Investigation of the influence of high-risk human papillomavirus on the biochemical composition of cervical cancer cells using vibrational spectroscopy

Abstract

The main aetiology of cervical cancer is infection with high risk human papillomavirus (HPV). Cervical cancer is almost 100% curable if detected in the early stages. Thus, information about the 10 presence and levels of HPV in patient samples has high clinical value. As current screening methods, such as the Pap smear test, are highly subjective and in many cases show low sensitivity and specificity, new supportive techniques are desirable to improve the quality of cervical cancer screening. In this study, vibrational spectroscopic techniques (Raman and Fourier Transform Infra Red absorption) have been applied to the investigation of four cervical cancer cell lines, HPV 15 negative C33A, HPV-18 positive HeLa with 20-50 integrated HPV copies per cell, HPV-16 positive SiHa with 1-2 integrated HPV strands per cell and HPV-16 positive CaSki containing 60-600 integrated HPV copies per cell. Results show that vibrational spectroscopic techniques can discriminate between the cell lines and elucidate cellular differences originating from proteins, nucleic acids and lipids. Similarities between C33A and SiHa cells were exhibited in the Raman 20 and infrared spectra and were confirmed by Principal Component Analysis (PCA). Analysis of the biochemical composition of the investigated cells, with the aid of PCA showed a clear discrimination between the C33A-SiHa group and HeLa and CaSki cell lines indicating the potential of vibrational spectroscopic techniques as support to current methods for cervical cancer screening. 25 IntroductionCervical cancer is second only to breast cancer as the most common malignancy in women worldwide 1 . The gradual progression of cervical cancer allows the application of screening and diagnostic programmes to detect neoplastic 30 changes before invasive cancer develops. The Papanicolaou test (also called the Pap test, Pap smear, or smear test) is a screening method which allows detection of infections and abnormalities of the cervix. The Pap smear test is the most widespread screening method for cervical neoplasia 2 and is 35 based on visual evaluation of the morphology of cells collected from the cervix under light microscopy. Microscopic examination brings subjectivity to the screening results, therefore, the smear test has a hugely variable sensitivity (17% -99%) and specificity (9% -100%) 3 . 40 The probability of developing cervical dysplasia is much higher for women infected with human papillomavirus (HPV) than those free of infection 4 . Infection with oncogenic or high-risk HPV is the main risk factor for cervical cancer 5 with 99.7% of invasive cervical neoplasia 45 associated with HPV infection 6 . Thus, HPV testing has been added to the range of clinical options for cervical cancer screening. Detection of HPV (HPV testing) is based on detecting the DNA of the virus. It has been found that the DNA of high risk strains of HPV are assimilated within the 50 cellular DNA of the host 7 . A drawback to HPV testing is that it is more expensive and time-consuming than other screening tes...

Correlation of p16INK4A expression and HPV copy number with cellular FTIR spectroscopic signatures of cervical cancer cells

“…Changes in lipid levels are possibly associated with the disruption of the membrane functionality caused by the virus which influences lipid rafts 15 61 . A similar behaviour was noted and reported in our previous study on cervical cancer cell lines, wherein both Raman and FTIR (point mode) techniques were utilised 62 . Moreover, it was reported previously by Wong et al that the degree of disorder of methylene chains in membrane lipids increases in 20 cervical neoplastic cells 63 .…”

“…Understanding and processing the biochemical information delivered by vibrational spectroscopic techniques and its 35 correlation with the existing screening and diagnostic methods is key to further development of realistic applications of Raman and FTIR spectroscopy to cervical cancer detection. It has recently been demonstrated that both Raman and FTIR absorption spectroscopy can effectively discriminate between 40 cell lines with varying HPV infection levels 44 . The current study explores the potential correlation of spectroscopic features with HPV infection levels characteristic of each cell line as well as the resultant expression levels of p 16INK4 biomarker.…”

Spectral pre and post processing for infrared and Raman spectroscopy of biological tissues and cells

“…In such studies, correlation with accepted or "gold standard" assays can be used to guide and validate the interpretation of the vibrational spectroscopic results. As well as standard cytotoxicological assays, the spectroscopic results can be correlated with more precise biomarkers, such as protein over-expression in the case of HPV transfected cells [3,4]. In advancing the applications of biospectroscopy, it is crucial to establish multivariate spectral equivalents of biomarkers which identify the action of for example chemotherapeutic agents or nanotoxicants.…”

“…IR absorption and Raman spectroscopy are very distinct physical processes [2], and therefore the spectral distortions can be of very different physical origin. Although many biomedical applications of the techniques have been targeted towards disease diagnostics, for which high specificity and sensitivity classification algorithms are desirable, more recent applications have been targeted at, for example, disease aetiology [3,4], radiation dosimetry [5], drug screening [6][7][8][9][10] and nanotoxicology [11][12][13], for which a range of other data mining and analysis protocols have been explored [14]. It is important, however, that these protocols are well validated, in order to progress the field with confidence.…”

Multivariate statistical methodologies applied in biomedical Raman spectroscopy: assessing the validity of partial least squares regression using simulated model datasets

“…radiation dose 18 or viral infection 19 . PLSR can be employed to construct predictive models for spectral response as a function of the target variable.…”