| 多数据库联合分析卵巢癌预后相关基因 |
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| 引用本文： | 王静,苏晓玲,贺海威,王志明,陆楠,徐明娟.多数据库联合分析卵巢癌预后相关基因[J].第二军医大学学报,2022,43(2):167-173. |
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| 作者姓名： | 王静 苏晓玲 贺海威 王志明 陆楠 徐明娟 |
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| 作者单位： | 海军军医大学(第二军医大学)第一附属医院妇产科,上海 200433,海军军医大学(第二军医大学)海军特色医学中心妇产科,上海 200433 |
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| 基金项目： | 海军军医大学第一附属医院“234学科攀登计划”MDT模式和个体化精准治疗卵巢癌中的应用(2019YXK014);深蓝123重点攻关项目海军特殊昨作业环境下女性官兵卵巢功能的变化及其生育力保护的研究,2020YSL009;海军计生课题长期海上航行对卵巢功能的影响及防治研究,19JSZ05 |
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| 摘 要： | 目的 寻找卵巢癌预后的关键基因,为卵巢癌治疗提供新的靶点.方法 从基因表达汇编(GEO)数据库GSE18520和GSE14407数据集、癌症基因组图谱(TCGA)数据库及基因型-组织表达(GTEx)数据库中下载卵巢癌相关数据,用R 3.6.2软件limma包进行差异表达基因分析,随后使用R 3.6.2软件cluster...
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| 关 键 词： | 卵巢肿瘤 预后 生物信息学 差异表达基因 |
| 收稿时间： | 2021/12/23 0:00:00 |
| 修稿时间： | 2022/2/23 0:00:00 |
Prognostic genes in ovarian cancer: a multi-database analysis |
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| WANG Jing,SU Xiao-ling,HE Hai-wei,WANG Zhi-ming,LU Nan,XU Ming-juan.Prognostic genes in ovarian cancer: a multi-database analysis[J].Academic Journal of Second Military Medical University,2022,43(2):167-173. |
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| Authors: | WANG Jing SU Xiao-ling HE Hai-wei WANG Zhi-ming LU Nan XU Ming-juan |
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| Institution: | Department of Obstetrics,The First Affiliated Hospital of Naval Medical University,Shanghai,,China,Department of Obstetrics and Gynecology,Special Medical Center,Naval Medical University,Shanghai,,China,Department of Obstetrics,The First Affiliated Hospital of Naval Medical University,Shanghai,,China,Department of Obstetrics,The First Affiliated Hospital of Naval Medical University,Shanghai,,China,Department of Obstetrics,The First Affiliated Hospital of Naval Medical University,Shanghai,,China,Department of Obstetrics,The First Affiliated Hospital of Naval Medical University,Shanghai,,China |
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| Abstract: | Objective To search for the hub genes for the prognosis of ovarian cancer and provide new targets for the treatment of ovarian cancer. Methods Ovarian cancer related data were downloaded from Gene Expression Omnibus (GEO) database (GSE18520 and GSE14407 datasets), The Cancer Genome Atlas (TCGA) database and the Genotype-Tissue Expression (GTEx) database. Differentially expressed genes were analyzed with limma package of R 3.6.2 software, and then clusterProfiler package was used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of these genes. Meanwhile, STRING was used to establish the protein-protein interaction network, and cytoHubba package of Cytoscape software was used to screen the hub genes. Gene Expression Profile Interaction Analysis (GEPIA) database was used to verify the expression of hub genes in ovarian cancer tissues. Then, Kaplan-Meier Plotter database was used to perform survival analysis on the hub genes. Results A total of 69 differentially expressed genes were screened by GEO (GSE18520 and GSE14407), TCGA and GTEx databases, and they were mainly enriched in the ABC transporter, retinol metabolism and Wnt signaling pathways. Protein-protein interaction network analysis showed that there were 9 hub genes, which were verified in GEPIA. Kaplan-Meier Plotter database analysis showed that the overall survival was shorter in the ovarian cancer patients with high expression of centrosomal protein 55 (CEP55), family with sequence similarity 83, member D (FAM83D), kinesin family member 20A (KIF20A), cyclin dependent-kinase subunit protein 2 (CKS2) and NIMA related kinase 2 (NEK2) genes; and the progression-free survival was shorter in patients with high expression of CEP55, FAM83D, KIF20A, forkhead box protein M1 (FOXM1) and TTK protein kinase (TTK) than those with low expression. Conclusion The expression of CEP55, FAM83D, KIF20A, CKS2, NEK2, FOXM1 and TTK are closely related to the prognosis of ovarian cancer patients. |
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| Keywords: | Ovarian cancer TCGA GEO Differentially Expressed Genes |
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