School of Clinical Medicine, Southwest Medical University, Luzhou, Sichuan, China, 646000.
Department of Pharmacology, School of Pharmacy, Southwest Medical University, Luzhou, Sichuan, China, 646000.
Curr Comput Aided Drug Des. 2022;18(3):185-195. doi: 10.2174/1573409918666220615151614.
Circular RNAs (circRNAs) act as competing endogenous RNAs (ceRNAs) that indirectly regulate gene expression and function by binding microRNAs (miRNAs). A growing body of evidence indicates that the ceRNA networks can be used as an effective method to investigate cancer; however, the construction and analysis of ceRNA networks, especially circRNA-miRNA-mRNA regulatory network, in different subtypes of breast cancer have not been previously performed.
In the present study, we generated a ceRNA network to explore their roles in two BC subtypes, namely Luminal A and triple negative breast cancer (TNBC).
First, the expression profiles of circRNA, miRNA, and mRNA were downloaded from the GEO database, differentially expressed genes were obtained using GEO2R, and a ceRNA network was constructed based on circRNA-miRNA pairs and miRNA-mRNA pairs, consisted of 10 circRNAs, 25 miRNAs and 39 mRNAs. Further studies of BC subtypes based on TCGA datasets were also performed to validate the effect of a novel ceRNA network.
Then, the related genes in the regulatory network were analyzed by GO functional annotation and KEGG pathway enrichment. The analysis showed that targeted genes were enriched in 97 GO terms and 25 KEGG pathways, involved in the molecular typing of breast cancer. Meanwhile, Kaplan-Meier analysis revealed that three key genes (MKI67, DEF8, and GFRA1) were significantly associated with BC tumor differentiation and prognosis.
The current study provides a potential application of the ceRNA network within BC subtypes and may offer new targets for their diagnosis, therapy and prognosis.
环状 RNA（circRNAs）作为竞争性内源性 RNA（ceRNAs），通过与 microRNA（miRNAs）结合，间接调控基因表达和功能。越来越多的证据表明，ceRNA 网络可作为一种有效方法来研究癌症；然而，不同亚型乳腺癌的 ceRNA 网络（尤其是 circRNA-miRNA-mRNA 调控网络）的构建和分析尚未进行。
本研究构建 ceRNA 网络，探讨其在两种乳腺癌亚型（Luminal A 和三阴性乳腺癌）中的作用。
首先，从 GEO 数据库中下载 circRNA、miRNA 和 mRNA 的表达谱，使用 GEO2R 获得差异表达基因，并基于 circRNA-miRNA 对和 miRNA-mRNA 对构建 ceRNA 网络，该网络包含 10 个 circRNA、25 个 miRNA 和 39 个 mRNA。进一步基于 TCGA 数据集对乳腺癌亚型进行研究，以验证新型 ceRNA 网络的作用。
然后，通过 GO 功能注释和 KEGG 通路富集分析对调控网络中的相关基因进行分析。分析表明，靶向基因富集于 97 个 GO 术语和 25 个 KEGG 通路，参与乳腺癌的分子分型。同时，Kaplan-Meier 分析显示，三个关键基因（MKI67、DEF8 和 GFRA1）与乳腺癌肿瘤分化和预后显著相关。
本研究为乳腺癌亚型中的 ceRNA 网络提供了一种潜在的应用，可能为其诊断、治疗和预后提供新的靶点。
