Identification of biomarkers associated with ovarian cancer based on transcriptome sequencing

Abstract

AbstractObjectiveThis study aimed to explore more biomarkers associated with ovarian cancer.MethodsCell lines SKOV-3 (ovarian serous carcinoma cells) and MCV152 (benign ovarian epithelial tumor cell) were used in this study and performed transcriptome sequencing. The differentially expressed genes (DEGs) between ovarian cancer cells (SKOV-3) and controls (MCV152) were identified, followed by function enrichment analysis. The expression levels of genes involved in the key pathway were validated through PCR and western blot analyses.ResultsTotal 2,020 upregulated and 1,673 downregulated DEGs were obtained between SKOV3 and MCV152 cells. The upregulated and downregulated DEGs were significantly associated with cell adhesion. In addition, the upregulated DEGs were significantly involved in pathways of ECM-receptor interaction, and the downregulated DEGs were involved in PI3K-Akt signaling pathway. PCR and western blot analyses showed that genes (proteins) expression related to PI3K-Akt signaling pathway were in consistent with bioinformatics analysis.ConclusionCell adhesion and extracellular matrix (ECM)-receptor interaction may play an important role in the invasion of ovarian cancer. PI3K-Akt signaling pathway may be involved in the progression of ovarian cancer by up-regulating ANGPT2, FGF18, ITGB4 and ITGB8, and downregulating AKT3 and PIK3AP1.HighlightsCell adhesion and ECM-receptor interaction may play important roles in ovarian cancer invasion.PI3K-Akt signaling pathway may involve in ovarian cancer progression.ANGPT2, FGF18, ITGB4, ITGB8, AKT3 and PIK3AP1 may serve as biomarkers in ovarian cancer.