Abstract
BACKGROUND: The outcomes of ovarian cancer patients are very poor, therefore it is necessary to find prognostic biomarkers and explore the potential underlying molecular mechanisms of ovarian cancer. METHODS: In this study, a gene expression microarray data set covering 562 ovarian serous cystadenocarcinomas and 12,042 genes was downloaded from The Cancer Genome Atlas (TCGA) database. For each candidate gene, samples were allocated into a "high group" or a "low group" according to the expression level. The overall survival (OS) rates were compared between the two groups. Then, a univariate analysis and a multivariate Cox proportional hazards test were carried out to examine the associations between genes and multiple clinicopathological parameters. RESULTS: Among all candidate genes, PI3 (peptidase inhibitor 3, often called elafin) and HLA-DOB (major histocompatibility complex, class II, DO beta) were identified as hub genes. PI3 (P=7.99e-7) and HLA-DOB (P=7.52e-6) showed significant associations with OS, especially in patients with stage III or IV disease. Both PI3 (HR =1.84, P=3.77e-7) and HLA-DOB (HR =0.68, P=0.001134) were identified as independent predictors of ovarian cancer patients OS. In addition, IRF1 (interferon regulatory factor 1) (P=1.16e-15) and SPI1 (Spi-1 proto-oncogene) (P=2.03e-6) were identified as the most significant transcription factors. CONCLUSIONS: Our data indicate that PI3 and HLA-DOB are potential biomarkers that could be used to predict the prognosis of ovarian cancer patients, and may play important roles in ovarian cancer progression. Further experimental and clinical studies with larger sample sizes are needed to confirm these findings.