Google Scholar 

  26. Wilting, R. H. & Dannenberg, J. H. Epigenetic mech-anisms in tumorigenesis, tumor cell heterogeneity and drug resistance. Drug Resist. Updat. 15, 21–38 (2012).

    Article  CAS  PubMed  Google Scholar 

  27. Borst, P. Cancer drug pan-resistance: pumps, cancer stem cells, quiescence, epithelial to mesenchymal transition, blocked cell death pathways, persisters or what? Open. Biol. 2, 120066 (2012).

    Google Scholar 

  28. Egeblad, M., Nakasone, E. S. & Werb, Z. Tumors as organs: complex tissues that interface with the entire organism. Dev. Cell 18, 884–901 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Correia, A. L. & Bissell, M. J. The tumor microenvironment is a dominant force in multidrug resistance. Drug Resist. Updat. 15, 39–49 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Meads, M. B., Gatenby, R. A. & Dalton, W. S. Environment-mediated drug resistance: a major contributor to minimal residual disease. Nature Rev. Cancer 9, 665–674 (2009).

    Article  CAS  Google Scholar 

  31. Hanahan, D. & Coussens, L. M. Accessories to the crime: functions of cells recruited to the tumor microenvironment. Cancer Cell 21, 309–322 (2012).

    Article  CAS  PubMed  Google Scholar 

  32. Gottesman, M. M., Fojo, T. & Bates, S. E. Multidrug resistance in cancer: role of ATP-dependent transporters. Nature Rev. Cancer 2, 48–58 (2002).

    Article  CAS  Google Scholar 

  33. 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 

  34. 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  PubMed  PubMed Central  Google Scholar 

  35. Huang, S. et al. MED12 controls the response to multiple cancer drugs through regulation of TGF-β receptor signaling. Cell 151, 937–950 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Gilbert, L. A. & Hemann, M. T. DNA damage-mediated induction of a chemoresistant niche. Cell 143, 355–366 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Gilbert, L. A. & Hemann, M. T. Chemotherapeutic resistance: surviving stressful situations. Cancer Res. 71, 5062–5066 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Shree, T. et al. Macrophages and cathepsin proteases blunt chemotherapeutic response in breast cancer. Genes Dev. 25, 2465–2479 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Nakasone, E. S. et al. Imaging tumor-stroma interactions during chemotherapy reveals contributions of the microenvironment to resistance. Cancer Cell 21, 488–503 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  40. Denardo, D. G. et al. Leukocyte complexity predicts breast cancer survival and functionally regulates response to chemotherapy. Cancer Discov. 1, 54–67 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Acharyya, S. et al. A CXCL1 paracrine network links cancer chemoresistance and metastasis. Cell 150, 165–178 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Kioi, M. et al. Inhibition of vasculogenesis, but not angiogenesis, prevents the recurrence of glioblastoma after irradiation in mice. J. Clin. Invest. 120, 694–705 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Bruchard, M. et al. Chemotherapy-triggered cathepsin B release in myeloid-derived suppressor cells activates the Nlrp3 inflammasome and promotes tumor growth. Nature Med. 19, 57–64 (2013).

    Article  CAS  PubMed  Google Scholar 

  44. Druker, B. J. et al. Effects of a selective inhibitor of the Abl tyrosine kinase on the growth of Bcr-Abl positive cells. Nature Med. 2, 561–566 (1996).

    Article  CAS  PubMed  Google Scholar 

  45. Druker, B. J. et al. Efficacy and safety of a specific inhibitor of the BCR-ABL tyrosine kinase in chronic myeloid leukemia. N. Engl. J. Med. 344, 1031–1037 (2001).

    Article  CAS  PubMed  Google Scholar 

  46. 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  Google Scholar 

  47. Soverini, S. et al. BCR-ABL kinase domain mutation analysis in chronic myeloid leukemia patients treated with tyrosine kinase inhibitors: recommendations from an expert panel on behalf of European LeukemiaNet. Blood 118, 1208–1215 (2011).

