Integrated Analysis of a Competing Endogenous RNA Network Revealing a Prognostic Signature for Cervical Cancer - Xia, Leilei; Wang, Han; Cai, Shengyun; Su, Xiaoling; Shen, Jizi; Meng, Qi; Chen, Yu; Li, Li; Yan, Jiuqiong; Zhang, Caihong; Xu, Mingjuan (Frontiers in Oncology, 2018)
Given the high morbidity and younger trend noted in cervical cancer, it is important to identify sensitive and effective biomarkers for predicting the survival outcome of patients. Based on the data of 307 cervical cancer cases acquired from the TCGA portal, 1920 differentially expressed mRNAs, 70 miRNAs, and 493 lncRNAs were screened by comparing cervical cancer tissues with paracancerous tissues. A ceRNA network containing 50 lncRNAs, 16 miRNAs, and 81 mRNAs was further constructed. Eighteen RNAs, namely, 13 mRNAs, 2 miRNAs, and 3 lncRNAs, were identified as significant prognostic factors by univariate Cox proportional hazards regression. ERG and FASN signatures were discovered using a multivariate Cox regression model built to identify independent prognostic factors in cervical cancer patients. ROC analysis was used to develop the optimal cut-off value to distinguish the risk level of cervical cancer patients. High-risk patients exhibit a poorer prognosis than low-risk patients. This study focused on ceRNA networks to provide a novel perspective and insight into cervical cancer and suggested that the signature could serve as an independent prognostic biomarker in cervical cancer.