Unknown

Dataset Information

Identification of the 11-lncRNA signatures associated with the prognosis of endometrial carcinoma.


ABSTRACT: Endometrial carcinoma (EC) is the fourth most common cancer in women. Some long non-coding RNAs (lncRNAs) are regarded as potential prognostic biomarkers or targets for treatment of many types of cancers. We aim to screen prognostic-related lncRNAs and build a possible lncRNA signature which can effectively predict the survival of patients with EC. We obtained lncRNA expression profiling from the TCGA database. The patients were classified into training set and verification set. By performing Univariate Cox regression model, Robust likelihood-based survival analysis, and Cox proportional hazards model, we developed a risk score with the Cox co-efficient of individual lncRNAs in the training set. The optimum cut-off point was selected by ROC analysis. Patients were effectively divided into h

SUBMITTER: Wan J 

PROVIDER: S-EPMC10358503 | biostudies-literature | 2021 Jan-Mar

REPOSITORIES: biostudies-literature