Vibrational spectroscopy techniques have demonstrated potential to provide non-destructive, rapid, clinically relevant diagnostic information. Early detection is the most important factor in the prevention of cancer. Raman and infrared spectroscopy enable the biochemical signatures from biological tissues to be extracted and analysed. In conjunction with advanced chemometrics such measurements can contribute to the diagnostic assessment of biological material. This paper also illustrates the complementary advantage of using Raman and FTIR spectroscopy technologies together. Clinical requirements are increasingly met by technological developments which show promise to become a clinical reality. This review summarises recent advances in vibrational spectroscopy and their impact on the diagnosis of cancer.
Spectroscopic techniques, such as Fourier-transform infrared (FTIR) spectroscopy, are used to study the interaction of light with biological materials. This interaction forms the basis of many analytical assays used in disease screening and diagnosis, microbiological studies, forensic and environmental investigations. Advantages of spectrochemical analysis are its low cost, minimal sample preparation, non-destructive nature and substantially accurate results. However, there is now an urgent need for repetition and validation of these methods in large-scale studies and across different research groups, which would bring the method closer to clinical and/or industrial implementation. In order for this to succeed, it is important to understand and reduce the effect of random spectral alterations caused by inter-individual, inter-instrument and/or inter-laboratory variations, such as variations in air humidity and CO2 levels, and the aging of instrumental parts.Thus, it is evident that spectral standardization is crucial for the widespread adoption of these spectrochemical technologies. By using calibration transfer procedures, where the spectral response of a secondary instrument is standardized to resemble the spectral response of a primary instrument, different sources of variations can be normalized into a single model using computational-based methods, such as direct standardization (DS) and piecewise direct standardization (PDS); therefore, measurements performed under different conditions can generate the same result, eliminating the need for a full recalibration. In this paper, we have constructed a protocol for model standardization using different transfer technologies described for FTIR spectrochemical applications. This is a critical step towards the construction of a practical spectrochemical analysis model for daily routine analysis, where uncertain and random variations are present. 4 worldwide are developing spectrochemical approaches for diagnosis, discrimination and monitoring of diseases, as well as for other uses. Combination of multiple datasets would facilitate the conduction of large-scale studies which are still lacking in the field of bio-spectroscopy. Sensor-based technologiesSensor-based technologies are an integral part of daily life ranging from locating sensorbased technology, such as global positioning system (GPS) 6 , to image biosensors, such as X-rays 7-10 and γ-rays [11][12][13] , which are used extensively for medical applications. Other powerful approaches that make use of sensor-based technologies toward medical disease examination and diagnostics include circular dichroism (CD) spectroscopy 14-17 , ultraviolet (UV) or visible spectroscopy 18,19 , fluorescence 20-24 , nuclear magnetic resonance (NMR) spectroscopy 25-29 and ultrasound (US) 7,30- .Over the last two decades, optical biosensors employing vibrational spectroscopy, particularly IR spectroscopy, have seen tremendous progress in biomedical and biological research. A number of studies using the above-mentioned methods ha...
Altered cellular metabolism is a hallmark of tumor cells and contributes to a host of properties associated with resistance to radiotherapy. Detection of radiation-induced biochemical changes can reveal unique metabolic pathways affecting radiosensitivity that may serve as attractive therapeutic targets. Using clinically relevant doses of radiation, we performed label-free single cell Raman spectroscopy on a series of human cancer cell lines and detected radiation-induced accumulation of intracellular glycogen. The increase in glycogen post-irradiation was highest in lung (H460) and breast (MCF7) tumor cells compared to prostate (LNCaP) tumor cells. In response to radiation, the appearance of this glycogen signature correlated with radiation resistance. Moreover, the buildup of glycogen was linked to the phosphorylation of GSK-3β, a canonical modulator of cell survival following radiation exposure and a key regulator of glycogen metabolism. When MCF7 cells were irradiated in the presence of the anti-diabetic drug metformin, there was a significant decrease in the amount of radiation-induced glycogen. The suppression of glycogen by metformin following radiation was associated with increased radiosensitivity. In contrast to MCF7 cells, metformin had minimal effects on both the level of glycogen in H460 cells following radiation and radiosensitivity. Our data demonstrate a novel approach of spectral monitoring by Raman spectroscopy to assess changes in the levels of intracellular glycogen as a potential marker and resistance mechanism to radiation therapy.
External beam radiation therapy is a standard form of treatment for numerous cancers. Despite this, there are no approved methods to account for patient specific radiation sensitivity. In this report, Raman spectroscopy (RS) was used to identify radiation-induced biochemical changes in human non-small cell lung cancer xenografts. Chemometric analysis revealed unique radiation-related Raman signatures that were specific to nucleic acid, lipid, protein and carbohydrate spectral features. Among these changes was a dramatic shift in the accumulation of glycogen spectral bands for doses of 5 or 15 Gy when compared to unirradiated tumours. When spatial mapping was applied in this analysis there was considerable variability as we found substantial intra- and inter-tumour heterogeneity in the distribution of glycogen and other RS spectral features. Collectively, these data provide unique insight into the biochemical response of tumours, irradiated in vivo, and demonstrate the utility of RS for detecting distinct radiobiological responses in human tumour xenografts.
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