Walsh Michael J, Singh Maneesh N, Stringfellow Helen F, Pollock Hubert M, Hammiche Azzedine, Grude Olaug, Fullwood Nigel J, Pitt Mark A, Martin-Hirsch Pierre L, Martin Francis L
Biomedical Sciences Unit, Department of Biological Sciences, Lancaster University, Lancaster, U.K.
Biomark Insights. 2008 Mar 25;3:179-189. doi: 10.4137/bmi.s592.
Infrared (IR) absorbance of cellular biomolecules generates a vibrational spectrum, which can be exploited as a "biochemical fingerprint" of a particular cell type. Biomolecules absorb in the mid-IR (2-20 mum) and Fourier-transform infrared (FTIR) microspectroscopy applied to discriminate different cell types (exfoliative cervical cytology collected into buffered fixative solution) was evaluated. This consisted of cervical cytology free of atypia (i.e. normal; n = 60), specimens categorised as containing low-grade changes (i.e. CIN1 or LSIL; n = 60) and a further cohort designated as high-grade (CIN2/3 or HSIL; n = 60). IR spectral analysis was coupled with principal component analysis (PCA), with or without subsequent linear discriminant analysis (LDA), to determine if normal versus low-grade versus high-grade exfoliative cytology could be segregated. With increasing severity of atypia, decreases in absorbance intensity were observable throughout the 1,500 cm(-1) to 1,100 cm(-1) spectral region; this included proteins (1,460 cm(-1)), glycoproteins (1,380 cm(-1)), amide III (1,260 cm(-1)), asymmetric (nu(as)) PO(2) (-) (1,225 cm(-1)) and carbohydrates (1,155 cm(-1)). In contrast, symmetric (nu(s)) PO(2) (-) (1,080 cm(-1)) appeared to have an elevated intensity in high-grade cytology. Inter-category variance was associated with protein and DNA conformational changes whereas glycogen status strongly influenced intra-category. Multivariate data reduction of IR spectra using PCA with LDA maximises inter-category variance whilst reducing the influence of intra-class variation towards an objective approach to class cervical cytology based on a biochemical profile.
细胞生物分子的红外(IR)吸光度会产生振动光谱,该光谱可用作特定细胞类型的“生化指纹”。评估了应用傅里叶变换红外(FTIR)显微光谱法对生物分子在中红外波段(2 - 20微米)的吸收情况进行分析,以区分不同细胞类型(收集到缓冲固定液中的宫颈脱落细胞学样本)。样本包括无异型性的宫颈细胞学样本(即正常样本;n = 60)、分类为含有低度病变的样本(即CIN1或LSIL;n = 60)以及另一组分类为高度病变的样本(CIN2/3或HSIL;n = 60)。IR光谱分析与主成分分析(PCA)相结合,有或没有后续的线性判别分析(LDA),以确定正常、低度和高度宫颈脱落细胞学样本是否可以区分。随着异型性严重程度的增加,在1500厘米⁻¹至1100厘米⁻¹光谱区域可观察到吸光度强度降低;这包括蛋白质(1460厘米⁻¹)、糖蛋白(1380厘米⁻¹)、酰胺III(1260厘米⁻¹)、不对称磷酸根(νas)(1225厘米⁻¹)和碳水化合物(1155厘米⁻¹)。相比之下,对称磷酸根(νs)(1080厘米⁻¹)在高度病变的细胞学样本中强度似乎有所升高。类别间差异与蛋白质和DNA构象变化有关,而糖原状态对类别内差异有强烈影响。使用PCA结合LDA对IR光谱进行多变量数据降维,可最大程度地增加类别间差异,同时减少类别内变化的影响,从而基于生化特征以客观方法对宫颈细胞学进行分类。