Maxime Fontanilles, Jean-David Heisbourg, Arthur Daban, Frederic Di Fiore, Louis-Ferdinand Pépin, Florent Marguet, Olivier Langlois, Cristina Alexandru, Isabelle Tennevet, Franklin Ducatez, Carine Pilon, Thomas Plichet, Déborah Mokbel, Céline Lesueur, Soumeya Bekri, Abdellah Tebani
{"title":"胶质母细胞瘤的代谢重塑:一项纵向多组学研究。","authors":"Maxime Fontanilles, Jean-David Heisbourg, Arthur Daban, Frederic Di Fiore, Louis-Ferdinand Pépin, Florent Marguet, Olivier Langlois, Cristina Alexandru, Isabelle Tennevet, Franklin Ducatez, Carine Pilon, Thomas Plichet, Déborah Mokbel, Céline Lesueur, Soumeya Bekri, Abdellah Tebani","doi":"10.1186/s40478-024-01861-5","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":6914,"journal":{"name":"Acta Neuropathologica Communications","volume":"12 1","pages":"162"},"PeriodicalIF":6.2000,"publicationDate":"2024-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11470540/pdf/","citationCount":"0","resultStr":"{\"title\":\"Metabolic remodeling in glioblastoma: a longitudinal multi-omics study.\",\"authors\":\"Maxime Fontanilles, Jean-David Heisbourg, Arthur Daban, Frederic Di Fiore, Louis-Ferdinand Pépin, Florent Marguet, Olivier Langlois, Cristina Alexandru, Isabelle Tennevet, Franklin Ducatez, Carine Pilon, Thomas Plichet, Déborah Mokbel, Céline Lesueur, Soumeya Bekri, Abdellah Tebani\",\"doi\":\"10.1186/s40478-024-01861-5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>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). 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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.
期刊介绍:
"Acta Neuropathologica Communications (ANC)" is a peer-reviewed journal that specializes in the rapid publication of research articles focused on the mechanisms underlying neurological diseases. The journal emphasizes the use of molecular, cellular, and morphological techniques applied to experimental or human tissues to investigate the pathogenesis of neurological disorders.
ANC is committed to a fast-track publication process, aiming to publish accepted manuscripts within two months of submission. This expedited timeline is designed to ensure that the latest findings in neuroscience and pathology are disseminated quickly to the scientific community, fostering rapid advancements in the field of neurology and neuroscience. The journal's focus on cutting-edge research and its swift publication schedule make it a valuable resource for researchers, clinicians, and other professionals interested in the study and treatment of neurological conditions.