Department of Pancreatic and Biliary Surgery, The First Hospital of China Medical University, Shenyang, Liaoning 110001, China.
Biomed Res Int. 2019 Mar 24;2019:3526407. doi: 10.1155/2019/3526407. eCollection 2019.
Cholangiocarcinoma (CCA) is the second most common malignant primary liver tumor and has shown an alarming increase in incidence over the last two decades. However, the mechanisms behind tumorigenesis and progression remain insufficient. The present study aimed to uncover the underlying regulatory mechanism on CCA and find novel biomarkers for the disease prognosis.
The RNA-sequencing (RNA-seq) datasets of lncRNAs, miRNAs, and mRNAs in CCA as well as relevant clinical information were obtained from the Cancer Genome Atlas (TCGA) database. After pretreatment, differentially expressed RNAs (DERNAs) were identified and further interrogated for their correlations with clinical information. Prognostic RNAs were selected using univariate Cox regression. Then, a ceRNA network was constructed based on these RNAs.
We identified a total of five prognostic DEmiRNAs, 63 DElncRNAs, and 90 DEmRNAs between CCA and matched normal tissues. Integrating the relationship between the different types of RNAs, an lncRNA-miRNA-mRNA network was established and included 28 molecules and 47 interactions. Screened prognostic RNAs involved in the ceRNA network included 3 miRNAs (hsa-mir-1295b, hsa-mir-33b, and hsa-mir-6715a), 7 lncRNAs (ENSG00000271133, ENSG00000233834, ENSG00000276791, ENSG00000241155, COL18A1-AS1, ENSG00000274737, and ENSG00000235052), and 18 mRNAs (ANO9, FUT4, MLLT3, ABCA3, FSCN2, GRID2IP, NCK2, MACC1, SLC35E4, ST14, SH2D3A, MOB3B, ACTL10, RAB36, ATP1B3, MST1R, SEMA6A, and SEL1L3).
Our study identified novel prognostic makers and predicted a previously unknown ceRNA regulatory network in CCA and may provide novel insight into a further understanding of lncRNA-mediated ceRNA regulatory mechanisms in CCA.
胆管癌(CCA)是第二常见的原发性肝脏恶性肿瘤,在过去二十年中其发病率呈惊人增长。然而,肿瘤发生和进展的机制仍不充分。本研究旨在揭示 CCA 的潜在调控机制,并找到疾病预后的新型生物标志物。
从癌症基因组图谱(TCGA)数据库中获取 CCA 的 lncRNA、miRNA 和 mRNA 的 RNA 测序(RNA-seq)数据集以及相关的临床信息。经过预处理后,鉴定差异表达的 RNA(DERNAs),并进一步研究它们与临床信息的相关性。使用单变量 Cox 回归选择预后 RNA。然后,基于这些 RNA 构建 ceRNA 网络。
我们总共鉴定出 5 个有预后意义的差异表达 miRNA、63 个差异表达 lncRNA 和 90 个差异表达 mRNA 在 CCA 和匹配的正常组织之间。整合不同类型 RNA 之间的关系,建立了一个 lncRNA-miRNA-mRNA 网络,其中包括 28 个分子和 47 个相互作用。筛选出的 ceRNA 网络中的预后 RNA 包括 3 个 miRNA(hsa-mir-1295b、hsa-mir-33b 和 hsa-mir-6715a)、7 个 lncRNA(ENSG00000271133、ENSG00000233834、ENSG00000276791、ENSG00000241155、COL18A1-AS1、ENSG00000274737 和 ENSG00000235052)和 18 个 mRNA(ANO9、FUT4、MLLT3、ABCA3、FSCN2、GRID2IP、NCK2、MACC1、SLC35E4、ST14、SH2D3A、MOB3B、ACTL10、RAB36、ATP1B3、MST1R、SEMA6A 和 SEL1L3)。
本研究鉴定了新的预后标志物,并预测了 CCA 中以前未知的 ceRNA 调控网络,可能为进一步了解 CCA 中 lncRNA 介导的 ceRNA 调控机制提供新的见解。