首页|基于转录组数据分析的妊娠乳腺癌复发关键基因识别研究

基于转录组数据分析的妊娠乳腺癌复发关键基因识别研究

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目的 通过转录组数据分析,识别妊娠乳腺癌复发的关键基因。方法 下载GEO数据库中与妊娠乳腺癌相关的基因集GSE53031的基因表达谱。利用"limma"软件包中的Wilcoxon检验方法对妊娠乳腺癌复发组和非复发组患者之间的基因表达差异进行分析。使用R软件包"ClusterProfiler"对这些差异基因进行基因本体(GO)功能注释和京都基因与基因组百科全书(KEGG)通路富集分析。使用STRING在线数据库构建差异基因的蛋白质相互作用网络(PPI网络),并使用"igraph"包对PPI网络进行分析以识别妊娠乳腺癌复发的关键基因。借助Kaplan-Meier(KM)方法和单因素Cox回归分析评估关键基因与妊娠乳腺癌患者无复发生存之间的关系。结果 在数据集GSE63514中,获得840个在妊娠乳腺癌复发样本中表达差异显著的基因,其中上调基因390个和下调基因450个。GO功能注释和KEGG通路富集分析结果显示,多个差异表达基因在细胞周期调控、错配修复、RNA降解、DNA复制、乳腺癌、p53信号通路等条目中显著富集。PPI网络分析结果显示,将网络中排名前 10 的节点基因:PLK1、STAT3、SRC、UHRF1、UBE2C、UBE2T、TRIP13、RAD51、MYC和TPX2初步定义为妊娠乳腺癌复发的关键基因。KM分析和单因素Cox分析结果均显示,PLK1、UBE2C、UBE2T、TRIP13、RAD51和TPX2是妊娠乳腺癌复发的风险基因[P<0。05,风险比(HR)>1],而STAT3 则是妊娠乳腺癌复发的保护基因(P<0。05,HR<1)。UBE2C、TPX2、UBE2T、TRIP13、PLK1、RAD51和STAT3确定为最终识别出的妊娠乳腺癌复发关键基因。结论 研究识别出7个妊娠乳腺癌复发的关键基因(UBE2C、TPX2、UBE2T、TRIP13、PLK1、RAD51和STAT3),为后续开展妊娠乳腺癌 复发研究提供了候选分子。
Study on the identification of key genes for recurrent breast cancer during pregnancy based on transcriptome data analysis
Objective To identify the key genes associated with recurrent breast cancer in pregnancy by transcriptome data analysis.Methods The gene expression profiles of the GSE53031 gene set,which was as-sociated with pregnancy-associated breast cancer,were downloaded from the GEO database.Gene expression differences between recurrent and non-recurrent breast cancer patients in pregnancy were analyzed using the Wilcoxon test method in the"limma"software package.The R package"ClusterProfiler"was used to perform Gene Ontology(GO)functional annotation and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway enrichment analysis of these differentially expressed genes.The protein-protein interaction(PPI)network of differentially expressed genes was constructed using the STRING online database,and the"igraph"package was used to analyze the PPI network to identify key genes of breast cancer recurrence during pregnancy.Kap-lan-Meier(KM)method and univariate Cox regression analysis were used to evaluate the relationship between the key genes and recurrence-free survival of breast cancer patients during pregnancy.Results In the GSE63514 dataset,840 genes with significant differences in the expression of recurrent breast cancer samples in pregnancy were obtained,including 390 up-regulated genes and 450 down-regulated genes.GO functional annotation and KEGG pathway enrichment analysis showed that multiple differentially expressed genes were significant enriched in cell cycle regulation,mismatch repair,RNA degradation,DNA replication,breast canc-er,and p53 signaling pathway.PPI network analysis showed that the top 10 node genes in the network were PLK1,STAT3,SRC,UHRF1,UBE2C,UBE2T,TRIP13,RAD51,MYC,and TPX2,which were initially de-fined as the key genes for the recurrence of breast cancer in pregnancy.KM analysis and univariate Cox analy-sis showed that PLK1,UBE2C,UBE2T,TRIP13,RAD51 and TPX2 were risk genes for the recurrence of breast cancer in pregnancy[P<0.05,hazard raiol(HR)>1],while STAT3 was a protective gene for the re-currence of breast cancer in pregnancy(P<0.05,HR<1).UBE2C,TPX2,UBE2T,TRIP13,PLK1,RAD51,and STAT3 were identified as the key genes for recurrence of breast cancer in pregnancy.Conclusion Seven key genes(UBE2C,TPX2,UBE2T,TRIP13,PLK1,RAD51,and STAT3)of breast cancer recurrence in preg-nancy were identified,which provided candidate molecular for future research on the recurrence of breast canc-er in pregnancy.

Breast cancer in pregnancyRecurrenceBioinformaticsKey genesTranscriptome data analysis

尹金宝、唐泽立、梁兰

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广东医科大学病理系,广东 东莞 523808

广东医科大学生物医学工程系,广东 东莞 523808

妊娠乳腺癌 复发 生物信息 关键基因 转录组数据分析

广东省卫生健康委医学科研项目

A2023169

2024

现代医药卫生
重庆市卫生信息中心

现代医药卫生

影响因子:0.758
ISSN:1009-5519
年,卷(期):2024.40(11)