    Article  CAS  PubMed  Google Scholar 

  48. 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  Google Scholar 

  49. Sequist, L. V. et al. Genotypic and histological evolution of lung cancers acquiring resistance to EGFR inhibitors. Sci. Transl. Med. 3, 75ra26 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  50. Ercan, D. et al. Amplification of EGFR T790M causes resistance to an irreversible EGFR inhibitor. Oncogene 29, 2346–2356 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Rosell, R. et al. Pretreatment EGFR T790M mutation and BRCA1 mRNA expression in erlotinib-treated advanced non-small-cell lung cancer patients with EGFR mutations. Clin. Cancer Res. 17, 1160–1168 (2011).

    Article  CAS  PubMed  Google Scholar 

  52. Su, K. Y. et al. Pretreatment epidermal growth factor receptor (EGFR) T790M mutation predicts shorter EGFR tyrosine kinase inhibitor response duration in patients with non-small-cell lung cancer. J. Clin. Oncol. 30, 433–440 (2012).

    Article  CAS  PubMed  Google Scholar 

  53. Prahallad, A. et al. Unresponsiveness of colon cancer to BRAF(V600E) inhibition through feedback activation of EGFR. Nature 483, 100–103 (2012).

    Article  CAS  PubMed  Google Scholar 

  54. Corcoran, R. B. et al. EGFR-mediated re-activation of MAPK signaling contributes to insensitivity of BRAF mutant colorectal cancers to RAF inhibition with vemurafenib. Cancer Discov. 2, 227–235 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. O'Hare, T., Zabriskie, M. S., Eiring, A. M. & Deininger, M. W. Pushing the limits of targeted therapy in chronic myeloid leukaemia. Nature Rev. Cancer 12, 513–526 (2012).

    Article  CAS  Google Scholar 

  56. Whittaker, S. et al. Gatekeeper mutations mediate resistance to BRAF-targeted therapies. Sci. Transl. Med. 2, 35ra41 (2010).

    Article  PubMed  CAS  Google Scholar 

  57. Poulikakos, P. I. & Rosen, N. Mutant BRAF melanomas--dependence and resistance. Cancer Cell 19, 11–15 (2011).

    Article  CAS  PubMed  Google Scholar 

  58. Johannessen, C. M. et al. COT drives resistance to RAF inhibition through MAP kinase pathway reactivation. Nature 468, 968–972 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Nazarian, R. et al. Melanomas acquire resistance to B-RAF(V600E) inhibition by RTK or N-RAS upregulation. Nature 468, 973–977 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Villanueva, J. et al. Acquired resistance to BRAF inhibitors mediated by a RAF kinase switch in melanoma can be overcome by cotargeting MEK and IGF-1R/PI3K. Cancer Cell 18, 683–695 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Das, T. M. et al. Modelling vemurafenib resistance in melanoma reveals a strategy to forestall drug resistance. Nature 494, 251–255 (2013).

    Article  CAS  Google Scholar 

  62. Wilson, T. R. et al. Widespread potential for growth-factor-driven resistance to anticancer kinase inhibitors. Nature 487, 505–509 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Straussman, R. et al. Tumour micro-environment elicits innate resistance to RAF inhibitors through HGF secretion. Nature 487, 500–504 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  64. Takayama, H., La Rochelle, W. J., Anver, M., Bockman, D. E. & Merlino, G. Scatter factor/hepatocyte growth factor as a regulator of skeletal muscle and neural crest development. Proc. Natl Acad. Sci. USA 93, 5866–5871 (1996).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Takayama, H. et al. Diverse tumorigenesis associated with aberrant development in mice overexpressing hepatocyte growth factor/scatter factor. Proc. Natl Acad. Sci. USA 94, 701–706 (1997).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Wang, W. et al. Crosstalk to stromal fibroblasts induces resistance of lung cancer to epidermal growth factor receptor tyrosine kinase inhibitors. Clin. Cancer Res. 15, 6630–6638 (2009).

    Article  CAS  PubMed  Google Scholar 

  67. Yano, S. et al. Hepatocyte growth factor expression in EGFR mutant lung cancer with intrinsic and acquired resistance to tyrosine kinase inhibitors in a Japanese cohort. J. Thorac. Oncol. 6, 2011–2017 (2011).

    Article  PubMed  Google Scholar 

  68. Blattman, J. N. & Greenberg, P. D. Cancer immunotherapy: a treatment for the masses. Science 305, 200–205 (2004).

    Article  CAS  PubMed  Google Scholar 

  69. Mellman, I., Coukos, G. & Dranoff, G. Cancer immunotherapy comes of age. Nature 480, 480–489 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  70. Rosenberg, S. A. Progress in human tumour immunology and immunotherapy. Nature 411, 380–384 (2001).

