Detecting normal and cancer skin cells via glycosylation and adhesion signatures: A path to enhanced microfluidic phenotyping.

Recruiting circulating cells based on interactions between surface receptors and corresponding ligands holds promise for capturing cells with specific adhesive properties. Our study investigates the adhesion of skin cells to specific lectins, particularly focusing on advancements in lectin-based biosensors with diagnostic potential. We explore whether we can successfully capture normal skin (melanocytes and keratinocytes) and melanoma (WM35, WM115, WM266-4) cells in a low-shear flow environment by coating surfaces with lectins. Specifically, we coated surfaces with Dolichos biflorus (DBA) and Maackia Amurensis (MAL) lectins, which were used to detect and capture specific skin cells from the flow of cell mixture. Alterations in glycan expression (confirmed by fluorescent microscopy) demonstrated that DBA binds predominantly to normal skin cells, while MAL interacts strongly with melanoma cells. Assessing adhesion under static and dynamic low-shear stress conditions (up to 30 mPa) underscores the reliability of DBA and MAL as markers for discriminating specific cell type. Melanocytes and keratinocytes adhere to DBA-coated surfaces, while melanoma cells prefer MAL-coated surfaces. A comprehensive analysis encompassing cell shape, cytoskeleton, and focal adhesions shows the independence of our approach from the inherent characteristics of cells, thus demonstrating its robustness. Our results carry practical implications for lectin-biosensor designs, emphasizing the significance of glycan-based discrimination of pathologically altered cells. Combined with microfluidics, it demonstrates the value of cell adhesion as a discriminant of cancer-related changes, with potential applications spanning diagnostics, therapeutic interventions, and advanced biomedical technologies.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)