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卵巢癌化疗耐药关键基因、miRNA及miRNA-mRNA调控通路的鉴定

Identification of keygenes, miRNAs and miRNA-mRNA regulatory pathways for chemotherapy resistance in ovarian cancer.

作者信息

Wang Wenwen, Zhang Wenwen, Hu Yuanjing

机构信息

Tianjin Medical University, Tianjin, China.

Department of Obstetrics and Gynecology, Beijing Tongren Hospital affiliated Capital Medical University, Beijing, China.

出版信息

PeerJ. 2021 Nov 8;9:e12353. doi: 10.7717/peerj.12353. eCollection 2021.

Abstract

BACKGROUND

Chemotherapy resistance, especially platinum resistance, is the main cause of poor prognosis of ovarian cancer. It is of great urgency to find molecular markers and mechanism related to platinum resistance in ovarian cancer.

METHODS

One mRNA dataset (GSE28739) and one miRNA dataset (GSE25202) were acquired from Gene Expression Omnibus (GEO) database. The GEO2R tool was used to screen out differentially expressed genes (DEGs) and differentially expressed miRNAs (DE-miRNAs) between platinum-resistant and platinum-sensitive ovarian cancer patients. Gene Ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for DEGs were performed using the DAVID to present the most visibly enriched pathways. Protein-protein interaction (PPI) of these DEGs was constructed based on the information of the STRING database. Hub genes related to platinum resistance were visualized by Cytoscape software. Then, we chose seven interested hub genes to further validate using qRT-PCR in A2780 ovarian cancer cell lines. And, at last, the TF-miRNA-target genes regulatory network was predicted and constructed using miRNet software.

RESULTS

A total of 63 upregulated DEGs, 124 downregulated DEGs, four upregulated miRNAs and six downregulated miRNAs were identified. From the PPI network, the top 10 hub genes were identified, which were associated with platinum resistance. Our further qRT-PCR showed that seven hub genes (BUB1, KIF2C, NUP43, NDC80, NUF2, CCNB2 and CENPN) were differentially expressed in platinum-resistant ovarian cancer cells. Furthermore, the upstream transcription factors (TF) for upregulated DE-miRNAs were SMAD4, NFKB1, SMAD3, TP53 and HNF4A. Three overlapping downstream target genes (KIF2C, STAT3 and BUB1) were identified by miRNet, which was regulated by hsa-miR-494.

CONCLUSIONS

The TF-miRNA-mRNA regulatory pairs, that is TF (SMAD4, NFKB1 and SMAD3)-miR-494-target genes (KIF2C, STAT3 and BUB1), were established. In conclusion, the present study is of great significance to find the key genes of platinum resistance in ovarian cancer. Further study is needed to identify the mechanism of these genes in ovarian cancer.

摘要

背景

化疗耐药,尤其是铂耐药,是卵巢癌预后不良的主要原因。寻找与卵巢癌铂耐药相关的分子标志物和机制迫在眉睫。

方法

从基因表达综合数据库(GEO)获取一个mRNA数据集(GSE28739)和一个miRNA数据集(GSE25202)。使用GEO2R工具筛选铂耐药和铂敏感卵巢癌患者之间的差异表达基因(DEGs)和差异表达miRNA(DE-miRNAs)。使用DAVID对DEGs进行基因本体(GO)功能和京都基因与基因组百科全书(KEGG)通路富集分析,以呈现最显著富集的通路。基于STRING数据库的信息构建这些DEGs的蛋白质-蛋白质相互作用(PPI)。通过Cytoscape软件可视化与铂耐药相关的枢纽基因。然后,我们选择七个感兴趣的枢纽基因,在A2780卵巢癌细胞系中使用qRT-PCR进一步验证。最后,使用miRNet软件预测并构建TF-miRNA-靶基因调控网络。

结果

共鉴定出63个上调的DEGs、124个下调的DEGs、4个上调的miRNAs和6个下调的miRNAs。从PPI网络中,鉴定出前10个枢纽基因,它们与铂耐药相关。我们进一步的qRT-PCR表明,七个枢纽基因(BUB1、KIF2C、NUP43、NDC80、NUF2、CCNB2和CENPN)在铂耐药卵巢癌细胞中差异表达。此外,上调的DE-miRNAs的上游转录因子(TF)为SMAD4、NFKB1、SMAD3、TP53和HNF4A。通过miRNet鉴定出三个重叠的下游靶基因(KIF2C、STAT3和BUB1),它们受hsa-miR-494调控。

结论

建立了TF-miRNA-mRNA调控对,即TF(SMAD4、NFKB1和SMAD3)-miR-494-靶基因(KIF2C、STAT3和BUB1)。总之,本研究对于发现卵巢癌铂耐药的关键基因具有重要意义。需要进一步研究以确定这些基因在卵巢癌中的作用机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/83ff/8582303/573661188814/peerj-09-12353-g001.jpg

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