Next Article in Journal
Achieving Metabolic Flux Analysis for S. cerevisiae at a Genome-Scale: Challenges, Requirements, and Considerations
Next Article in Special Issue
Cancer Metabolomics and the Human Metabolome Database
Previous Article in Journal
Integrating Multiple Analytical Datasets to Compare Metabolite Profiles of Mouse Colonic-Cecal Contents and Feces
Article Menu

Export Article

Open AccessArticle
Metabolites 2015, 5(3), 502-520; doi:10.3390/metabo5030502

Metabolomic Screening of Tumor Tissue and Serum in Glioma Patients Reveals Diagnostic and Prognostic Information

1
Department of Chemistry, Umeå University, SE 901 87 Umeå, Sweden
2
Department of Clinical Neuroscience, Neurosurgery, Umeå University, SE 901 85 Umeå, Sweden
3
Department of Radiation Sciences, Oncology, Umeå University, SE 901 85 Umeå, Sweden
4
Department of Medical Biosciences, Pathology, Umeå University, SE 901 87 Umeå, Sweden
*
Author to whom correspondence should be addressed.
Academic Editors: Natalie Serkova and Peter Meikle
Received: 9 June 2015 / Revised: 20 August 2015 / Accepted: 6 September 2015 / Published: 15 September 2015
(This article belongs to the Special Issue Cancer Metabolomics 2016)
View Full-Text   |   Download PDF [696 KB, uploaded 17 September 2015]   |  

Abstract

Glioma grading and classification, today based on histological features, is not always easy to interpret and diagnosis partly relies on the personal experience of the neuropathologists. The most important feature of the classification is the aimed correlation between tumor grade and prognosis. However, in the clinical reality, large variations exist in the survival of patients concerning both glioblastomas and low-grade gliomas. Thus, there is a need for biomarkers for a more reliable classification of glioma tumors as well as for prognosis. We analyzed relative metabolite concentrations in serum samples from 96 fasting glioma patients and 81 corresponding tumor samples with different diagnosis (glioblastoma, oligodendroglioma) and grade (World Health Organization (WHO) grade II, III and IV) using gas chromatography-time of flight mass spectrometry (GC-TOFMS). The acquired data was analyzed and evaluated by pattern recognition based on chemometric bioinformatics tools. We detected feature patterns in the metabolomics data in both tumor and serum that distinguished glioblastomas from oligodendrogliomas (ptumor = 2.46 × 10−8, pserum = 1.3 × 10−5) and oligodendroglioma grade II from oligodendroglioma grade III (ptumor = 0.01, pserum = 0.0008). Interestingly, we also found patterns in both tumor and serum with individual metabolite features that were both elevated and decreased in patients that lived long after being diagnosed with glioblastoma compared to those who died shortly after diagnosis (ptumor = 0.006, pserum = 0.004; AUROCCtumor = 0.846 (0.647–1.000), AUROCCserum = 0.958 (0.870–1.000)). Metabolic patterns could also distinguish long and short survival in patients diagnosed with oligodendroglioma (ptumor = 0.01, pserum = 0.001; AUROCCtumor = 1 (1.000–1.000), AUROCCserum = 1 (1.000–1.000)). In summary, we found different metabolic feature patterns in tumor tissue and serum for glioma diagnosis, grade and survival, which indicates that, following further verification, metabolomic profiling of glioma tissue as well as serum may be a valuable tool in the search for latent biomarkers for future characterization of malignant glioma. View Full-Text
Keywords: glioma; diagnosis; prognosis; blood; tumor; metabolomics; chemometrics; latent biomarkers glioma; diagnosis; prognosis; blood; tumor; metabolomics; chemometrics; latent biomarkers
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Mörén, L.; Bergenheim, A.T.; Ghasimi, S.; Brännström, T.; Johansson, M.; Antti, H. Metabolomic Screening of Tumor Tissue and Serum in Glioma Patients Reveals Diagnostic and Prognostic Information. Metabolites 2015, 5, 502-520.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Metabolites EISSN 2218-1989 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top