Identification of pathway-related modules in high-grade osteosarcoma based on topological centrality of network strategy
B. Ning, D.-L. Xu, J.-H. Gao, L.-L. Wang, S.-Y. Yan, S. Cheng Department of Orthopaedics, People’s Hospital of Dongying, Dongying, Shandong Province, China. boning2015@yeah.net
OBJECTIVE: The objective of this paper is to identify pathway-related modules which are defined as in high-grade osteosarcoma based on topological centralities analysis of networks.
MATERIALS AND METHODS: Co-expression network was constructed by weighted gene co-expression network analysis (WGCNA) based on differentially expressed genes (DEGs). Pathway enrichment analysis was conducted by Kyoto Encyclopedia of Genes and Genomes (KEGG) database to detect pathway enriched genes. Pathway-related modules of pathway enriched genes were mined from the co-expression network. Then topological centralities (degree, closeness, stress and betweenness centrality) analyses for co-expression network and sub-networks were performed to explore hub genes. Validation of hub genes was carried out utilizing reverse transcription-polymerase chain reaction (RT-PCR) assays.
RESULTS: There were 129 nodes and 1229 edges in co-expression network. We obtained a total of 16 hub genes and 11 pathway-related modules. Module 17 (Bladder cancer module) was the most significant module, which comprising 9 of 16 hub genes and 6 pathway enriched genes, taking intersection elements (CAV1 and CCND1). RT-PCR results showed that both of CAV1 and CCND1 in high-grade osteosarcoma were significantly differentially expressed compared with normal controls.
CONCLUSIONS: This work may contribute to understanding the molecular pathogenesis and provide potential biomarkers for detections and effective therapies of high-grade osteosarcoma.
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To cite this article
B. Ning, D.-L. Xu, J.-H. Gao, L.-L. Wang, S.-Y. Yan, S. Cheng
Identification of pathway-related modules in high-grade osteosarcoma based on topological centrality of network strategy
Eur Rev Med Pharmacol Sci
Year: 2016
Vol. 20 - N. 11
Pages: 2209-2220