E. Kuznecova, Z. Daneberga, E. Berga-Švītiņa, M. Nakazawa-Miklaševiča, A. Irmejs, J. Gardovskis, E. Miklaševičs
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引用次数: 0
摘要
三阴性乳腺癌(Triple negative breast cancer, TNBC)是一种以雌激素受体、孕激素受体和人表皮生长因子受体缺乏为特征的乳腺癌亚型,其预后比其他类型的癌症差。本研究的目的是确定中心基因和分子途径可能的预后标记TNBC。使用Illumina平台对19个乳腺癌转录组进行测序,并分析鉴定TNBC亚型的差异表达基因。利用ToppGene工具进行基因本体富集分析。然后,利用STRING在线数据库构建蛋白质-蛋白质相互作用(PPI)网络。使用Cytohubba和MCODE插件筛选功能模块和枢纽基因。通过差异基因表达分析,TNBC组共鉴定出229个deg。从PPI网络中筛选出FOXA1、ESR1、TFF1、GATA3、TFF3、AR、SLC39A6、COL9A1 8个基因。总之,本研究表明,分子亚型特异性基因表达模式为靶向、生物标志物驱动的治疗方案提供了有用的信息。
Identification of Altered Transcripts and Pathways in Triple Negative Breast Cancer
Abstract Triple negative breast cancer (TNBC) is a breast cancer subtype characterised by lack of oestrogen receptor, progesterone receptor, and human epidermal growth factor receptor, and by worse prognosis than other cancer types. The aim of this study was to identify hub genes and molecular pathways for possible prognostic markers for TNBC. Nineteen breast cancer transcriptomes were sequenced using Illumina platform and analysed to identify differentially expressed genes in the TNBC subtype. Gene ontology enrichment analysis was conducted using the ToppGene tool. Then, the STRING online database was used for protein-protein interaction (PPI) network construction. Cytohubba and the MCODE plug-in were used to screen functional modules and hub genes. In total, 229 DEGs were identified by differential gene expression analysis in the TNBC group. Eight genes were screened out from the PPI network — FOXA1, ESR1, TFF1, GATA3, TFF3, AR, SLC39A6, COL9A1. In conclusion, this study indicates that the molecular subtype specific gene expression pattern provides useful information for targeted, biomarker-driven treatment options.