SMR-guided molecular subtyping and machine learning model reveals novel prognostic biomarkers and therapeutic targets in non-small cell lung adenocarcinoma

Abstract Non-small cell lung adenocarcinoma (LUAD) is a markedly heterogeneous disease, with its underlying molecular mechanisms and prognosis prediction presenting ongoing challenges. In this study, we integrated data from multiple public datasets, including TCGA, GSE31210, and GSE13213, encompassi...

وصف كامل

التفاصيل البيبلوغرافية
الحاوية / القاعدة:Scientific Reports
المؤلفون الرئيسيون: Baozhen Wang, Yichen Yin, Anqi Wang, Weidi Liu, Jing Chen, Tao Li
التنسيق: مقال
اللغة:الإنجليزية
منشور في: Nature Portfolio 2025-01-01
الموضوعات:
Non-small cell lung adenocarcinoma, LUAD
Mendelian randomization
Molecular subtypes
Machine learning prognostic model
Multi-omics integrative analysis
الوصول للمادة أونلاين:https://doi.org/10.1038/s41598-025-85471-8

الانترنت

https://doi.org/10.1038/s41598-025-85471-8

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