A pilot study: Metabolic profiling of plasma and saliva samples from newly diagnosed glioblastoma patients
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. Cu...
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| Format: | Article |
| Language: | English |
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Wiley
2023-05-01
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| Series: | Cancer Medicine |
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| Online Access: | https://doi.org/10.1002/cam4.5857 |
| _version_ | 1797810448897146880 |
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| author | Juliana Muller Bark Avinash V. Karpe James D. Doecke Paul Leo Rosalind L. Jeffree Benjamin Chua Bryan W. Day David J. Beale Chamindie Punyadeera |
| author_facet | Juliana Muller Bark Avinash V. Karpe James D. Doecke Paul Leo Rosalind L. Jeffree Benjamin Chua Bryan W. Day David J. Beale Chamindie Punyadeera |
| author_sort | Juliana Muller Bark |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-13T07:07:57Z |
| format | Article |
| id | doaj.art-bf2d3199e1af4d7b9ff4a2375a3e5b34 |
| institution | Directory Open Access Journal |
| issn | 2045-7634 |
| language | English |
| last_indexed | 2024-03-13T07:07:57Z |
| publishDate | 2023-05-01 |
| publisher | Wiley |
| record_format | Article |
| series | Cancer Medicine |
| spelling | doaj.art-bf2d3199e1af4d7b9ff4a2375a3e5b342023-06-06T07:30:47ZengWileyCancer Medicine2045-76342023-05-011210114271143710.1002/cam4.5857A pilot study: Metabolic profiling of plasma and saliva samples from newly diagnosed glioblastoma patientsJuliana Muller Bark0Avinash V. Karpe1James D. Doecke2Paul Leo3Rosalind L. Jeffree4Benjamin Chua5Bryan W. Day6David J. Beale7Chamindie Punyadeera8Faculty of Health, Centre for Biomedical Technologies School of Biomedical Sciences, Queensland University of Technology Brisbane Queensland AustraliaEnvironment, Commonwealth Scientific and Industrial Research Organization (CSIRO), Ecosciences Precinct Dutton Park Queensland AustraliaAustralian eHealth Research Centre, CSIRO. Level 7, Surgical Treatment and Rehabilitation Service – STARS Royal Brisbane and Women's Hospital Herston Queensland AustraliaFaculty of Health School of Biomedical Sciences, Queensland University of Technology Gardens Point Queensland AustraliaQIMR Berghofer Medical Research Institute Herston Queensland AustraliaFaculty of Medicine University of Queensland Herston Queensland AustraliaFaculty of Health School of Biomedical Sciences, Queensland University of Technology Gardens Point Queensland AustraliaEnvironment, Commonwealth Scientific and Industrial Research Organization (CSIRO), Ecosciences Precinct Dutton Park Queensland AustraliaSaliva and Liquid Biopsy Translational Laboratory Griffith Institute for Drug Discovery – Griffith University Brisbane Queensland AustraliaAbstract 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.https://doi.org/10.1002/cam4.5857bloodglioblastomalipidsmetabolitesmetabolomicssaliva |
| spellingShingle | Juliana Muller Bark Avinash V. Karpe James D. Doecke Paul Leo Rosalind L. Jeffree Benjamin Chua Bryan W. Day David J. Beale Chamindie Punyadeera A pilot study: Metabolic profiling of plasma and saliva samples from newly diagnosed glioblastoma patients Cancer Medicine blood glioblastoma lipids metabolites metabolomics saliva |
| title | A pilot study: Metabolic profiling of plasma and saliva samples from newly diagnosed glioblastoma patients |
| title_full | A pilot study: Metabolic profiling of plasma and saliva samples from newly diagnosed glioblastoma patients |
| title_fullStr | A pilot study: Metabolic profiling of plasma and saliva samples from newly diagnosed glioblastoma patients |
| title_full_unstemmed | A pilot study: Metabolic profiling of plasma and saliva samples from newly diagnosed glioblastoma patients |
| title_short | A pilot study: Metabolic profiling of plasma and saliva samples from newly diagnosed glioblastoma patients |
| title_sort | pilot study metabolic profiling of plasma and saliva samples from newly diagnosed glioblastoma patients |
| topic | blood glioblastoma lipids metabolites metabolomics saliva |
| url | https://doi.org/10.1002/cam4.5857 |
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