====== Glioma coexpression analysis ======

Systemic [[coexpression analysis]] of [[glioma]] could be beneficial for the identification and development of new prognostic and predictive [[marker]]s in the clinical management.

Shi et al., from [[Hangzhou]], Department of Neurosurgery, Changhai Hospital, Second Military Medical University, [[Shanghai]]. Department of Neurosurgery, Huai'an Second People's Hospital, The Affiliated Huai'an Hospital of Xuzhou Medical University, Huai'an, [[China]], extracted [[data set]]s from the [[Gene Expression Omnibus]] [[data set]] by using "glioma" as the keyword. Then, a [[coexpression]] [[module]] was constructed with the help of [[Weighted Gene Coexpression Network Analysis]] software. Besides, [[Gene Ontology]] (GO) and [[Kyoto Encyclopedia of Genes and Genomes]] (KEGG) enrichment analyses were performed on the [[gene]]s in these modules. As a result, the critical modules and target genes were identified. Eight coexpression modules were constructed using the 4,000 genes with a high expression value of the total 141 glioma samples. The result of the analysis of the interaction among these modules showed that there was a high scale independence degree among them. The GO and KEGG enrichment analyses showed that there was a significant difference in the enriched terms and degree among these eight modules, and module 5 was identified as the most important module. Besides, the pathways it was enriched in, hsa04510: Focal adhesion and hsa04610: Complement and coagulation cascades, were determined as the most important pathways. In summary, module 5 and the pathways it was enriched in, hsa04510: Focal adhesion and has 04610: Complement and coagulation cascades, have the potential to serve as [[glioma biomarker]]s 
((Shi T, Chen J, Li J, Yang BY, Zhang QL. Identification of key gene modules and
pathways of human glioma through [[coexpression network]]. J Cell Physiol. 2018 Aug
1. doi: 10.1002/jcp.27059. [Epub ahead of print] PubMed PMID: 30067869.
)).