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Comprehensive characterization of glioblastoma tumor tissues for biomarker identification using mass spectrometry-based label-free quantitative proteomics. Physiol Genomics 2014 Jul 01;46(13):467-81

Date

05/08/2014

Pubmed ID

24803679

Pubmed Central ID

PMC4587597

DOI

10.1152/physiolgenomics.00034.2014

Scopus ID

2-s2.0-84903603535   27 Citations

Abstract

Cancer is a complex disease; glioblastoma (GBM) is no exception. Short survival, poor prognosis, and very limited treatment options make it imperative to unravel the disease pathophysiology. The critically important identification of proteins that mediate various cellular events during disease is made possible with advancements in mass spectrometry (MS)-based proteomics. The objective of our study is to identify and characterize proteins that are differentially expressed in GBM to better understand their interactions and functions that lead to the disease condition. Further identification of upstream regulators will provide new potential therapeutic targets. We analyzed GBM tumors by SDS-PAGE fractionation with internal DNA markers followed by liquid chromatography-tandem mass spectrometry (MS). Brain tissue specimens obtained for clinical purposes during epilepsy surgeries were used as controls, and the quantification of MS data was performed by label-free spectral counting. The differentially expressed proteins were further characterized by Ingenuity Pathway Analysis (IPA) to identify protein interactions, functions, and upstream regulators. Our study identified several important proteins that are involved in GBM progression. The IPA revealed glioma activation with z score 2.236 during unbiased core analysis. Upstream regulators STAT3 and SP1 were activated and CTNN╬▒ was inhibited. We verified overexpression of several proteins by immunoblot to complement the MS data. This work represents an important step towards the identification of GBM biomarkers, which could open avenues to identify therapeutic targets for better treatment of GBM patients. The workflow developed represents a powerful and efficient method to identify biomarkers in GBM.

Author List

Heroux MS, Chesnik MA, Halligan BD, Al-Gizawiy M, Connelly JM, Mueller WM, Rand SD, Cochran EJ, LaViolette PS, Malkin MG, Schmainda KM, Mirza SP

Authors

Elizabeth J. Cochran MD Professor in the Pathology department at Medical College of Wisconsin
Jennifer M. Connelly MD Associate Professor in the Neurology department at Medical College of Wisconsin
Peter LaViolette PhD Associate Professor in the Radiology department at Medical College of Wisconsin
Wade M. Mueller MD Professor in the Neurosurgery department at Medical College of Wisconsin
Kathleen M. Schmainda PhD Professor in the Biophysics department at Medical College of Wisconsin




MESH terms used to index this publication - Major topics in bold

Adult
Aged
Biomarkers, Tumor
Brain Neoplasms
Female
Glioblastoma
Humans
Male
Mass Spectrometry
Middle Aged
Proteomics
Staining and Labeling
Young Adult