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Toward understanding and exploiting tumor heterogeneity

Abstract

The extent of tumor heterogeneity is an emerging theme that researchers are only beginning to understand. How genetic and epigenetic heterogeneity affects tumor evolution and clinical progression is unknown. The precise nature of the environmental factors that influence this heterogeneity is also yet to be characterized. Nature Medicine, Nature Biotechnology and the Volkswagen Foundation organized a meeting focused on identifying the obstacles that need to be overcome to advance translational research in and tumor heterogeneity. Once these key questions were established, the attendees devised potential solutions. Their ideas are presented here.

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Figure 1: Herrenhausen Palace.
Figure 2: The clonality of tumor evolution.
Figure 3: Influences on cancer cell state.

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References

  1. Zardavas, D. et al. Clinical management of breast cancer heterogeneity. Nat. Rev. Clin. Oncol. 12, 381–394 (2015).

    Article  CAS  Google Scholar 

  2. Marusyk, A. et al. Intra-tumour heterogeneity: a looking glass for cancer? Nat. Rev. Cancer 12, 323–334 (2012).

    Article  CAS  Google Scholar 

  3. McGranahan, N. & Charles Swanton, C. Biological and therapeutic impact of intratumor heterogeneity in cancer evolution. Cancer Cell 27, 15–26 (2015).

    Article  CAS  Google Scholar 

  4. Chen, J.C. et al. Identification of causal genetic drivers of human disease through systems-level analysis of regulatory networks. Cell 159, 402–414 (2014).

    Article  CAS  Google Scholar 

  5. Gould, S.E., Junttila, M.R. & de Sauvage, F.J. Translational value of mouse models in oncology drug development. Nat. Med. 21, 431–439 (2015).

    Article  CAS  Google Scholar 

  6. Li, S. et al. Dynamic evolution of clonal epialleles revealed by methclone. Genome Biol. 15, 472 (2014).

    Article  Google Scholar 

  7. de Biasi, A.R., Villena-Vargas, J. & Adusumilli, P.S. Cisplatin-induced antitumor immunomodulation: a review of preclinical and clinical evidence. Clin. Cancer Res. 20, 5384–5391 (2014).

    Article  CAS  Google Scholar 

  8. Postow, M.A. et al. Immunologic correlates of the abscopal effect in a patient with melanoma. N. Engl. J. Med. 366, 925–931 (2012).

    Article  CAS  Google Scholar 

  9. Twyman-Saint Victor, C. et al. Radiation and dual checkpoint blockade activate non-redundant immune mechanisms in cancer. Nature 520, 373–377 (2015).

    Article  CAS  Google Scholar 

  10. Zamarin, D. et al. Localized oncolytic virotherapy overcomes systemic tumor resistance to immune checkpoint blockade immunotherapy. Sci. Transl. Med. 6, 26ra32 (2014).

    Article  Google Scholar 

  11. Andtbacka, R.H.I. et al. Talimogene laherparepvec improves durable response rate in patients with advanced melanoma. J. Clin. Oncol. doi:10.1200/JCO.2014.58.3377 (26 May 2015).

  12. Eggermont, A.M. et al. Cancer Core Europe: a consortium to address the cancer care-cancer research continuum challenge. Eur. J. Cancer 50, 2745–2746 (2014).

    Article  Google Scholar 

  13. Bansal, M. et al. A community computational challenge to predict the activity of pairs of compounds. Nat. Biotechnol. 32, 1213–1222 (2014).

    Article  CAS  Google Scholar 

  14. Siravegna, G. et al. Clonal evolution and resistance to EGFR blockade in the blood of colorectal cancer patients. Nat. Med. doi:10.1038/nm.3870 (1 June 2015).

  15. Thress, K.S. et al. Acquired EGFR C797S mutation mediates resistance to AZD9291 in non–small cell lung cancer harboring EGFR T790M. Nat. Med. 21, 560–562 (2015).

    Article  CAS  Google Scholar 

  16. Newman, A.M. et al. An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage. Nat. Med. 20, 548–554 (2014).

    Article  CAS  Google Scholar 

  17. Dawson, S.J. et al. Analysis of circulating tumor DNA to monitor metastatic breast cancer. N. Engl. J. Med. 368, 1199–1209 (2013).

