AI Article Synopsis
- The study aims to improve early diagnosis of mucinous epithelial ovarian cancer (mEOC) by analyzing gene expression using weighted gene co-expression network analysis (WGCNA).
- By reanalyzing the GSE26193 gene expression dataset, researchers identified 11 gene co-expression modules, with a specific focus on the turquoise module linked to mEOC, and validated 10 hub genes related to this subtype.
- The identified hub genes may serve as potential biomarkers to enhance the understanding and early diagnosis of mEOC, offering a more precise framework for this cancer type.
Article Abstract
Purpose: In order to identify the molecular characteristics and improve the efficacy of early diagnosis of mucinous epithelial ovarian cancer (mEOC), here, the transcriptome profiling by weighted gene co-expression network analysis (WGCNA) has been proposed as an effective method.
Methods: The gene expression dataset GSE26193 was reanalyzed with a systematical approach, WGCNA. mEOC-related gene co-expression modules were detected and the functional enrichments of these modules were performed at GO and KEGG terms. Ten hub genes in the mEOC-related modules were validated using two independent datasets GSE44104 and GSE30274.
Results: 11 co-expressed gene modules were identified by WGCNA based on 4917 genes and 99 epithelial ovarian cancer samples. The turquoise module was found to be significantly associated with the subtype of mEOC. KEGG pathway enrichment analysis showed genes in the turquoise module significantly enriched in metabolism of xenobiotics by cytochrome P450 and steroid hormone biosynthesis. Ten hub genes (LIPH, BCAS1, FUT3, ZG16B, PTPRH, SLC4A4, MUC13, TFF1, HNF4G and TFF2) in the turquoise module were validated to be highly expressed in mEOC using two independent gene expression datasets GSE44104 and GSE30274.
Conclusion: Our work proposed an applicable framework of molecular characteristics for patients with mEOC, which may help us to obtain a precise and comprehensive understanding on the molecular complexities of mEOC. The hub genes identified in our study, as potential specific biomarkers of mEOC, may be applied in the early diagnosis of mEOC in the future.
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| http://dx.doi.org/10.1016/j.gene.2019.05.034 | DOI Listing |
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