    Article  CAS  PubMed  Google Scholar 

  71. Boon, T., Coulie, P. G., Van den Eynde, B. J. & van der, B. P. Human T cell responses against melanoma. Annu. Rev. Immunol. 24, 175–208 (2006).

    Article  CAS  PubMed  Google Scholar 

  72. Atkins, M. B. et al. High-dose recombinant interleukin 2 therapy for patients with metastatic melanoma: analysis of 270 patients treated between 1985 and 1993. J. Clin. Oncol. 17, 2105–2116 (1999).

    Article  CAS  PubMed  Google Scholar 

  73. Rosenberg, S. A., Yang, J. C. & Restifo, N. P. Cancer immunotherapy: moving beyond current vaccines. Nature Med. 10, 909–915 (2004).

    Article  CAS  PubMed  Google Scholar 

  74. Dudley, M. E. et al. Cancer regression and autoimmunity in patients after clonal repopulation with antitumor lymphocytes. Science 298, 850–854 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  75. Yee, C. et al. Adoptive T cell therapy using antigen-specific CD8+ T cell clones for the treatment of patients with metastatic melanoma: in vivo persistence, migration, and antitumor effect of transferred T cells. Proc. Natl Acad. Sci. USA 99, 16168–16173 (2002).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  76. Dudley, M. E. et al. Adoptive cell transfer therapy following non-myeloablative but lymphodepleting chemotherapy for the treatment of patients with refractory metastatic melanoma. J. Clin. Oncol. 23, 2346–2357 (2005).

    Article  CAS  PubMed  Google Scholar 

  77. Mackensen, A. et al. Phase I study of adoptive T-cell therapy using antigen-specific CD8+ T cells for the treatment of patients with metastatic melanoma. J. Clin. Oncol. 24, 5060–5069 (2006).

    Article  CAS  PubMed  Google Scholar 

  78. Chapuis, A. G. et al. Transferred melanoma-specific CD8+ T cells persist, mediate tumor regression, and acquire central memory phenotype. Proc. Natl Acad. Sci. USA 109, 4592–4597 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  79. Restifo, N. P., Dudley, M. E. & Rosenberg, S. A. Adoptive immunotherapy for cancer: harnessing the T cell response. Nature Rev. Immunol. 12, 269–281 (2012).

    Article  CAS  Google Scholar 

  80. Khong, H. T. & Restifo, N. P. Natural selection of tumor variants in the generation of “tumor escape” phenotypes. Nature Immunol. 3, 999–1005 (2002).

    Article  CAS  Google Scholar 

  81. Restifo, N. P. et al. Loss of functional beta 2-microglobulin in metastatic elanomas from five patients receiving immunotherapy. J. Natl Cancer Inst. 88, 100–108 (1996).

    Article  CAS  PubMed  Google Scholar 

  82. Jager, E. et al. Immunoselection in vivo: independent loss of MHC class I and melanocyte differentiation antigen expression in metastatic melanoma. Int. J. Cancer. 71, 142–147 (1997).

    Article  CAS  PubMed  Google Scholar 

  83. Khong, H. T., Wang, Q. J. & Rosenberg, S. A. Identification of multiple antigens recognized by tumor-infiltrating lymphocytes from a single patient: tumor escape by antigen loss and loss of MHC expression. J. Immunother. 27, 184–190 (2004).

    Article  PubMed  PubMed Central  Google Scholar 

  84. Garrido, F. Cabrera, T., & Aptsiauri, N. “Hard” and “soft” lesions underlying the HLA class I alterations in cancer cells: implications for immunotherapy. Int. J. Cancer. 127, 249–256 (2010).

    CAS  PubMed  Google Scholar 

  85. Rosenberg, S. A. et al. Tumor progression can occur despite the induction of very high levels of self/tumor antigen-specific CD8+ T cells in patients with melanoma. J. Immunol. 175, 6169–6176 (2005).

    Article  CAS  PubMed  Google Scholar 

  86. Appay, V. et al. New generation vaccine induces effective melanoma-specific CD8+ T cells in the circulation but not in the tumor site. J. Immunol. 177, 1670–1678 (2006).

