Capture and On-chip analysis of Melanoma Cells Using Tunable Surface Shear forces View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2016-04

AUTHORS

Simon Chang-Hao Tsao, Ramanathan Vaidyanathan, Shuvashis Dey, Laura G Carrascosa, Christopher Christophi, Jonathan Cebon, Muhammad J A Shiddiky, Andreas Behren, Matt Trau

ABSTRACT

With new systemic therapies becoming available for metastatic melanoma such as BRAF and PD-1 inhibitors, there is an increasing demand for methods to assist with treatment selection and response monitoring. Quantification and characterisation of circulating melanoma cells (CMCs) has been regarded as an excellent non-invasive candidate but a sensitive and efficient tool to do these is lacking. Herein we demonstrate a microfluidic approach for melanoma cell capture and subsequent on-chip evaluation of BRAF mutation status. Our approach utilizes a recently discovered alternating current electrohydrodynamic (AC-EHD)-induced surface shear forces, referred to as nanoshearing. A key feature of nanoshearing is the ability to agitate fluid to encourage contact with surface-bound antibody for the cell capture whilst removing nonspecific cells from the surface. By adjusting the AC-EHD force to match the binding affinity of antibodies against the melanoma-associated chondroitin sulphate proteoglycan (MCSP), a commonly expressed melanoma antigen, this platform achieved an average recovery of 84.7% from biological samples. Subsequent staining with anti-BRAF(V600E) specific antibody enabled on-chip evaluation of BRAF(V600E) mutation status in melanoma cells. We believe that the ability of nanoshearing-based capture to enumerate melanoma cells and subsequent on-chip characterisation has the potential as a rapid screening tool while making treatment decisions. More... »

PAGES

19709

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1038/srep19709

DOI

http://dx.doi.org/10.1038/srep19709

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1019399413

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26815318


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