A new classification method for MALDI imaging mass spectrometry data acquired on formalin-fixed paraffin-embedded tissue samples.
Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) shows a high potential for applications in histopathological diagnosis, and in particular for supporting tumor typing and subtyping. The development of such applications requires the extraction of spectral fingerprints that are relevant for the given tissue and the identification of biomarkers associated with these spectral patterns. We propose a novel data analysis method based on the extraction of characteristic spectral patterns (CSPs) that allow automated generation of classification models for spectral data. Formalin-fixed paraffin embedded (FFPE) tissue samples from N=445 patients assembled on 12 tissue microarrays were analyzed. The method was applied to discriminate primary lung and pancreatic cancer, as well as adenocarcinoma and squamous cell carcinoma of the lung. A classification accuracy of 100% and 82.8%, resp., could be achieved on core level, assessed by cross-validation. The method outperformed the more conventional classification method based on the extraction of individual m/z values in the first application, while achieving a comparable accuracy in the second. LC-MS/MS peptide identification demonstrated that the spectral features present in selected CSPs correspond to peptides relevant for the respective classification. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.
Center for Industrial Mathematics, University of Bremen, Bremen, Germany; SCiLS GmbH, Bremen, Germany. Electronic address: tboskamp@uni-bremen.de.
Tobias
T
Boskamp
Center for Industrial Mathematics, University of Bremen, Bremen, Germany.
Delf
D
Lachmund
MALDI Imaging Lab, University of Bremen, Bremen, Germany.
Janina
J
Oetjen
Center for Industrial Mathematics, University of Bremen, Bremen, Germany.
Yovany
Y
Cordero Hernandez
SCiLS GmbH, Bremen, Germany.
Dennis
D
Trede
Center for Industrial Mathematics, University of Bremen, Bremen, Germany; MALDI Imaging Lab, University of Bremen, Bremen, Germany; SCiLS GmbH, Bremen, Germany.
Peter
P
Maass
Proteopath GmbH, Trier, Germany.
Rita
R
Casadonte
Proteopath GmbH, Trier, Germany; Center for Histology, Cytology and Molecular Diagnostic, Trier, Germany.
Jörg
J
Kriegsmann
Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany.
Arne
A
Warth
Thoraxklinik Heidelberg, University of Heidelberg, Heidelberg, Germany.
Hendrik
H
Dienemann
Institute of Pathology, Technical University of Munich, Munich, Germany.
Wilko
W
Weichert
Institute of Pathology, Heidelberg University Hospital, Heidelberg, Germany.
Mark
M
Kriegsmann
D000230:Adenocarcinoma / Q000175:diagnosis / Q000378:metabolism / Q000473:pathology; D000077192:Adenocarcinoma of Lung; D014408:Biomarkers, Tumor / Q000378:metabolism; D002294:Carcinoma, Squamous Cell / Q000175:diagnosis / Q000378:metabolism / Q000473:pathology; D005557:Formaldehyde / Q000737:chemistry*; D006801:Humans; D008175:Lung Neoplasms / Q000175:diagnosis / Q000378:metabolism / Q000473:pathology; D010190:Pancreatic Neoplasms / Q000175:diagnosis / Q000378:metabolism / Q000473:pathology; D010232:Paraffin / Q000737:chemistry*; D010455:Peptides / Q000378:metabolism; D019032:Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization / Q000379:methods; D046888:Tissue Array Analysis / Q000379:methods
D014408:Biomarkers, Tumor; D010455:Peptides; D005557:Formaldehyde; D010232:Paraffin
Characteristic spectral patterns; Classification; Feature extraction; Formalin-fixed paraffin-embedded; MALDI imaging MS; Tumor typing