Proteomic profiling of tumor microenvironment and prognosis risk prediction in stage I lung adenocarcinoma

•Mass spectrometry-based proteomics profiling of tumor microenvironment in LUAD.•The top enriched bio-functions were cellular movement and immune cell trafficking.•Five prognostic biomarkers (ADAM10, MIF, TEK, THBS2, and MAOA) were identified.•The risk score model effectively predicts recurrence and...

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Published in:Lung cancer (Amsterdam, Netherlands) Netherlands), 2024-05, Vol.191, p.107791, Article 107791
Main Authors: Lu, Yueh-Feng, Chang, Ya-Hsuan, Chen, Yi-Ju, Hsieh, Min-Shu, Lin, Mong-Wei, Hsu, Hsao-Hsun, Han, Chia-Li, Chen, Yu-Ju, Yu, Sung-Liang, Chen, Jin-Shing, Chen, Hsuan-Yu
Format: Article
Language:English
Subjects:
Adenocarcinoma of Lung - diagnosis
Adenocarcinoma of Lung - metabolism
Adenocarcinoma of Lung - mortality
Adenocarcinoma of Lung - pathology
Aged
Biomarkers, Tumor - metabolism
Computational Biology - methods
Female
Humans
Lung adenocarcinoma
Lung Neoplasms - diagnosis
Lung Neoplasms - metabolism
Lung Neoplasms - mortality
Lung Neoplasms - pathology
Male
Mass spectrometry
Middle Aged
Neoplasm Recurrence, Local - metabolism
Neoplasm Recurrence, Local - pathology
Neoplasm Staging
Prognosis
Prognostic biomarker
Proteomic
Proteomics - methods
Taiwan - epidemiology
Tumor Microenvironment
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Summary:•Mass spectrometry-based proteomics profiling of tumor microenvironment in LUAD.•The top enriched bio-functions were cellular movement and immune cell trafficking.•Five prognostic biomarkers (ADAM10, MIF, TEK, THBS2, and MAOA) were identified.•The risk score model effectively predicts recurrence and survival outcomes. With the increasing popularity of CT screening, more cases of early-stage lung cancer are being diagnosed. However, 24.5% of stage I non-small-cell lung cancer (NSCLC) patients still experience treatment failure post-surgery. Biomarkers to predict lung cancer patients at high risk of recurrence are needed. We collected protein mass spectrometry data from the Taiwan Lung Cancer Moonshot Project and performed bioinformatics analysis on proteins with differential expressions between tumor and adjacent normal tissues in 74 stage I lung adenocarcinoma (LUAD) cases, aiming to explore the tumor microenvironment related prognostic biomarkers. Findings were further validated in 6 external cohorts. The analysis of differentially expressed proteins revealed that the most enriched categories of diseases and biological functions were cellular movement, immune cell trafficking, and cancer. Utilizing proteomic profiling of the tumor microenvironment, we identified five prognostic biomarkers (ADAM10, MIF, TEK, THBS2, MAOA). We then developed a risk score model, which independently predicted recurrence-free survival and overall survival in stage I LUAD. Patients with high risk scores experienced worse recurrence-free survival (adjusted hazard ratio = 8.28, p 
ISSN:0169-5002
1872-8332
1872-8332
DOI:10.1016/j.lungcan.2024.107791