Shen Li, Zhao Lizhi, Tang Jiquan, Wang Zhiwei, Bai Weisong, Zhang Feng, Wang Shouli, Li Weihua
Department of Digestive Surgery, HanZhong Central Hospital, Hanzhong, Shaanxi, 723000, China.
The People's Hospital in Gansu Province, Center Lab, No, 204 west Donggang Rood, Lanzhou City, Gansu Province, 730000, China.
Pathol Oncol Res. 2017 Oct;23(4):745-752. doi: 10.1007/s12253-016-0178-y. Epub 2017 Jan 5.
RNA-seq data of stomach adenocarcinoma (STAD) were analyzed to identify critical genes in STAD. Meanwhile, relevant small molecule drugs, transcription factors (TFs) and microRNAs (miRNAs) were also investigated. Gene expression data of STAD were downloaded from The Cancer Genome Atlas (TCGA). Differential analysis was performed with package edgeR. Relationships with correlation coefficient > 0.6 were retained in the gene co-expression network. Functional enrichment analysis was performed for the genes in the network with DAVID and KOBASS 2.0. Modules were identified using Cytoscape. Relevant small molecules drugs, transcription factors (TFs) and microRNAs (miRNAs) were revealed by using CMAP and WebGestalt databases. A total of 520 DEGs were identified between 285 STAD samples and 33 normal controls, including 244 up-regulated and 276 down-regulated genes. A gene co-expression network containing 53 DEGs and 338 edges was constructed, the genes of which were significantly enriched in focal adhesion, ECM-receptor interaction and vascular smooth muscle contraction pathways. Three modules were identified from the gene co-expression network and they were associated with skeletal system development, inflammatory response and positive regulation of cellular process, respectively. A total of 20 drugs, 9 TFs and 6 miRNAs were acquired that may regulate the DEGs. NFAT-COL1A1/ANXA1, HSF2-FOS, SREBP-IL1RN and miR-26-COL5A2 regulation axes may be important mechanisms for STAD.
对胃腺癌（STAD）的RNA测序数据进行分析，以鉴定STAD中的关键基因。同时，还研究了相关的小分子药物、转录因子（TFs）和微小RNA（miRNAs）。从癌症基因组图谱（TCGA）下载STAD的基因表达数据。使用edgeR软件包进行差异分析。基因共表达网络中保留相关系数>0.6的关系。使用DAVID和KOBASS 2.0对网络中的基因进行功能富集分析。使用Cytoscape识别模块。通过使用CMAP和WebGestalt数据库揭示相关的小分子药物、转录因子（TFs）和微小RNA（miRNAs）。在285个STAD样本和33个正常对照之间共鉴定出520个差异表达基因（DEGs），包括244个上调基因和276个下调基因。构建了一个包含53个DEGs和338条边的基因共表达网络，其中的基因在粘着斑、细胞外基质受体相互作用和血管平滑肌收缩途径中显著富集。从基因共表达网络中识别出三个模块，它们分别与骨骼系统发育、炎症反应和细胞过程的正调控相关。共获得了20种药物、9个TFs和6个miRNAs，它们可能调控这些DEGs。NFAT-COL1A1/ANXA1、HSF2-FOS、SREBP-IL1RN和miR-26-COL5A2调控轴可能是STAD的重要机制。
