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Rapid single-cell physical phenotyping of mechanically dissociated tissue biopsies

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Soteriou,  Despina
Guck Division, Max Planck Institute for the Science of Light, Max Planck Society;
Guck Division, Max-Planck-Zentrum für Physik und Medizin, Max Planck Institute for the Science of Light, Max Planck Society;

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Kubánková,  Markéta
Guck Division, Max Planck Institute for the Science of Light, Max Planck Society;
Guck Division, Max-Planck-Zentrum für Physik und Medizin, Max Planck Institute for the Science of Light, Max Planck Society;

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Schweitzer,  Christine
Guck Division, Max Planck Institute for the Science of Light, Max Planck Society;
Guck Division, Max-Planck-Zentrum für Physik und Medizin, Max Planck Institute for the Science of Light, Max Planck Society;

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Guck,  Jochen
Guck Division, Max Planck Institute for the Science of Light, Max Planck Society;
Guck Division, Max-Planck-Zentrum für Physik und Medizin, Max Planck Institute for the Science of Light, Max Planck Society;
Friedrich-Alexander-Universität Erlangen-Nürnberg;

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Nat Biomed Eng 2023 Soteriou.pdf
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Citation

Soteriou, D., Kubánková, M., Schweitzer, C., López-Posadas, R., Pradhan, R., Thoma, O.-M., et al. (2023). Rapid single-cell physical phenotyping of mechanically dissociated tissue biopsies. Nature Biomedical Engineering, 7, 1392-1403. doi:10.1038/s41551-023-01015-3.


Cite as: https://hdl.handle.net/21.11116/0000-0009-9484-A
Abstract
During surgery, rapid and accurate histopathological diagnosis is essential for clinical decision making. Yet the prevalent method of intra-operative consultation pathology is intensive in time, labour and costs, and requires the expertise of trained pathologists. Here we show that biopsy samples can be analysed within 30 min by sequentially assessing the physical phenotypes of singularized suspended cells dissociated from the tissues. The diagnostic method combines the enzyme-free mechanical dissociation of tissues, real-time deformability cytometry at rates of 100–1,000 cells s−1 and data analysis by unsupervised dimensionality reduction and logistic regression. Physical phenotype parameters extracted from brightfield images of single cells distinguished cell subpopulations in various tissues, enhancing or even substituting measurements of molecular markers. We used the method to quantify the degree of colon inflammation and to accurately discriminate healthy and tumorous tissue in biopsy samples of mouse and human colons. This fast and label-free approach may aid the intra-operative detection of pathological changes in solid biopsies.