High‐resolution MALDI‐FT‐ICR MS imaging for the analysis of metabolites from formalin‐fixed, paraffin‐embedded clinical tissue samples

We present the first analytical approach to demonstrate the in situ imaging of metabolites from formalin‐fixed, paraffin‐embedded (FFPE) human tissue samples. Using high‐resolution matrix‐assisted laser desorption/ionization Fourier‐transform ion cyclotron resonance mass spectrometry imaging (MALDI‐FT‐ICR MSI), we conducted a proof‐of‐principle experiment comparing metabolite measurements from FFPE and fresh frozen tissue sections, and found an overlap of 72% amongst 1700 m/z species. In particular, we observed conservation of biomedically relevant information at the metabolite level in FFPE tissues. In biomedical applications, we analysed tissues from 350 different cancer patients and were able to discriminate between normal and tumour tissues, and different tumours from the same organ, and found an independent prognostic factor for patient survival. This study demonstrates the ability to measure metabolites in FFPE tissues using MALDI‐FT‐ICR MSI, which can then be assigned to histology and clinical parameters. Our approach is a major technical, histochemical, and clinicopathological advance that highlights the potential for investigating diseases in archived FFPE tissues. Copyright © 2015 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

[1]  Fulvio Magni,et al.  A MALDI-Mass Spectrometry Imaging method applicable to different formalin-fixed paraffin-embedded human tissues. , 2015, Molecular bioSystems.

[2]  Peter J H Webborn,et al.  Mass spectrometry imaging in drug development. , 2015, Analytical chemistry.

[3]  Suming Chen,et al.  MALDI-TOF MS imaging of metabolites with a N-(1-naphthyl) ethylenediamine dihydrochloride matrix and its application to colorectal cancer liver metastasis. , 2015, Analytical chemistry.

[4]  Steven J. M. Jones,et al.  Comprehensive molecular characterization of gastric adenocarcinoma , 2014, Nature.

[5]  A. Walch,et al.  High‐resolution metabolite imaging of light and dark treated retina using MALDI‐FTICR mass spectrometry , 2014, Proteomics.

[6]  Noel W. Clarke,et al.  Assessment of paraffin removal from prostate FFPE sections using transmission mode FTIR-FPA imaging , 2014 .

[7]  B. Spengler,et al.  Mass spectrometry imaging with high resolution in mass and space , 2013, Histochemistry and Cell Biology.

[8]  Richard M Caprioli,et al.  Analysis of tissue specimens by matrix-assisted laser desorption/ionization imaging mass spectrometry in biological and clinical research. , 2013, Chemical reviews.

[9]  David S. Wishart,et al.  HMDB 3.0—The Human Metabolome Database in 2013 , 2012, Nucleic Acids Res..

[10]  J. Asara,et al.  A positive/negative ion–switching, targeted mass spectrometry–based metabolomics platform for bodily fluids, cells, and fresh and fixed tissue , 2012, Nature Protocols.

[11]  R. Casadonte,et al.  Proteomic analysis of formalin-fixed paraffin-embedded tissue by MALDI imaging mass spectrometry , 2011, Nature Protocols.

[12]  J. Asara,et al.  Metabolomic Profiling from Formalin-Fixed, Paraffin-Embedded Tumor Tissue Using Targeted LC/MS/MS: Application in Sarcoma , 2011, PloS one.

[13]  R. Shah,et al.  Cluster analysis of immunohistochemical profiles delineates CK7, vimentin, S100A1 and C‐kit (CD117) as an optimal panel in the differential diagnosis of renal oncocytoma from its mimics , 2011, Histopathology.

[14]  Liam A. McDonnell,et al.  Imaging mass spectrometry data reduction: Automated feature identification and extraction , 2010, Journal of the American Society for Mass Spectrometry.

[15]  Kurt Zatloukal,et al.  Proteomic analysis of PAXgene-fixed tissues. , 2010, Journal of proteome research.

[16]  Zoltan Takats,et al.  Histology by mass spectrometry: label-free tissue characterization obtained from high-accuracy bioanalytical imaging. , 2010, Angewandte Chemie.

[17]  David S. Wishart,et al.  MetaboAnalyst: a web server for metabolomic data analysis and interpretation , 2009, Nucleic Acids Res..

[18]  D. Wishart Proteomics and the Human Metabolome Project , 2007, Expert review of proteomics.

[19]  Dante Mantini,et al.  LIMPIC: a computational method for the separation of protein MALDI-TOF-MS signals from noise , 2007, BMC Bioinformatics.

[20]  R. Abagyan,et al.  METLIN: A Metabolite Mass Spectral Database , 2005, Therapeutic drug monitoring.

[21]  K. Bodger,et al.  Detection of sulfated glycoproteins in intestinal metaplasia: a comparison of traditional mucin staining with immunohistochemistry for the sulfo-Lewisa carbohydrate epitope , 2003, Journal of clinical pathology.

[22]  T. Irimura,et al.  Expression of sulfated carbohydrate chain and core peptides of mucin detected by monoclonal antibodies in Barrett's esophagus and esophageal adenocarcinoma , 1998, Journal of Gastroenterology.

[23]  F. André,et al.  The carbohydrate and ester sulfate content of mucosal biopsies in health and in patients with duodenal ulcer. , 1974, Clinica chimica acta; international journal of clinical chemistry.

[24]  N. G. Klyuyeva,et al.  Biotherapy of Malignant Tumours , 1964 .

[25]  J. Schrager Sulphated Mucopolysaccharides of the Gastric Secretion , 1964, Nature.

[26]  J. Brierley Classification of Malignant Tumours , 1963, British medical journal.

[27]  O. Warburg [Origin of cancer cells]. , 1956, Oncologia.

[28]  Nikhil Wagle,et al.  High-throughput detection of actionable genomic alterations in clinical tumor samples by targeted, massively parallel sequencing. , 2012, Cancer discovery.

[29]  L. Sobin,et al.  TNM Classification of Malignant Tumours , 1987, UICC International Union Against Cancer.