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Histomolecular interpretation of pleomorphic adenomas of the salivary gland by matrix‐assisted laser desorption ionization imaging and spatial segmentation
Author(s) -
Ernst Günther,
Guntinas–Lichius Orlando,
Hauberg–Lotte Lena,
Trede Dennis,
Becker Michael,
Alexandrov Theodore,
von Eggeling Ferdinand
Publication year - 2015
Publication title -
head and neck
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.012
H-Index - 127
eISSN - 1097-0347
pISSN - 1043-3074
DOI - 10.1002/hed.23713
Subject(s) - maldi imaging , pleomorphic adenoma , mass spectrometry imaging , pathology , segmentation , histology , laser capture microdissection , transdifferentiation , computer science , matrix assisted laser desorption/ionization , biology , artificial intelligence , salivary gland , mass spectrometry , chemistry , medicine , desorption , microbiology and biotechnology , gene , stem cell , biochemistry , gene expression , organic chemistry , adsorption , chromatography
Background Despite efforts in localization of key proteins using immunohistochemistry, the complex proteomic composition of pleomorphic adenomas has not yet been characterized. Matrix‐assisted laser desorption/ionization imaging mass spectrometry (MALDI imaging) allows label‐free and spatially resolved detection of hundreds of proteins directly from tissue sections and of histomorphological regions by finding colocalized molecular signals. Spatial segmentation of MALDI imaging data is an algorithmic method for finding regions of similar proteomic composition as functionally similar regions. Methods We investigated 2 pleomorphic adenomas by applying spatial segmentation to the MALDI imaging data of tissue sections. Results The spatial segmentation subdivided the tissue in a good accordance with the tissue histology. Numerous molecular signals colocalized with histologically defined tissue regions were found. Conclusion Our study highlights the cellular transdifferentiation within the pleomorphic adenoma. It could be shown that spatial segmentation of MALDI imaging data is a promising approach in the emerging field of digital histological analysis and characterization of tumors. © 2014 Wiley Periodicals, Inc. Head Neck 37: 1014–1021, 2015