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Candidate Genes and Pathways Associated with Brain Metastasis from Lung Cancer Compared with Lymph Node Metastasis

Overview
Journal Exp Ther Med
Specialty Pathology
Date 2019 Aug 1
PMID 31363372
Citations 1
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Abstract

Brain metastasis from lung cancer (BMLC) is one of the common types of metastasis associated with poor prognosis. The aim of the present study was to elucidate the underlying molecular mechanisms of BMLC. The mRNA microarray dataset GSE18549 was downloaded from the Gene Expression Omnibus database. The Limma package of R was used to screen the differentially expressed genes (DEGs). Based on the DAVID database, functional and pathway enrichment analyses of DEGs were performed. Furthermore, the protein-protein interaction (PPI) network was predicted using the STRING database and visualized with Cytoscape software. In addition, hub genes and significant modules were selected based on the network. A total of 190 DEGs with log|(fold change)|>1, including 129 significantly downregulated DEGs and 61 upregulated DEGs, were obtained. Gene Ontology functional enrichment analysis indicated that downregulated DEGs were mainly associated with 'immune response', 'cell activation' and 'leukocyte activation', while the upregulated DEGs were involved in 'DNA repair' and 'viral process'. Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that the downregulated DEGs were mainly enriched in 'chemokine signaling pathway', whereas the upregulated DEGs were associated with 'oocyte meiosis'. Based on the PPI network, 9 hub genes were selected, namely tumor necrosis factor, C-C motif chemokine ligand (CCL) 2, CD34, vascular cell adhesion molecule 1, CD48, CD27, CCL19, C-X-C motif chemokine receptor 6 and C-C motif chemokine receptor 2. The present study sheds light on the molecular mechanisms of BMLC and may provide molecular targets and diagnostic biomarkers for BMLC.

Citing Articles

Immune related biomarkers for cancer metastasis to the brain.

Chen W, Chu T, Xu L, Zhao C, Poon W, Leung G Exp Hematol Oncol. 2022; 11(1):105.

PMID: 36527157 PMC: 9756766. DOI: 10.1186/s40164-022-00349-z.

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