SERS plasmonic droplet assay for non-invasive early oral cancer screening using saliva samples

Early and accurate detection of oral cancer is crucial for improving patient outcomes, particularly through non-invasive diagnostic approaches. Saliva is a human biofluid rich in various proteins and metabolites that reflect an individual's health status, making its analysis a non-invasive and effective approach for oral cancer screening. This study demonstrates the feasibility of using a plasmonic SERS droplet assay platform combined with a custom-built portable Raman system for saliva-based oral cancer screening. Unlike conventional SERS-based saliva analysis, in this work, a SERS substrate, designed with regions of contrasting surface wettability, enables the splitting of saliva into sub-microliter droplets, allowing multiplexed analysis with minimal sample volume. This approach addresses key limitations of conventional SERS techniques, including variability in substrate fabrication and low analyte concentrations, by improving both spectral sensitivity and reproducibility. The Raman spectral differences among saliva samples from different classes of oral cancer, such as normal, premalignant, and malignant cases, are analyzed and compared to identify the class-specific variations. Further, integrating the spectroscopic data with a nu-SVC-based ML algorithm demonstrated excellent classification among the groups with a predictive accuracy of over 85 % in distinguishing between normal, premalignant, and malignant samples. The proposed method holds strong potential for use in the early, non-invasive detection of oral cancer in clinical diagnostic settings. • The plasmonic droplet assay enables multiplexed analysis via sub-microliter saliva droplets. • A portable fiber-based Raman system integrated with PDAP for non-invasive cancer screening. • Raman–ML approach classifies normal, premalignant, and malignant samples with >85 % accuracy.