Identification of Proteomic Markers in Head and Neck Cancer Using MALDI-MS Imaging, LC-MS/MS, and Immunohistochemistry.

Abstract:

PURPOSE: The heterogeneity of squamous cell carcinoma tissue greatly complicates diagnosis and individualized therapy. Therefore, characterizing the heterogeneity of tissue spatially and identifying appropriate biomarkers is crucial. MALDI-MS imaging (MSI) is capable of analyzing spatially resolved tissue biopsies on a molecular level. EXPERIMENTAL DESIGN: MALDI-MSI is used on snap frozen and formalin-fixed and paraffin-embedded (FFPE) tissue samples from patients with head and neck cancer (HNC) to analyze m/z values localized in tumor and nontumor regions. Peptide identification is performed using LC-MS/MS and immunohistochemistry (IHC). RESULTS: In both FFPE and frozen tissue specimens, eight characteristic masses of the tumor's epithelial region are found. Using LC-MS/MS, the peaks are identified as vimentin, keratin type II, nucleolin, heat shock protein 90, prelamin-A/C, junction plakoglobin, and PGAM1. Lastly, vimentin, nucleolin, and PGAM1 are verified with IHC. CONCLUSIONS AND CLINICAL RELEVANCE: The combination of MALDI-MSI, LC-MS/MS, and subsequent IHC furnishes a tool suitable for characterizing the molecular heterogeneity of tissue. It is also suited for use in identifying new representative biomarkers to enable a more individualized therapy.

SEEK ID: https://funginet.hki-jena.de/publications/168

PubMed ID: 30411850

Projects: Z2

Publication type: Not specified

Journal: Proteomics Clin Appl

Citation: Proteomics Clin Appl. 2019 Jan;13(1):e1700173. doi: 10.1002/prca.201700173. Epub 2018 Nov 26.

Date Published: 10th Nov 2018

Registered Mode: Not specified

Authors: F. Hoffmann, C. Umbreit, T. Kruger, D. Pelzel, G. Ernst, O. Kniemeyer, O. Guntinas-Lichius, A. Berndt, F. von Eggeling

help Submitter
Activity

Views: 1280

Created: 17th Feb 2021 at 12:25

Last updated: 17th Jan 2024 at 10:24

help Tags

This item has not yet been tagged.

help Attributions

None

Powered by
(v.1.13.4)
Copyright © 2008 - 2023 The University of Manchester and HITS gGmbH