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胶质母细胞瘤中的代谢重编程:一项纵向多组学研究。

Metabolic remodeling in glioblastoma: a longitudinal multi-omics study.

机构信息

INSERM U1245, Cancer and Brain Genomics, IRON group, Normandie Univ, UNIROUEN, Rouen, France.

Department of Medical Oncology, Cancer Centre Henri Becquerel, Rue d'Amiens, 76038, Rouen, France.

出版信息

Acta Neuropathol Commun. 2024 Oct 12;12(1):162. doi: 10.1186/s40478-024-01861-5.

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.

摘要

利用非侵入性液体活检监测肿瘤演变和预测生存是胶质母细胞瘤患者的未满足需求。蛋白质组学和代谢组学血液分析的时代可能有助于解决这一问题。进行了一项病例对照研究。患者纳入 GLIOPLAK 试验(ClinicalTrials.gov 标识符:NCT02617745),这是一项于 2015 年 11 月至 2022 年 12 月在两个中心进行的前瞻性研究。患者仅接受活检,并接受放疗和替莫唑胺治疗。在三个不同时间点采集血液样本:同期放化疗前后和肿瘤进展时。使用代谢组学和蛋白质组学分析患者和对照者的血浆样本,生成 371 个组学特征。进行描述性、差异和预测分析,以评估血浆组学特征水平与患者结局之间的关系。还分析了诊断性能和纵向变化。该研究纳入了 67 名受试者(34 名患者和 33 名对照者)。患者和对照者之间的代谢物和蛋白质表达存在显著差异。使用组学特征的预测模型在区分患者和对照者方面具有很高的准确性。纵向分析显示,少数组学特征(包括 CD22、CXCL13、EGF、IL6、GZMH、KLK4 和 TNFRSP6B)存在时间变化。生存分析确定了 77 个与 OS 显著相关的组学特征,其中 ERBB2 和 ITGAV 在所有时间点均与 OS 相关。通路分析显示,涉及胶质母细胞瘤进展的动态致癌通路。本研究为血浆组学特征作为胶质母细胞瘤诊断、进展和总生存期的生物标志物提供了新的见解。现在应在专门的前瞻性试验中探讨其临床意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7e38/11470540/8087bec16646/40478_2024_1861_Fig1_HTML.jpg

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