Li Liu1, Zhe Song2, Xu-Dong Gao3, Xian Chen1, Xiao-Bin Wu1, Mi Wang1, Yu-De Hong1. 1. Department of Urology, The Second Hospital, University of South China, Hengyang, 421001, Hunan, China. 2. Department of Urology, The Second Hospital, University of South China, Hengyang, 421001, Hunan, China. songzhe_USC@163.com. 3. College of Health Science and Nursing, Wuhan Polytechnic University, Wuhan, 420000, China.
Abstract
BACKGROUND: Wilms tumor (WT) is the most common malignant renal tumor in children. The aim of this study was to identify potential susceptibility gene of WT for better prognosis. METHODS: Weighted gene coexpression network analysis is used for the detection of clinically important biomarkers associated with WT. RESULTS: In the study, 59 tissue samples from National Cancer Institute were pretreated for constructing gene co-expression network, while 224 samples also downloaded from National Cancer Institute were used for hub gene validation and module preservation analysis. Three modules were found to be highly correlated with WT, and 44 top hub genes were identified in these key modules eventually. In addition, both the module preservation analysis and gene validation showed ideal results based on other dataset with 224 samples. Meanwhile, Functional enrichment analysis showed that genes in module were enriched to sister chromatid cohesion, cell cycle, oocyte meiosis. CONCLUSION: In summary, we established a gene co-expression network to identify 44 hub genes are closely to recurrence and staging of WT, and 6 of these hub genes was closely related to the poor prognosis of patients. Our findings revealed that those hub genes may be used as potential susceptibility gene for clinical diagnosis and prognosis of this tumor.
BACKGROUND:Wilms tumor (WT) is the most common malignant renal tumor in children. The aim of this study was to identify potential susceptibility gene of WT for better prognosis. METHODS: Weighted gene coexpression network analysis is used for the detection of clinically important biomarkers associated with WT. RESULTS: In the study, 59 tissue samples from National Cancer Institute were pretreated for constructing gene co-expression network, while 224 samples also downloaded from National Cancer Institute were used for hub gene validation and module preservation analysis. Three modules were found to be highly correlated with WT, and 44 top hub genes were identified in these key modules eventually. In addition, both the module preservation analysis and gene validation showed ideal results based on other dataset with 224 samples. Meanwhile, Functional enrichment analysis showed that genes in module were enriched to sister chromatid cohesion, cell cycle, oocyte meiosis. CONCLUSION: In summary, we established a gene co-expression network to identify 44 hub genes are closely to recurrence and staging of WT, and 6 of these hub genes was closely related to the poor prognosis of patients. Our findings revealed that those hub genes may be used as potential susceptibility gene for clinical diagnosis and prognosis of this tumor.
Authors: Matthew S Squires; Ruth E Feltell; Nicola G Wallis; E Jonathan Lewis; Donna-Michelle Smith; David M Cross; John F Lyons; Neil T Thompson Journal: Mol Cancer Ther Date: 2009-01-27 Impact factor: 6.261
Authors: Benjamin J Halliday; Ryuji Fukuzawa; David M Markie; Richard G Grundy; Jackie L Ludgate; Michael A Black; Jane E Skeen; Robert J Weeks; Daniel R Catchpoole; Aedan G K Roberts; Anthony E Reeve; Ian M Morison Journal: PLoS Genet Date: 2018-06-18 Impact factor: 5.917