Chen Juan, Qian Zhenwen, Li Fengling, Li Jinzhi, Lu Yi
Four Ward, Taian Disabled Soldiers Hospital of Shandong Province, Taian, China.
Department of Inspection, Affiliated Hospital of Jining Medical College of Shandong Province, Jining, China.
Gut Liver. 2017 Jan 15;11(1):112-120. doi: 10.5009/gnl16063.
BACKGROUND/AIMS: The integration of multiple profiling data and the construction of a transcriptional regulatory network may provide additional insights into the molecular mechanisms of hepatocellular carcinoma (HCC). The present study was conducted to investigate the deregulation of genes and the transcriptional regulatory network in HCC.
An integrated analysis of HCC gene expression datasets was performed in Gene Expression Omnibus. Functional annotation of the differentially expression genes (DEGs) was conducted. Furthermore, transcription factors (TFs) were identified, and a global transcriptional regulatory network was constructed.
An integrated analysis of eight eligible gene expression profiles of HCC led to 1,835 DEGs. Consistent with the fact that the cell cycle is closely related to various tumors, the functional annotation revealed that genes involved in the cell cycle were significantly enriched. A transcriptional regulatory network was constructed using the 62 TFs, which consisted of 872 TF-target interactions between 56 TFs and 672 DEGs in the context of HCC. The top 10 TFs covering the most downstream DEGs were ZNF354C, NFATC2, ARID3A, BRCA1, ZNF263, FOXD1, GATA3, FOXO3, FOXL1, and NR4A2. This network will appeal to future investigators focusing on the development of HCC.
The transcriptional regulatory network can provide additional information that is valuable in understanding the underlying molecular mechanism in hepatic tumorigenesis.
背景/目的：整合多种分析数据并构建转录调控网络，可能为深入了解肝细胞癌（HCC）的分子机制提供更多线索。本研究旨在探究HCC中基因的失调情况及转录调控网络。
在基因表达综合数据库中对HCC基因表达数据集进行综合分析。对差异表达基因（DEG）进行功能注释。此外，鉴定转录因子（TF）并构建全局转录调控网络。
对8个符合条件的HCC基因表达谱进行综合分析，共得到1835个DEG。鉴于细胞周期与各种肿瘤密切相关，功能注释显示参与细胞周期的基因显著富集。利用62个TF构建了转录调控网络，在HCC背景下，该网络由56个TF与672个DEG之间的872个TF-靶标相互作用组成。覆盖最下游DEG的前10个TF为ZNF354C、NFATC2、ARID3A、BRCA1、ZNF263、FOXD1、GATA3、FOXO3、FOXL1和NR4A2。该网络将吸引未来专注于HCC发展的研究人员。
转录调控网络可为理解肝脏肿瘤发生的潜在分子机制提供有价值的额外信息。
