ReviewOncology letters2026
Advances in cerebrospinal fluid biomarkers for the diagnosis, treatment and monitoring of leptomeningeal metastases (Review).
Review in Oncology letters, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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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Authors and funding
7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Leptomeningeal metastasis (LM) is an aggressive complication characterized by the dissemination of malignant cells to the leptomeninges, typically resulting in rapid neurological deterioration and poor prognosis. Clinical diagnosis and management are impeded by non-specific symptoms and the limited sensitivity of conventional cerebrospinal fluid (CSF) cytology. Consequently, CSF biomarkers have emerged as critical tools for diagnosis, treatment monitoring and prognostic evaluation. The present review summarizes recent advancements in CSF biomarkers, categorizing them into proteins, nucleic acids and metabolites. These biomarkers enhance diagnostic accuracy, facilitate longitudinal disease tracking and assess therapeutic efficacy. Despite notable progress, challenges persist regarding biomarker sensitivity, specificity and standardization. Furthermore, the potential of multi-omics technologies and single-cell analysis is discussed as a pathway for discovering novel biomarkers to enable the precise stratification and personalized management of LM.
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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 Socratic graph.