[1]魏本飞,王 洁.基于生物信息学的宫颈癌关键基因筛选及生物学途径分析[J].医学信息,2023,36(17):7-14.[doi:10.3969/j.issn.1006-1959.2023.17.002]
　WEI Ben-fei,WANG Jie.Key Gene Screening and Biological Pathway Analysis of Cervical Cancer Based on Bioinformatics[J].Journal of Medical Information,2023,36(17):7-14.[doi:10.3969/j.issn.1006-1959.2023.17.002]
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基于生物信息学的宫颈癌关键基因筛选及生物学途径分析()
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医学信息[ISSN:1006-1959/CN:61-1278/R]

卷:
36卷
期数:
2023年17期
页码:
7-14
栏目:
生物信息学
出版日期:
2023-09-01

文章信息/Info

Title:
Key Gene Screening and Biological Pathway Analysis of Cervical Cancer Based on Bioinformatics
文章编号:
1006-1959（2023）17-0007-08
作者:
魏本飞; 王 洁
（扬州大学附属医院肿瘤科，江苏 扬州 225000）
Author(s):
WEI Ben-fei; WANG Jie
(Department of Oncology,Affiliated Hospital of Yangzhou University,Yangzhou 225000,Jiangsu,China)
关键词:
宫颈癌; 差异表达基因; 分子标志物
Keywords:
Cervical cancer; Differentially expressed genes; Molecular markers
分类号:
R737.33
DOI:
10.3969/j.issn.1006-1959.2023.17.002
文献标志码:
A
摘要:
目的 用生物信息学技术分析宫颈癌发生、发展的关键基因及生物学途径，为宫颈癌的临床诊断、预后评估及靶向治疗提供理论依据。方法 在NCBI-GEO数据库中下载GSE6791、GSE63514、GSE7803、GSE52903和GSE9750共5组宫颈癌基因芯片表达谱，利用Venn在线软件对数据进行整合分析得到宫颈癌组织和正常宫颈组织的差异表达基因（DEGs），并对差异表达基因进行GO、KEGG富集分析。利用STRING数据库构建DEGs的蛋白互作网络，基于Cytoscape软件的MCODE插件识别重要的功能模块，基于cytoHubba插件筛选出关键基因，并通过GEPIA数据库对关键基因进行验证。结果 共筛选出138个DEGs，其中上调基因81个，下调基因57个。GO功能分析显示，DEGs涉及的分子功能包括蛋白质结合、DNA复制起点结合、染色质结合、丝氨酸型肽酶及内肽酶活性、蛋白激酶结合、DNA解旋酶活性、ATP结合。KEGG通路分析显示，DEGs主要富集在细胞周期、DNA复制、卵母细胞减数分裂、p53信号通路、膀胱癌等通路。通过蛋白互作网络发现3个重要功能模块，筛选出16个关键基因，其中与患者预后相关基因有3个：CDC45、TOP2A、RRM2。结论 TOP2A、CDC45、RRM2在宫颈癌组织中高表达，与患者预后明显相关，是宫颈癌临床诊断、治疗及预后的潜在分子标志物和作用靶点。
Abstract:
Objective To analyze the key genes and biological pathways of the occurrence and development of cervical cancer by bioinformatics, and to provide theoretical basis for clinical diagnosis, prognosis evaluation and targeted therapy of cervical cancer.Methods Five groups of cervical cancer gene chip expression profiles of GSE6791, GSE63514, GSE7803, GSE52903 and GSE9750 were downloaded from NCBI-GEO database. Venn online software was used to integrate and analyze the data to obtain differentially expressed genes (DEGs) in cervical cancer tissues and normal cervical tissues, and GO and KEGG enrichment analysis were performed on differentially expressed genes. The protein interaction network of DEGs was constructed using the STRING database. The important functional modules were identified based on the MCODE plug-in of Cytoscape software. The key genes were screened based on the cytoHubba plug-in, and the key genes were verified by the GEPIA database.Results A total of 138 DEGs were screened, including 81 up-regulated genes and 57 down-regulated genes. GO functional analysis showed that the molecular functions involved in DEGs included protein binding, DNA replication origin binding, chromatin binding, serine peptidase and endopeptidase activity, protein kinase binding, DNA helicase activity, ATP binding. KEGG pathway analysis showed that DEGs were mainly enriched in cell cycle, DNA replication, oocyte meiosis, p53 signaling pathway, bladder cancer and other pathways. Through the protein interaction network, three important functional modules were found, and 16 key genes were screened. Among them, there were three genes related to the prognosis of patients: CDC45, TOP2 A, and RRM2.Conclusion TOP2A, CDC45 and RRM2 are highly expressed in cervical cancer, which are significantly related to the prognosis of patients, and may be potential molecular markers and targets for clinical diagnosis, treatment and prognosis.

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更新日期/Last Update: 1900-01-01