Department of Laboratory Medicine, Central Hospital of Panyu District, Guangzhou, Guangdong 511400, China.
Leizhou Center for Disease Control and Prevention, Leizhou, Guangdong 524200, China.
Biomed Res Int. 2021 Jul 23;2021:6662897. doi: 10.1155/2021/6662897. eCollection 2021.
To analyze the molecular regulation network of circular RNA (circRNA) in colon cancer (CC) by bioinformatics method.
hsa_circ_0007843 and hsa_circ_0007331 proved to be associated with CC in previous studies were chosen as the research object. ConSite database was used to predict the transcription factors associated with circRNA, and the CC-associated transcription factors were screened out after intersection. The CircInteractome database was used to predict the RNA-binding proteins (RBPs) interacting with circRNAs and screen out the CC-associated RBPs after an intersection. Furthermore, the CircInteractome database was used to predict the miRNAs interrelated with circRNAs, and the HMDD v3.2 database was used to search for miRNAs associated with CC. The target mRNAs of miRNA were predicted by the miRWalk v3.0 database. CC-associated target genes were screened out from the GeneCards database, and the upregulated genes were enriched and analyzed by the FunRich 3.1.3 software. Finally, the molecular regulatory network diagram of circRNA in CC was plotted.
The ConSite database predicted a total of 14 common transcription factors of hsa_circ_0007843 and hsa_circ_0007331, among which Snail, SOX17, HNF3, C-FOS, and ROR-1 were related to CC. The CircInteractome database predicted that the RBPs interacting with these two circRNAs were AGO2 and EIF4A3, and both of them were related to CC. A total of 17 miRNAs interacting with hsa_circ_0007843 and hsa_circ_0007331 were predicted by CircInteractome database. miR-145-5p, miR-21, miR-330-5p, miR-326, and miR-766 were associated with CC according to the HMDDv3.2 database. miR-145-5p and miR-330-5p, lowly expressed in CC, were analyzed in the follow-up study. A total of 676 common target genes of these two miRNAs were predicted by the miRWalk3.0 database. And 57 target genes were involved in the occurrence and development of CC from the GeneCards database, with 23 genes downregulated and 34 genes upregulated. Additionally, GO analysis showed that the 34 upregulated genes were mainly enriched in biological processes such as signal transduction and cell communication. KEGG pathway analysis showed that the upregulated genes were closely related to integrin, ErbB receptor, and ALK1 signal pathways. Finally, a complete regulatory network of hsa_circ_0007843 and hsa_circ_0007331 in CC was proposed, whereby each one of the participants was either directly or indirectly associated and whose deregulation may result in CC progression.
Predicting the molecular regulatory network of circRNAs by bioinformatics provides a new theoretical basis for further occurrence and development pathogenesis of CC and good guidance for future experimental research.
通过生物信息学方法分析结肠癌（CC）中环状 RNA（circRNA）的分子调控网络。
选择先前研究中与 CC 相关的 hsa_circ_0007843 和 hsa_circ_0007331 作为研究对象。使用 Consite 数据库预测与 circRNA 相关的转录因子，并在交集后筛选出与 CC 相关的转录因子。使用 CircInteractome 数据库预测与 circRNAs 相互作用的 RNA 结合蛋白（RBPs），并在交集后筛选出与 CC 相关的 RBPs。此外，使用 CircInteractome 数据库预测与 circRNAs 相关的 miRNAs，使用 HMDD v3.2 数据库搜索与 CC 相关的 miRNAs。使用 miRWalk v3.0 数据库预测 miRNA 的靶基因。从 GeneCards 数据库中筛选出与 miRNA 相关的靶基因，使用 FunRich 3.1.3 软件对上调基因进行富集分析。最后，绘制 CC 中 circRNA 的分子调控网络图。
Consite 数据库共预测出 hsa_circ_0007843 和 hsa_circ_0007331 的 14 个共同转录因子，其中 Snail、SOX17、HNF3、C-FOS 和 ROR-1 与 CC 相关。CircInteractome 数据库预测出与这两种 circRNAs 相互作用的 RBPs 是 AGO2 和 EIF4A3，两者均与 CC 相关。CircInteractome 数据库共预测出与 hsa_circ_0007843 和 hsa_circ_0007331 相互作用的 17 个 miRNAs。根据 HMDDv3.2 数据库，miR-145-5p、miR-21、miR-330-5p、miR-326 和 miR-766 与 CC 相关。在后续研究中分析了在 CC 中低表达的 miR-145-5p 和 miR-330-5p。miRWalk3.0 数据库共预测出这两个 miRNA 的 676 个共同靶基因。从 GeneCards 数据库中筛选出与这两个 miRNA 相关的 57 个靶基因，其中 23 个基因下调，34 个基因上调。此外，GO 分析显示，34 个上调基因主要富集在信号转导和细胞通讯等生物学过程中。KEGG 通路分析表明，上调基因与整合素、ErbB 受体和 ALK1 信号通路密切相关。最后，提出了 hsa_circ_0007843 和 hsa_circ_0007331 在 CC 中的完整调控网络，其中每个参与者都直接或间接地相互关联，其失调可能导致 CC 的进展。
通过生物信息学预测 circRNAs 的分子调控网络，为进一步研究 CC 的发生发展机制提供了新的理论依据，为今后的实验研究提供了良好的指导。
