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CANCER DIAGNOSTICS

Seeing whole-tumour heterogeneity

Nature Biomedical Engineering volume 1, pages 772–774 (2017)Cite this article

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Light-sheet microscopy reveals 3D tumour heterogeneity in optically cleared paraffin-embedded tumour samples.

Diagnostic accuracy is essential for the prognosis of cancer patients and for deciding on the most suitable course of treatment. At present, routine histopathological diagnosis is based on the staining of thin sections of tumour tissue; therefore, pathologists only inspect a small fraction of the available sample. However, it has long been known that a tumour can present different histological features depending on the area examined, which is one of the main sources of inter-observer variability, even among experienced pathologists. Importantly, a multitude of recent genome-wide analyses of isolated single tumour cells have demonstrated that considerable heterogeneity exists at the molecular level between individual cells in a tumour, and that such heterogeneity plays a crucial role in tumour dissemination and in the development of drug resistance1. Although current molecular diagnostic methods can provide information about the presence of cancer biomarkers in the tumour tissue, they are not informative of tumour heterogeneity, because molecular alterations are not typically mapped to their spatial location within the tumour. Hence, the ability to comprehensively characterize tumour heterogeneity in the entire biopsy tissue available to the pathologist, rather than only a few thin sections of it, represents an unmet need in clinical diagnostics.

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Fig. 1: Advantages of whole-tissue imaging over traditional histology.
Fig. 2: The DIPCO pipeline for phenotyping entire FFPE tumour samples in three dimensions.

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Authors and Affiliations

  1. Department of Microvascular Biology and Pathobiology, Centre for Biomedicine and Medical Technology Mannheim, Medical Faculty Mannheim, University of Heidelberg, Ludolf-Krehl-Str. 13–17, 68167, Mannheim, Germany

    Boyan K. Garvalov

  2. Institute of Neuropathology, University of Giessen, Aulweg 128, 35392, Giessen, Germany

    Boyan K. Garvalov

  3. Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig Maximilian University of Munich, Feodor-Lynen str. 17, 81377, Munich, Germany

    Ali Ertürk

  4. Munich Cluster for Systems Neurology (SyNergy), Feodor-Lynen str. 17, 81377, Munich, Germany

    Ali Ertürk

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  1. Boyan K. Garvalov
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  2. Ali Ertürk
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Correspondence to Boyan K. Garvalov or Ali Ertürk.

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Garvalov, B.K., Ertürk, A. Seeing whole-tumour heterogeneity. Nat Biomed Eng 1, 772–774 (2017). https://doi.org/10.1038/s41551-017-0150-5

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