ArticleNeuro-oncology advances
Multiomics profiling of paired primary and recurrent glioblastoma patient tissues.
Article in Neuro-oncology advances. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 21 citations in OpenAlex.
- Comparative cross-methodological analysis of the IDH-wildtype glioblastoma tumor microenvironment.Journal of cancer research and clinical oncology · 2026Article
- Atypical behavior of recurrent glioblastoma tumor cells with a highly adherent radial glial phenotype.CNS oncology · 2025Article
- Investigative needle core biopsies support multimodal deep-data generation in glioblastoma.Nature communications · 2025Article
- Personalising glioblastoma medicine: explant organoid applications, challenges and future perspectives.Acta neuropathologica communications · 2025Review
- Navigating Cancer Complexity: Integrative Multi-Omics Methodologies for Clinical Insights.Clinical Medicine Insights. Oncology · 2025Review
- Multidimensional analysis of matched primary and recurrent glioblastoma identifies contributors to tumor recurrence influencing time to relapse.Journal of neuropathology and experimental neurology · 2025Article
- Artificial intelligence (AI) and machine learning (ML) in precision oncology: a review on enhancing discoverability through multiomics integration.The British journal of radiology · 2023Review
- Pyk2/FAK Signaling Is Upregulated in Recurrent Glioblastoma Tumors in a C57BL/6/GL261 Glioma Implantation Model.International journal of molecular sciences · 2023Article
- Quantitative proteomic landscapes of primary and recurrent glioblastoma reveal a protumorigeneic role for FBXO2-dependent glioma-microenvironment interactions.Neuro-oncology · 2023Article
- Slow Off-Rate Modified Aptamer (SOMAmer) Proteomic Analysis of Patient-Derived Malignant Glioma Identifies Distinct Cellular Proteomes.International journal of molecular sciences · 2021Article
- Integrative Multi-Omics Approaches in Cancer Research: From Biological Networks to Clinical Subtypes.Molecules and cells · 2021Review
- A Systems Approach to Brain Tumor Treatment.Cancers · 2021Review
- Tumor resection in glioblastoma mouse models: Surgical techniques and translational potential.Neuro-oncology advancesReview
Corrections and comments
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Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDespite maximal therapy with surgery, chemotherapy, and radiotherapy, glioblastoma (GBM) patients have a median survival of only 15 months. Almost all patients inevitably experience symptomatic tumor recurrence. A hallmark of this tumor type is the large heterogeneity between patients and within tumors itself which relates to the failure of standardized tumor treatment. In this study, tissue samples of paired primary and recurrent GBM tumors were investigated to identify individual factors related to tumor progression.
methodsPaired primary and recurrent GBM tumor tissues from 8 patients were investigated with a multiomics approach using transcriptomics, proteomics, and phosphoproteomics.
resultsIn the studied patient cohort, large variations between and within patients are observed for all omics analyses. A few pathways affected at the different omics levels partly overlapped if patients are analyzed at the individual level, such as synaptogenesis (containing the SNARE complex) and cholesterol metabolism. Phosphoproteomics revealed increased STMN1(S38) phosphorylation as part of ERBB4 signaling. A pathway tool has been developed to visualize and compare different omics datasets per patient and showed potential therapeutic drugs, such as abobotulinumtoxinA (synaptogenesis) and afatinib (ERBB4 signaling). Afatinib is currently in clinical trials for GBM.
conclusionsA large variation on all omics levels exists between and within GBM patients. Therefore, it will be rather unlikely to find a drug treatment that would fit all patients. Instead, a multiomics approach offers the potential to identify affected pathways on the individual patient level and select treatment options.
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