A pilot study: Metabolic profiling of plasma and saliva samples from newly diagnosed glioblastoma patients

Juliana Muller Bark; Avinash V Karpe; James D Doecke; Paul Leo; Rosalind L Jeffree; Benjamin Chua; Bryan W Day; David J Beale; Chamindie Punyadeera

doi:10.1002/cam4.5857

A pilot study: Metabolic profiling of plasma and saliva samples from newly diagnosed glioblastoma patients

Cancer Med. 2023 May;12(10):11427-11437. doi: 10.1002/cam4.5857. Epub 2023 Apr 9.

Authors

Juliana Muller Bark^{1

2

3}, Avinash V Karpe^{4

5}, James D Doecke⁶, Paul Leo^{3

7}, Rosalind L Jeffree^{8

9

10

11}, Benjamin Chua^{9

12}, Bryan W Day^{3

9

11}, David J Beale⁴, Chamindie Punyadeera^{2

13

14}

Affiliations

¹ Faculty of Health, Centre for Biomedical Technologies, School of Biomedical Sciences, Queensland University of Technology, Brisbane, Queensland, Australia.
² Saliva and Liquid Biopsy Translational Laboratory, Griffith Institute for Drug Discovery - Griffith University, Brisbane, Queensland, Australia.
³ Faculty of Health, School of Biomedical Sciences, Queensland University of Technology, Gardens Point, Queensland, Australia.
⁴ Environment, Commonwealth Scientific and Industrial Research Organization (CSIRO), Ecosciences Precinct, Dutton Park, Queensland, Australia.
⁵ Agriculture and Food, Commonwealth Scientific and Industrial Research Organization (CSIRO), Acton, Australian Capital Territory, Australia.
⁶ Australian eHealth Research Centre, CSIRO. Level 7, Surgical Treatment and Rehabilitation Service - STARS, Royal Brisbane and Women's Hospital, Herston, Queensland, Australia.
⁷ Faculty of Health, Translational Genomics Group, School of Biomedical Sciences, Queensland University of Technology, Woolloongabba, Australia.
⁸ QIMR Berghofer Medical Research Institute, Herston, Queensland, Australia.
⁹ Faculty of Medicine, University of Queensland, Herston, Queensland, Australia.
¹⁰ Kenneth G. Jamieson Department of Neurosurgery, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia.
¹¹ Cell and Molecular Biology Department, Sid Faithfull Brain Cancer Laboratory, QIMR Berghofer MRI, Brisbane, Queensland, Australia.
¹² Cancer Care Services, Royal Brisbane and Women's Hospital, Brisbane, Queensland, Australia.
¹³ Menzies Health Institute, Griffith University, Southport, Queensland, Australia.
¹⁴ Translational Research Institute, Woolloongabba, Queensland, Australia.

Abstract

Background: Despite aggressive treatment, more than 90% of glioblastoma (GBM) patients experience recurrences. GBM response to therapy is currently assessed by imaging techniques and tissue biopsy. However, difficulties with these methods may cause misinterpretation of treatment outcomes. Currently, no validated therapy response biomarkers are available for monitoring GBM progression. Metabolomics holds potential as a complementary tool to improve the interpretation of therapy responses to help in clinical interventions for GBM patients.

Methods: Saliva and blood from GBM patients were collected pre and postoperatively. Patients were stratified conforming their progression-free survival (PFS) into favourable or unfavourable clinical outcomes (>9 months or PFS ≤ 9 months, respectively). Analysis of saliva (whole-mouth and oral rinse) and plasma samples was conducted utilising LC-QqQ-MS and LC-QTOF-MS to determine the metabolomic and lipidomic profiles. The data were investigated using univariate and multivariate statistical analyses and graphical LASSO-based graphic network analyses.

Results: Altogether, 151 metabolites and 197 lipids were detected within all saliva and plasma samples. Among the patients with unfavourable outcomes, metabolites such as cyclic-AMP, 3-hydroxy-kynurenine, dihydroorotate, UDP and cis-aconitate were elevated, compared to patients with favourable outcomes during pre-and post-surgery. These metabolites showed to impact the pentose phosphate and Warburg effect pathways. The lipid profile of patients who experienced unfavourable outcomes revealed a higher heterogeneity in the abundance of lipids and fewer associations between markers in contrast to the favourable outcome group.

Conclusion: Our findings indicate that changes in salivary and plasma metabolites in GBM patients can potentially be employed as less invasive prognostic biomarkers/biomarker panel but validation with larger cohorts is required.

Keywords: blood; glioblastoma; lipids; metabolites; metabolomics; saliva.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Biomarkers
Brain Neoplasms* / pathology
Glioblastoma* / pathology
Humans
Lipids
Metabolomics
Pilot Projects
Saliva

Substances

Biomarkers
Lipids