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Identification of prognostic biomarkers and immunotherapy response predictors in lung adenocarcinoma: integrative Mendelian randomization and machine learning analysis

   
@article{TLCR116510,
	author = {Chenlin Cao and Wan Qin and Ruoxuan Gong and Zhiyong Luo and Hong Zhang and Xianglin Yuan and Yanmei Zou and Shengling Fu and Hua Xiong},
	title = {Identification of prognostic biomarkers and immunotherapy response predictors in lung adenocarcinoma: integrative Mendelian randomization and machine learning analysis},
	journal = {Translational Lung Cancer Research},
	volume = {15},
	number = {4},
	year = {2026},
	keywords = {},
	abstract = {Lung adenocarcinoma (LUAD), the most prevalent and clinically heterogeneous form of lung cancer, lacks robust biomarkers for prognosis and immunotherapy response prediction. This study aimed to identify key prognostic genes and develop a predictive framework to guide personalized treatment strategies.},
	issn = {2226-4477},	url = {https://tlcr.amegroups.org/article/view/116510}
}