标题:
Weighted gene co-expression network analysis identifies specific modules and hub genes related to Wilms tumor
讲者:
唐认桥
单位:
首都儿科研究所
播放:
1527
论文摘要:
Objective Wilms tumor is known as the most common pediatric renal cancer. In the past, candidate diagnostic biomarkers and therapeutic targets have been delineated from genes that were found to be differentially expressed in normal versus tumour samples. Recently, new systems biology approaches have been developed to analyse gene expression data, which may yield new biomarkers.
Methods Five gene expression profile data (GSE2712, GSE11024, GSE11151, GSE66405 and GSE73209) about Wilms tumor from the Gene Expression Omnibus (GEO) database, were included in our analysis. After pre-processing of the data, we built two final datasets, control profile and case profile, encompassing 20 normal kidney samples and 105 Wilms tumor samples, respectively. Using weighted gene co-expression network analysis (WGCNA), we identified modules of coexpressed genes distinguishing normal kidney from disease conditions. Functional annotations of the genes in these modules were carried out to highlight biological processes that may be involved in the development of Wilms tumor.
Results Using WGCNA, we identified 14 lowly preserved modules that may play important roles in Wilms tumor. These modules are mainly related to cell cycle process, chromatin assembly or disassembly, or muscle contraction. Hub genes in each modules were determined by extremely high kME values in both networks, including Ect2, Cox10, Acp5,Anxa2p1,Acta1,Dbn1,Bcl7a ,Birc5, Ddx1, Clta, Dnmt1, Fance, Dhx15, respectively.
Conclusions: Using this new systems biology approach, we identified several genes which may be involved in the progression of Wilms tumor. As such, they may represent potential diagnostic biomarkers as well as therapeutic targets with clinical utility.