High-Accuracy Renal Cell Carcinoma Discrimination through Label-Free SERS of Blood Serum and Multivariate Analysis
نویسندگان
چکیده
Renal cell carcinoma (RCC) represents the sixth most frequently diagnosed cancer in men and is asymptomatic, being detected mostly incidentally. The apparition of symptoms correlates with advanced disease, aggressive histology, poor outcomes. development Surface-Enhanced Raman Scattering (SERS) technique opened way for investigating detecting small molecules, especially biological liquids such as serum or blood plasma, urine, saliva, tears, was proposed a simple diagnosis various diseases, including cancer. In this study, we investigated use label-free SERS combined two multivariate analysis tests: Principal Component Analysis Linear Discriminate (PCA-LDA) Supported Vector Machine (SVM) discrimination 50 RCC patients from 45 apparently healthy donors. case LDA-PCA, obtained accuracy 100% using 12 principal components quadratic function. between stages 88%. SVM approach, training 100%, validation 92% controls, an 81% stages. We also performed standard statistical tests aimed at improving assignment vibration bands, which, according to our data, are mainly due purinic metabolites (uric acid hypoxanthine). Moreover, results these assignments Student’s t-test suggest that main differences spectra increase uric concentration (a conclusion agreement recent literature), while hypoxanthine not statistically different groups. Our demonstrate chemometrics holds great promise non-invasive early detection RCC. However, more studies needed validate when other urological diseases.
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ژورنال
عنوان ژورنال: Biosensors
سال: 2023
ISSN: ['0265-928X', '1873-4219']
DOI: https://doi.org/10.3390/bios13080813