Institute of Polymers, Composites and Biomaterials, National Research Council of Italy, via Campi Flegrei, 34, Olivetti Buildings, 80078 Pozzuoli, NA, Italy.
Institute of Biosciences and Bio Resources, National Research Council of Italy, via P. Castellino 111, 80131 Naples, NA, Italy.
Spectrochim Acta A Mol Biomol Spectrosc. 2017 Feb 15;173:476-488. doi: 10.1016/j.saa.2016.09.034. Epub 2016 Sep 20.
Hyperspectral Raman images of human prostatic cells have been collected and analysed with several approaches to reveal differences among normal and tumor cell lines. The objective of the study was to test the potential of different chemometric methods in providing diagnostic responses. We focused our analysis on the ν(CH) region (2800-3100cm) owing to its optimal Signal-to-Noise ratio and because the main differences between the spectra of the two cell lines were observed in this frequency range. Multivariate analysis identified two principal components, which were positively recognized as due to the protein and the lipid fractions, respectively. The tumor cells exhibited a modified distribution of the cytoplasmatic lipid fraction (mainly localized alongside the cell boundary) which may result very useful for a preliminary screening. Principal Component analysis was found to provide high contrast and to be well suited for image-processing purposes. Self-Modelling Curve Resolution made available meaningful spectra and relative-concentration values; it revealed a 97% increase of the lipid fraction in the tumor cell with respect to the control. Finally, a univariate approach confirmed significant and reproducible differences between normal and tumor cells.
已经收集和分析了人类前列腺细胞的高光谱拉曼图像，采用了几种方法来揭示正常细胞系和肿瘤细胞系之间的差异。该研究的目的是测试不同化学计量学方法在提供诊断反应方面的潜力。我们的分析重点集中在 ν(CH)区域（2800-3100cm），因为该区域具有最佳的信噪比，并且在该频率范围内观察到两个细胞系光谱之间的主要差异。多元分析确定了两个主成分，它们分别被积极识别为蛋白质和脂质分数。肿瘤细胞表现出细胞质脂质分数的改变分布（主要位于细胞边界附近），这对于初步筛选可能非常有用。主成分分析被发现提供了高对比度，非常适合图像处理目的。自建模曲线分辨率提供了有意义的光谱和相对浓度值；它显示肿瘤细胞中的脂质分数相对于对照增加了 97%。最后，单变量方法证实了正常细胞和肿瘤细胞之间存在显著且可重复的差异。
