Research Data Leeds Repository

Citation

Armistead, Fern and Gala de Pablo, Julia and Gadêlha, Hermes and Peyman, Sally A. and Evans, Stephen D. (2020) Dataset associated with 'Physical biomarkers of disease progression: on-chip monitoring of changes in mechanobiology of colorectal cancer cells'. University of Leeds. [Dataset] https://doi.org/10.5518/702

Dataset description

Disease can induce changes to subcellular components, altering cell phenotype and leading to measurable bulk-material mechanical properties. The mechanical phenotyping of single cells therefore offers many potential diagnostic applications. Cells are viscoelastic and their response to an applied stress is highly dependent on the magnitude and timescale of the actuation. Microfluidics can be used to measure cell deformability over a wide range of flow conditions, operating two distinct flow regimes (shear and inertial) which can expose subtle mechanical properties arising from subcellular components. Here, we investigate the deformability of three colorectal cancer (CRC) cell lines using a range of flow conditions. These cell lines offer a model for CRC metastatic progression; SW480 derived from primary adenocarcinoma, HT29 from a more advanced primary tumor and SW620 from lymph-node metastasis. HL60 (leukemia cells) were also studied as a model circulatory cell, offering a non-epithelial comparison. We demonstrate that microfluidic induced flow deformation can be used to robustly detect mechanical changes associated with CRC progression. We also show that single-cell multivariate analysis, utilising deformation and relaxation dynamics, offers potential to distinguish these different cell types. These results point to the benefit of multiparameter determination for improving detection and accuracy of disease stage diagnosis.

Subjects:	F000 - Physical sciences > F300 - Physics > F350 - Medical physics
Divisions:	Faculty of Engineering and Physical Sciences > School of Physics and Astronomy
Related resources:	Location Type https://doi.org/10.1038/s41598-020-59952-x Publication https://eprints.whiterose.ac.uk/156060/ Publication
License:	Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited:	23 Feb 2020 11:25
URI:	https://archive.researchdata.leeds.ac.uk/id/eprint/645
Additional details Additional details Creators or authors: Creators ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type Armistead, Fern https://orcid.org/0000-0003-1274-5379 University of Leeds https://ror.org/024mrxd33 ror Gala de Pablo, Julia https://orcid.org/0000-0003-0557-9632 University of Leeds https://ror.org/024mrxd33 ror Gadêlha, Hermes https://orcid.org/0000-0001-8053-9249 University of Bristol https://ror.org/0524sp257 ror Peyman, Sally A. https://orcid.org/0000-0002-1600-5100 University of Leeds https://ror.org/024mrxd33 ror Evans, Stephen D. https://orcid.org/0000-0001-8342-5335 University of Leeds https://ror.org/024mrxd33 ror Type of data: Dataset Research funders: EPSRC and MRC, MRC Grant numbers: EP/P023266/1, MR/M009084/1 Publication date: 2020 Resource language: English Metadata language: English Publisher: University of Leeds Contact email: ed10fja@leeds.ac.uk Last Modified: 30 Oct 2024 11:33

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