    Article  CAS  PubMed  Google Scholar 

  87. Baitsch, L. et al. Exhaustion of tumor-specific CD8+ T cells in metastases from melanoma patients. J. Clin. Invest. 121, 2350–2360 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Wherry, E. J. T cell exhaustion. Nature Immunol. 12, 492–499 (2011).

    Article  CAS  Google Scholar 

  89. Soudja, S. M. et al. Tumor-initiated inflammation overrides protective adaptive immunity in an induced melanoma model in mice. Cancer Res. 70, 3515–3525 (2010).

    Article  CAS  PubMed  Google Scholar 

  90. Meyer, C. et al. Chronic inflammation promotes myeloid-derived suppressor cell activation blocking antitumor immunity in transgenic mouse melanoma model. Proc. Natl Acad. Sci. USA 108, 17111–17116 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Zou, W. Immunosuppressive networks in the tumour environment and their therapeutic relevance. Nature Rev. Cancer 5, 263–274 (2005).

    Article  CAS  Google Scholar 

  92. Rabinovich, G. A., Gabrilovich, D. & Sotomayor, E. M. Immunosuppressive strategies that are mediated by tumor cells. Annu. Rev. Immunol. 25, 267–296 (2007).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  93. Mellor, A. L. & Munn, D. H. Creating immune privilege: active local suppression that benefits friends, but protects foes. Nature Rev. Immunol. 8, 74–80 (2008).

    Article  CAS  Google Scholar 

  94. Schreiber, R. D., Old, L. J. & Smyth, M. J. Cancer immunoediting: integrating immunity's roles in cancer suppression and promotion. Science 331, 1565–1570 (2011).

    Article  CAS  PubMed  Google Scholar 

  95. Kohlmeyer, J. et al. Complete regression of advanced primary and metastatic mouse melanomas following combination chemoimmunotherapy. Cancer Res. 69, 6265–6274 (2009).

    Article  CAS  PubMed  Google Scholar 

  96. Landsberg, J. et al. Autochthonous primary and metastatic melanomas in Hgf-Cdk4 R24C mice evade T-cell-mediated immune surveillance. Pigment Cell Melanoma Res. 23, 649–660 (2010).

    Article  CAS  PubMed  Google Scholar 

  97. Landsberg, J. et al. Melanomas resist T-cell therapy through inflammation-induced reversible dedifferentiation. Nature 490, 412–416 (2012).

    Article  CAS  PubMed  Google Scholar 

  98. Hendrix, M. J., Seftor, E. A., Hess, A. R. & Seftor, R. E. Molecular plasticity of human melanoma cells. Oncogene 22, 3070–3075 (2003).

    Article  CAS  PubMed  Google Scholar 

  99. White, R. M. & Zon, L. I. Melanocytes in development, regeneration, and cancer. Cell Stem Cell. 3, 242–252 (2008).

    Article  CAS  PubMed  Google Scholar 

  100. Bailey, C. M., Morrison, J. A. & Kulesa, P. M. Melanoma revives an embryonic igration program to promote plasticity and invasion. Pigment Cell Melanoma Res. 25, 573–583 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Quintana, E. et al. Phenotypic heterogeneity among tumorigenic melanoma cells from patients that is reversible and not hierarchically organized. Cancer Cell 18, 510–523 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  102. Boiko, A. D. et al. Human melanoma-initiating cells express neural crest nerve growth factor receptor CD271. Nature 466, 133–137 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  103. Civenni, G. et al. Human CD271-positive melanoma stem cells associated with metastasis establish tumor heterogeneity and long-term growth. Cancer Res. 71, 3098–3109 (2011).

    Article  CAS  PubMed  Google Scholar 

  104. Hoek, K. S. et al. In vivo switching of human melanoma cells between proliferative and invasive states. Cancer Res. 68, 650–656 (2008).

    Article  CAS  PubMed  Google Scholar 

  105. Pinner, S. et al. Intravital imaging reveals transient changes in pigment production and Brn2 expression during metastatic melanoma dissemination. Cancer Res. 69, 7969–7977 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  106. Roesch, A. et al. A temporarily distinct subpopulation of slow-cycling melanoma cells is required for continuous tumor growth. Cell 141, 583–594 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  107. Javelaud, D. et al. GLI2 and M-MITF transcription factors control exclusive gene expression programs and inversely regulate invasion in human melanoma cells. Pigment Cell Melanoma Res. 24, 932–943 (2011).

