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In last decades infrared spectroscopy has demonstrated potential as a novel technology for early cancer diagnosis. Among the various IR spectroscopic techniques special interest has arisen from methods based on evanescent wave absorbance due to the possibility for in situand in vivoimplementation. The goal of the present study is to examine the potential of Attenuated Total Reflectance (ATR) spectroscopy for early detection of premalignant changes. As a model we used both cell lines and primary cells, which were transformed to be malignant by a retrovirus. Spectral measurements were performed at various post infection stages in parallel with morphological observations. Our results showed gradual and consistent spectral alterations in both cell cultures due to carcinogenesis, which were outlined using Principal Component Analysis (PCA). The main spectral differences appeared in three spectral ranges: at 3000–2800 cm−1(attributed to stretching vibrational modes of lipids and proteins), at 1470–1300 cm−1(attributed to bending overlapping modes of lipids and proteins) and also at the highly overlapping spectral range at 1000–1200 cm−1(attributed to bending and starching vibrational modes corresponding to all types of biological macromolecules). In order to obtain robust unsupervised classifications of the malignant progression we applied approaches of Linear Discriminant Analysis (LDA). The classifications based on Mahalanobis distances allowed us to discern that the accuracy of successful identification of premalignant stages varied between 86.5–97.2%. Our results show that ATR spectroscopy in tandem with proper statistical tools may provide a promising technique for early detectable signals of malignant progression. [ABSTRACT FROM AUTHOR]

Purpose: Colon cancer is a major public health problem due to its high disease rate and death toll worldwide. The use of FTIR microscopy in the field of cancer diagnosis has become attractive over the past 20 years. In the present study, the authors investigated the potential of FTIR microscopy to define spectral changes among normal, polyp, and cancer human colonic biopsied tissues. Methods: A large database of FTIR microscopic spectra was compiled from 230 human colonic biopsies. The database was divided into five subgroups: Normal, cancerous tissues, and three stages of benign colonic polyps, namely, mild, moderate, and severe polyps, which are precursors of carcinoma. All biopsied tissue sections were classified concurrently by an expert pathologist. The authors applied the principal components analysis (PCA) model to reduce the dimension of the original data size to 13 principal components. Results: While PCA analysis shows only partial success in distinguishing among cancer, polyp, and the normal tissues, multivariate analysis (e.g., LDA) shows a promising distinction even within the polyp subgroups. Conclusions: Good classification accuracy among normal, polyp, and cancer groups was achieved with a success rate of approximately 85%. These results strongly support the potential of developing FTIR microscopy as a simple, reagent-free tool for early detection of colon cancer and, in particular, for discriminating among the benign premalignant colonic polyps having increasing degrees of dysplasia severity (mild, moderate, and severe). [ABSTRACT FROM AUTHOR]

Light-induced fluorescence (LIF) spectroscopy has demonstrated ability as a novel, noninvasive and sensitive technology for early detection of cancer. The goal of the present study is to examine the potential of this spectroscopic method for early detection and characterization of premalignant changes. As a model we used both cell lines and primary cells, which were transformed to malignant by retrovirus. Fluorescence measurements and morphological observations of the infected cells were performed at various postinfection times. Our results showed gradual attenuation of fluorescence intensities due to cancer progression which corresponds to aromatic amino acids and nicotinamide adenine dinucleotide (NADH) molecules. In order to obtain grading and supervised classifications of the spectral premalignant changes we used approaches of linear discriminant analysis. The classifications based on Mahalanobis distances allowed us to demonstrate that the accuracy of identification of premalignant stages varied between 83.1% and 96.4%. In summary, we conclude that LIF in tandem with proper statistical tools may be a promising technique for early detection of malignant progression. [ABSTRACT FROM AUTHOR]