Biospectroscopy insights into the multi-stage process of cervical cancer development: probing for spectral biomarkers in cytology to distinguish grades

Abstract

Cervical cancer screening programmes have greatly reduced the burden associated with this disease. However, conventional cervical cytology screening still lacks sensitivity and specificity. There is an urgent need for the development of a low-cost robust screening technique. By generating a spectral "biochemical-cell fingerprint", Fourier-transform infrared (FTIR) spectroscopy has been touted as a tool capable of segregating grades of dysplasia. A total of 529 specimens were collected over a period of one year at two colposcopy centres in Dublin, Ireland. Of these, n = 128 were conventionally classed as high-grade, n = 186 as low-grade and n = 215 as normal. Following FTIR spectroscopy, derived spectra were examined for segregation between classes in scores plots generated with subsequent multivariate analysis. A degree of crossover between classes was noted and this could be associated with imperfect conventional screening resulting in an inaccurate diagnosis or an incomplete transition between classes. Maximal crossover associated with n = 102 of 390 specimens analyzed was found between normal and low-grade specimens. However, robust spectral differences (P≤ 0.0001) were still observed at 1512 cm(-1), 1331 cm(-1) and 937 cm(-1). For high-grade vs. low-grade specimens, spectral differences (P≤ 0.0001) were observed at Amide I (1624 cm(-1)), Amide II (1551 cm(-1)) and asymmetric phosphate stretching vibrations (νasPO2(-); 1215 cm(-1)). Least crossover (n = 50 of 343 specimens analyzed) was seen when comparing high-grade vs. normal specimens; significant inter-class spectral differences (P≤ 0.0001) were noted at Amide II (1547 cm(-1)), 1400 cm(-1) and 995 cm(-1). Deeper understanding of the underlying changes in the transition between cervical cytology classes (normal vs. low-grade vs. high-grade) is required in order to develop biospectroscopy tools as a screening approach. This will then allow for the development of blind classification algorithms.

Histology Verification Demonstrates That Biospectroscopy Analysis of Cervical Cytology Identifies Underlying Disease More Accurately than Conventional Screening: Removing the Confounder of Discordance

“…While earlier biospectroscopy studies were challenged on grounds that the segregation between cytological categories could be due to contaminated samples, more recent studies using LBC have resolved this issue [18], [20], [26]–[29]. Large-scale studies of IR spectroscopy have emerged in recent years and shown promise for this technique to be used as a screening or diagnostic tool for cervical cancer [19], [29], [30].…”

“…Large-scale studies of IR spectroscopy have emerged in recent years and shown promise for this technique to be used as a screening or diagnostic tool for cervical cancer [19], [29], [30]. However, significant overlap between various cytology categories had been observed suggesting a lower accuracy for IR spectroscopy [29], [31]. This has led to the conclusion that biospectroscopy-based categorisation of cervical cytology is apparently flawed in its ability to detect atypia or underlying disease.…”

An imaging dataset of cervical cells using scanning near-field optical microscopy coupled to an infrared free electron laser

“…During our experiment, the IR-FEL at ALICE was tuneable over the range of 5.5 to 8.8 μm (~1,818 cm −1 to ~1,136 cm −1 ), which includes a number of biologically important biomarkers 11 at designated wavenumbers or wavelengths within the ‘fingerprint’ region (1,800–900 cm −1 ). Previous work has shown that ATR-FTIR spectroscopy is able to diagnose underlying cervical disease and segregate grades of cervical dyskaryosis more precisely than conventional cytology based upon changes within the ‘fingerprint’ region 12,13 . We selected four wavenumbers/wavelengths from this region to explore with SNOM-IR-FEL (Table 1).…”

Classification of cervical cytology for human papilloma virus (HPV) infection using biospectroscopy and variable selection techniques

“…2 More than 200 genotypes have been identied and associated with benign (low-risk, lrHPV) or malignant (high-risk, hrHPV) cutaneous or mucosal lesions. The hrHPV subtypes 16,18,31,33, and 51 have been recovered from more than 95% of cervical cancers. 3 Studies aimed at describing the distribution of HPV types in invasive cervical cancer strongly implicate subtypes 16 and 18 in approximately 70% of all cervical cancers.…”