Zheng Jianfeng, Guo Jialu, Zhang Huizhi, Cao Benben, Xu Guomin, Zhang Zhifen, Tong Jinyi
Department of Obstetrics and Gynecology, Affiliated Hangzhou Hospital, Nanjing Medical University, Hangzhou, China.
Department of Obstetrics and Gynecology, Hangzhou Women's Hospital, Hangzhou, China.
Front Genet. 2021 Jul 2;12:672674. doi: 10.3389/fgene.2021.672674. eCollection 2021.
Long non-coding RNAs (lncRNAs) play crucial roles in ovarian cancer (OC) development. However, prognosis-associated lncRNAs (PALs) for OC have not been completely elucidated. Our study aimed to identify the PAL signature of OC. A total of 663 differentially expressed lncRNAs were identified in the databases. According to the weighted gene coexpression analysis, the highly correlated genes were clustered into seven modules related to the clinical phenotype of OC. A total of 25 lncRNAs that were significantly related to overall survival were screened based on univariate Cox regression analysis. The prognostic risk model constructed contained seven PALs based on the parameter λ, which could stratify OC patients into two risk groups. The results showed that the risk groups had different overall survival rates in both The Cancer Genome Atlas (TCGA) and two verified Gene Expression Omnibus (GEO) databases. Univariate and multivariate Cox regression analyses confirmed that the risk model was an independent risk factor for OC. Gene enrichment analysis revealed that the identified genes were involved in some pathways of malignancy. The competitive endogenous RNA (ceRNA) network included five PALs, of which four were selected for cell function assays. The four PALs were downregulated in 33 collected OC tissues and 3 OC cell lines relative to the control. They were shown to regulate the proliferative, migratory, and invasive potential of OC cells via Cell Counting Kit-8 (CCK-8) and transwell assays. Our study fills the gaps of the four PALs in OC, which are worthy of further study.
长链非编码RNA（lncRNAs）在卵巢癌（OC）的发生发展中起关键作用。然而，OC的预后相关lncRNAs（PALs）尚未完全阐明。我们的研究旨在确定OC的PAL特征。在数据库中总共鉴定出663个差异表达的lncRNAs。根据加权基因共表达分析，高度相关的基因被聚类为与OC临床表型相关的七个模块。基于单变量Cox回归分析筛选出总共25个与总生存期显著相关的lncRNAs。基于参数λ构建的预后风险模型包含7个PALs，可将OC患者分为两个风险组。结果显示，在癌症基因组图谱（TCGA）和两个经过验证的基因表达综合数据库（GEO）中，风险组的总生存率不同。单变量和多变量Cox回归分析证实，该风险模型是OC的独立危险因素。基因富集分析表明，鉴定出的基因参与了一些恶性肿瘤相关途径。竞争性内源性RNA（ceRNA）网络包括5个PALs，其中4个被选用于细胞功能测定。相对于对照，在收集的33个OC组织和3个OC细胞系中，这4个PALs表达下调。通过细胞计数试剂盒-8（CCK-8）和transwell试验表明，它们可调节OC细胞的增殖、迁移和侵袭能力。我们的研究填补了OC中这4个PALs的研究空白，值得进一步研究。
