A comparative analysis of different biofluids towards ovarian cancer diagnosis using Raman microspectroscopy
| Autor: | Nicholas J Wood, Francis Martin, Rita Oliwia Grabowska, Pierre L. Martin-Hirsch, Panagiotis Giamougiannis, Camilo L. M. Morais, Katherine M. Ashton |
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| Rok vydání: | 2020 |
| Předmět: |
Adult
Serum Support Vector Machine Diagnostic methods Infrared spectroscopy Spectrum Analysis Raman Sensitivity and Specificity 01 natural sciences Biochemistry Liquid biopsies Analytical Chemistry Plasma 03 medical and health sciences symbols.namesake Ovarian cancer Biofluids Blood plasma medicine Ascitic Fluid Humans Sample preparation Spectroscopy F180 Aged 030304 developmental biology Ovarian Neoplasms Principal Component Analysis 0303 health sciences Chromatography Chemistry 010401 analytical chemistry Discriminant Analysis Middle Aged medicine.disease 0104 chemical sciences Raman microspectroscopy Case-Control Studies Raman spectroscopy symbols Female Algorithms Research Paper |
| Zdroj: | Analytical and Bioanalytical Chemistry |
| ISSN: | 1618-2650 1618-2642 |
| DOI: | 10.1007/s00216-020-03045-1 |
| Popis: | Biofluids, such as blood plasma or serum, are currently being evaluated for cancer detection using vibrational spectroscopy. These fluids contain information of key biomolecules, such as proteins, lipids, carbohydrates and nucleic acids, that comprise spectrochemical patterns to differentiate samples. Raman is a water-free and practically non-destructive vibrational spectroscopy technique, capable of recording spectrochemical fingerprints of biofluids with minimum or no sample preparation. Herein, we compare the performance of these two common biofluids (blood plasma and serum) together with ascitic fluid, towards ovarian cancer detection using Raman microspectroscopy. Samples from thirty-eight patients were analysed (n = 18 ovarian cancer patients, n = 20 benign controls) through different spectral pre-processing and discriminant analysis techniques. Ascitic fluid provided the best class separation in both unsupervised and supervised discrimination approaches, where classification accuracies, sensitivities and specificities above 80% were obtained, in comparison to 60–73% with plasma or serum. Ascitic fluid appears to be rich in collagen information responsible for distinguishing ovarian cancer samples, where collagen-signalling bands at 1004 cm−1 (phenylalanine), 1334 cm−1 (CH3CH2 wagging vibration), 1448 cm−1 (CH2 deformation) and 1657 cm−1 (Amide I) exhibited high statistical significance for class differentiation (P Graphical abstract |
| Databáze: | OpenAIRE |
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