Identification and analysis of genes associated with epithelial ovarian cancer by integrated bioinformatics methods

摘要

Background Though considerable efforts have been made to improve the treatment of epithelial ovarian cancer (EOC), the prognosis of patients has remained poor. Identifying differentially expressed genes (DEGs) involved in EOC progression and exploiting them as novel biomarkers or therapeutic targets is of great value.