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MALDI imaging and in‐source decay for top‐down characterization of glioblastoma
Author(s) -
AitBelkacem Rima,
Berenguer Caroline,
Villard Claude,
Ouafik L'Houcine,
FigarellaBranger Dominique,
Chinot Olivier,
Lafitte Daniel
Publication year - 2014
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.201300329
Subject(s) - glioblastoma , carcinogenesis , maldi imaging , pathology , molecular imaging , brain tumor , glioma , high resolution , cancer research , computational biology , biology , medicine , chemistry , in vivo , cancer , matrix assisted laser desorption/ionization , genetics , remote sensing , organic chemistry , adsorption , desorption , geology
Glioblastoma multiforme is one of the most common intracranial tumors encountered in adults. This tumor of very poor prognosis is associated with a median survival rate of approximately 14 months. One of the major issues to better understand the biology of these tumors and to optimize the therapy is to obtain the molecular structure of glioblastoma. MALDI molecular imaging enables location of molecules in tissues without labeling. However, molecular identification in situ is not an easy task. In this paper, we used MALDI imaging coupled to in‐source decay to characterize markers of this pathology. We provided MALDI molecular images up to 30 μm spatial resolution of mouse brain tissue sections. MALDI images showed the heterogeneity of the glioblastoma. In the various zones and at various development stages of the tumor, using our top‐down strategy, we identified several proteins. These proteins play key roles in tumorigenesis. Particular attention was given to the necrotic area with characterization of hemorrhage, one of the most important poor prognosis factors in glioblastoma.