High-throughput atomic force microscopy measurements reveal mechanical signatures of cell mixtures for liquid biopsy

Abstract

Due to the pivotal role of circulating tumor cells (CTCs) in cancer metastasis, CTC-based liquid biopsies hold the prospect to revolutionize tumor diagnosis and treatment, but the sensitivity of current CTC detection methods still needs to be substantially improved for clinical deployment. Concurrently, mechanical forces are crucial in regulating cellular physiological and pathological processes, and characterizing the mechanical properties of individual cells is gaining increasing attention to provide complementary information about cells. Atomic force microscopy (AFM) has emerged as a key platform for single-cell force measurements, but its application in constructing the mechanical signatures of CTCs in liquid biopsy specimens has been challenging due to the low throughput. In this work, we leverage the recently developed high-throughput AFM single-cell indentation assay to reveal the distinctive mechanical phenotype of mixed CTCs for liquid biopsy. Using the deep learning model, cells in the optical bright-field images are accurately identified in real time and the identification results are transmitted to the AFM control software, which is programmed to run in a cycle to achieve the autonomous high-throughput AFM single-cell indentation assay of numerous cells. Experiments performed on co-cultured adherent cells distinctly show the multimodal stiffness profiles of mixed cells whose pattern was sensitive to the ratio between the co-cultured cells. Subsequently, combined with microfluidics-based cell sorting, the effectiveness of the proposed method was verified on heterogeneous CTCs isolated from blood samples. This study illustrates a promising method based on high-throughput AFM to reveal the unique mechanical signatures of mixed CTCs for improving the sensitivity of CTC-based liquid biopsies, which will facilitate the practical utility of AFM-based single-cell mechanics with translational significance to advance cancer management.