Label-free differentiation of human pituitary adenomas by FT-IR spectroscopic imaging
Faculty of Medicine Carl Gustav Carus, Dresden University of Technology, Clinical Sensoring and Monitoring, 01307, Dresden, Germany.Analytical and Bioanalytical Chemistry (Impact Factor: 3.44). 04/2012; 403(3):727-35. DOI: 10.1007/s00216-012-5824-y
Fourier transform infrared (FT-IR) spectroscopic imaging has been used to characterize different types of pituitary gland tumors and normal pituitary tissue. Freshly resected tumor tissue from surgery was prepared as thin cryosections and examined by FT-IR spectroscopic imaging. Tissue types were discriminated via k-means cluster analysis and a supervised classification algorithm based on linear discriminant analysis. Spectral classification allowed us to discriminate between tumor and non-tumor cells, as well as between tumor cells that produce human growth hormone (hGH+) and tumor cells that do not produce that hormone (hGH-). The spectral classification was compared and contrasted with a histological PAS and orange G stained image. It was further shown that hGH+ pituitary tumor cells show stronger amide bands than tumor cells that do not produce hGH. This study demonstrates that FT-IR spectroscopic imaging can not only potentially serve as a fast and objective approach for discriminating pituitary gland tumors from normal tissue, but that it can also detect hGH-producing tumor cells.
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ABSTRACT: Purpose: Vibrational spectroscopy enables the label-free characterization of cells and tissue by probing the biochemical composition. Here, we evaluated these techniques to identify glioblastoma stem cells. Materials and methods: The biochemical fingerprints of glioblastoma cells were established in human cell lines with high and low content of CD133 (cluster of differentiation 133)-positive cells using attenuated total reflection Fourier-transform infrared (ATR FT-IR) on vital cells and FT-IR mapping, which delivers spatially resolved spectroscopic datasets. After data preprocessing, unsupervised cluster analysis was applied. CD133 was addressed with flow cytometry and immunohistochemistry and used as a stemness marker. Results: In all preparations, the algorithm was able to correctly classify the spectra, differentiating CD133-rich and -poor populations. The main spectral differences were found in the region of 1000 cm(- 1) to 1150 cm(- 1) that can be assigned to vibrations of chemical bonds of DNA, RNA, carbohydrates and phospholipids. Interestingly, this spectral region is a key feature to discern glioblastoma from normal brain parenchyma, as FT-IR spectroscopic mapping of experimental brain tumors demonstrated. Conclusions: We were able to show biochemical differences between glioblastoma cell populations with high and low content of cancer stem cells that are presumably related to changes in the RNA/DNA content.International Journal of Radiation Biology 03/2014; 90(8). DOI:10.3109/09553002.2014.899447 · 1.69 Impact Factor
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ABSTRACT: In the surgical treatment of malignant tumors, it is crucial to characterize the tumor as precisely as possible. The determination of the exact tumor location as well as the analysis of its properties is very important in order to obtain an accurate diagnosis as early as possible. In neurosurgical applications, the optical, non-invasive and in situ techniques allow for the label-free analysis of tissue, which is helpful in neuropathology. In the past decades, optical spectroscopic methods have been investigated drastically in the management of cancer. In the optical spectroscopic techniques, tissue interrogate with sources of light which are ranged from the ultraviolet to the infrared wavelength in the spectrum. The information accumulation of light can be in a reflection which is named reflectance spectroscopy; or interactions with tissue at different wavelengths which are called fluorescence and Raman spectroscopy. This review paper introduces the optical spectroscopic methods which are used to characterize brain tumors (neuro-oncology). Based on biochemical information obtained from these spectroscopic methods, it is possible to identify tumor from normal brain tissues, to indicate tumor margins, the borders towards normal brain tissue and infiltrating gliomas, to distinguish radiation damage of tissues, to detect particular central nervous system (CNS) structures to identify cell types using particular neurotransmitters, to detect cells or drugs which are optically labeled within therapeutic intermediations and to estimate the viability of tissue and the prediction of apoptosis beginning in vitro and in vivo. The label-free, optical biochemical spectroscopic methods can provide clinically relevant information and need to be further exploited to develop a safe and easy-to-use technology for in situ diagnosis of malignant tumors.Journal of Lasers in Medical Sciences 03/2015; 6(2):51.
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