Lung adenocarcinoma prognosis marker and model

By constructing a prognostic model for lung adenocarcinoma that comprehensively considers the PCD pathway and lncRNA, the problem of insufficient predictive accuracy of existing models in the Chinese population has been solved, enabling more efficient prognostic assessment and personalized treatment support.

CN120700141BActive Publication Date: 2026-06-02ZHEJIANG UNIV
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
ZHEJIANG UNIV
Filing Date
2025-05-20
Publication Date
2026-06-02

AI Technical Summary

Technical Problem

Existing prognostic models for lung adenocarcinoma fail to effectively consider the entire programmed cell death (PCD) pathway and the role of long non-coding RNAs (lncRNAs), resulting in insufficient predictive accuracy and applicability, especially in the Chinese population where there is a lack of effective prognostic models.

Method used

A prognostic model based on PCD-related mRNAs and lncRNAs was constructed, taking into account the molecular characteristics of various PCD pathways. The expression scores of PCD-related mRNAs and lncRNAs were established using a random survival forest (RSF) model. The prognostic scoring formula PTS=I1×PMS+I2×PLS was constructed using a multivariate Cox regression model. The expression levels of biomarkers were detected by combining sequencing technology and nucleic acid hybridization technology.

Benefits of technology

It improves the accuracy and reliability of prognostic prediction for lung adenocarcinoma, provides support for personalized treatment plans for the Chinese population, and enhances the ability to classify and identify cancer patients.

✦ Generated by Eureka AI based on patent content.

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Abstract

The application provides a lung adenocarcinoma prognosis marker and model, a lung adenocarcinoma prognosis model based on programmed cell death (PCD) related mRNA and lncRNA is constructed, and the biological function of the lncRNA model in lung adenocarcinoma is explored through bioinformatics analysis and experiments. The prognosis model covers all PCD pathways and various molecules, has a robust prognosis prediction accuracy, and can provide potential molecular targets for personalized treatment. The method of the application comprehensively constructs a lung adenocarcinoma diagnosis model suitable for Chinese population by using PCD related mRNA and lncRNA, enhances the recognition ability of tumor patient classification from multiple aspects, improves the accuracy and reliability of prognosis prediction, can provide strong support for promoting the personalized treatment strategy of lung adenocarcinoma patients, and is suitable for popularization and application.
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