AgNWs-COF SERS biosensor for oral cancer diagnosis based on exhaled breath and saliva

Over recent years, surface-enhanced Raman spectroscopy (SERS) has shown its unparalleled sensitivity and molecular specificity in biomedical applications. However, noninvasive and sensitive detection of biomarkers with conventional SERS for oral cancer diagnosis remains challenges. For early diagnosis of oral cancer, there are two difficulties in spectral recognition: one involving low-concentration and dynamic biomarkers capturing, and the other is the complex interference in breath and saliva samples. To address these challenges, we developed a plasmonic covalent organic framework (COF) synthetic SERS biosensor to enhance the SERS signal and improve the biomarker adsorption efficiency. This sensing platform integrates the silver nanowire network and the COF-TpPa film with micropores. Both the liquid and gaseous molecules are demonstrated to have excellent SERS performance based on this plasmonic COF substrate without any pretreatment. Taking advantage of the deep learning analysis with the Light Gradient Boosting (LGB) algorithm based on the spliced SERS spectra of gaseous and liquid analytes, the oral cancer identification accuracy reaches to 98 % in the experiment using artificial exhaled methyl mercaptan and salivary uric acid. This work explores SERS application in detecting gas-liquid fluid analytes and noninvasive clinical cancer diagnosis, and may have an important future role in food safety and environmental monitoring.