Cell separation coupled with surface-enhanced Raman spectroscopy: A critical review

The integration of cell separation technologies with surface-enhanced Raman spectroscopy (SERS) offers a powerful approach for sensitive molecular diagnostics. This review critically evaluates label-dependent (FACS, MACS) and label-free (DEP, acoustic, magnetic, inertial, DLD) separation methods coupled with SERS detection for cancer diagnosis, pathogen detection, and environmental monitoring. On-chip integration provides continuous operation, reduced sample loss, and real-time monitoring, while off-chip approaches allow independent optimization of separation chemistry and SERS substrates. Hybrid cascaded architectures combining multiple separation mechanisms achieve both high throughput and high specificity. Key challenges include substrate standardization, long-term stability, and limited clinical validation on large cohorts. Machine learning integration and portable Raman spectrometers are accelerating translation to point-of-care settings. This review provides a roadmap for developing robust, reproducible, and clinically deployable SERS-based diagnostic platforms.