ArticleNeuro-oncology advances
Utility of cerebrospinal fluid circulating tumor cell quantification and next-generation sequencing in patients with suspicion for leptomeningeal disease.
Article in Neuro-oncology advances. 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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Abstract
Background: Leptomeningeal disease (LMD) is characterized by the spread of cancer to the leptomeninges and cerebrospinal fluid (CSF) and is associated with poor survival. Diagnosing LMD is challenging, as traditional methods such as MRI and CSF cell cytology demonstrate variable sensitivity. This study aims to explore the diagnostic potential of CSF circulating tumor cell (CTC) quantification for LMD in conjunction with current standards. Methods: This retrospective case series includes 12 patients with suspected LMD who underwent CSF analysis with the CNSide assay for CTC quantification and next-generation sequencing (NGS), alongside MRI and CSF cytology. Relying on a composite definition of LMD-positive, the diagnostic performance of CTC quantification was assessed. Results: Of 12 patients evaluated for LMD with CNSide, 11 were found to have brain metastases (BM). Lung carcinoma was the most common primary cancer (4/12). Nine patients were deemed LMD-positive based on clinical criteria: 7/9 had a preceding brain metastasis diagnosis, while 2/9 co-presented with LMD and BM. CNSide detected CTCs in 7/12 patients (7/9 of those with LMD) and influenced clinical decision-making by guiding chemotherapy selection and prompting proton craniospinal irradiation. Of the three patients deemed LMD-negative with clinical criteria, all three had negative results on the CNSide assay. The CNSide assay demonstrated a sensitivity of 77.8%, specificity of 100%, and overall accuracy of 83.3%. Conclusion: The integration of CTC quantification with next-generation sequencing (NGS) can be a valuable adjunct to cell cytology in diagnosing leptomeningeal disease. CSF liquid biopsy may provide earlier detection and inform treatment decisions, ultimately improving patient outcomes.
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