Identification of potential biomarkers in ovarian carcinoma and an evaluation of their prognostic value.

BACKGROUND: Ovarian cancer is one of the most common malignant tumors in female genital organs, and its incidence rate is high. However, the pathogenesis and prognostic markers of ovarian cancer are unclear. This study sought to screen potential markers of ovarian cancer and to explore their prognostic value.

METHODS: The Cancer Genome Atlas, Gene Expression Omnibus, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases were used in this study. The least absolute shrinkage and selection operator (LASSO), multivariate Cox regression and stepwise regression analysis were chosen to screen genes and construct risk model. Gene Set Enrichment Analysis (GSEA) and an immune-infiltration analysis were performed.

RESULTS: One hundred thirty two co-expressed genes were found. They involved in metabolism, protein phosphorylation, mitochondria, and immune signaling pathways. Twelve genes significantly related to the survival of ovarian cancer were identified. Eight risk genes (i.e., CACNB1 , FAM120B , HOXB2 , MED19 , PTPN2 , SMU1 , WAC.AS1 , and BCL2L11 ) were further screened and used to construct the risk model. The risk status might be an independent prognostic factor of ovarian cancer, and most of the biological functions of genes expressed in high-risk ovarian cancer were related to synapse, adhesion, and immune-related functions. The clusters of CD4+ T cells and M2 macrophages were high in high-risk status samples.

CONCLUSIONS: In ovarian cancer, the abnormal expression of 8 genes, including CACNB1 , FAM120B , HOXB2 , MED19 , PTPN2 , SMU1 , WAC.AS1 , and BCL2L11 , is closely related to ovarian cancer progression, and these genes can serve as independent prognosis markers of ovarian cancer.