Genome-wide expression profiling reveals novel biomarkers in epithelial ovarian cancer

Abstract

Epithelial ovarian cancer (EOC) is the most aggressive and frequent malignancy detected among women worldwide. The pathophysiology of OC should, therefore be better understood to identify diagnostic, prognostic, and predictive novel biomarkers necessary for early detection, management, and prognostication. In this study, we aimed to investigate transcriptomic landscape and biomarker through RNA-seq data analysis. Further analysis by Protein Protein network identified top 10 Differentially Expressed Genes (DEGs). KEGG pathway enrichment analysis revealed the significant enrichment of DEGs in basal cell carcinoma, cell cycle and FoxO signalling pathway. The RNA-seq results of 10 DEGs were validated by QRT-PCR and TCGA database. Correlation studies were also performed between gene expression and clinical characteristics followed by survival analysis. Finally, 8 DEGs (CDKN1A, BCL6, CDC45, WNT2, TLR5, AQP5) including two novel DEGs (CSN1S1 and NKILA) were identified showing significant correlations with EOC characteristics. These may serve as interesting biomarkers and novel treatment targets and warrant further investigation into the functional outcome of EOC.

Keywords: Bioinformatics analysis; Diagnostic biomarkers; Differentially expressed genes (DEGs); Epithelial ovarian cancer; Gene expression; QRT-PCR; RNA-sequencing.