Immunoinfiltration Analysis of Mitochondrial Damage-Related Genes in Lung Adenocarcinoma and Construction of a Classification and Prognostic Model Integrated With WGCNA and Machine Learning Algorithms.

Journal: Cancer medicine

PMID: 39823156

Abstract

BACKGROUND: Lung adenocarcinoma (LUAD) exhibits molecular heterogeneity, with mitochondrial damage affecting progression. The relationship between mitochondrial damage and immune infiltration, and Weighted Gene Co-expression Network Analysis (WGCNA)-derived biomarkers for LUAD classification and prognosis, remains unexplored.

Authors

Jirong Zhang

Department of Neurosurgery, Shengli Oilfield Central Hospital of Binzhou Medical University, Dongying, Shandong, China.
Lin Lin

Central Laboratory, The First Affiliated Hospital of Xiamen University, Xiamen, China, zhibinli33@163.com, liusuhuan@xmu.edu.cn.

Keywords

Adenocarcinoma of Lung Biomarkers, Tumor Computational Biology Databases, Genetic Gene Expression Profiling Gene Expression Regulation, Neoplastic Gene Regulatory Networks Humans Lung Neoplasms Machine Learning Mitochondria Prognosis

External Resources

View on PubMed Access via DOI PubMed (39823156)

Immunoinfiltration Analysis of Mitochondrial Damage-Related Genes in Lung Adenocarcinoma and Construction of a Classification and Prognostic Model Integrated With WGCNA and Machine Learning Algorithms.

Abstract

Authors

Keywords

External Resources

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