Comprehensive analyses reveal three-gene signatures in ovarian cancer

Abstract

Background: Ovarian cancer is a common cancer that affects the quality of women’s life. With the limitation of the early diagnosis of the disease, ovarian cancer has a high mortality rate worldwide. However, the molecular mechanisms underlying tumor invasion, proliferation, and metastasis in ovarian cancer remain unclear. We aimed to identify, using bioinformatics, important genes and pathways that may serve crucial roles in the prevention, diagnosis, and treatment of ovarian cancer. Methods: Three microarray datasets (GSE14407, GSE36668, and GSE26712) were selected for whole-genome gene expression profiling , and differentially expressed genes were identified between normal and ovarian cancer tissues. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using DAVID. Additionally, a protein-protein interaction network was constructed to reveal possible interactions among the differently expressed genes. The prognostic values of the hub genes were investigated using Gene Expression Profiling Interactive Analysis (GEPIA) and the KM plotter database. Meanwhile, the mRNA expression analysis of the hub genes was performed using the GEPIA database. Results: We obtained 247 upregulated and 530 downregulated differently expressed genes, and 52 hub genes in the significant gene modules. Enrichment analysis revealed that the hub genes were significantly ( P < 0.05) associated with proliferation. Additionally, BIRC5, CXCL13, and PBK were revealed to be significantly associated with the clinical prognosis of patients with ovarian cancer. Immunohistochemical staining results obtained from the Human Protein Atlas revealed that BIRC5, PBK, and CXCL13 were highly expressed in ovaria cancer tissues. Conclusion Three-gene signatures ( BIRC5, CXCL13 , and PBK ) are associated with the occurrence, development, and prognosis of OC, and may therefore serve as biological markers of the disease.

MFAP2 aggravates tumor progression through activating FOXM1/β‐catenin‐mediated glycolysis in ovarian cancer

“…Li et al selected three microarray datasets (GSE14407, GSE36668, and GSE26712) for genome-wide gene expression profile analysis and identified MFAP2 as one of the differentially expressed genes between normal and ovarian cancer tissues. 12 In addition, Considine et al confirmed the overlapping genetic association signals between plasma protein levels of MFAP2 and EOC risk by using the regional genome map. 13 Based on this, we evaluated MFAP2 expression using the TCGA database of ovarian cancer cohort high-throughput RNA-sequencing data Gene Expression Profiling Interactive Analysis (GEPIA; http://gepia.cancer-pku.cn).…”

“…Li et al selected three microarray datasets (GSE14407, GSE36668, and GSE26712) for genome‐wide gene expression profile analysis and identified MFAP2 as one of the differentially expressed genes between normal and ovarian cancer tissues 12 . In addition, Considine et al confirmed the overlapping genetic association signals between plasma protein levels of MFAP2 and EOC risk by using the regional genome map 13 .…”