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Exploring biomarkers of MAPK pathway co-expression in lung adenocarcinoma and their functions based on machine learning algorithms and single-cell analysis

Rapid Communications

Exploring biomarkers of MAPK pathway co-expression in lung adenocarcinoma and their functions based on machine learning algorithms and single-cell analysis

Lin Mingkai
Zheng Ruoyi
Liang Peixian
Huang Jiayang
Ke Xintong
Zhang Wenjing
Shang Pei
Genes & Diseases第12卷, 第1期纸质出版 2025-01-01在线发表 2024-01-26
300

Nowadays, although the treatment and diagnostic approaches have been improved, lung adenocarcinoma (LUAD) is still the leading cause of cancer-related death in the world with overall survival of less than five years1. Diagnosis of LUAD in the early stage is still a challenge, resulting from that early symptoms are not obvious2, which leads to the fact that most patients eventually die from cancer progression and chemotherapy resistance. LUAD is reported to be associated with the MAPK pathway, however, the mechanism at the cellular and genetic levels has not been clearly elucidated. Therefore, functional exploration of LUAD- and MAPK pathway-related genes is essential for understanding the pathogenesis of LUAD and exploring therapeutic measures. Figure S1 illustrates the flowchart of this study.

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