Wang Jiawu, Zhang Chengyao, He Weiyang, Gou Xin
Department of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Department of Head and Neck Cancer Center, Chongqing University Cancer Hospital & Chongqing Cancer Institute & Chongqing Cancer Hospital, Chongqing, China.
J Cell Biochem. 2019 Feb;120(2):2576-2593. doi: 10.1002/jcb.27557. Epub 2018 Oct 2.
This study aimed to assess the long noncoding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) regulatory network in clear cell renal cell carcinoma (ccRCC) by gene expression analyses.
LncRNA, miRNA, and mRNA expression profiles in ccRCC were obtained from The Cancer Genome Atlas. Differentially expressed lncRNAs, mRNAs (cut-off: |log 2 [fold change, FC])| > 2.0 and adjusted P < 0.01) and miRNAs (|log 2FC| > 1.5 and adjusted P < 0.01) were unveiled using R. Cox regression analysis was performed to identify prognostic factors of ccRCC related to overall survival (OS). A protein-protein interaction (PPI) network was constructed for differentially expressed mRNAs (DEmRNAs) by Search Tool for the Retrieval of Interacting Genes (STRING). Key hub genes were screened from top 300 DEmRNAs. LncRNA-miRNA and miRNA-mRNA regulatory network were constructed and combined into the competing endogenous RNA regulatory network. Gene ontology biological terms were screened by STRING; Kyoto Encyclopedia of Genes and Genomes pathways were identified using the "clusterProfiler" package in R.
A total of 2331, 1517, and 83 DEmRNAs, lncRNAs, and miRNAs were identified, respectively. Eleven lncRNAs (AC016773.1, HOTTIP, LINC00460, NALCN-AS1, PVT1, TRIM36-IT1, WT1-AS, COL18A1-AS1, LINC00443, LINC00472, and TCL6), three miRNAs (hsa-mir-21, hsa-mir-144, and hsa-mir-155), and three mRNAs (COL4A4, NOD2, and GOLGA8B) were associated with OS. Specifically, four lncRNAs (PVT1, LINC00472, TCL6, and WT1-AS1) and one mRNA (Collagen Type IV Alpha 4 Chain) were verified as independent prognostic factors by Gene Expression Profiling Interactive Analysis. Eleven key hub genes were obtained by PPI analysis. "Cell adhesion molecules (CAMs)," "chemical carcinogenesis," and "cytokine-cytokine receptor interaction" were significantly enriched in the network.
The findings clarify the pathogenesis of ccRCC and might provide potential therapeutic targets.
本研究旨在通过基因表达分析评估透明细胞肾细胞癌（ccRCC）中的长链非编码RNA（lncRNA）-微小RNA（miRNA）-信使RNA（mRNA）调控网络。
从癌症基因组图谱获取ccRCC中的lncRNA、miRNA和mRNA表达谱。使用R软件揭示差异表达的lncRNAs、mRNAs（截断值：|log₂[倍数变化，FC]|>2.0且校正P<0.01）和miRNAs（|log₂FC|>1.5且校正P<0.01）。进行Cox回归分析以确定与总生存期（OS）相关的ccRCC预后因素。通过检索相互作用基因的搜索工具（STRING）为差异表达的mRNA（DEmRNAs）构建蛋白质-蛋白质相互作用（PPI）网络。从300个排名靠前的DEmRNAs中筛选关键枢纽基因。构建lncRNA-miRNA和miRNA-mRNA调控网络并合并为竞争性内源性RNA调控网络。通过STRING筛选基因本体生物学术语；使用R软件中的“clusterProfiler”包鉴定京都基因与基因组百科全书途径。
分别鉴定出2331个、1517个和83个DEmRNAs、lncRNAs和miRNAs。11个lncRNAs（AC016773.1、HOTTIP、LINC00460、NALCN-AS1、PVT1、TRIM36-IT1、WT1-AS、COL18A1-AS1、LINC00443、LINC00472和TCL6）、3个miRNAs（hsa-mir-21、hsa-mir-144和hsa-mir-155）和3个mRNAs（COL4A4、NOD2和GOLGA8B）与OS相关。具体而言，通过基因表达谱交互分析验证了4个lncRNAs（PVT1、LINC00472、TCL6和WT1-AS1）和1个mRNA（IV型胶原α4链）为独立预后因素。通过PPI分析获得11个关键枢纽基因。“细胞黏附分子（CAMs）”、“化学致癌作用”和“细胞因子-细胞因子受体相互作用”在网络中显著富集。
这些发现阐明了ccRCC的发病机制，并可能提供潜在的治疗靶点。
