Abstract
Background: Ovarian cancer is the gynecologic tumor with the highest fatality rate, and high-grade serous ovarian cancer (HGSOC) is the most common and malignant type of ovarian cancer. One important reason for the poor prognosis of HGSOC is the lack of effective diagnostic and prognostic biomarkers. New biomarkers are necessary for improvement of treatment strategies and to ensure appropriate healthcare decisions.Methods: To construct the co-expression network of HGSOC samples, we applied weighted gene co-expression network analysis (WGCNA) to assess the proteomic data downloaded from Clinical Proteomic Tumor Analysis Consortium (CPTAC), and module-trait relationship was then analyzed and plotted in a heat map to choose key module associated with HGSOC. Enrichment analysis was performed on the genes in the key modules to explore the functional information in which these genes participate. Hub genes with high connectivity in key module were identified by Cytoscape software. Furthermore, the true hub gene was selected through survival analysis, followed by expression verification with transcriptome dataset from TCGA and GTEx. Finally, the potential biological functions of hub gene were analyzed via single-gene Gene Set Enrichment Analysis (GSEA).Results: After merging similar modules, a total of 9 modules were identified. Module-trait analysis revealed that the brown module (cor = 0.7) was significantly associated with HGSOC. The results of enrichment analysis of the genes in the brown module show that these genes were related to the functions of the extracellular matrix, the complement system and the blood system. Ten hub genes with the highest connectivity were selected by protein-protein interaction analysis. After survival analysis and expression verification of hub genes, only ALB was confirmed to be the true hub gene and positively correlated with HGSOC prognosis. Single gene GSEA revealed that ALB was associated with cell material degradation.Conclusion: We conducted the first gene co-expression analysis based on proteomic data from HGSOC samples, and found that ALB had prognostic value, which could be applied in the treatment of HGSOC in the future.
Integrated weighted gene co‐expression network analysis reveals biomarkers associated with prognosis of high‐grade serous ovarian cancer
