ArticleOncology letters2019
Identification of potential biomarkers of lung adenocarcinoma brain metastases via microarray analysis of cDNA expression profiles.
Article in Oncology letters, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 9 citations in OpenAlex.
- E3 ligase LMO7 enhances temozolomide sensitivity by promoting MGMT degradation in lung cancer.The Journal of biological chemistry · 2026Article
- Spatial Omics Profiling of Treatment-Naïve Lung Adenocarcinoma with Brain Metastasis as the Initial Presentation.Cancers · 2025Article
- scRNA-seq reveals chemotherapy-induced tumor microenvironment changes in pancreatic ductal adenocarcinoma.Translational cancer research · 2025Article
- Micro-RNAs from Plasma-Derived Small Extracellular Vesicles as Potential Biomarkers for Tic Disorders Diagnosis.Brain sciences · 2022Article
- Gene Expression Profile in Primary Tumor Is Associated with Brain-Tropism of Metastasis from Lung Adenocarcinoma.International journal of molecular sciences · 2021Article
- An immune-related gene expression signature predicts brain metastasis in lung adenocarcinoma patients after surgery: gene expression profile and immunohistochemical analyses.Translational lung cancer research · 2021Article
- The Expression Patterns ofJournal of clinical medicine · 2020Article
- Epigenomic dysregulation-mediated alterations of key biological pathways and tumor immune evasion are hallmarks of gingivo-buccal oral cancer.Clinical epigenetics · 2019Article
- Identification of key genes associated with lung adenocarcinoma by bioinformatics analysis.Science progressArticle
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Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Brain metastases originating from lung adenocarcinoma (LAD) occur frequently. The aim of the current study was to assess potential biomarkers for the prognosis of lung adenocarcinoma brain metastasis (LAD-BM) through the analysis of gene expression microarrays. The current study downloaded two gene expression datasets, GSE14108 and GSE10245, from the Gene Expression Omnibus database. From GSE14108 and GSE10245, 19 LAD-BM samples and 40 primary LAD samples were selected for analysis. To identify the differentially expressed genes (DEGs), the current study compared the two sample groups, using the limma R package. Subsequently, pathway enrichment analysis was conducted using the Cluster Profiler R package, and the construction of the protein-protein interaction (PPI) network was executed utilizing the Search Tool for the Retrieval of Interacting Genes database. The microRNA-target network was built using the TargetScore R package. Then, these networks were established and visualized using Cytoscape software. An array of 463 DEGs was identified in the LAD-BM samples, including 256 upregulated and 207 downregulated genes. Based on functional term enrichment analysis using the Gene Ontology database and signaling pathway enrichment analysis using the Kyoto Encyclopedia of Genes and Genomes database, it was identified that the overlapping DEGs were primarily involved in chemokine-associated signal transduction, which may mediate lung cancer cell metastasis to the brain. Chemokine ligand 2, lysozyme, matrix metalloproteinase-2 (MMP-2), lysyl oxidase (LOX) and granzyme B were identified as potential biomarkers according to a topological analysis of the PPI networks. Two notable nodes, MMP-2 and LOX, appeared in the PPI network and were key points in the microRNA-target network, as they were regulated by hsa-let-7d. Many DEGs and microRNAs were regarded as prognostic biomarkers for lung adenocarcinoma metastasis in the current study. These DEGs were primarily associated with chemokine-mediated signaling pathways. In addition, MMP-2 and LOX were predicted to be targets of hsa-let-7d.
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