    Article  CAS  Google Scholar 

  18. Rodrigues, T.B. et al. Magnetic resonance imaging of tumor glycolysis using hyperpolarized 13C-labeled glucose. Nat. Med. 20, 93–97 (2014).

    Article  CAS  Google Scholar 

  19. Newman, A.M. et al. Robust enumeration of cell subsets from tissue expression profiles. Nat. Methods 12, 453–457 (2015).

    Article  CAS  Google Scholar 

  20. Gentles, A.J. et al. The prognostic landscape of genes and infiltrating immune cells across human cancers. Nat. Med. 21, 940–947 (2015).

    Article  Google Scholar 

  21. Pan, X. et al. Proc. Natl. Acad. Sci. USA 110, 594–599 (2013).

    Article  CAS  Google Scholar 

  22. Macosko, E.Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).

    Article  CAS  Google Scholar 

  23. Klein, A.M. et al. Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161, 1187–1201 (2015).

    Article  CAS  Google Scholar 

  24. Fan, H.C., Fu, G.K. & Fodor, S.P. Expression profiling. Combinatorial labeling of single cells for gene expression cytometry. Science 347, 910–914 (2015).

    Article  Google Scholar 

  25. Murphy, P.J. et al. Single-molecule analysis of combinatorial epigenomic states in normal and tumor cells. Proc. Natl. Acad. Sci. USA 110, 7772–7777 (2013).

    Article  CAS  Google Scholar 

  26. Li, S. et al. The pivotal regulatory landscape of RNA modifications. Annu. Rev. Genomics. Hum. Genet. 15, 127–150 (2014).

    Article  CAS  Google Scholar 

  27. Dey, S.S. et al. Integrated genome and transcriptome sequencing of the same cell. Nat. Biotechnol. 33, 285–289 (2015).

    Article  CAS  Google Scholar 

  28. Seligson, D.B. et al. Global histone modification patterns predict risk of prostate cancer recurrence. Nature 435, 1262–1266 (2005).

    Article  CAS  Google Scholar 

  29. Gomez, D. et al. Detection of histone modifications at specific gene loci in single cells in histological sections. Nat. Methods 10, 171–177 (2013).

    Article  CAS  Google Scholar 

  30. Giesen, C. et al. Highly multiplexed imaging of tumor tissues with subcellular resolution by mass cytometry. Nat. Methods 11, 417–422 (2014).

    Article  CAS  Google Scholar 

  31. Angelo, M. et al. Multiplexed ion beam imaging of human breast tumors. Nat. Med. 20, 436–442 (2014).

    Article  CAS  Google Scholar 

  32. Lee, J.H. et al. Fluorescent in situ sequencing (FISSEQ) of RNA for gene expression profiling in intact cells and tissues. Nat. Protoc. 10, 442–458 (2015).

    Article  CAS  Google Scholar 

  33. Chen, K.H., Boettiger, A.N., Moffitt, J.R., Wang, S. & Zhuang, X. Spatially resolved, highly multiplexed RNA profiling in single cells. Science 348, 6233 (2015).

    Google Scholar 

  34. Lee, J.H. et al. Highly multiplexed subcellular RNA sequencing in situ. Science 343, 1360–1363 (2014).

    Article  CAS  Google Scholar 

  35. O'Connor, J.P. et al. Imaging intratumor heterogeneity: role in therapy response, resistance, and clinical outcome. Clin. Cancer Res. 21, 249–257 (2015).

    Article  CAS  Google Scholar 

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

    Article  CAS  Google Scholar 

Download references

Acknowledgements

We would like to thank O. Grewe, M. Ruessman and S. Kim for their help in the organization of the meeting.

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Correspondence to Hannah Stower.

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Competing interests

A.A.A. is a cofounder of CAPP-Medical and a consultant for Roche, Genentech, CAPP-Medical and Celgene. K.P. has a sponsored research agreement and consultancy with Novartis Oncology.

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Alizadeh, A., Aranda, V., Bardelli, A. et al. Toward understanding and exploiting tumor heterogeneity. Nat Med 21, 846–853 (2015). https://doi.org/10.1038/nm.3915

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