The purpose of this study was to investigate molecular changes associated with glioma tissues by Raman microspectroscopy in order to develop its use in clinical practice. Spectroscopic markers obtained from C6 glioma tissues were compared to conventional histological and histochemical techniques. Cholesterol and phospholipid contents were highest in corpus callosum and decreased gradually towards the cortex surface as well as in the tumor. Two different necrotic areas have been identified: a fully necrotic zone characterized by the presence of plasma proteins and a peri-necrotic area with a high lipid content. This result was confirmed by Nile Red staining. Additionally, one structure was detected in the periphery of the tumor. Invisible with histopathological hematoxylin and eosin staining, it was revealed by immunohistochemical Ki-67 and MT1-MMP staining used to visualize the proliferative and invasive activities of glioma, respectively. Hierarchical cluster analysis on the only cluster averaged spectra showed a clear distinction between normal, tumoral, necrotic and edematous tissues. Raman microspectroscopy can discriminate between healthy and tumoral brain tissue and yield spectroscopic markers associated with the proliferative and invasive properties of glioblastoma. Development of in vivo Raman spectroscopy could thus accurately define tumor margins, identify tumor remnants, and help in the development of novel therapies for glioblastoma.
The potential of Raman spectroscopy for ex vivo and in vivo classification of normal and glioblastoma brain tumor development was investigated. High-quality spectra of normal and tumor tissues were obtained using a portable Raman spectrometer coupled to a microprobe with a signal integration time of 5 s. Ex vivo results demonstrated that by using the biochemical information contained in the spectra, we were able to distinguish between normal brain features (white and gray matter), invasion, and tumor tissues with a classification accuracy of 100%. Differences between these features resulted from variations in their lipid signal contributions, which probably reflect differences in the level of myelinization. This finding supports the ability of in vivo Raman spectroscopy to delineate tumor margins during surgery. After implanting C6 cells in rat brain, we monitored, in vivo, the development of glioblastoma tumor from days 0 to 20 post-implantation (PI). The classification exhibited a clear separation of the data into two clusters: one cluster was associated with normal brain tissues (cortex), and the second was related to data measured from tumor evolution. The second cluster could be divided into two subclusters, one associated with tumor tissue from 4 to 13 days PI and the second related to tumor tissue from 15 to 20 days PI. Histological analysis reveals that the differences between these two subclusters are: the presence of a massive infiltration zone in the brain tissue from 4 to 13 days PI, and; a maturation of the tumor characterized by the appearance of edematous and necrotic zones, as well as a diminution in the proliferative and invasive area, from 15 days. This work demonstrates the potential of Raman spectroscopy to provide diagnostic information for the early detection of tumors in vivo.
Pathological changes associated with the development of brain tumor were investigated by Fourier transform infrared microspectroscopy (FT-IRM) with high spatial resolution. Using multivariate statistical analysis and imaging, all normal brain structures were discriminated from tumor and surrounding tumor tissues. These structural changes were mainly related to qualitative and quantitative changes in lipids (tumors contain little fat) and were correlated to the degree of myelination, an important factor in several neurodegenerative disorders. Lipid concentration and composition may thus be used as spectroscopic markers to discriminate between healthy and tumor tissues. Additionally, we have identified one peculiar structure all around the tumor. This structure could be attributed to infiltrative events, such as peritumoral oedema observed during tumor development. Our results highlight the ability of FT-IRM to identify the molecular origin that gave rise to the specific changes between healthy and diseased states. Comparison between pseudo-FT-IRM maps and histological examinations (Luxol fast blue, Luxol fast blue-cresyl violet staining) showed the complementarities of both techniques for early detection of tissue abnormalities.
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