Time-dependent cell adhesion to lectin-coated surfaces as a predictor of flow-based separation efficiency.

Cell surface glycosylation patterns are dynamically altered in malignancy and can serve as cancer detection and sorting biomarkers. Lectins, which bind specific glycan motifs, offer a label-free approach to distinguish between normal and cancerous cells. However, practical application of lectin-based capture under flow conditions requires a mechanistic understanding of how adhesion evolves with time. This study investigates whether time-dependent cell adhesion, as measured by Single-Cell Force Spectroscopy (SCFS), can predict the efficiency of lectin-mediated cell capture under flow in a microfluidic system. Pancreatic cancer cells (PANC-1) and their non-malignant counterparts (hTERT-HPNE) were tested for adhesion to surfaces functionalized with MAL and PHA-E lectins. SCFS was used to quantify adhesion forces at defined contact times (0.1-5 s). Fluorescent microscopy assessed lectin binding, while parallel microfluidic assays measured cell capture across varying flow rates. Effective contact times were mathematically estimated based on channel geometry and flow velocity. Lectin binding was cell-type specific: PANC-1 cells adhered firmly to MAL, while hTERT-HPNE cells preferentially interacted with PHA-E. SCFS revealed that adhesion strength and the number of binding events increased with contact time, plateauing around 1.5-3 s. These time-dependent adhesion profiles closely matched cell retention under flow, with effective capture occurring only when contact time exceeded a critical threshold. Flow rates exceeding 1000 μL/h reduced contact time below this threshold, abolishing adhesion. The study demonstrates that SCFS-derived adhesion kinetics accurately predict flow-based capture efficiency in lectin-coated microchannels. These findings establish a quantitative framework for tuning flow conditions to maximize selectivity in glycan-mediated cell separation. This integrative approach offers new opportunities for biophysics-informed diagnostics and label-free microfluidic enrichment of cancer cells.