Giamougiannis Panagiotis, Morais Camilo L M, Grabowska Rita, Ashton Katherine M, Wood Nicholas J, Martin-Hirsch Pierre L, Martin Francis L
Department of Obstetrics and Gynaecology, Lancashire Teaching Hospitals NHS Foundation Trust, Preston, PR2 9HT, UK.
School of Pharmacy and Biomedical Sciences, University of Central Lancashire, Preston, PR1 2HE, UK.
Anal Bioanal Chem. 2021 Jan;413(3):911-922. doi: 10.1007/s00216-020-03045-1. Epub 2020 Nov 26.
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 (phenylalanine), 1334 cm (CHCH wagging vibration), 1448 cm (CH deformation) and 1657 cm (Amide I) exhibited high statistical significance for class differentiation (P < 0.001). The efficacy of vibrational spectroscopy, in particular Raman spectroscopy, combined with ascitic fluid analysis, suggests a potential diagnostic method for ovarian cancer. Raman microspectroscopy analysis of ascitic fluid allows for discrimination of patients with benign gynaecological conditions or ovarian cancer.
目前正在评估生物流体，如血浆或血清，用于通过振动光谱法检测癌症。这些流体包含关键生物分子的信息，如蛋白质、脂质、碳水化合物和核酸，它们构成了区分样本的光谱化学模式。拉曼光谱是一种无水且几乎无损的振动光谱技术，能够在最少或无需样品制备的情况下记录生物流体的光谱化学指纹。在此，我们使用拉曼显微光谱法比较了这两种常见生物流体（血浆和血清）以及腹水在检测卵巢癌方面的性能。通过不同的光谱预处理和判别分析技术，对38例患者的样本进行了分析（n = 18例卵巢癌患者，n = 20例良性对照）。在无监督和有监督的判别方法中，腹水提供了最佳的类别分离，其分类准确率、敏感性和特异性均高于80%，而血浆或血清的相应指标为60 - 73%。腹水似乎富含负责区分卵巢癌样本的胶原蛋白信息，其中在1004 cm（苯丙氨酸）、1334 cm（CHCH摇摆振动）、1448 cm（CH变形）和1657 cm（酰胺I）处的胶原蛋白信号带在类别区分上具有高度统计学意义（P < 0.001）。振动光谱法，特别是拉曼光谱法与腹水分析相结合的有效性，表明了一种潜在的卵巢癌诊断方法。对腹水进行拉曼显微光谱分析可以区分患有良性妇科疾病或卵巢癌的患者。
