Integrating Inertial Microfluidics with SERS Bioprobe for Efficient Enrichment and Accurate Identification of Tumor Cells in Gastric Fluid and Ascites

Gastric cancer (GC) is a disease with high mortality rates and remains a central focus in medical research. Efficient enrichment, separation, and precise diagnosis of human gastric cancer (HGC) cells from biological samples are essential for early detection and treatment. However, the similarity in size of white blood cells (WBCs) and HGC cells in gastric fluid has posed vital challenges in the rapid identification and precise diagnosis of GC. To address this issue, a smart system that combines enrichment and detection of HGC cells using inertial microfluidic chips and a label-free surface-enhanced Raman spectroscopy (SERS) bioprobe has been developed. The HGC cells in simulated gastric fluid and ascites are rapidly separated and enriched by a spiral microfluidic chip. Silver bioprobes with excellent SERS performance are prepared to collect the label-free SERS spectra of HGC cells, normal gastric cells, and WBCs. SERS spectral data analysis and model prediction are performed by machine-learning-assisted principal component analysis-linear discriminant analysis (PCA-LDA). The result shows that HGC cells can be well identified with an accuracy as high as 96%. The microfluidic-SERS system proposed in this study can effectively separate and accurately identify tumor cells in body fluids, providing a new method of precision gastric cancer detection.