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Novel approaches toward understanding the evolution of disease can lead to the discovery of biomarkers that will enable better management of disease progression and improve prognostic evaluation. Raman spectroscopy is a promising investigative and diagnostic tool that can assist in uncovering the molecular basis of disease and provide objective, quantifiable molecular information for diagnosis and treatment evaluation. This technique probes molecular vibrations/rotations associated with chemical bonds in a sample to obtain information on molecular structure, composition, and intermolecular interactions. Raman scattering occurs when light interacts with a molecular vibration/rotation and a change in polarizability takes place during molecular motion. This results in light being scattered at an optical frequency shifted (up or down) from the incident light. By monitoring the intensity profile of the inelastically scattered light as a function of frequency, the unique spectroscopic fingerprint of a tissue sample is obtained. Since each sample has a unique composition, the spectroscopic profile arising from Raman-active functional groups of nucleic acids, proteins, lipids, and carbohydrates allows for the evaluation, characterization, and discrimination of tissue type. This review provides an overview of the theory of Raman spectroscopy, instrumentation used for measurement, and variation of Raman spectroscopic techniques for clinical applications in cancer, including detection of brain, ovarian, breast, prostate, and pancreatic cancers and circulating tumor cells.
Novel approaches toward understanding the evolution of disease can lead to the discovery of biomarkers that will enable better management of disease progression and improve prognostic evaluation. Raman spectroscopy is a promising investigative and diagnostic tool that can assist in uncovering the molecular basis of disease and provide objective, quantifiable molecular information for diagnosis and treatment evaluation. This technique probes molecular vibrations/rotations associated with chemical bonds in a sample to obtain information on molecular structure, composition, and intermolecular interactions. Raman scattering occurs when light interacts with a molecular vibration/rotation and a change in polarizability takes place during molecular motion. This results in light being scattered at an optical frequency shifted (up or down) from the incident light. By monitoring the intensity profile of the inelastically scattered light as a function of frequency, the unique spectroscopic fingerprint of a tissue sample is obtained. Since each sample has a unique composition, the spectroscopic profile arising from Raman-active functional groups of nucleic acids, proteins, lipids, and carbohydrates allows for the evaluation, characterization, and discrimination of tissue type. This review provides an overview of the theory of Raman spectroscopy, instrumentation used for measurement, and variation of Raman spectroscopic techniques for clinical applications in cancer, including detection of brain, ovarian, breast, prostate, and pancreatic cancers and circulating tumor cells.
Today's minimally invasive biosensors are often based on chemical reagents and suffer from, e.g., oxygen dependence, toxic reaction products, excess analyte consumption, and/or degradation of the reagents. Here, we show the first successful analyte quantification by means of a minimally invasive sensor in vivo, which does not use chemical reactions. The concentration of glucose is determined continuously in vivo using transcutaneous, fiber-based mid-infrared laser spectroscopy. When comparing the infrared data measured in vivo with the 127 reference readings of glucose obtained in vitro, an overall standard deviation of 17.5% and a median of the absolute values of the relative deviations of 11.0% are achieved. The encouraging results open up the path toward a reagent-free long-term implant for the continuous surveillance of metabolites. In addition, the high sampling rate facilitates important research in body metabolism as well as its application outside the field of medicine such as real-time analyte sensing during fermentation.
Early diagnosis of oral cancers, one of the major cancers, is of utmost importance as 5-year disease-free survival rates are some of the lowest, despite advances in treatment and surgical modalities. In vivo Raman spectroscopy has shown efficacy in the detection of normal, premalignant and malignant lesions and even of early changes such as cancer-field-effects/malignancy-associated-changes. However, the need for a dedicated instrument and stringent laboratory conditions, at all diagnostic centers, limits wide screening applications of this method. In light of this, it is pertinent to explore ex vivo samples like serum due to its ease of collection, storage, transport and analysis at a centralized facility. Hence, Raman studies were carried out on serum from 14 buccal mucosa and 40 tongue cancers as well as 16 healthy control samples. Spectral features indicate differential contributions of proteins, DNA, and amino acids like Phe, Trp and Tyr and β-carotene in the analyzed groups. Highly intense Raman bands assigned to β-carotene could be due to resonance Raman, and were observed in all sera with the highest relative intensity in normal samples. Higher DNA and protein content were observed in the mean cancer spectra. Principal component-linear discriminant analysis (PC-LDA) followed by cross-validation using leave-one-out cross-validation (LOOCV) were employed for data analysis which was carried out both spectra- and patient-wise. Findings indicate the possibility of classifying normal and oral cancer sera in both these approaches; however, the patient-wise approach could be the preferred mode for prospective studies. Besides, a tendency of classification for buccal mucosa and tongue cancers was also observed. Prospective validation of these results on a large sample size may help in the translation of this methodology to clinics.
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