Identification of differentially expressed genes and signaling pathways in ovarian cancer by integrated bioinformatics analysis

Abstract excerpt

BACKGROUND: The mortality rate associated with ovarian cancer ranks the highest among gynecological malignancies. However, the cause and underlying molecular events of ovarian cancer are not clear. Here, we applied integrated bioinformatics to identify key pathogenic genes involved in ovarian cancer and reveal potential molecular mechanisms. RESULTS: The expression profiles of GDS3592, GSE54388, and GSE66957 were...

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