Source abstract
Abstract
Engineered microbeads have a wide range of applications in cancer research including identification, characterization, and sorting of cancer cells. In particular, the microbead-based cancer identification techniques are mainly based on the known genetic or biochemical biomarkers; and detection specificity is yet to be improved. On the other hand, it has been discovered that biomechanical properties of cancer cells such as cell-body elasticity can be considered as cancer biomarkers. Here, we report a straightforward microfluidic classification scheme for floating/dissociated normal and cancer epithelial cells using a confining microchannel device together with calcium-alginate hydrogel microbeads. The hydrogel microbeads are generated based on the microfluidic emulsion process, with characterization on the process parameters (e.g., liquid driving pressure and cross-linking duration) in order to specify the resultant bead diameter and elasticity. These engineered microbeads are first mixed with a cell mixture of dissociated human nasopharyngeal epithelial cells (NP460) and nasopharyngeal carcinoma cells (NPC43). The cell elasticity can then be reflected from the locations of captured cells in the device. Experiments further demonstrate that the cell classification has a success rate of >95%. Furthermore, we performed the microbead-based cell classification on a whole blood sample containing floating human breast epithelial cells (MCF-10A) and breast cancer epithelial cells (MDA-MB-231) with a success rate of >75%, revealing its directly applicability to identification of circulating tumor cells in human blood. Together, this research demonstrates a new application of engineered hydrogel microbeads for classification of cells based on their mechanical properties.
Source: openalex_inverted_index · Quality: baseline
Affiliations
Department of Biomedical Engineering, City University of Hong Kong, Kowloon, Hong Kong, Special Administrative Region of the People’s Republic of China
School of Biomedical Sciences, The University of Hong Kong, Pok Fu Lam, Hong Kong, Special Administrative Region of the People’s Republic of China
Department of Architecture and Civil Engineering, City University of Hong Kong, Kowloon, Hong Kong, Special Administrative Region of the People’s Republic of China
City University of Hong Kong, Shenzhen Research Institute, Shenzhen 518057, China
Centre for Biosystems, Neuroscience, and Nanotechnology, City University of Hong Kong, Kowloon, Hong Kong, Special Administrative Region of the People’s Republic of China
Funding
Research Grants Council, University Grants Committee · National Natural Science Foundation of China