Browsing by Author "D. Sockalingum, Ganesh"
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Item Characterization of inflammatory breast cancer: a vibrational microspectroscopy and imaging approach at the cellular and tissue level(Royal Society of Chemistry, 2018) Taha Mohamed, Hossam; Untereiner, Valérie; Proult, Isabelle; Abdelaziz Ibrahim, Sherif; Götte, Martin; El-Shinawi, Mohamed; Mostafa Mohamed, Mona; D. Sockalingum, Ganesh; Brézillon, StéphaneInflammatory breast cancer (IBC) has a poor prognosis because of the lack of specific biomarkers and its late diagnosis. An accurate and rapid diagnosis implemented early enough can significantly improve the disease outcome. Vibrational spectroscopy has proven to be useful for cell and tissue characterization based on the intrinsic molecular information. Here, we have applied infrared and Raman microspectroscopy and imaging to differentiate between non-IBC and IBC at both cell and tissue levels. Two human breast cancer cell lines (MDA-MB-231 and SUM-149), 20 breast cancer patients (10 non-IBC and 10 IBC), and 4 healthy volunteer biopsies were investigated. Fixed cells and tissues were analyzed by FTIR microspectroscopy and imaging, while live cells were studied by Raman microspectroscopy. Spectra were analyzed by hierarchical cluster analysis (HCA) and images by common k-means clustering algorithms. For both cell suspensions and single cells, FTIR spectroscopy showed sufficient high inter-group variability to delineate MDA-MB-231 and SUM-149 cell lines. Most significant differences were observed in the spectral regions of 1096–1108 and 1672–1692 cm−1. Analysis of live cells by Raman microspectroscopy gave also a good discrimination of these cell types. The most discriminant regions were 688–992, 1019–1114, 1217–1375 and 1516–1625 cm−1. Finally, k-means cluster analysis of FTIR images allowed delineating non-IBC from IBC tissues. This study demonstrates the potential of vibrational spectroscopy and imaging to discriminate between non-IBC and IBC at both cell and tissue levels.Item Implementation of infrared and Raman modalities for glycosaminoglycan characterization in complex systems(Springer US, 2017) Taha Mohamed, Hossam; Untereiner, Valérie; D. Sockalingum, Ganesh; Brézillon, StéphaneGlycosaminoglycans (GAGs) are natural, linear and negatively charged heteropolysaccharides which are incident in every mammalian tissue. They consist of repeating disaccharide units, which are composed of either sulfated or non-sulfated monosaccharides. Depending on tissue types, GAGs exhibit structural heterogeneity such as the position and degree of sulfation or within their disaccharide units composition being heparin, heparan sulfate, chondroitine sulfate, dermatan sulfate, keratan sulfate, and hyaluronic acid. They are covalently linked to a core protein (proteoglycans) or as free chains (hyaluronan). GAGs affect cell properties and functions either by direct interaction with cell receptors or by sequestration of growth factors. These evidences of divert biological roles of GAGs make their characterization at cell and tissue levels of importance. Thus, non-invasive techniques are interesting to investigate, to qualitatively and quantitatively characterize GAGs in vitro in order to use them as diagnostic biomarkers and/or as therapeutic targets in several human diseases including cancer. Infrared and Raman microspectroscopies and imaging are sensitive enough to differentiate and classify GAG types and subtypes in spite of their close molecular structures. Spectroscopic markers characteristic of reference GAG molecules were identified. Beyond these investigations of the standard GAG spectral signature, infrared and Raman spectral signatures of GAG were searched in complex biological systems like cells. The aim of the present review is to describe the implementation of these complementary vibrational spectroscopy techniques, and to discuss their potentials, advantages and disadvantages for GAG analysis. In addition, this review presents new data as we show for the first time GAG infrared and Raman spectral signatures from conditioned media and live cells, respectively.