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高级别浆液性卵巢癌复发相关的潜在功能性关键miRNA-mRNA:基于生物信息学方法
引用本文:张攀扬,何明敏,曾园媛,蔡雄伟.高级别浆液性卵巢癌复发相关的潜在功能性关键miRNA-mRNA:基于生物信息学方法[J].南方医科大学学报,2023,43(1):8-16.
作者姓名:张攀扬  何明敏  曾园媛  蔡雄伟
作者单位:重庆市妇幼保健院(重庆医科大学附属妇女儿童医院)妇产科,重庆 401147;陆军军医大学第一附属医院妇产科,重庆 400038
基金项目:国家自然科学基金(81874213)~~;
摘    要:目的 探讨在高级别浆液性卵巢癌(HGSOC)中的潜在功能性miRNA-mRNA调控网络与复发的相关性及其生物学意义。方法 使用来自癌症和肿瘤基因图谱(TCGA)数据库的HGSOC患者样本表达数据,根据基因本体论生物过程(GO_BP)将HGSOC患者分成不同的亚型,分析不同亚型与复发的相关性;通过基因表达综合(GEO)数据库找到两个与复发相关的数据集,与TCGA数据取交集,获得共同差异表达的miRNAs;预测miRNAs的靶基因,构建与HGSOC复发相关的关键miRNA-mRNA网络;通过RT-qPCR及Western blot检测miR-506-3p与SNAI2的表达水平;双荧光素酶实验验证miR-506-3p与SNAI2的靶向结合;划痕实验及Trans well实验检测miR-506-3p对卵巢癌细胞迁移与侵袭的影响。结果 共筛选出与HGSOC相关通路活性的303个GO通路,确定两个亚型C1和C2。亚型与复发相关,C1患者的复发概率显著高于C2患者。C1和C2亚型之间的差异表达基因主要富集在上皮间质转化(EMT)通路,GSE25204、GSE73582及TCGA 3个数据集中有5个共...

关 键 词:高级别浆液性卵巢癌  复发  上皮间质转化  miRNA

Identification of key molecules in miRNA-mRNA regulatory network associated with high-grade serous ovarian cancer recurrence using bioinformatic analysis
ZHANG Panyang,HE Mingmin,ZENG Yuanyuan,CAI Xiongwei.Identification of key molecules in miRNA-mRNA regulatory network associated with high-grade serous ovarian cancer recurrence using bioinformatic analysis[J].Journal of Southern Medical University,2023,43(1):8-16.
Authors:ZHANG Panyang  HE Mingmin  ZENG Yuanyuan  CAI Xiongwei
Institution:Department of Gynecology, Chongqing Health Center for Women and Children(Women and Children's Hospital of Chongqing Medical University), Chongqing 401147, China; Department of Obstetrics and Gynecology, First Affiliated Hospital of Army Medical University, Chongqing 400038, China
Abstract:Objective To investigate the correlation of the potential functional microRNA (miRNA)-mRNA regulatory network with recurrence of high-grade serous ovarian carcinoma (HGSOC) and its biological significance. Methods This study was performed based on the data of 354 patients with HGSOC from the Cancer Genome Atlas database. In these patients, HGSOC was divided into different subtypes based on the pathways identified by GO analysis, and the correlations of the subtypes with HGSOC recurrence and differentially expressed miRNAs and mRNAs were assessed. Two relapse-related datasets were identified using the Gene Set Enrichment (GSE) database, from which the differentially expressed miRNAs were identified by intersection with the TCGA data. The target genes of these miRNAs were predicted using miRWalk 2.0 database, and these common differentially expressed miRNAs and mRNAs were used to construct the key miRNA-mRNA network associated with HGSOC recurrence. The expression of miR-506-3p and SNAI2 in two ovarian cancer cell lines was detected using RT-qPCR and Western blotting, and their targeted binding was verified using a double luciferase assay. The effect of miR-506-3p expression modulation on ovarian cancer cell migration was detected using scratch assay and Transwell assay. Results We screened 303 GO terms of HGSOC-related pathways and identified two HGSOC subtypes (C1 and C2). The subtype C1 was associated with a significantly higher recurrence rate than C2. The differentially expressed genes between C1 and C2 subtypes were mainly enriched in epithelial- mesenchymal transition (EMT). Five miRNAs were identified as potential regulators of EMT, and a total of 41 target genes were found to be involved in the differential expressions of EMT pathway between C1 and C2 subtypes. The key miRNA-mRNA network associated with HGSOC recurrence was constructed based on these 5 miRNAs and 41 mRNAs. MiR-506-3p was confirmed to bind to SNAI2, and up-regulation of miR-506-3p significantly inhibited SNAI2 expression and reduced migration and invasion of SKOV3 and CAOV3 cells (P<0.05), while miR-506-3p knockdown produced the opposite effects (P<0.05). Conclusion MiR-506-3p and SNAI2 are the key molecules associated with HGSOC recurrence. MiR-506-3p may affect EMT of ovarian cancer cells by regulating cell migration and invasion via SNAI2, and its expression level has predictive value for HGSOC recurrence.
Keywords:high-grade serous ovarian cancer  recurrence  epithelial-mesenchymal transition  miRNA  
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