    Article  CAS  PubMed  Google Scholar 

  108. Cheli, Y. et al. Mitf is the key molecular switch between mouse or human melanoma initiating cells and their differentiated progeny. Oncogene 30, 2307–2318 (2011).

    Article  CAS  PubMed  Google Scholar 

  109. Widmer, D. S. et al. Systematic classification of melanoma cells by phenotype-specific gene expression mapping. Pigment Cell Melanoma Res. 25, 343–353 (2012).

    Article  CAS  PubMed  Google Scholar 

  110. Knutson, K. L. et al. Immunoediting of cancers may lead to epithelial to mesenchymal transition. J. Immunol. 177, 1526–1533 (2006).

    Article  CAS  PubMed  Google Scholar 

  111. Santisteban, M. et al. Immune-induced epithelial to mesenchymal transition in vivo generates breast cancer stem cells. Cancer Res. 69, 2887–2895 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Asiedu, M. K., Ingle, J. N., Behrens, M. D., Radisky, D. C. & Knutson, K. L. TGFβ/TNFα-mediated epithelial-mesenchymal transition generates breast cancer stem cells with a claudin-low phenotype. Cancer Res. 71, 4707–4719 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  113. Schwitalla, S. et al. Intestinal tumorigenesis initiated by dedifferentiation and acquisition of stem-cell-like properties. Cell 152, 25–38 (2013).

    Article  CAS  PubMed  Google Scholar 

  114. Gupta, P. B. et al. Stochastic state transitions give rise to phenotypic equilibrium in populations of cancer cells. Cell 146, 633–644 (2011).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  116. Kulbe, H. et al. A dynamic inflammatory cytokine network in the human ovarian cancer microenvironment. Cancer Res. 72, 66–75 (2012).

    Article  CAS  PubMed  Google Scholar 

  117. Gray-Schopfer, V. C., Karasarides, M., Hayward, R. & Marais, R. Tumor necrosis factor-alpha blocks apoptosis in melanoma cells when BRAF signaling is inhibited. Cancer Res. 67, 122–129 (2007).

    Article  CAS  PubMed  Google Scholar 

  118. Yao, Z. et al. TGF-beta IL-6 axis mediates selective and adaptive mechanisms of resistance to molecular targeted therapy in lung cancer. Proc. Natl Acad. Sci. USA 107, 15535–15540 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Toh, B. et al. Mesenchymal transition and dissemination of cancer cells is driven by myeloid-derived suppressor cells infiltrating the primary tumor. PLoS. Biol. 9, e1001162 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Li, G. et al. Downregulation of E-cadherin and Desmoglein 1 by autocrine hepatocyte growth factor during melanoma development. Oncogene 20, 8125–8135 (2001).

    Article  CAS  PubMed  Google Scholar 

  121. Koefinger, P. et al. The cadherin switch in melanoma instigated by HGF is mediated through epithelial-mesenchymal transition regulators. Pigment Cell Melanoma Res. 24, 382–385 (2011).

    Article  CAS  PubMed  Google Scholar 

  122. Witta, S. E. et al. Restoring E-cadherin expression increases sensitivity to epidermal growth factor receptor inhibitors in lung cancer cell lines. Cancer Res. 66, 944–950 (2006).

    Article  CAS  PubMed  Google Scholar 

  123. Creighton, C. J. et al. Residual breast cancers after conventional therapy display mesenchymal as well as tumor-initiating features. Proc. Natl Acad. Sci. USA 106, 13820–13825 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Cheng, W. Y., Kandel, J. J., Yamashiro, D. J., Canoll, P. & Anastassiou, D. A multi-cancer mesenchymal transition gene expression signature is associated with prolonged time to recurrence in glioblastoma. PLoS ONE 7, e34705 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Zhang, Z. et al. Activation of the AXL kinase causes resistance to EGFR-targeted therapy in lung cancer. Nature Genet. 44, 852–860 (2012).

    Article  CAS  PubMed  Google Scholar 

  126. Byers, L. A. et al. An epithelial-mesenchymal transition gene signature predicts resistance to EGFR and PI3K inhibitors and identifies Axl as a therapeutic target for overcoming EGFR inhibitor resistance. Clin. Cancer Res. 19, 279–290 (2013).

    Article  CAS  PubMed  Google Scholar 

  127. Qian, B. Z. & Pollard, J. W. Macrophage diversity enhances tumor progression and metastasis. Cell 141, 39–51 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  128. Kanno, Y., Vahedi, G., Hirahara, K., Singleton, K. & O'Shea, J. J. Transcriptional and epigenetic control of T helper cell specification: molecular mechanisms underlying commitment and plasticity. Annu. Rev. Immunol. 30, 707–731 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  129. Sica, A. & Mantovani, A. Macrophage plasticity and polarization: in vivo veritas. J. Clin. Invest. 122, 787–795 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  130. Qian, B. Z. et al. CCL2 recruits inflammatory monocytes to facilitate breast-tumour metastasis. Nature 475, 222–225 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  131. Pylayeva-Gupta, Y., Lee, K. E., Hajdu, C. H., Miller, G. & Bar-Sagi, D. Oncogenic Kras-induced GM-CSF production promotes the development of pancreatic neoplasia. Cancer Cell 21, 836–847 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  132. Taube, J. M. et al. Colocalization of inflammatory response with B7-h1 expression in human melanocytic lesions supports an adaptive resistance mechanism of immune escape. Sci. Transl. Med. 4, 127ra37 (2012).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  133. Pilon-Thomas, S., Mackay, A., Vohra, N. & Mule, J. J. Blockade of programmed death ligand 1 enhances the therapeutic efficacy of combination immunotherapy against melanoma. J. Immunol. 184, 3442–3449 (2010).

    Article  CAS  PubMed  Google Scholar 

  134. Peng, W. et al. PD-1 blockade enhances T-cell migration to tumors by elevating IFN-gamma inducible chemokines. Cancer Res. 72, 5209–5218 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  135. Zaidi, M. R. et al. Interferon-gamma links ultraviolet radiation to melanomagenesis in mice. Nature 469, 548–553 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  136. Motz, G. T. & Coukos, G. The parallel lives of angiogenesis and immunosuppression: cancer and other tales. Nature Rev. Immunol. 11, 702–711 (2011).

    Article  CAS  Google Scholar 

  137. Facciabene, A. et al. Tumour hypoxia promotes tolerance and angiogenesis via CCL28 and Treg cells. Nature 475, 226–230 (2011).

    Article  CAS  PubMed  Google Scholar 

  138. Hansen, W. et al. Neuropilin 1 deficiency on CD4+Foxp3+ regulatory T cells impairs mouse melanoma growth. J. Exp. Med. 209, 2001–2016 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  139. Calcinotto, A. et al. Modulation of microenvironment acidity reverses anergy in human and murine tumor-infiltrating T lymphocytes. Cancer Res. 72, 2746–2756 (2012).

    Article  CAS  PubMed  Google Scholar 

  140. Bakhoum, S. F. & Compton, D. A. Chromosomal instability and cancer: a complex relationship with therapeutic potential. J. Clin. Invest. 122, 1138–1143 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  141. 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).

    CAS  PubMed  Google Scholar 

  142. 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  PubMed  PubMed Central  Google Scholar 

  143. Calbo, J. et al. A functional role for tumor cell heterogeneity in a mouse model of small cell lung cancer. Cancer Cell 19, 244–256 (2011).

    Article  CAS  PubMed  Google Scholar 

  144. Mullighan, C. G. et al. Genomic analysis of the clonal origins of relapsed acute lymphoblastic leukemia. Science 322, 1377–1380 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  145. Anderson, K. et al. Genetic variegation of clonal architecture and propagating cells in leukaemia. Nature 469, 356–361 (2011).

    Article  CAS  PubMed  Google Scholar 

  146. Notta, F. et al. Evolution of human BCR-ABL1 lymphoblastic leukaemia-initiating cells. Nature 469, 362–367 (2011).

    Article  CAS  PubMed  Google Scholar 

  147. Colotta, F., Allavena, P., Sica, A., Garlanda, C. & Mantovani, A. Cancer-related inflammation, the seventh hallmark of cancer: links to genetic instability. Carcinogenesis 30, 1073–1081 (2009).

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  149. Acar, M., Mettetal, J. T. & van, O.A. Stochastic switching as a survival strategy in fluctuating environments. Nature Genet. 40, 471–475 (2008).

    Article  CAS  PubMed  Google Scholar 

  150. Brogan, J. et al. Imaging molecular pathways: reporter genes. Radiat. Res. 177, 508–513 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  151. Glunde, K. & Bhujwalla, Z. M. Metabolic tumor imaging using magnetic resonance spectroscopy. Semin. Oncol. 38, 26–41 (2011).

    Article  PubMed  PubMed Central  Google Scholar 

  152. Kobus, D., Giesen, Y., Ullrich, R., Backes, H. & Neumaier, B. A fully automated two-step synthesis of an 18F-labelled tyrosine kinase inhibitor for EGFR kinase activity imaging in tumors. Appl. Radiat. Isot. 67, 1977–1984 (2009).

    Article  CAS  PubMed  Google Scholar 

  153. Eisen, M. B., Spellman, P. T., Brown, P. O. & Botstein, D. Cluster analysis and display of genome-wide expression patterns. Proc. Natl Acad. Sci. USA 95, 14863–14868 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  154. Waddington, C. H. The Strategy of the Genes: a Discussion of Some Aspects of Theoretical Biology (Taylor & Francis, 1957).

    Google Scholar 

  155. Huang, S., Ernberg, I. & Kauffman, S. Cancer attractors: a systems view of tumors from a gene network dynamics and developmental perspective. Semin. Cell Dev. Biol. 20, 869–876 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  156. Chang, H. H., Hemberg, M., Barahona, M., Ingber, D. E. & Huang, S. Transcriptome-wide noise controls lineage choice in mammalian progenitor cells. Nature 453, 544–547 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  157. Eldar, A. & Elowitz, M. B. Functional roles for noise in genetic circuits. Nature 467, 167–173 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  158. Hoek, K. S. & Goding, C. R. Cancer stem cells versus phenotype-switching in melanoma. Pigment Cell Melanoma Res. 23, 746–759 (2010).

    Article  CAS  PubMed  Google Scholar 

  159. Bozic, I. et al. Accumulation of driver and passenger mutations during tumor progression. Proc. Natl Acad. Sci. USA 107, 18545–18550 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  160. Antal, T. & Krapivsky, P. L. Exact solution of a two-type branching process: models of tumor progression. J. Statist. Mechanics. Theor. Exp. 08, P08018 (2011).

    Google Scholar 

  161. Leder, K., Holland, E. C. & Michor, F. The therapeutic implications of plasticity of the cancer stem cell phenotype. PLoS ONE 5, e14366 (2010).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  162. Bolker, B. & Pacala, S. W. Using moment equations to understand stochastically driven spatial pattern formation in ecological systems. Theor. Popul. Biol. 52, 179–197 (1997).

    Article  CAS  PubMed  Google Scholar 

  163. Law, R. & Dieckmann, U. in The Geometry of Ecological Interactions: Simplifying Spatial Complexity (eds Dieckmann, U., Law, R. & Metz, J. A. J.) 252–270 (Cambridge University Press, 2000).

    Book  Google Scholar 

  164. Etheridge, A. M. Survival and extinction in a locally regulated population. Ann. Appl. Probab. 14, 188–214 (2004).

    Article  Google Scholar 

  165. Fournier, N. & Méléard, S. A microscopic probabilistic description of a locally regulated population and macroscopic approximation. Ann. Appl. Probab. 14, 1880–1919 (2004).

    Article  Google Scholar 

  166. Champagnat, N. A microscopic interpretation for adaptive dynamics trait substitution sequence models. Stoch. Proc. Appl. 116, 127–1160 (2006).

    Google Scholar 

  167. Champagnat, N. & Lambert, A. Evolution of discrete populations and the canonical diffusion of adaptive dynamics. Ann. Appl. Probab. 17, 102–155 (2007).

    Article  Google Scholar 

  168. Champagnat, N. & Méléard, S. Polymorphic evolution sequence and evolutionary branching. Probab. Theor. Relat. Field. 151, 45–94 (2011).

