Glynn, Macdara ORCID: 0000-0002-6347-4348, Nwankire, Charles, Lemass, Kate, Kinahan, David J. ORCID: 0000-0003-1968-2016 and Ducrée, Jens ORCID: 0000-0002-0366-1897 (2015) Cluster size distribution of cancer cells in blood using stopped-flow centrifugation along scale-matched gaps of a radially inclined rail. Microsystems & Nanoengineering, 2015 (1). ISSN 2055-7434
Abstract
There is increasing evidence that, in addition to their presence, the propensity of circulating tumour cells to form multi-cellular clusters bears significant information about both cellular resistance to chemotherapy and overall prognosis. We present a novel two-stage, stopped-flow, continuous centrifugal sedimentation strategy to measure the size distributions of events (defined here as cells or clusters thereof) in a blood sample. After off-chip removal of red blood cells, healthy white blood cells are sequestered by negative-immunocapture. The purified events are then resolved along a radially inclined rail featuring a series of gaps with increasing width, each connected to a designated outer collection bin. The isolation of candidate events independent of target-specific epitopes is successfully demonstrated for HL60 (EpCAM positive) and sk-mel28 (EpCAM negative) cells using identical protocols and reagents. The propensity to form clusters was quantified for a number of cell lines, showing a negligible, moderate or elevated tendency towards cluster formation. We show that the occupancy distribution of the collection bins closely correlates with the range of cluster sizes intrinsic to the specific cell line.
Metadata
Item Type: | Article (Published) |
---|---|
Refereed: | Yes |
Subjects: | Biological Sciences > Microfluidics |
DCU Faculties and Centres: | Research Initiatives and Centres > Biomedical Diagnostics Institute (BDI) |
Publisher: | Nature Publishing Group |
Official URL: | http://www.nature.com/articles/micronano201518 |
Copyright Information: | © 2015 The Authors |
Use License: | This item is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 3.0 License. View License |
ID Code: | 20772 |
Deposited On: | 16 Sep 2015 10:33 by David Kinahan . Last Modified 26 Oct 2018 09:58 |
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