Metabolic remodeling in glioblastoma: a longitudinal multi-omics study

Monitoring tumor evolution and predicting survival using non-invasive liquid biopsy is an unmet need for glioblastoma patients. The era of proteomics and metabolomics blood analyzes, may help in this context. A case-control study was conducted. Patients were included in the GLIOPLAK trial (ClinicalTrials.gov Identifier: NCT02617745), a prospective bicentric study conducted between November 2015 and December 2022. Patients underwent biopsy alone and received radiotherapy and temozolomide. Blood samples were collected at three different time points: before and after concomitant radiochemotherapy, and at the time of tumor progression. Plasma samples from patients and controls were analyzed using metabolomics and proteomics, generating 371 omics features. Descriptive, differential, and predictive analyses were performed to assess the relationship between plasma omics feature levels and patient outcome. Diagnostic performance and longitudinal variations were also analyzed. The study included 67 subjects (34 patients and 33 controls). A significant differential expression of metabolites and proteins between patients and controls was observed. Predictive models using omics features showed high accuracy in distinguishing patients from controls. Longitudinal analysis revealed temporal variations in a few omics features including CD22, CXCL13, EGF, IL6, GZMH, KLK4, and TNFRSP6B. Survival analysis identified 77 omics features significantly associated with OS, with ERBB2 and ITGAV consistently linked to OS at all timepoints. Pathway analysis revealed dynamic oncogenic pathways involved in glioblastoma progression. This study provides insights into the potential of plasma omics features as biomarkers for glioblastoma diagnosis, progression and overall survival. Clinical implication should now be explored in dedicated prospective trials.

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Publication Details

Journal
Acta Neuropathologica Communications
Published
2024-10-12
DOI
https://doi.org/10.1186/s40478-024-01861-5
Citations
18
Primary Topic
Cancer, Hypoxia, and Metabolism
Type
article
Field-Weighted Citation Impact
5.13

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article

Metabolic remodeling in glioblastoma: a longitudinal multi-omics study

Frédéric Di Fiore, Carine Pilon, Franklin Ducatez, Soumeya Bekri et al.
18 citations
Acta Neuropathologica Communications
Cancer, Hypoxia, and Metabolism
5.13
article

Metabolic remodeling in glioblastoma: a longitudinal multi-omics study

Frédéric Di Fiore, Carine Pilon, Franklin Ducatez, Soumeya Bekri, Maxime Fontanilles, Arthur Daban, Abdellah Tebani, Thomas Plichet, Olivier Langlois, Isabelle Tennevet, Louis‐Ferdinand Pépin, Florent Marguet, Déborah Mokbel, Jean-David Heisbourg, Céline Lesueur, Cristina Alexandru
article en
18 citations

Abstract

Monitoring tumor evolution and predicting survival using non-invasive liquid biopsy is an unmet need for glioblastoma patients. The era of proteomics and metabolomics blood analyzes, may help in this context. A case-control study was conducted. Patients were included in the GLIOPLAK trial (ClinicalTrials.gov Identifier: NCT02617745), a prospective bicentric study conducted between November 2015 and December 2022. Patients underwent biopsy alone and received radiotherapy and temozolomide. Blood samples were collected at three different time points: before and after concomitant radiochemotherapy, and at the time of tumor progression. Plasma samples from patients and controls were analyzed using metabolomics and proteomics, generating 371 omics features. Descriptive, differential, and predictive analyses were performed to assess the relationship between plasma omics feature levels and patient outcome. Diagnostic performance and longitudinal variations were also analyzed. The study included 67 subjects (34 patients and 33 controls). A significant differential expression of metabolites and proteins between patients and controls was observed. Predictive models using omics features showed high accuracy in distinguishing patients from controls. Longitudinal analysis revealed temporal variations in a few omics features including CD22, CXCL13, EGF, IL6, GZMH, KLK4, and TNFRSP6B. Survival analysis identified 77 omics features significantly associated with OS, with ERBB2 and ITGAV consistently linked to OS at all timepoints. Pathway analysis revealed dynamic oncogenic pathways involved in glioblastoma progression. This study provides insights into the potential of plasma omics features as biomarkers for glioblastoma diagnosis, progression and overall survival. Clinical implication should now be explored in dedicated prospective trials.

Acta Neuropathologica CommunicationsVol. 12(1)
Inserm (FR), Normandie Université (FR), Laboratoire National Henri Becquerel (FR), Centre Hospitalier Universitaire de Rouen (FR), Centre Henri Becquerel (FR), Génomique du cancer et du cerveau, Université de Rouen Normandie (FR)
Advanced Remanufacturing and Technology Centre
Zero hunger
Openalex Percentile: Top 4%
Cancer, Hypoxia, and Metabolism
5.13
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