Abstract
Background: Lung adenocarcinoma (LADC) is the most common type of lung cancer and is a subtype of non-small-cell lung cancer (NSCLC). Approximately 40% of LADC patients experience brain metastases (BMs) during the course of the disease. In this study, integrated bioinformatics methods were applied to identify key genes related to brain metastasis in lung adenocarcinoma.
Methods: We derived and characterized genes differentially expressed between the primary tumour and brain metastases using tumour cells isolated from two lung cancer Patient-derived xenografts (PDX) cases (GSE 69405). Gene ontology (GO) and KEGG pathway enrichment analyses were applied, and protein-protein interaction (PPI) networks and Cytoscape software were utilized to identify key genes.
Results: Four key genes, including CKAP4 (Cytoskeleton Associated Protein 4), SERPINA1 (Serpin Family A Member 1), SDC2 (Syndecan 2) and GNG11 (G Protein Subunit Gamma 11) were identified for BM-LADC by the Venn diagram.
Conclusion: We believe these key genes may be potential biomarkers for improved prognosis and treatment of lung adenocarcinoma.
Keywords: Lung adenocarcinoma, brain metastases, single-cell RNA sequencing, bioinformatics, key genes, biomarker.
Current Gene Therapy
Title:Single-cell RNA Sequencing Analysis Identifies Key Genes in Brain Metastasis from Lung Adenocarcinoma
Volume: 21 Issue: 4
Author(s): Zilong Zhang*, Feifei Cui, Murong Zhou, Song Wu*, Quan Zou*Bo Gao*
Affiliation:
- Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054,China
- Director of Preventive Treatment of Disease Centre, Qinhuangdao Hospital of Traditional Chinese Medicine, Qinhuangdao 066000,China
- Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu 610054,China
- Second Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin, 150080,China
Keywords: Lung adenocarcinoma, brain metastases, single-cell RNA sequencing, bioinformatics, key genes, biomarker.
Abstract:
Background: Lung adenocarcinoma (LADC) is the most common type of lung cancer and is a subtype of non-small-cell lung cancer (NSCLC). Approximately 40% of LADC patients experience brain metastases (BMs) during the course of the disease. In this study, integrated bioinformatics methods were applied to identify key genes related to brain metastasis in lung adenocarcinoma.
Methods: We derived and characterized genes differentially expressed between the primary tumour and brain metastases using tumour cells isolated from two lung cancer Patient-derived xenografts (PDX) cases (GSE 69405). Gene ontology (GO) and KEGG pathway enrichment analyses were applied, and protein-protein interaction (PPI) networks and Cytoscape software were utilized to identify key genes.
Results: Four key genes, including CKAP4 (Cytoskeleton Associated Protein 4), SERPINA1 (Serpin Family A Member 1), SDC2 (Syndecan 2) and GNG11 (G Protein Subunit Gamma 11) were identified for BM-LADC by the Venn diagram.
Conclusion: We believe these key genes may be potential biomarkers for improved prognosis and treatment of lung adenocarcinoma.
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Cite this article as:
Zhang Zilong *, Cui Feifei , Zhou Murong , Wu Song *, Zou Quan*, Gao Bo *, Single-cell RNA Sequencing Analysis Identifies Key Genes in Brain Metastasis from Lung Adenocarcinoma, Current Gene Therapy 2021; 21 (4) . https://dx.doi.org/10.2174/1566523221666210319104752
DOI https://dx.doi.org/10.2174/1566523221666210319104752 |
Print ISSN 1566-5232 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-5631 |
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