一种检测肺腺癌EGFR突变的基因组合物及其应用
By detecting the expression levels of genes such as CST5, ENPP3, FNDC5, GLIS2, IFNLR1, LRRC31, PSPH, and TNFRSF10B in patients with lung adenocarcinoma, a scoring model was constructed. This solved the problems of high cost and cumbersome procedures in the existing technology for detecting EGFR mutations in lung adenocarcinoma, achieving high sensitivity and high specificity detection and supporting personalized treatment.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- ZHONGSHAN HOSPITAL FUDAN UNIV
- Filing Date
- 2022-11-09
- Publication Date
- 2026-07-17
AI Technical Summary
Existing methods for detecting EGFR mutations in lung adenocarcinoma are costly and cumbersome, lacking highly sensitive and specific detection methods, making it difficult to achieve personalized treatment.
The expression levels of genes such as CST5, ENPP3, FNDC5, GLIS2, IFNLR1, LRRC31, PSPH, and TNFRSF10B were detected. A scoring model was used to score the expression levels and determine the presence of EGFR mutations. The scoring model was constructed using Lasso regression and logistic regression to detect EGFR mutations in lung adenocarcinoma.
It achieves a highly efficient, specific, and applicable detection method. Through the scoring model of the detection model, and through the application of the detection model, it provides a highly sensitive, specific, and applicable detection means. The detection model can detect EGFR mutations in lung adenocarcinoma with high sensitivity and high specificity, high cost performance, and support for personalized treatment.
Smart Images
Figure CN115910204B_ABST