Lung cancer soft meningeal metastasis marker and application thereof
By detecting specific biomarkers in cerebrospinal fluid and constructing machine learning models, the diagnostic challenge of leptomeningeal metastasis has been solved, improving the diagnostic accuracy and sensitivity of leptomeningeal metastasis in solid tumors such as lung cancer, and providing a more reliable diagnostic tool.
Patent Information
- Application Number
- CN202511731380.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-24
- Publication Date
- 2026-02-13
AI Technical Summary
Current technologies are insufficient for effectively diagnosing and monitoring leptomeningeal metastases, especially those caused by solid tumors such as lung cancer, breast cancer, gastric cancer, and melanoma, leading to difficulties in clinical diagnosis and complex treatment options.
Using biomarkers such as Hydroxyphenyllactic acid, Betaine, 3-Methoxytyrosine, L-Kynurenine, 1-Methylguanosine, and 2-Hydroxyethanesulfonate, combined with targeted or non-targeted techniques such as nuclear magnetic resonance, chromatography, spectroscopy, and mass spectrometry, a machine learning algorithm diagnostic model was constructed to diagnose leptomeningeal metastasis by detecting the biomarker levels in cerebrospinal fluid samples.
It has improved the diagnostic accuracy and sensitivity of leptomeningeal metastasis, especially the diagnostic efficacy of lung cancer leptomeningeal metastasis, provided more reliable diagnostic tools and methods, and reduced the risk of misdiagnosis.