ArticleGenes2022
Identification of a Four-Gene Signature Associated with the Prognosis Prediction of Lung Adenocarcinoma Based on Integrated Bioinformatics Analysis.
Article in Genes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed.
- A Decade-Old Atlas of TMEM (Transmembrane) Protein Family in Lung Cancer: Lessons Learnt and Future Directions.International journal of molecular sciences · 2026Review
- Identification of potential biomarkers for lung cancer using integrated bioinformatics and machine learning approaches.PloS one · 2025Article
- Article
- Single-cell transcriptomics and machine learning unveil ferroptosis features in tumor-associated macrophages: Prognostic model and therapeutic strategies for lung adenocarcinoma.Frontiers in pharmacology · 2025Article
- Exploring the mechanism of ellagic acid against gastric cancer based on bioinformatics analysis and network pharmacology.Journal of cellular and molecular medicine · 2023Article
- A novel hypoxia-associated gene signature for prognosis prediction in head and neck squamous cell carcinoma.BMC oral health · 2023Article
- Identification of potential prognostic markers for lung adenocarcinoma using comprehensive analysis.Molecular medicine reports · 2023Article
- Selenium-binding protein 1 inhibits malignant progression and induces apoptosis via distinct mechanisms in non-small cell lung cancer.Cancer medicine · 2023Article
- Identification of New Prognostic Genes and Construction of a Prognostic Model for Lung Adenocarcinoma.Diagnostics (Basel, Switzerland) · 2023Article
- Estimation of hub genes and exploration of multi-omics level alterations in the landscape of lung adenocarcinoma.American journal of translational research · 2023Article
- NetSHy: network summarization via a hybrid approach leveraging topological properties.Bioinformatics (Oxford, England) · 2023Article
- Aberrant Expression and Prognostic Potential of IL-37 in Human Lung Adenocarcinoma.Biomedicines · 2022Article
- Construction of a predictive model for immunotherapy efficacy in lung squamous cell carcinoma based on the degree of tumor-infiltrating immune cells and molecular typing.Journal of translational medicine · 2022Article
- Chordin-Like 1 Regulates Epithelial-to-Mesenchymal Transition and MetastasisFrontiers in oncology · 2022Article
- Identification of N7-methylguanosine related signature for prognosis and immunotherapy efficacy prediction in lung adenocarcinoma.Frontiers in medicine · 2022Article
- Artificial intelligence predictive system of individual survival rate for lung adenocarcinoma.Computational and structural biotechnology journal · 2022Article
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Authors and funding
7 authors.
Funding
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Abstract
Lung adenocarcinoma (LUAD) is often diagnosed at an advanced stage, so it is necessary to identify potential biomarkers for the early diagnosis and prognosis of LUAD. In our study, a gene co-expression network was constructed using weighted gene co-expression network analysis (WGCNA) in order to obtain the key modules and genes correlated with LUAD prognosis. Four hub genes (HLF, CHRDL1, SELENBP1, and TMEM163) were screened out using least absolute shrinkage and selection operator (LASSO)-Cox regression analysis; then, a prognostic model was established for predicting overall survival (OS) based on these four hub genes..Furthermore, the prognostic values of this four-gene signature were verified in four validation sets (GSE26939, GSE31210, GSE72094, and TCGA-LUAD) as well as in the GEPIA database. To assess the prognostic values of hub genes, receiver operating characteristic (ROC) curves were constructed and a nomogram was created. We found that a higher expression of four hub genes was associated with a lower risk of patient death. In a training set, it was demonstrated that this four-gene signature was a better prognostic factor than clinical factors such as age and stage of disease. Moreover, our results revealed that these four genes were suppressor factors of LUAD and that their high expression was associated with a lower risk of death. In summary, we demonstrated that this four-gene signature could be a potential prognostic factor for LUAD patients. These findings provide a theoretical basis for exploring potential biomarkers for LUAD prognosis prediction in the future.
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