The prognosis of ovarian cancer (OC) remains poor. Thus, the present study aims to identify independent prognostic factor in OC patients. OC gene expression studies GSE26712 and TCGA-OV were included in this study. Prognosis-associated differentially expressed genes (DEGs) between normal ovarian tissue and OC were identified. LASSO Cox proportional hazards regression model was conducted and a prognostic signature was constructed based on these DEGs. The predictive ability of the signature was analyzed in the training set and test set. The prognosis performance of the signature was compared with CA-125 and HE4. Gene set enrichment analysis (GSEA) was conducted to identify relevant mechanism. 332 DEGs were identified, out of which 64 DEGs were significantly correlated with the overall survival (OS) of OC patients, and 5 DEGs (IGF2, PEG3, DCN, LYPD1 and RARRES1) were applied to build a 5-gene signature. Patients in the 5-gene signature low-risk group had significantly better OS compared to those in the 5-gene high-risk group (p=0.0004) in the training set. Similar results were found in the test set, and the signature was also an independent prognostic factor. The prognosis performance of the 5-gene signature was significantly better than that of CA-125 and HE4. GSEA suggested that OC samples in the 5-gene high-risk group were significantly enriched in WNT/β-catenin signaling and epithelialmesenchymal transition. We developed and validated a 5-gene signature that might be used as an independent prognostic factor in patients with OS.

ABSTRACT. miR-137, a brain-enriched microRNA, is involved in the control of neuronal proliferation, differentiation, and dendritic arborization, all of which are important for proper neurogenesis and relevant to schizophrenia. miR-137 is also known to regulate many genes implicated in schizophrenia risk. Although reports have associated the miR-137 polymorphism rs1625579 with this disease, their results have been inconsistent. The aim of this meta-analysis was to evaluate the relationship between rs1625579 and schizophrenia. Data were obtained from an electronic database, and pooled odds ratios (ORs) with 95% confidence intervals (95%CI) were used to test the association using the RevMan 5.3 software. Twelve case-control studies comprising 11,583 cases and 14,315 controls were included. An estimated lambda value of 0.46 was recorded, suggesting that a codominant model of inheritance was most likely. A statistically significant association was established under allelic (T vs G: OR = 1.15, 95%CI = 1.10-1.21, P < 0.001) and homogeneous codominant models (TT vs GG: OR = 1.32, 95%CI = 1.13-1.54, P < 0.001), but no such relationship was detected using the heterogeneous codominant model (GT vs GG: OR = 1.14, 95%CI = 0.97-1.34, P = 0.11). This meta-analysis demonstrates that the rs1625579 miR-137 genetic variant significantly increases schizophrenia risk.