Weighted Gene Co-expression Network Analysis in Identification of Endometrial Cancer Prognosis Markers

Objective: Endometrial cancer (EC) is the most common gynecologic malignancy. Identification of potentialbiomarkers of EC would be helpful for the detection and monitoring of malignancy, improving clinical outcomes.
Methods: The Weighted Gene Co-expression Network Analysis method was used to identify prognostic markersfor EC in this study. Moreover, underlying molecular mechanisms were characterized by KEGG pathwayenrichment and transcriptional regulation analyses.
Results: Seven gene co-expression modules were obtained,but only the turquoise module was positively related with EC stage. Among the genes in the turquoise module,COL5A2 (collagen, type V, alpha 2) could be regulated by PBX (pre-B-cell leukemia homeobox 1)1/2 andHOXB1(homeobox B1) transcription factors to be involved in the focal adhesion pathway; CENP-E (centromereprotein E, 312kDa) by E2F4 (E2F transcription factor 4, p107/p130-binding); MYCN (v-myc myelocytomatosisviral related oncogene, neuroblastoma derived [avian]) by PAX5 (paired box 5); and BCL-2 (B-cell CLL/lymphoma 2) and IGFBP-6 (insulin-like growth factor binding protein 6) by GLI1. They were predicted to beassociated with EC progression via Hedgehog signaling and other cancer related-pathways.
Conclusions: Thesedata on transcriptional regulation may provide a better understanding of molecular mechanisms and clues topotential therapeutic targets in the treatment of EC.