摘要
背景:肺腺癌(LADC)是最常见的肺癌类型,是非小细胞肺癌(NSCLC)的一个亚型。大约 40% 的 LADC 患者在疾病过程中经历脑转移 (BM)。本研究应用综合生物信息学方法鉴定肺腺癌脑转移相关的关键基因。 方法:我们使用从两个肺癌患者来源的异种移植物 (PDX) 病例 (GSE 69405) 中分离的肿瘤细胞,衍生并表征了原发肿瘤和脑转移瘤之间差异表达的基因。应用基因本体(GO)和KEGG通路富集分析,并利用蛋白质-蛋白质相互作用(PPI)网络和Cytoscape软件识别关键基因。 结果:通过维恩图确定了 BM-LADC 的四个关键基因,包括 CKAP4(细胞骨架相关蛋白 4)、SERPINA1(Serpin 家族 A 成员 1)、SDC2(Syndecan 2)和 GNG11(G 蛋白亚基 Gamma 11)。 结论:我们相信这些关键基因可能是改善肺腺癌预后和治疗的潜在生物标志物。
关键词: 肺腺癌、脑转移、单细胞RNA测序、生物信息学、关键基因、生物标志物。
图形摘要
Current Gene Therapy
Title:Single-cell RNA Sequencing Analysis Identifies Key Genes in Brain Metastasis from Lung Adenocarcinoma
Volume: 21 Issue: 4
关键词: 肺腺癌、脑转移、单细胞RNA测序、生物信息学、关键基因、生物标志物。
摘要:
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:
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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