A three miRNAs signature predicts survival in cervical cancer using bioinformatics analysis.

ABSTRACT: Growing evidences showed that a large number of miRNAs were abnormally expressed in cervical cancer tissues and played irreplaceable roles in tumorigenesis, progression and metastasis. The aim of the present study was to identify the differential miRNAs expression between cervical cancer and normal cervical tissues by analyzing the high-throughput miRNA data downloaded from TCGA database. Additionally, we evaluated the prognostic values of the differentially expressed miRNAs and constructed a three-miRNA signature that could effectively predict patient survival. According to the cut-off criteria (P < 0.05 and |log₂FC| > 2.0), a total of 78 differentially expressed miRNAs were identified between cervical cancer tissues and matched normal tissues, including 37 up-regulated miRNAs

SUBMITTER: Liang B 

PROVIDER: S-EPMC5514022 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature