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.

  • Review Article
  • Published:

Intra-tumour heterogeneity: a looking glass for cancer?

Key Points

  • Primary human tumours consist of cells that differ in clinically important phenotypic features. This phenotypic heterogeneity is a result of the interplay between genetic and non-genetic factors that shape cellular phenotypes.

  • Genomic instability, which is frequently observed in human cancers, in combination with the large numbers of cell divisions required for the formation of macroscopic tumours, leads to inevitable genetic diversity in populations of tumour cells.

  • Somatic evolution that drives tumour progression is characterized by complex dynamics arising from the Darwinian nature of the process. As a result, individual tumours have a unique clonal architecture that is spatially and temporally heterogeneous.

  • The cancer stem cell perspective can explain only some of the non-genetic variability in tumour cell phenotypes. A more comprehensive explanation of non-genetic sources of phenotypic heterogeneity necessitates the consideration of mechanisms that underlie cellular phenotypes.

  • Both deterministic and stochastic determinants of cellular phenotypes can be substantially affected during oncogenic transformation and tumour progression, contributing both to abnormal phenotypes and to an increased degree of phenotypic plasticity.

  • Phenotypic and genetic heterogeneity within tumours impedes clinical diagnostics: owing to topological heterogeneity in the distribution of diagnostically important phenotypes even multiple sampling might not provide adequate information. At the same time, given the link between a high degree of genetic heterogeneity and poor prognosis, a measure of heterogeneity by itself may be useful as a prognostic marker.

  • Phenotypic heterogeneity in tumour cell populations that results from both genetic and non-genetic determinants constitutes a major source of therapeutic resistance. Initial phenotypic heterogeneity and changes in cellular phenotypes resulting from adaptation to response and selection for resistant phenotypes need to be accounted for in order to achieve substantial improvements in therapeutic outcomes.

Abstract

Populations of tumour cells display remarkable variability in almost every discernable phenotypic trait, including clinically important phenotypes such as ability to seed metastases and to survive therapy. This phenotypic diversity results from the integration of both genetic and non-genetic influences. Recent technological advances have improved the molecular understanding of cancers and the identification of targets for therapeutic interventions. However, it has become exceedingly apparent that the utility of profiles based on the analysis of tumours en masse is limited by intra-tumour genetic and epigenetic heterogeneity, as characteristics of the most abundant cell type might not necessarily predict the properties of mixed populations. In this Review, we discuss both genetic and non-genetic causes of phenotypic heterogeneity of tumour cells, with an emphasis on heritable phenotypes that serve as a substrate for clonal selection. We discuss the implications of intra-tumour heterogeneity in diagnostics and the development of therapeutic resistance.

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

Access options

Buy this article

Purchase on Springer Link

Instant access to full article PDF

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

Figure 1: Differentiation hierarchies in normal tissues and cancers.
Figure 2: Factors that shape cellular phenotypes: normal tissues versus tumours.
Figure 3: Tumour heterogeneity in metastatic spread.
Figure 4: Tumour heterogeneity in diagnostics.

Similar content being viewed by others

References

  1. Fidler, I. J. Tumor heterogeneity and the biology of cancer invasion and metastasis. Cancer Res. 38, 2651–2660 (1978).

    CAS  PubMed  Google Scholar 

  2. Gerlinger, M. et al. Intratumor heterogeneity and branched evolution revealed by multiregion sequencing. N. Engl. J. Med. 366, 883–892 (2012). This paper demonstrated substantial spatial genetic heterogeneity within tumours, including synonymous driving mutations independently arising in distinct clones. Furthermore, it reported distinct diagnostic signatures from different biopsies of the same tumour.

    CAS  PubMed  PubMed Central  Google Scholar 

  3. Anderson, K. et al. Genetic variegation of clonal architecture and propagating cells in leukaemia. Nature 469, 356–361 (2011). This paper demonstrated substantial genetic variability in putative driver mutations between leukaemia stem cells, suggesting complex patterns of clonal evolution.

    CAS  PubMed  Google Scholar 

  4. Campbell, L. L. & Polyak, K. Breast tumor heterogeneity: cancer stem cells or clonal evolution? Cell Cycle 6, 2332–2338 (2007).

    CAS  PubMed  Google Scholar 

  5. Shackleton, M., Quintana, E., Fearon, E. R. & Morrison, S. J. Heterogeneity in cancer: cancer stem cells versus clonal evolution. Cell 138, 822–829 (2009).

    CAS  PubMed  Google Scholar 

  6. Notta, F. et al. Evolution of human BCR-ABL1 lymphoblastic leukaemia-initiating cells. Nature 469, 362–367 (2011). This paper demonstrated substantial genetic diversity between leukaemia-initiating cells, suggesting complex clonal architecture.

    CAS  PubMed  Google Scholar 

  7. Shipitsin, M. et al. Molecular definition of breast tumor heterogeneity. Cancer Cell 11, 259–273 (2007). This paper demonstrated that presumed stem cell and non-stem cell subpopulations in breast tumours can have different patterns of mutations.

    CAS  PubMed  Google Scholar 

  8. Vogelstein, B. & Kinzler, K. W. Cancer genes and the pathways they control. Nature Med. 10, 789–799 (2004).

    CAS  PubMed  Google Scholar 

  9. Rangarajan, A., Hong, S. J., Gifford, A. & Weinberg, R. A. Species- and cell type-specific requirements for cellular transformation. Cancer Cell 6, 171–183 (2004).

    CAS  PubMed  Google Scholar 

  10. Ruiz, C. et al. Advancing a clinically relevant perspective of the clonal nature of cancer. Proc. Natl Acad. Sci. USA 108, 12054–12059 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. Ashworth, A., Lord, C. J. & Reis-Filho, J. S. Genetic interactions in cancer progression and treatment. Cell 145, 30–38 (2011).

    CAS  PubMed  Google Scholar 

  12. Raj, A. & van Oudenaarden, A. Nature, nurture, or chance: stochastic gene expression and its consequences. Cell 135, 216–226 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. Niepel, M., Spencer, S. L. & Sorger, P. K. Non-genetic cell-to-cell variability and the consequences for pharmacology. Curr. Opin. Chem. Biol. 13, 556–561 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  14. Altschuler, S. J. & Wu, L. F. Cellular heterogeneity: do differences make a difference? Cell 141, 559–563 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  15. Huang, S. Non-genetic heterogeneity of cells in development: more than just noise. Development 136, 3853–3862 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  17. Dalerba, P. et al. Single-cell dissection of transcriptional heterogeneity in human colon tumors. Nature Biotechnol. 29, 1120–1127 (2011).

    CAS  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  19. Rosen, J. M. & Jordan, C. T. The increasing complexity of the cancer stem cell paradigm. Science 324, 1670–1673 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  20. Chaffer, C. L. et al. Normal and neoplastic nonstem cells can spontaneously convert to a stem-like state. Proc. Natl Acad. Sci. USA. 108, 7950–7955 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Quintana, E. et al. Efficient tumour formation by single human melanoma cells. Nature 456, 593–598 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. Balazsi, G., van Oudenaarden, A. & Collins, J. J. Cellular decision making and biological noise: from microbes to mammals. Cell 144, 910–925 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. Arias, A. M. & Hayward, P. Filtering transcriptional noise during development: concepts and mechanisms. Nature Rev. Genet. 7, 34–44 (2006).

    CAS  PubMed  Google Scholar 

  24. Hughes, T. R. et al. Functional discovery via a compendium of expression profiles. Cell 102, 109–126 (2000).

    CAS  PubMed  Google Scholar 

  25. Luo, J., Solimini, N. L. & Elledge, S. J. Principles of cancer therapy: oncogene and non-oncogene addiction. Cell 136, 823–837 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Whitesell, L. & Lindquist, S. L. HSP90 and the chaperoning of cancer. Nature Rev. Cancer 5, 761–772 (2005).

    CAS  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  28. Allinen, M. et al. Molecular characterization of the tumor microenvironment in breast cancer. Cancer Cell 6, 17–32 (2004).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  30. Bissell, M. J., Kenny, P. A. & Radisky, D. C. Microenvironmental regulators of tissue structure and function also regulate tumor induction and progression: the role of extracellular matrix and its degrading enzymes. Cold Spring Harb. Symp. Quant. Biol. 70, 343–356 (2005).

    CAS  PubMed  PubMed Central  Google Scholar 

  31. Anderson, A. R., Weaver, A. M., Cummings, P. T. & Quaranta, V. Tumor morphology and phenotypic evolution driven by selective pressure from the microenvironment. Cell 127, 905–915 (2006).

    CAS  PubMed  Google Scholar 

  32. Chen, J., Sprouffske, K., Huang, Q. & Maley, C. C. Solving the puzzle of metastasis: the evolution of cell migration in neoplasms. PloS ONE 6, e17933 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  33. Polyak, K. & Weinberg, R. A. Transitions between epithelial and mesenchymal states: acquisition of malignant and stem cell traits. Nature Rev. Cancer 9, 265–273 (2009).

    CAS  Google Scholar 

  34. Hendrix, M. J., Seftor, E. A., Hess, A. R. & Seftor, R. E. Vasculogenic mimicry and tumour-cell plasticity: lessons from melanoma. Nature Rev. Cancer 3, 411–421 (2003).

    CAS  Google Scholar 

  35. Radisky, D. C. & Bissell, M. J. Matrix metalloproteinase-induced genomic instability. Curr. Opin. Genet. Dev. 16, 45–50 (2006).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  37. Farmer, P. et al. A stroma-related gene signature predicts resistance to neoadjuvant chemotherapy in breast cancer. Nature Med. 15, 68–74 (2009).

    CAS  PubMed  Google Scholar 

  38. Finak, G. et al. Stromal gene expression predicts clinical outcome in breast cancer. Nature Med. 14, 518–527 (2008).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  40. 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).

    CAS  Google Scholar 

  41. Jones, P. A. & Baylin, S. B. The epigenomics of cancer. Cell 128, 683–692 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  42. Brock, A., Chang, H. & Huang, S. Non-genetic heterogeneity--a mutation-independent driving force for the somatic evolution of tumours. Nature Rev. Genetics 10, 336–342 (2009).

    CAS  Google Scholar 

  43. Weinberg, R. A. The Biology of Cancer (Garland Science, 2007).

    Google Scholar 

  44. Barrick, J. E. & Lenski, R. E. Genome-wide mutational diversity in an evolving population of Escherichia coli. Cold Spring Harb. Symp. Quant. Biol. 74, 119–129 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. Desai, M. M., Fisher, D. S. & Murray, A. W. The speed of evolution and maintenance of variation in asexual populations. Curr. Biol. 17, 385–394 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  46. Marusyk, A. & Polyak, K. Tumor heterogeneity: causes and consequences. Biochim. Biophys. Acta 1805, 105–117 (2010).

    CAS  PubMed  Google Scholar 

  47. Navin, N. et al. Tumour evolution inferred by single-cell sequencing. Nature 472, 90–94 (2011). The first report that interrogated genomic-wide diversity within tumours on a single-cell level.

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  Google Scholar 

  49. Gonzalez-Garcia, I., Sole, R. V. & Costa, J. Metapopulation dynamics and spatial heterogeneity in cancer. Proc. Natl Acad. Sci. USA 99, 13085–13089 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

  50. Snuderl, M. et al. Mosaic amplification of multiple receptor tyrosine kinase genes in glioblastoma. Cancer Cell 20, 810–817 (2011).

    CAS  PubMed  Google Scholar 

  51. Stoecklein, N. H. & Klein, C. A. Genetic disparity between primary tumours, disseminated tumour cells, and manifest metastasis. Int. J. Cancer. 126, 589–598 (2010).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  Google Scholar 

  53. Ramaswamy, S., Ross, K. N., Lander, E. S. & Golub, T. R. A molecular signature of metastasis in primary solid tumors. Nature Genet. 33, 49–54 (2003).

    CAS  PubMed  Google Scholar 

  54. Weigelt, B. et al. Molecular portraits and 70-gene prognosis signature are preserved throughout the metastatic process of breast cancer. Cancer Res. 65, 9155–9158 (2005).

    CAS  PubMed  Google Scholar 

  55. Klein, C. A. Parallel progression of primary tumours and metastases. Nature Rev. Cancer 9, 302–312 (2009).

    CAS  Google Scholar 

  56. Mardis, E. R. Cancer genomics identifies determinants of tumor biology. Genome Biol. 11, 211 (2010).

    PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  58. Shah, S. P. et al. Mutational evolution in a lobular breast tumour profiled at single nucleotide resolution. Nature 461, 809–813 (2009). The first report that used next-generation sequencing to interrogate clonal diversity and evolution during breast cancer progression.

    CAS  PubMed  Google Scholar 

  59. Ding, L. et al. Genome remodelling in a basal-like breast cancer metastasis and xenograft. Nature 464, 999–1005 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. Perou, C. M., Parker, J. S., Prat, A., Ellis, M. J. & Bernard, P. S. Clinical implementation of the intrinsic subtypes of breast cancer. Lancet Oncol. 11, 718–719 (2010).

    PubMed  Google Scholar 

  61. Sorlie, T. et al. Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc. Natl Acad. Sci. USA 98, 10869–10874 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Komaki, K., Sano, N. & Tangoku, A. Problems in histological grading of malignancy and its clinical significance in patients with operable breast cancer. Breast cancer 13, 249–253 (2006).

    PubMed  Google Scholar 

  63. Bertos, N. R. & Park, M. Breast cancer - one term, many entities? J. Clin. Invest. 121, 3789–3796 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. 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  PubMed  Google Scholar 

  65. Maley, C. C. et al. Genetic clonal diversity predicts progression to esophageal adenocarcinoma. Nature Genet. 38, 468–473 (2006). This paper linked higher extent of genetic clonal diversity with poor clinical outcome.

    CAS  PubMed  Google Scholar 

  66. Merlo, L. M. & Maley, C. C. The role of genetic diversity in cancer. J. Clin. Invest. 120, 401–403 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. Park, S. Y. et al. Heterogeneity for stem cell-related markers according to tumor subtype and histologic stage in breast cancer. Clin. Cancer Res. 16, 876–887 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  68. 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).

    CAS  Google Scholar 

  69. Ebos, J. M. et al. Accelerated metastasis after short-term treatment with a potent inhibitor of tumor angiogenesis. Cancer Cell 15, 232–239 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  70. Paez-Ribes, M. et al. Antiangiogenic therapy elicits malignant progression of tumors to increased local invasion and distant metastasis. Cancer Cell 15, 220–231 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  71. Deininger, M. Resistance to imatinib: mechanisms and management. J. Natl Compr. Canc. Netw. 3, 757–768 (2005).

    PubMed  Google Scholar 

  72. Corless, C. L. & Heinrich, M. C. Molecular pathobiology of gastrointestinal stromal sarcomas. Annu. Rev. Pathol. 3, 557–586 (2008).

    CAS  PubMed  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  74. Engelman, J. A. et al. MET amplification leads to gefitinib resistance in lung cancer by activating ERBB3 signaling. Science 316, 1039–1043 (2007).

    CAS  PubMed  Google Scholar 

  75. Edwards, S. L. et al. Resistance to therapy caused by intragenic deletion in BRCA2. Nature 451, 1111–1115 (2008).

    CAS  PubMed  Google Scholar 

  76. Sakai, W. et al. Secondary mutations as a mechanism of cisplatin resistance in BRCA2-mutated cancers. Nature 451, 1116–1120 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  77. Roche-Lestienne, C., Lai, J. L., Darre, S., Facon, T. & Preudhomme, C. A mutation conferring resistance to imatinib at the time of diagnosis of chronic myelogenous leukemia. N. Engl. J. Med. 348, 2265–2266 (2003).

    PubMed  Google Scholar 

  78. Ding, L. et al. Clonal evolution in relapsed acute myeloid leukaemia revealed by whole-genome sequencing. Nature 481, 506–510 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  80. Glasspool, R. M., Teodoridis, J. M. & Brown, R. Epigenetics as a mechanism driving polygenic clinical drug resistance. Br. J. Cancer 94, 1087–1092 (2006).

    CAS  PubMed  PubMed Central  Google Scholar 

  81. Janne, P. A., Gray, N. & Settleman, J. Factors underlying sensitivity of cancers to small-molecule kinase inhibitors. Nature Rev. Drug Discov. 8, 709–723 (2009).

    CAS  Google Scholar 

  82. Sharma, S. V. et al. A chromatin-mediated reversible drug-tolerant state in cancer cell subpopulations. Cell 141, 69–80 (2010). This study linked therapy resistance with a distinct epigenetic switch that arises through a spontaneous phenotypic switch. Although this phenotypic state is reversible, it can persist for multiple cell generations and thus serve as a substrate for Darwinian selection.

    CAS  PubMed  PubMed Central  Google Scholar 

  83. Cohen, A. A. et al. Dynamic proteomics of individual cancer cells in response to a drug. Science 322, 1511–1516 (2008).

    CAS  PubMed  Google Scholar 

  84. Spencer, S. L., Gaudet, S., Albeck, J. G., Burke, J. M. & Sorger, P. K. Non-genetic origins of cell-to-cell variability in TRAIL-induced apoptosis. Nature 459, 428–432 (2009). This study implicated noise-driven stochastic non-genetic variability in short-term resistance to therapy.

    CAS  PubMed  PubMed Central  Google Scholar 

  85. Heppner, G. H. Cancer cell societies and tumor progression. Stem Cells 11, 199–203 (1993).

    CAS  PubMed  Google Scholar 

  86. Bonavia, R., Inda, M. M., Cavenee, W. K. & Furnari, F. B. Heterogeneity maintenance in glioblastoma: a social network. Cancer Res. 71, 4055–4060 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  87. Park, S. Y., Gönen, M., Kim, H. J., Michor, F. & Polyak, K. Cellular and genetic diversity in the progression of in situ human breast carcinomas to an invasive phenotype. J. Clin. Invest. 120, 636–644 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  88. Merlo, L. M. et al. A comprehensive survey of clonal diversity measures in Barrett's esophagus as biomarkers of progression to esophageal adenocarcinoma. Cancer Prev. Res. (Phila) 3, 1388–1397 (2010).

    Google Scholar 

  89. Russnes, H. G., Navin, N., Hicks, J. & Borresen-Dale, A. L. Insight into the heterogeneity of breast cancer through next-generation sequencing. J. Clin. Invest. 121, 3810–3818 (2011).

    CAS  Google Scholar 

  90. Navin, N. et al. Inferring tumor progression from genomic heterogeneity. Genome Res. 20, 68–80 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  91. Xu, X. et al. Single-cell exome sequencing reveals single-nucleotide mutation characteristics of a kidney tumor. Cell 148, 886–895 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  92. Hou, Y. et al. Single-cell exome sequencing and monoclonal evolution of a JAK2-negative myeloproliferative neoplasm. Cell 148, 873–885 (2012).

    CAS  PubMed  Google Scholar 

  93. Miller, B. E., Machemer, T., Lehotan, M. & Heppner, G. H. Tumor subpopulation interactions affecting melphalan sensitivity in palpable mouse mammary tumors. Cancer Res. 51, 4378–4387 (1991).

