Revealing heterogeneity in cancer cell populations based on high throughput single-cell adhesion on materials Buddhika Gayani, Paul J. Molino, Michael J. Higgins Intelligent Polymer Research Institute, University of Wollongong, Australia Tumour heterogeneity contributes to misleading cancer diagnostics and treatments, and this challenge persists until cancer progresses to the metastatic stage, becoming more difficult to treat. One major reason for this threat is that cell populations comprising rare cell types or sub-populations can be left undetected, be misdiagnosed, or remain unresponsive to anticancer drugs. Currently, potential materials are being studied 1 to address this challenge by exploring new phenotypic biomarkers using cutting-edge analysis tools 2 . In this context, Single-Cell Analysis (SCA) with high throughput offers an advantage as it provides cellular-level information while facilitating data analysis at the population level 3 . Here, we demonstrate the use of cell-material interactions as an alternative or supplement means to understand, distinguish, or detect differences between cell populations. For that, acoustic force spectroscopy (AFS), explored as a new SCA tool with a sufficient throughput, was used to measure the adhesion of cells on materials, followed by feasible analysis and interpretation of the data. First, the adhesion properties of MCF7 breast cancer cells were compared with those of MCF10A normal breast cells, focusing on their interaction with collagen, an extracellular matrix component. Then, the adhesion properties of MCF7 cells were monitored by changing the material surface chemistry functionalized with carboxylated and amino groups. The distributions of adhesion strength and adhesion energy were analyzed using machine learning clustering methods. We distinguished the adhesion differences between cancer and normal cells based on the qualitatively and quantitatively derived data from AFS profiles. We also discovered population-level and subpopulation-level dependencies of cancer cell adhesion properties on the surface chemistry of the materials. Our findings highlight the importance of measuring high-throughput single-cell interactions with materials that exhibit different surface chemistries in designing future diagnostics and treatments for metastatic cancers. This research also offers insights for the integration of advanced materials with cell adhesion-based high-throughput SCA, which could potentially overcome the limitations of existing cancer diagnostics and provide precise predictions of cancer metastasis. References 1. J. Dong, J.-F. Chen, M. Smalley, M. Zhao, Z. Ke, Y. Zhu and H.-R. Tseng, Advanced Materials , 2020, 32 , 1903663. 2. M. S. Manak, J. S. Varsanik, B. J. Hogan, M. J. Whitfield, W. R. Su, N. Joshi, N. Steinke, A. Min, D. Berger, R. J. Saphirstein, G. Dixit, T. Meyyappan, H.-M. Chu, K. B. Knopf, D. M. Albala, G. R. Sant and A. C. Chander, Nat Biomed Eng , 2018, 2 , 761-772. 3. J. Källberg, W. Xiao, D. Van Assche, J.-C. Baret and V. Taly, Lab on a chip , 2022, 22 , 2403-2422.
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