Identification Cuproptosis-related Genes Signature to Predict the Prognosis of Lung Cancer
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View abstract on PubMed
Summary
This summary is machine-generated.This study reveals a new way to predict lung adenocarcinoma (LUAD) outcomes using cuproptosis-related genes. A five-gene signature helps identify patient risk and guides immunotherapy strategies.
Area Of Science
- Oncology
- Molecular Biology
- Immunology
Background
- Cuproptosis, a copper-driven cell death, is linked to cancer, but its role in lung adenocarcinoma (LUAD) prognosis is unknown.
- Understanding cuproptosis-related genes (CuRGs) is crucial for developing new LUAD biomarkers and therapeutic targets.
Purpose Of The Study
- To investigate the prognostic value of 19 cuproptosis-related genes (CuRGs) in lung adenocarcinoma (LUAD).
- To develop and validate a CuRG-based prognostic signature for LUAD patients.
- To explore the relationship between CuRG subtypes and the tumor immune microenvironment.
Main Methods
- Utilized multiple public datasets for expression analysis of 19 CuRGs in LUAD.
- Applied consensus clustering to identify molecular subtypes and LASSO-Cox regression to build a prognostic risk signature (CuRG_score).
- Validated the CuRG_score using independent datasets and analyzed immune cell infiltration and immunophenoscore (IPS).
Main Results
- Identified two distinct LUAD molecular subtypes with differing clinical outcomes and immune profiles.
- Developed a five-gene CuRG_score that accurately predicts overall survival in LUAD patients (AUCs: 0.761, 0.618, 0.642).
- High-risk patients showed immunosuppressive features, while low-risk patients may respond better to immunotherapy.
Conclusions
- A novel CuRG-based molecular signature serves as a robust prognostic predictor for LUAD.
- The CuRG_score can guide personalized immunotherapy strategies for LUAD patients.
- Cuproptosis-related genes offer potential therapeutic targets and biomarkers for LUAD management.
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