Exploring prognostic genes in ovarian cancer stage-related coexpression network modules

Medicine
Lili YangYing Yue

Abstract

Identification of meaningful cluster modules of differential genes or representative biomarkers related to the stages of ovarian cancer (OC) is pivotal, which may help to detect mechanisms of OC progression and evaluate OC patients' prognosis.We downloaded gene expression data and the corresponding clinical information of OC patients from The Cancer Genome Atlas (TCGA) database, which included 379 ovarian cancer patients. Differentially expressed genes (DEGs) of OC patients between stages were picked out using R. There were 731 differential genes between ovarian cancer stage II and stage III (DEGs II-III) and 563 differential genes between ovarian cancer stage III and stage IV (DEGs III-IV), then we performed GO analysis and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway analysis using Database for Annotation, Visualization and Integrated Discovery (DAVID). Moreover, CytoHubba was used to detect the top 20 hub genes in DEGs II-III and DEGs III-IV, followed Cytoscape with search tool for the retrieval of interacting genes (STRING) and MCODE plug-in was utilized to construct protein-protein interaction (PPI) modules of these genes. Three important coexpression modules of DEGs II-III and 3 more meaningful modules of DEGs III...Continue Reading

References

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Software Mentioned

GEPIA
cytoHubba
MCODE
R Language ( Edger R package )
R
Edger R package
Edger R
Search Tool for the Retrieval
DAVID
STRING

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