Proteins inform survival-based differences in patients with glioblastoma

Author:

Stetson L C1,Ostrom Quinn T23,Schlatzer Daniela4,Liao Peter1,Devine Karen1,Waite Kristin15,Couce Marta E6,Harris Peggy L R7,Kerstetter-Fogle Amber7,Berens Michael E8,Sloan Andrew E17,Islam Mohammad M9,Rajaratnam Vilashini9,Mirza Shama P9,Chance Mark R14,Barnholtz-Sloan Jill S15ORCID

Affiliation:

1. Case Comprehensive Cancer Center, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA

2. Department of Medicine and Division of Hematology-Oncology, Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, Texas, USA

3. Department of Medicine, Section of Epidemiology and Population Sciences, Baylor College of Medicine, Houston, Texas, USA

4. Center for Proteomics and Bioinformatics and Department of Nutrition, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA

5. Department of Population and Quantitative Health Sciences and Cleveland Center for Health Outcomes Research (CCHOR), Case Western Reserve University School of Medicine, Cleveland, Ohio, USA

6. Department of Pathology, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA

7. Brain Tumor and Neuro-Oncology Center & Center of Excellence, Translational Neuro-Oncology, Department of Neurosurgery, Seidman Cancer Center, University Hospitals Cleveland Medical Center, Cleveland, Ohio, USA

8. Translational Genomics Research Institute (TGen), Phoenix, Arizona, USA

9. Department of Chemistry and Biochemistry, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA

Abstract

Abstract Background Improving the care of patients with glioblastoma (GB) requires accurate and reliable predictors of patient prognosis. Unfortunately, while protein markers are an effective readout of cellular function, proteomics has been underutilized in GB prognostic marker discovery. Methods For this study, GB patients were prospectively recruited and proteomics discovery using liquid chromatography–mass spectrometry analysis (LC-MS/MS) was performed for 27 patients including 13 short-term survivors (STS) (≤10 months) and 14 long-term survivors (LTS) (≥18 months). Results Proteomics discovery identified 11 941 peptides in 2495 unique proteins, with 469 proteins exhibiting significant dysregulation when comparing STS to LTS. We verified the differential abundance of 67 out of these 469 proteins in a small previously published independent dataset. Proteins involved in axon guidance were upregulated in STS compared to LTS, while those involved in p53 signaling were upregulated in LTS. We also assessed the correlation between LS MS/MS data with RNAseq data from the same discovery patients and found a low correlation between protein abundance and mRNA expression. Finally, using LC-MS/MS on a set of 18 samples from 6 patients, we quantified the intratumoral heterogeneity of more than 2256 proteins in the multisample dataset. Conclusions These proteomic datasets and noted protein variations present a beneficial resource for better predicting patient outcome and investigating potential therapeutic targets.

Funder

Skirball Foundation

Ben and Catherine Ivy Foundation

National Cancer Institute Case Comprehensive Cancer Center Support Grant

National Institutes of Health Case Western Reserve University School of Medicine Clinical Translational Science Collaborative

Peter D Cristal Endowment

The Kimble Foundation

James C. Benjamin Fund for Brain Tumor Research

Froedtert Foundation Grant

UWM Research Growth Initiative

Publisher

Oxford University Press (OUP)

Subject

Electrical and Electronic Engineering,Building and Construction

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