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

Abstract

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 μm) 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 (νas) PO2− (1,225 cm−1) and carbohydrates (1,155 cm−1). In contrast, symmetric (νs) 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.

Multivariate Analysis for Fourier Transform Infrared Spectra of Complex Biological Systems and Processes

“…In this view, the advantage of LDA is that it makes it possible to reveal clusters, identifying objectively also the most contributory wavenumbers responsible for spectra discrimination [21,58]. In particular, the application of PCA-LDA to spectroscopic investigation of complex biological systems proved to be a useful tool for the identification of spectral biomarkers of the process under investigation [7,35,69,70,71].…”

“…Indeed, a limit of using PCA alone is that it does not allow to obtain an unambiguous grouping of the data into clusters, requiring therefore the application of another analysis step able to reduce the intra-category variation while maximizing that inter-category [69]. The coupling, for instance, of PCA with LDA is a well established procedure which enables not only to classify the observations into groups but to quantify the importance of the single variables for this group separation.…”

“…Furthermore, in the work of Walsh and colleagues [69], ATR microspectroscopy has been successfully applied to the characterization of samples of exfoliative cervical cytology of different categories, with increasing severity of atypia. The spectral analysis was supported by PCA, with or without subsequent LDA, to verify if it was possible to discriminate among normal, low grade and high grade of exfoliative cytology.…”

Infrared spectroscopic imaging detects chemical modifications in liver fibrosis due to diabetes and disease

“…3(A)). The high degree of intra-class variance demonstrated in the hepatocytes may be a source of concern as it can mask important spectral variance for disease typing in a similar fashion to what was found in early work using IR spectroscopy of exfoliative cervical cytology [14]. The source of this intra-class variance will most likely be due to two sources; accumulation of glycogen [15] in the liver as part of glucose homeostasis (which may be affected by diabetes) and contribution from clear cell inclusions as part of liver disease.…”

Towards Chemical Mapping at Sub-Micron Resolution: Near-Field Spectroscopic Delineation of Interphase Boundaries

“…In a study of exfoliative cervical cytology [15], it was found that biomarkers of progression from normal to lowgrade, high-grade and severe dyskaryosis included the degree of protein phosphorylation at a wavenumber of 970 cm -1 , glycogen at 1030 cm -1 , and shifts in the centroid of the amide I peak at around 1650 cm -1 , indicating changes in the secondary structure of intracellular proteins. Cancer of the prostate gland, which is composed of a number of different zones (peripheral, transitional, and central), has also been studied using microspectroscopy [12].…”