FTIR Microspectroscopy Coupled with Two-Class Discrimination Segregates Markers Responsible for Inter- and Intra-Category Variance in Exfoliative Cervical Cytology

• Published in: Biomarker insights Vol. 3; pp. 179 - 189
• Main Authors: 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
• Format: Journal Article
• Language: English
• Published: United States Libertas Academica 25-03-2008; SAGE Publishing
• Subjects: biomarker; cervical cytology; Fourier-transform infrared microspectroscopy; high-grade; low-grade; Original Research; principal component analysis
• ISSN: 1177-2719; 1177-2719

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.