Developing New Diagnostic Tools Based on SERS Analysis of Filtered Salivary Samples for Oral Cancer Detection

唾液 癌症 尿酸 拉曼光谱 表面增强拉曼光谱 化学 医学 内科学 拉曼散射 光学 物理
作者
R. Borsa,Valentin Toma,Anca Onaciu,Cristian Moldovan,Radu Mărginean,Diana Cenariu,Gabriela-Fabiola Știufiuc,Cristian-Mihail Dinu,Simion Bran,Horia Opriș,Sergiu Văcăraș,Florin Onișor,Dorin Sentea,Mihaela Băciuț,Cristina Adela Iuga,Rareş Ştiufiuc
出处
期刊:International Journal of Molecular Sciences [Multidisciplinary Digital Publishing Institute]
卷期号:24 (15): 12125-12125 被引量:9
标识
DOI:10.3390/ijms241512125
摘要

Cancer still represents one of the biggest challenges in current medical practice. Among different types of cancer, oral cancer has a huge impact on patients due to its great visibility, which is more likely to create social stigma and increased anxiety. New early diagnose methods are still needed to improve treatment efficiency and patients’ life quality. Raman/SERS (Surface Enhanced Raman Spectroscopy) spectroscopy has a unique and powerful potential for detecting specific molecules that can become priceless biomarkers in different pathologies, such as oral cancer. In this study, a batch of saliva samples obtained from a group of 17 patients with oro-maxillofacial pathologies compared with saliva samples from 18 healthy donors using the aforementioned methods were evaluated. At the same time, opiorphin, potassium thiocyanate and uric acid were evaluated as potential specific biomarkers for oro-maxillofacial pathologies using multivariate analysis. A careful examination of SERS spectra collected on saliva samples showed that the spectra are dominated by the vibrational bands of opiorphin, potassium thiocyanate and uric acid. Given the fact that all these small molecules are found in very small amounts, we filtrated all the samples to get rid of large molecules and to improve our analysis. By using solid plasmonic substrates, we were able to gain information about molecular concentration and geometry of interaction. On the other hand, the multivariate analysis of the salivary spectra contributed to developing a new detection method for oral cancer.
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