ArticleNeuro-oncology advances
Leveraging the CSF proteome toward minimally-invasive diagnostics surveillance of brain malignancies.
Article in Neuro-oncology advances. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 14 papers, 1 of them a synthesis that pooled it.
What it found
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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.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.
- Is There a Role for Machine Learning in Liquid Biopsy for Brain Tumors? A Systematic Review.International journal of molecular sciences · 2023Pooled it
- A shared injury-homeostasis gradient in the human CSF proteome across neurological disease.Research square · 2026Article
- Urine and cerebrospinal fluid biomarkers for early glioma detection: a systematic review.Diagnostic and prognostic research · 2026Review
- Women in neurosurgical oncology: Mapping the milestones and shaping the future.Neuro-oncology advances · 2026Review
- Comparative evaluation of analytical methods for CSF proteomics.Clinical proteomics · 2025Article
- Review
- Review
- A hitchhiker's guide to cerebrospinal fluid biomarkers for neuro-oncology.Neuro-oncology · 2025Review
- A field resource for the glioma cerebrospinal fluid proteome: Impacts of resection and location on biomarker discovery.Neuro-oncology · 2025Article
- Immune checkpoint inhibitors for glioblastoma: emerging science, clinical advances, and future directions.Journal of neuro-oncology · 2025Review
- Leptomeningeal metastatic disease: new frontiers and future directions.Nature reviews. Clinical oncology · 2025Review
- Establishing the utility of multi-platform liquid biopsy by integrating the CSF methylome and proteome in CNS tumours.Journal of neuro-oncology · 2024Article
- Cerebrospinal fluid D-2-hydroxyglutarate for IDH-mutant glioma monitoring.Neuro-oncology advancesArticle
- Cerebrospinal fluid protein biomarkers are associated with response to multiagent intraventricular chemotherapy in patients with CNS lymphoma.Neuro-oncology advancesArticle
Corrections and comments
- Erratum issued
Authors and funding
13 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Diagnosis and prognostication of intra-axial brain tumors hinges on invasive brain sampling, which carries risk of morbidity. Minimally-invasive sampling of proximal fluids, also known as liquid biopsy, can mitigate this risk. Our objective was to identify diagnostic and prognostic cerebrospinal fluid (CSF) proteomic signatures in glioblastoma (GBM), brain metastases (BM), and primary central nervous system lymphoma (CNSL). Methods: CSF samples were retrospectively retrieved from the Penn State Neuroscience Biorepository and profiled using shotgun proteomics. Proteomic signatures were identified using machine learning classifiers and survival analyses. Results: Using 30 µL CSF volumes, we recovered 755 unique proteins across 73 samples. Proteomic-based classifiers identified malignancy with area under the receiver operating characteristic (AUROC) of 0.94 and distinguished between tumor entities with AUROC ≥0.95. More clinically relevant triplex classifiers, comprised of just three proteins, distinguished between tumor entities with AUROC of 0.75-0.89. Novel biomarkers were identified, including GAP43, TFF3 and CACNA2D2, and characterized using single cell RNA sequencing. Survival analyses validated previously implicated prognostic signatures, including blood-brain barrier disruption. Conclusions: Reliable classification of intra-axial malignancies using low CSF volumes is feasible, allowing for longitudinal tumor surveillance.
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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.