Raman spectroscopy can provide a molecular-level fingerprint of the biochemical composition and structure of cells with excellent spatial resolution and could be useful to monitor changes in composition for dysplasia and early, non-invasive cancer diagnosis (carcinoma in situ), both ex-vivo and in vivo. In this study, we demonstrate this potential by collecting Raman spectra of the nucleoli, nuclei and cytoplasm from oral epithelial cancer (SCC-4) and dysplastic (pre-cancerous, DOK) cell lines and from normal oral epithelial primary cell cultures, in vitro, which were then analysed by principal component analysis (PCA) as a multivariate statistical method to discriminate the spectra. Results show significant discrimination between cancer and normal cell lines. Furthermore, the dysplastic and cancer cell lines could be discriminated based on the spectral profiles of the cytoplasmic regions. The principal component loading plot, which elucidates the biochemical features responsible for the discrimination, showed significant contributions of nucleic acid and proteins for nucleolar and nuclear sites and variation in features of lipids for the cytoplasmic area. This technique may provide a rapid screening method and have potential use in the diagnosis of dysplasia and early, non-invasive oral cancer, the treatment of which involves much less extensive and complex surgery and a reduction in associated co-morbidity for the patient.
Raman spectroscopy can provide a molecular-level fingerprint of the biochemical
Raman spectroscopy can provide a molecular-level signature of the biochemical composition and structure of cells with submicrometer spatial resolution and could be useful to monitor changes in composition for early stage and non-invasive cancer diagnosis, both ex-vivo and in vivo. In particular, the fingerprint spectral region (400-1800cm) has been shown to be very promising for optical biopsy purposes. However, limitations for discrimination of dysplastic and inflammatory processes based on the fingerprint region have been demonstrated. In addition, the Raman spectral signal of dysplastic cells is one important source of misdiagnosis of normal versus pathological tissues. The high wavenumber region (2800-3600cm) provides more specific information based on NH, OH and CH vibrations and can be used to identify the subtle changes which could be important for discrimination of samples. In this study, we demonstrate the potential of the high-wavenumber spectral region in this context by collecting Raman spectra of nucleolus, nucleus and cytoplasm from oral epithelial cancer (SCC-4) and dysplastic (DOK) cell lines and from normal oral epithelial primary cells, in vitro, in water immersion, which were then analyzed by principal components analysis as a method to discriminate the spectra. Analysis was performed before and after digital subtraction of the bulk water signal. In the normal cell line, the three subcellular regions are well differentiated before water subtraction, although the discrimination of the two nuclear regions is less well defined after water subtraction. Comparing the respective subcellular regions of the three cell lines, before water subtraction, the cell lines can be discriminated using sequential PCA and Feature Discriminant Analysis with up to ~100% sensitivity and 97% specificity for the cytoplasm, which is improved to 100% sensitivity and 99% specificity for the nucleus. The results are discussed in terms of discrimination comparing the CH vibrational modes of nucleic acids, proteins and lipids. The potential role of the OH vibrations, considering free water and confined water, in the discrimination of cell cultures and pathological processes are also discussed.
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