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振动生物光谱学与多元分析相结合,从卵巢癌患者的血浆/血清中提取潜在的诊断特征。

Vibrational biospectroscopy coupled with multivariate analysis extracts potentially diagnostic features in blood plasma/serum of ovarian cancer patients.

机构信息

Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, LA1 4YQ, UK; Department of Obstetrics and Gynaecology, Central Lancashire Teaching Hospitals, Preston, UK.

出版信息

J Biophotonics. 2014 Apr;7(3-4):200-9. doi: 10.1002/jbio.201300157. Epub 2013 Nov 20.

Abstract

Despite numerous advances in "omics" research, early detection of ovarian cancer still remains a challenge. The aim of this study was to determine whether attenuated total reflection Fourier-transform infrared (ATR-FTIR) or Raman spectroscopy could characterise alterations in the biomolecular signatures of human blood plasma/serum obtained from ovarian cancer patients compared to non-cancer controls. Blood samples isolated from ovarian cancer patients (n = 30) and healthy controls (n = 30) were analysed using ATR-FTIR spectroscopy. For comparison, a smaller cohort of samples (n = 8) were analysed using an InVia Renishaw Raman spectrometer. Resultant spectra were pre-processed prior to being inputted into principal component analysis (PCA) and linear discriminant analysis (LDA). Statistically significant differences (P < 0.001) were observed between spectra of ovarian cancer versus control subjects for both biospectroscopy methods. Using a support vector machine classifier for Raman spectra of blood plasma, a diagnostic accuracy of 74% was achieved, while the same classifier showed 93.3% accuracy for IR spectra of blood plasma. These observations suggest that a biospectroscopy approach could be applied to identify spectral alterations associated with the presence of insidious ovarian cancer.

摘要

尽管“组学”研究取得了众多进展,但卵巢癌的早期检测仍然是一个挑战。本研究旨在确定衰减全反射傅里叶变换红外(ATR-FTIR)或拉曼光谱是否可以表征从卵巢癌患者与非癌症对照中获得的人血浆/血清的生物分子特征的改变。使用 ATR-FTIR 光谱分析从卵巢癌患者(n = 30)和健康对照(n = 30)中分离的血液样本。为了比较,使用 InVia Renishaw 拉曼光谱仪分析了较小的样本队列(n = 8)。对所得光谱进行预处理,然后输入主成分分析(PCA)和线性判别分析(LDA)。两种生物光谱方法均观察到卵巢癌与对照之间的光谱存在统计学显著差异(P < 0.001)。使用用于血浆拉曼光谱的支持向量机分类器,实现了 74%的诊断准确性,而对于血浆 IR 光谱,同一分类器显示出 93.3%的准确性。这些观察结果表明,生物光谱方法可用于识别与隐匿性卵巢癌存在相关的光谱改变。

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