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| Main Authors: | , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2026
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.00467 |
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| _version_ | 1866912994730967040 |
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| author | Zhang, Yuhao Zhao, Luyao Huang, Zhengfu Song, Kenan Wang, Xianqiao Chen, Xianyan Xie, Jin Zhao, Yiping Li, He Mao, Leidong Teng, Yong Liu, Yang |
| author_facet | Zhang, Yuhao Zhao, Luyao Huang, Zhengfu Song, Kenan Wang, Xianqiao Chen, Xianyan Xie, Jin Zhao, Yiping Li, He Mao, Leidong Teng, Yong Liu, Yang |
| contents | Cell stiffness is a key determinant of how cells deform, migrate, and adapt to mechanically restrictive environments, yet existing single-cell stiffness assays remain difficult to combine with molecular analysis and downstream functional studies. To address these limitations, we introduce a microfluidic platform, stiffness-based ferrohydrodynamic cell sorting (Stiff-FCS), designed for high-throughput quantification of single-cell stiffness, on-chip molecular analysis, and post-assay cell recovery. Stiff-FCS combines ferrofluid-driven actuation with graded confinement channels to control cell movement, induce deformation, and spatially separate cells based on stiffness. An inverse computational model converts cell position and morphology into quantitative Young's modulus values. We demonstrate stiffness profiling of hundreds to thousands of cells per chip within minutes, same-cell fluorescence-based protein analysis, and recovery of stiffness-defined cells for downstream assays. Across diverse human and mouse cell lines, Lamin A/C showed the most consistent association with stiffness, whereas softer cells exhibited greater migratory capacity than stiffer cells. In a series of human head and neck cancer cell models, Stiff-FCS further resolved a stiff, less migratory subpopulation enriched in a higher-molecular-weight Vimentin state, offering a workflow for linking single-cell stiffness to molecular heterogeneity and cell behavior. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_00467 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Stiff-FCS: Single-Cell Stiffness Profiling With Integrated Molecular and Functional Analysis Zhang, Yuhao Zhao, Luyao Huang, Zhengfu Song, Kenan Wang, Xianqiao Chen, Xianyan Xie, Jin Zhao, Yiping Li, He Mao, Leidong Teng, Yong Liu, Yang Cell Behavior Cell stiffness is a key determinant of how cells deform, migrate, and adapt to mechanically restrictive environments, yet existing single-cell stiffness assays remain difficult to combine with molecular analysis and downstream functional studies. To address these limitations, we introduce a microfluidic platform, stiffness-based ferrohydrodynamic cell sorting (Stiff-FCS), designed for high-throughput quantification of single-cell stiffness, on-chip molecular analysis, and post-assay cell recovery. Stiff-FCS combines ferrofluid-driven actuation with graded confinement channels to control cell movement, induce deformation, and spatially separate cells based on stiffness. An inverse computational model converts cell position and morphology into quantitative Young's modulus values. We demonstrate stiffness profiling of hundreds to thousands of cells per chip within minutes, same-cell fluorescence-based protein analysis, and recovery of stiffness-defined cells for downstream assays. Across diverse human and mouse cell lines, Lamin A/C showed the most consistent association with stiffness, whereas softer cells exhibited greater migratory capacity than stiffer cells. In a series of human head and neck cancer cell models, Stiff-FCS further resolved a stiff, less migratory subpopulation enriched in a higher-molecular-weight Vimentin state, offering a workflow for linking single-cell stiffness to molecular heterogeneity and cell behavior. |
| title | Stiff-FCS: Single-Cell Stiffness Profiling With Integrated Molecular and Functional Analysis |
| topic | Cell Behavior |
| url | https://arxiv.org/abs/2604.00467 |