Cell Spreading-Enhanced Electron-Transfer Electrochemical Cytosensor Enabling Single-Cell Detection

Achieving single-cell detection with electrochemical cytosensors remains challenging, owing to a poor understanding of how electroactive redox probes generate measurable signals near large, insulating cells. Here, we validate a cell–electrode interfacial electron-transfer effect, in situ visualizing that the measurable current signal originating from redox probes located at the cell–electrode adjacent interface, rather than from those distributed on the cell surface. Notably, cell spreading enlarges this cell-adjacent interface, thereby enabling effective current amplification. Guided by this effect, we design an integrated cytosensor platform that combines a highly conductive lamellar reduced graphene oxide (RGO)/Ti3C2Tx electrode chip, which facilitates lamellipodia-driven cell spreading, with a high peroxidase-activity FeCN single-atom nanozyme. This platform exhibits a 7.6-fold signal enhancement over conventional chips and a detection limit of 0.03 cells mL−1, allowing a resolvable current response from a single cell on the 2 cm2 large-sized chip. Furthermore, it demonstrates potential feasibility for clinical detection of circulating tumor cells, achieving 96% specificity and 87% sensitivity across 55 blood samples in distinguishing cancer patients from healthy controls. This work establishes a cell spreading-enhanced electron-transfer paradigm and advances electrochemical cytosensing toward high-performance liquid biopsy applications. Electrochemical cytosensors have emerged as powerful tools for single-cell analysis, but generating robust signals from individual cells remains a major challenge. The authors uncover a cell-electrode interfacial electron-transfer effect, in which only redox probes at the cell-electrode interface contribute to measurable currents. Exploiting this mechanism, they develop a cell spreading-enhanced electron-transfer (SEET) cytosensor and apply it to circulating tumor cell detection in 55 patient samples, achieving 96% specificity and 87% sensitivity.