    Article  Google Scholar 

  169. Clayton, A. & Evans, S. N. Mutation-selection balance with recombination: convergence to equilibrium for polynomial selection costs. SIAM J. Appl. Math 69, 1772–1792 (2009).

    Article  Google Scholar 

  170. Bovier, A. & Wang, S. D. Multi-time scales in adaptive dynamics: microscopic interpretation of a trait substitution tree model. Preprint at http://arxiv.org/abs/1207.4690 (2012).

  171. Schroeder, T. Long-term single-cell imaging of mammalian stem cells. Nature Methods 8, S30–S35 (2011).

    Article  CAS  PubMed  Google Scholar 

  172. Kastenmuller, W., Torabi-Parizi, P., Subramanian, N., Lammermann, T. & Germain, R. N. A spatially-organized multicellular innate immune response in lymph nodes limits systemic pathogen spread. Cell 150, 1235–1248 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  173. Kreso, A. et al. Variable clonal repopulation dynamics influence chemotherapy response in colorectal cancer. Science 339, 543–548 (2013).

    Article  CAS  PubMed  Google Scholar 

  174. Shintani, Y. et al. Epithelial to mesenchymal transition is a determinant of sensitivity to chemoradiotherapy in non-small cell lung cancer. Ann. Thorac. Surg. 92, 1794–1804 (2011).

    Article  PubMed  Google Scholar 

  175. Uramoto, H., Shimokawa, H., Hanagiri, T., Kuwano, M. & Ono, M. Expression of selected gene for acquired drug resistance to EGFR-TKI in lung adenocarcinoma. Lung Cancer 73, 361–365 (2011).

    Article  PubMed  Google Scholar 

  176. Lee, M. J. et al. Sequential application of anticancer drugs enhances cell death by rewiring apoptotic signaling networks. Cell 149, 780–794 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  177. Klein, C. A. & Holzel, D. Systemic cancer progression and tumor dormancy: mathematical models meet single cell genomics. Cell Cycle 5, 1788–1798 (2006).

    Article  CAS  PubMed  Google Scholar 

  178. Haeno, H. et al. Computational modeling of pancreatic cancer reveals kinetics of metastasis suggesting optimum treatment strategies. Cell 148, 362–375 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  179. Iwami, S., Haeno, H. & Michor, F. A race between tumor immunoescape and genome maintenance selects for optimum levels of (epi)genetic instability. PLoS. Comput. Biol. 8, e1002370 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was supported by the following grants: German Research Foundation SP A12 in the SFB832 and SP22 in the SFB704 to T.T.; German Cancer Aid SP9 in the German Melanoma Research Network to T.T.; German Research Foundation SPP 1590 “Probabilistic structures in evolution” to A.B.. M.H., A.B. and T.T. are members of the Excellence Cluster ImmunoSensation at the University of Bonn, Germany. The authors thank all members of the Hölzel, Tüting and Bovier groups for helpful discussions and critical reading.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Thomas Tüting.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Related links

Glossary

Cancer stem cell (CSC) model

Rare quiescent and self-renewing cancer stem cells cause relapse after cytoreductive therapies, thus rebuilding a hierarchical tumour organization.

Darwinian clonal selection

Tumour cell variants with pre-existing or acquired hardwired genetic aberrations that confer therapy resistance are selected in a Darwinian evolutionary process. Typically, genomic instability and genetic heterogeneity by branched tumour evolution are a source of such resistant cell variants.

Epithelial-to-mesenchymal transition

(EMT). A reversible developmental programme that describes the acquisition of mesenchymal traits by epithelial cells. EMT programmes are reactivated in invasive cancers and believed to be a prerequisite for metastatic spread.

Phenotypic plasticity

In contrast to genomic instability or hardwired mutations, phenotypic plasticity is a source of tumour heterogeneity by, in principle, reversible phenotype switches. Altered epigenetic states are prominent examples.

Quiescent state models

Non-cycling cells are insensitive to DNA-damaging agents and any quiescent cell that can switch back into the proliferative state can cause a relapse, irrespectively of properties such as stemness or its degree of differentiation.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Hölzel, M., Bovier, A. & Tüting, T. Plasticity of tumour and immune cells: a source of heterogeneity and a cause for therapy resistance?. Nat Rev Cancer 13, 365–376 (2013). https://doi.org/10.1038/nrc3498

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrc3498

This article is cited by

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer