生物信息学分析鉴定子宫内膜癌的 6 个候选基因。
Identification of six candidate genes for endometrial carcinoma by bioinformatics analysis.
机构信息
Department of Gynaecology, The First Affiliated Hospital of Zhejiang Chinese Medical University; Zhejiang Provincial Hospital of Traditional Chinese Medicine, Youdian Road, Hangzhou, 310006, Zhejiang, China.
Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Cancer Hospital of University of Chinese Academy of Sciences, Zhejiang Cancer Hospital, Hangzhou, 310022, Zhejiang, China.
出版信息
World J Surg Oncol. 2020 Jul 8;18(1):161. doi: 10.1186/s12957-020-01920-w.
BACKGROUND
Endometrial carcinoma (EC) is the most common gynecological malignant tumors which poses a serious threat to women health. This study aimed to screen the candidate genes differentially expressed in EC by bioinformatics analysis.
METHODS
GEO database and GEO2R online tool were applied to screen the differentially expressed genes (DEGs) of EC from the microarray datasets. Protein-protein interaction (PPI) network for the DEGs was constructed to further explore the relationships among these genes and identify hub DEGs. Gene ontology and KEGG enrichment analyses were performed to investigate the biological role of DEGs. Besides, correlation analysis, genetic alteration, expression profile, and survival analysis of these hub DEGs were also investigated to further explore the roles of these hub gene in mechanism of EC tumorigenesis. qRT-PCR analysis was also performed to verify the expression of identified hub DEGs.
RESULTS
A total of 40 DEGs were screened out as the DEGs with 3 upregulated and 37 downregulated in EC. The gene ontology analysis showed that these genes were significantly enriched in cell adhesion, response to estradiol, and growth factor activity, etc. The KEGG pathway analysis showed that DEGs were enriched in focal adhesion, leukocyte transendothelial migration, PI3K-Akt signaling pathway, and ECM-receptor interaction pathway. More importantly, COL1A1, IGF1, COL5A1, CXCL12, PTEN, and SPP1 were identified as the hub genes of EC. The genetic alteration analysis showed that hub genes were mainly altered in mutation and deep deletion. Expression validation by bioinformatic analysis and qRT-PCR also proved the expression of these six hub genes were differentially expressed in EC. Additionally, significantly better overall survival and disease-free survival were observed with six hub genes altered, and survival outcome in high expression of COL1A1, IGF1, and PTEN patients was also significantly better than low expression patients.
CONCLUSIONS
COL1A1, IGF1, COL5A1, CXCL12, PTEN, and SPP1 involved in the pathogenesis of EC and might be candidate genes for diagnosis of EC.
背景
子宫内膜癌（EC）是最常见的妇科恶性肿瘤，严重威胁着女性健康。本研究旨在通过生物信息学分析筛选 EC 中差异表达的候选基因。
方法
应用 GEO 数据库和 GEO2R 在线工具从微阵列数据集筛选 EC 的差异表达基因（DEGs）。构建 DEGs 的蛋白质-蛋白质相互作用（PPI）网络，进一步探讨这些基因之间的关系，识别关键 DEGs。进行基因本体论和 KEGG 富集分析，以研究 DEGs 的生物学作用。此外，还对这些关键基因的相关性分析、遗传改变、表达谱和生存分析进行了研究，以进一步探讨这些关键基因在 EC 肿瘤发生机制中的作用。还进行了 qRT-PCR 分析以验证鉴定的关键 DEGs 的表达。
结果
筛选出 40 个 DEGs，其中 3 个上调，37 个下调。基因本体论分析表明，这些基因显著富集在细胞黏附、雌二醇反应和生长因子活性等方面。KEGG 通路分析表明，DEGs 富集在粘着斑、白细胞跨内皮迁移、PI3K-Akt 信号通路和 ECM 受体相互作用通路。更重要的是，COL1A1、IGF1、COL5A1、CXCL12、PTEN 和 SPP1 被鉴定为 EC 的关键基因。遗传改变分析表明，关键基因主要在突变和深度缺失中发生改变。通过生物信息学分析和 qRT-PCR 的表达验证也证明了这六个关键基因在 EC 中的表达存在差异。此外，关键基因改变的患者总体生存率和无病生存率显著提高，COL1A1、IGF1 和 PTEN 高表达患者的生存结果也显著优于低表达患者。
结论
COL1A1、IGF1、COL5A1、CXCL12、PTEN 和 SPP1 参与 EC 的发病机制，可能是 EC 诊断的候选基因。
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