Dysregulation of pseudogene/lncRNA-hsa-miR-363-3p-SPOCK2 pathway fuels stage progression of ovarian cancer.

竞争性内源性RNA 阶段(地层学) 长非编码RNA 信使核糖核酸 基因表达 临床意义 内科学 基因敲除
作者
Weiyang Lou,Bisha Ding,Guansheng Zhong,Chengyong Du,Weimin Fan,Peifen Fu
出处
期刊:Aging [Impact Journals LLC]
卷期号:11 (23): 11416-11439 被引量:24
标识
DOI:10.18632/aging.102538
摘要

Objective: Ovarian cancer is one of the most common and lethal cancer types in women. The molecular mechanism of ovarian cancer progression is still unclear. Results: Here, we first reported that expression levels of three genes, GJB2, S100A2 and SPOCK2, were significantly higher in advanced stage than that in early stage of ovarian cancer, and upregulation of them indicated poor prognosis of patients with ovarian cancer. Subsequently, 8, 6 and 20 miRNAs were predicted to target GJB2, S100A2 and SPOCK2, respectively. Among these miRNA-mRNA pairs, hsa-miR-363-3p-SPOCK2 axis was the most potential in suppressing progression of ovarian cancer. Mechanistically, we found that hsa-miR-363-3p-SPOCK2 axis was involved in regulation of actin cytoskeleton. Moreover, 6 pseudogenes and 8 lncRNAs were identified to potentially inhibit hsa-miR-363-3p-SPOCK2 axis in ovarian cancer. Conclusions: Collectively, we elucidate a regulatory role of pseudogene/lncRNA-hsa-miR-363-3p-SPOCK2 pathway in progression of ovarian cancer, which may provide effective therapeutic approaches and promising prognostic biomarkers for ovarian cancer. Materials and methods: Differentially expressed genes (DEGs) in ovarian cancer were first screened using {type:entrez-geo,attrs:{text:GSE12470,term_id:12470}}GSE12470, after which DEGs expression were validated using GEPIA. Kaplan-Meier analysis was employed to assess the prognostic values. Potential miRNAs were predicted by seven target prediction databases, and upstream lncRNAs and pseudogenes of hsa-miR-363-3p were forecasted through miRNet or starBase. UALCAN and starBase were used to obtain the co-expressed genes of SPOCK. Enrichment analysis for these co-expressed genes was performed by Enrichr.
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