%0 Journal Article
%T FTIR Microspectroscopy Coupled with Two-Class Discrimination Segregates Markers Responsible for Inter- and Intra-Category Variance in Exfoliative Cervical Cytology
%A Michael J. Walsh
%A Maneesh N. Singh
%A Helen F. Stringfellow
%A Hubert M. Pollock
%J Biomarker Insights
%D 2008
%I 
%X 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¨C20 ¦Ìm) 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 (¦Ías) PO2   (1,225 cm 1) and carbohydrates (1,155 cm 1). In contrast, symmetric (¦Ís) PO2   (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.
%K biomarker
%K cervical cytology
%K Fourier-transform infrared microspectroscopy
%K high-grade
%K low-grade
%K principal component analysis
%U http://la-press.com/article.php?article_id=646