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...

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SummaryThis chapter outlines some developments in the applications of vibrational spectroscopy for disease diagnostics and demonstrates how the applications of the spectroscopic techniques can be extended to the analysis and evaluation of disease aetiology and the mechanisms of interaction with and the cellular and subcellular responses to, for example, chemotherapeutic agents and nanoparticles. The primary emphasis is on Raman spectroscopy, although some examples are based on infrared absorption spectroscopy. The studies presented are chosen to illustrate how a range of multivariate analytical techniques can be employed to maximize the potential benefits of the complex spectral information obtained from tissue or cells.

Vibrational spectroscopy (Raman and FTIR microspectroscopy) is an attractive modality for the analysis of biological samples since it provides a complete noninvasive acquisition of the biochemical fingerprint of the sample. Studies in our laboratory have applied vibrational spectroscopy to the analysis of biological function in response to external agents (chemotherapeutic drugs, ionising radiation, nanoparticles), together with studies of the pathology of tissue (skin and cervix) in health and disease. Genetic algorithms have been used to optimize spectral treatments in tandem with the analysis of the data (using generalized regression neural networks (GRNN), artificial neural networks (ANN), partial least squares modelling (PLS), and support vector machines (SVM)), to optimize the complete analytical scheme and maximize the predictive capacity of the spectroscopic data. In addition we utilise variable selection techniques to focus on spectral features that provide maximal classification or regression of the spectroscopic data against analytical targets. This approach has yielded interesting insights into the variation of biochemical features of the biological system with its state, and has also provided the means to develop further the analytical and predictive capabilities of vibrational spectroscopy in biological analysis.