Abstract

Previous on-chip technologies for characterizing the cellular mechanical properties often suffer from a low throughput and limited sensitivity. Herein, an inertial multi-force deformability cytometry (IMFDC) is developed for high-throughput, high-accuracy, and high-applicability tumor cell mechanotyping. Three different deformations, including shear deformations and stretch deformations under different forces, are integrated with the IMFDC. The 3D inertial focusing of cells enables the cells to deform by an identical fluid flow, and 10 parameters, such as cell area, perimeter, deformability, roundness, and rectangle deformability, are obtained in three deformations. The IMFDC is able to evaluate the deformability of different cells that are sensitive to different forces on a single chip, demonstrating the high applicability of the IMFDC in analyzing different cell lines. In identifying cell types, the three deformations exhibit different mechanical responses to cells with different sizes and deformability. A discrimination accuracy of ≈93% for both MDA-MB-231 and MCF-10A cells and a throughput of ≈500cellss-1 can be achieved using the multiple-parameters-based machine learning model. Finally, the mechanical properties of metastatic tumor cells in pleural and peritoneal effusions are characterized, enabling the practical application of the IMFDC in clinical cancer diagnosis.

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