Abstract
Liquid biopsies are expected to advance cancer management, and particularly physical cues are gaining attention for indicating tumorigenesis and metastasis. Atomic force microscopy (AFM) has become a standard and important tool for detecting the mechanical properties of single living cells, but studies of developing AFM-based methods to efficiently measure the mechanical properties of circulating tumor cells (CTCs) in liquid biopsy for clinical utility are still scarce. Herein, we present a proof-of-concept study based on the complementary combination of AFM and microfluidics, which allows label-free sorting of individual CTCs and subsequent automated AFM measurements of the mechanical properties of CTCs. With the use of a microfluidic system containing contraction-expansion microchannels, specific cancer cell types were separated and harvested in a marker-independent manner. Subsequently, automated AFM indentation and force spectroscopy experiments were performed on the enriched cells under the precise guidance of the label-free identification of cells using a deep learning optical image recognition model. The effectiveness of the presented method was verified on three experimental sample systems, including mixed microspheres with different sizes, a mixture of different types of cancer cells, and a mixture of cancer cells and blood cells. The study illustrates a feasible framework based on the integration of AFM and microfluidics for non-destructive and efficient nanomechanical phenotyping of CTCs in bodily fluids, which offers additional possibilities for the clinical applications of AFM-based nanomechanical analysis and will also benefit the field of mechanobiology as well as cancer liquid biopsy.
Published Version
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