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Identification and validation of a 9-gene signature for the prognosis of ovarian cancer by integrated bioinformatical analysis

5 Sept 2022

Abstract excerpt

Background: Ovarian cancer (OC) is the most lethal malignancy among gynecological cancers worldwide. It is urgent to identify effective biomarkers for the prognosis and diagnosis of OC. Methods: We analyzed 4 OC Gene Expression Omnibus (GEO) data sets to detect differentially expressed genes (DEGs). To explore potential correlations between the gene sets and clinical features, we conducted weighted gene...

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PMID: 36330389
DOI: 10.21037/atm-22-3752

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