Wang Jianxin, Yu Hualong, Ye Lan, Jin Lei, Yu Miao, Lv Yanfeng
Department of Anorectal Surgery, The Second Hospital of Shandong University Jinan 250033, Shandong Province, China.
Department of Oncology, The Second Hospital of Shandong University Jinan 250033, Shandong Province, China.
Int J Clin Exp Pathol. 2015 Jan 1;8(1):517-29. eCollection 2015.
CRC (Colorectal cancer) is a lethal cancer for death worldwide and the underlying pathological mechanisms for CRC progression remain unclear. We aimed to explore the regulatory mechanism of CRC and provide novel biomarkers for CRC screening.
Downloading from GEO (Gene Expression Omnibus) database, Microarray data GSE44861 were consisted of 111 colon tissues samples including 55 from adjacent noncancerous tissues and 56 from tumors tissues. After data pre-processing, up- and down regulated DEGs (differentially expressed genes) were identified using Bayes moderated t-test. Then DIVAD (Database for Annotation, Visualization and Integrated Discovery) was recruited to perform functional analysis for DEGs. Thereafter, PPI (protein-protein interaction) network was constructed by mapping DEGs into STRING (Search Tool for the Retrieval of Interacting Genes) database. Further, PPI modules were constructed and the protein domains of DEGs in the modules were analyzed. Moreover, miRNA regulatory network was established through GSEA (gene set enrichment analysis) method.
In summary, 96 up- and 212 down-regulated DEGs were identified. Totally, ten DEGs with high degrees in the constructed PPI network were selected, in which COLL1A1, PTGS2 and ASPN were also identified as crucial genes in PPI modules. Furthermore, COLL1A1 was predicted to be targeted by miR-29, while PTGS2 and ASPN were both predicted to be regulated by miR-101 and miR-26.
COL11A1 might involve in the progression of CRC via being targeted by miR-29, whereas PTGS2 and ASPN were both regulated by miR-101 and miR-26. Moreover, ASPN may be supposed as a novel biomarker for CRC detection and prevention.
结直肠癌(CRC)是全球致死率很高的癌症,其进展的潜在病理机制仍不清楚。我们旨在探索CRC的调控机制,并为CRC筛查提供新的生物标志物。
从基因表达综合数据库(GEO)下载微阵列数据GSE44861,该数据由111个结肠组织样本组成,包括55个来自相邻非癌组织和56个来自肿瘤组织的样本。经过数据预处理后,使用贝叶斯调节t检验识别上调和下调的差异表达基因(DEG)。然后利用注释、可视化和综合发现数据库(DIVAD)对DEG进行功能分析。此后,通过将DEG映射到STRING(检索相互作用基因的搜索工具)数据库构建蛋白质-蛋白质相互作用(PPI)网络。进一步构建PPI模块,并分析模块中DEG的蛋白质结构域。此外,通过基因集富集分析(GSEA)方法建立miRNA调控网络。
总之,共识别出96个上调和212个下调的DEG。在构建的PPI网络中总共选择了10个高度连接的DEG,其中COL1A1、PTGS2和ASPN也被确定为PPI模块中的关键基因。此外,预测COL1A1受miR-29靶向,而PTGS2和ASPN均被预测受miR-101和miR-26调控。
COL11A1可能通过被miR-29靶向参与CRC的进展,而PTGS2和ASPN均受miR-101和miR-26调控。此外,ASPN可能被视为一种用于CRC检测和预防的新型生物标志物。