A marker group for kidney cancer screening and diagnosis and use thereof
By combining biomarker combinations and mass spectrometry to detect peptide biomarkers in serum, and integrating machine learning algorithms, the problem of insufficient sensitivity and specificity in the early diagnosis and screening of renal cell carcinoma has been solved, achieving efficient diagnosis and early screening of renal cell carcinoma.
Patent Information
- Application Number
- CN202511736154.1
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- Filing Date
- 2025-11-25
- Publication Date
- 2026-04-14
- Estimated Expiration
- 2045-11-25
AI Technical Summary
Current technologies lack highly sensitive and specific biomarkers for the early diagnosis and screening of renal cell carcinoma. Imaging examinations pose radiation risks and are subject to operational dependence, while liquid biopsy methods suffer from inconsistencies and difficulty in separating viable CTCs.
A biomarker set, including peptides with specific sequences, is used to detect peptide biomarkers in serum using mass spectrometry. Combined with machine learning algorithms, a diagnostic model is constructed to achieve auxiliary diagnosis and early screening of renal cell carcinoma.
It improves the sensitivity and specificity of renal cell carcinoma diagnosis, outperforming existing imaging examinations and multi-gene methylation analysis, while reducing radiation risk and operational dependence, and improving the accuracy of early screening.