    CAS  PubMed  Google Scholar 

  94. 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).

    CAS  PubMed  Google Scholar 

  95. Marks, P. A. & Dokmanovic, M. Histone deacetylase inhibitors: discovery and development as anticancer agents. Expert Opin. Investig. Drugs 14, 1497–1511 (2005).

    CAS  PubMed  Google Scholar 

  96. Gregory, R. I. & Shiekhattar, R. Chromatin modifiers and carcinogenesis. Trends Cell. Biol. 14, 695–702 (2004).

    CAS  PubMed  Google Scholar 

  97. Bissell, M. J. & Hines, W. C. Why don't we get more cancer? A proposed role of the microenvironment in restraining cancer progression. Nature Med. 17, 320–329 (2011).

    CAS  PubMed  Google Scholar 

  98. Attolini, C. S. & Michor, F. Evolutionary theory of cancer. Ann. NY Acad. Sci. 1168, 23–51 (2009).

    CAS  PubMed  Google Scholar 

  99. DeGregori, J. Evolved tumor suppression: why are we so good at not getting cancer? Cancer Res. 71, 3739–3744 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  101. Gatenby, R. A., Silva, A. S., Gillies, R. J. & Frieden, B. R. Adaptive therapy. Cancer Res. 69, 4894–4903 (2009). This paper proposes 'adaptive therapy', which takes into account clonal competition in order to prevent therapy-resistant cells from taking over the population.

    CAS  PubMed  PubMed Central  Google Scholar 

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

    Google Scholar 

  103. Huang, S. & Kauffman, S. A. in Encyclopedia of Complexity and Systems Science (ed. Meyers, R. A.) 1180–1213 (Springer, 2009).

    Google Scholar 

  104. Fisher, A. G. Cellular identity and lineage choice. Nature Rev. Immunol. 2, 977–982 (2002).

    CAS  Google Scholar 

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

    CAS  PubMed  PubMed Central  Google Scholar 

  106. Leedham, S. J. et al. Individual crypt genetic heterogeneity and the origin of metaplastic glandular epithelium in human Barrett's oesophagus. Gut 57, 1041–1948 (2008).

    CAS  PubMed  Google Scholar 

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

    PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank members of our laboratory and F. Michor and S. Itzkovitz for their critical reading of our manuscript and for stimulating discussions. Tumour diversity research in the authors' laboratory is supported by US Army Congressionally Directed Research W81XWH-07-1-0294 (K.P.) and BC087579 (A.M.), US National Cancer Institute PO1 CA80111 (K.P.), Susan G. Komen Foundation (K.P.), Breast Cancer Research Foundation (K.P.) and the Cellex Foundation (V.A.).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Kornelia Polyak.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Related links

FURTHER INFORMATION

Kornelia Polyak's homepage

Glossary

Phenotypic plasticity

The ability of cells to change phenotype stochastically or in response to changes in the environment.

Effective population sizes

The numbers of tumour cells capable of passing their genotypes to next generations.

Allelic imbalances

Changes in the copy number of alleles as a result of chromosomal amplification or deletions.

Heat shock protein response

A response to cellular stress involving the activation of molecular chaperones called heat shock proteins (HSPs). HSPs help to maintain cellular homeostasis and to promote survival in the face of stress.

Clone

A group of cells that share a common ancestor and that are genetically identical. Whereas all of the cells in the body originate from a single ancestor, every new mutation creates a new clone (a subclone).

Clonal diversity

The diversity of clones within a tumour; results from a branching pattern of evolution. Increased with larger population size, smaller fitness differences, higher mutation rates and heterogeneity of environments.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Marusyk, A., Almendro, V. & Polyak, K. Intra-tumour heterogeneity: a looking glass for cancer?. Nat Rev Cancer 12, 323–334 (2012). https://doi.org/10.1038/nrc3261

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/nrc3261

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