Network-Based Coexpression Analysis Identifies Functional and Prognostic Long Noncoding RNAs in Hepatocellular Carcinoma

Four Prognosis-Associated lncRNAs Serve as Biomarkers in Ovarian Cancer

Long non-coding RNAs (lncRNAs) play crucial roles in ovarian cancer (OC) development. However, prognosis-associated lncRNAs (PALs) for OC have not been completely elucidated. Our study aimed to identify the PAL signature of OC. A total of 663 differentially expressed lncRNAs were identified in the databases. According to the weighted gene coexpression analysis, the highly correlated genes were clustered into seven modules related to the clinical phenotype of OC. A total of 25 lncRNAs that were significantly related to overall survival were screened based on univariate Cox regression analysis. The prognostic risk model constructed contained seven PALs based on the parameter λ_min, which could stratify OC patients into two risk groups. The results showed that the risk groups had different overall survival rates in both The Cancer Genome Atlas (TCGA) and two verified Gene Expression Omnibus (GEO) databases. Univariate and multivariate Cox regression analyses confirmed that the risk model was an independent risk factor for OC. Gene enrichment analysis revealed that the identified genes were involved in some pathways of malignancy. The competitive endogenous RNA (ceRNA) network included five PALs, of which four were selected for cell function assays. The four PALs were downregulated in 33 collected OC tissues and 3 OC cell lines relative to the control. They were shown to regulate the proliferative, migratory, and invasive potential of OC cells via Cell Counting Kit-8 (CCK-8) and transwell assays. Our study fills the gaps of the four PALs in OC, which are worthy of further study.