ArticleCancer cell international2019
A novel 4-gene signature for overall survival prediction in lung adenocarcinoma patients with lymph node metastasis.
Article in Cancer cell international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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39 citing papers in PubMed.
- Evidence for PDZ-Binding Kinase in Lung Disease With an Emphasis on PAH.Pulmonary circulation · 2026Review
- Single-cell profiling reveals FAM117A as a key regulator linking macrophage-epithelial crosstalk with the progression of lung adenocarcinoma.Experimental hematology & oncology · 2026Article
- Integrated multi-omics analysis and experimental investigation of mitochondrial dynamics-related genes: molecular subtypes, immune landscape, and prognostic implications in lung adenocarcinoma.Frontiers in immunology · 2025Article
- Characterization of lncRNA and mRNA profiles in the process of repairing peripheral nerve defects with cell-matrixed nerve grafts.BMC genomics · 2024Article
- The bioinformatics analysis and experimental validation of the carcinogenic role of EXO1 in lung adenocarcinoma.Frontiers in oncology · 2024Article
- Genomic profiling of thymoma using a targeted high-throughput approach.Archives of medical science : AMS · 2024Article
- An eleven-gene risk model associated with lymph node metastasis predicts overall survival in lung adenocarcinoma.Scientific reports · 2023Article
- Identification and validation of a novel stress granules-related prognostic model in colorectal cancer.Frontiers in genetics · 2023Article
- Detection of key mRNAs in liver tissue of hepatocellular carcinoma patients based on machine learning and bioinformatics analysis.MethodsX · 2023Article
- Construction and validation of a prognostic model based on 11 lymph node metastasis-related genes for overall survival in endometrial cancer.Cancer medicine · 2022Article
- Article
- Identification of seven-gene marker to predict the survival of patients with lung adenocarcinoma using integrated multi-omics data analysis.Journal of clinical laboratory analysis · 2022Article
- Construction of Lymph Node Metastasis-Related Prognostic Model and Analysis of Immune Infiltration Mode in Lung Adenocarcinoma.Computational and mathematical methods in medicine · 2022Article
- A novel tumor mutational burden-based risk model predicts prognosis and correlates with immune infiltration in ovarian cancer.Frontiers in immunology · 2022Article
- The pattern of expression and prognostic value of key regulators for mFrontiers in genetics · 2022Article
- Expression and Potential Biomarkers of Regulators for M7G RNA Modification in Gliomas.Frontiers in neurology · 2022Article
- NEIL3 may act as a potential prognostic biomarker for lung adenocarcinoma.Cancer cell international · 2021Article
- Immunogenomic Gene Signature of Cell-Death Associated Genes with Prognostic Implications in Lung Cancer.Cancers · 2021Article
- Autophagy-Related Three-Gene Prognostic Signature for Predicting Survival in Esophageal Squamous Cell Carcinoma.Frontiers in oncology · 2021Article
- Identification of a Three-Gene Signature Based on Epithelial-Mesenchymal Transition of Lung Adenocarcinoma Through Construction and Validation of a Risk-Prediction Model.Frontiers in oncology · 2021Article
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8 authors.
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Abstract
backgroundLung adenocarcinoma (LUAD) patients experiencing lymph node metastasis (LNM) always exhibit poor clinical outcomes. A biomarker or gene signature that could predict survival in these patients would have a substantial clinical impact, allowing for earlier detection of mortality risk and for individualized therapy.
methodsWith the aim to identify a novel mRNA signature associated with overall survival, we analysed LUAD patients with LNM extracted from The Cancer Genome Atlas (TCGA). LASSO Cox regression was applied to build the prediction model. An external cohort was applied to validate the prediction model.
resultsWe identified a 4-gene signature that could effectively stratify a high-risk subset of these patients, and time-dependent receiver operating characteristic (tROC) analysis indicated that the signature had a powerful predictive ability. Gene Set Enrichment Analysis (GSEA) showed that the high-risk subset was mainly associated with important cancer-related hallmarks. Moreover, a predictive nomogram was established based on the signature integrated with clinicopathological features. Lastly, the signature was validated by an external cohort from Gene Expression Omnibus (GEO).
conclusionIn summary, we developed a robust mRNA signature as an independent factor to effectively classify LUAD patients with LNM into low- and high-risk groups, which might provide a basis for personalized treatments for these patients.
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