ArticleCancer research2020
Localized Metabolomic Gradients in Patient-Derived Xenograft Models of Glioblastoma.
Article in Cancer research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
57 citing papers in PubMed, 96 citations in OpenAlex.
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- Crosstalk in the brain tumor microenvironment: mechanisms, therapeutic strategies, and clinical advances.Military Medical Research · 2026Review
- Knockdown of SUCLG2 inhibits glioblastoma proliferation and promotes apoptosis through LMNA acetylation and the mediation of H4K16la lactylation.Cell death discovery · 2025Article
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- Metabolic remodeling and its hidden heterogeneity in uterine fibroids: comprehensive metabolomic profiling and mass spectrometry imaging.Metabolomics : Official journal of the Metabolomic Society · 2025Article
- Insight into pericytes in glioblastoma angiogenesis: In vivo tracking by two-photon microscopy and proteomic profiling.Animal models and experimental medicine · 2025Article
- From Multi-Omics to Visualization and Beyond: Bridging Micro and Macro Insights in CAR-T Cell Therapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Review
- TRAF3 loss protects glioblastoma cells from lipid peroxidation and immune elimination via dysregulated lipid metabolism.The Journal of clinical investigation · 2025Article
- Cancer 3D Models: Essential Tools for Understanding and Overcoming Drug Resistance.Oncology research · 2025Review
- Recent Applications of Artificial Intelligence and Related Technical Challenges in MALDI MS and MALDI-MSI: A Mini Review.Mass spectrometry (Tokyo, Japan) · 2025Review
- Single-cell and spatial omics unravel the spatiotemporal biology of tumour border invasion and haematogenous metastasis.Clinical and translational medicine · 2024Review
- Deciphering breast cancer dynamics: insights from single-cell and spatial profiling in the multi-omics era.Biomarker research · 2024Review
- Chrysomycin A Reshapes Metabolism and Increases Oxidative Stress to Hinder Glioblastoma Progression.Marine drugs · 2024Article
- Frontiers in Mass Spectrometry-Based Spatial Metabolomics: Current Applications and Challenges in the Context of Biomedical Research.Trends in analytical chemistry : TRAC · 2024Article
- Mass spectrometry imaging methods for visualizing tumor heterogeneity.Current opinion in biotechnology · 2024Review
- Multiscale biochemical mapping of the brain through deep-learning-enhanced high-throughput mass spectrometry.Nature methods · 2024Article
- Simultaneously quantifying hundreds of acylcarnitines in multiple biological matrices within ten minutes using ultrahigh-performance liquid-chromatography and tandem mass spectrometry.Journal of pharmaceutical analysis · 2024Article
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15 authors at 8 institutions in 1 country.
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Abstract
Glioblastoma (GBM) is increasingly recognized as a disease involving dysfunctional cellular metabolism. GBMs are known to be complex heterogeneous systems containing multiple distinct cell populations and are supported by an aberrant network of blood vessels. A better understanding of GBM metabolism, its variation with respect to the tumor microenvironment, and resulting regional changes in chemical composition is required. This may shed light on the observed heterogeneous drug distribution, which cannot be fully described by limited or uneven disruption of the blood-brain barrier. In this work, we used mass spectrometry imaging (MSI) to map metabolites and lipids in patient-derived xenograft models of GBM. A data analysis workflow revealed that distinctive spectral signatures were detected from different regions of the intracranial tumor model. A series of long-chain acylcarnitines were identified and detected with increased intensity at the tumor edge. A 3D MSI dataset demonstrated that these molecules were observed throughout the entire tumor/normal interface and were not confined to a single plane. mRNA sequencing demonstrated that hallmark genes related to fatty acid metabolism were highly expressed in samples with higher acylcarnitine content. These data suggest that cells in the core and the edge of the tumor undergo different fatty acid metabolism, resulting in different chemical environments within the tumor. This may influence drug distribution through changes in tissue drug affinity or transport and constitute an important consideration for therapeutic strategies in the treatment of GBM. SIGNIFICANCE: GBM tumors exhibit a metabolic gradient that should be taken into consideration when designing therapeutic strategies for treatment.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.