Kun Xue1,2, Junmei Yang3, Jia Hu2, Jianhui Liu2, Xingang Li1. 1. a Department of Neurosurgery , Qilu Hospital of Shandong University , Jinan , Shandong , China. 2. b Department of Neurosurgery , Yantaishan Hospital , Yantai , Shandong , China. 3. c Second Traumatic orthopedics , Yantaishan Hospital , Yantai , Shandong , China.
Abstract
BACKGROUND: Recently, microRNA-133b (miR-133b) dysregulation has been shown to play a key role in several human cancers, as well as glioma. In this study, we aimed to investigate the clinical significance and prognostic value of miR-133b in glioma. METHODS: Real-time quantitative PCR was employed to measure the expression level of miR-133b in tissues. Survival analysis was carried out by using the log-rank test and Kaplan-Meier method. Prognostic factors for overall survival were identified by univariate and multivariate analyses using the Cox proportional hazards regression model. RESULTS: The expression level of miR-133b was significantly lower in glioma tissues compared with matched non-cancerous brain tissues (p < .05). Its level was strongly correlated with Karnofsky Performance Scale score (p < .001) and WHO grade (p < .001). Kaplan-Meier survival and log-rank analysis indicated that the decreased expression of miR-133b was strongly correlated with shorter overall survival of patients with glioma (log-rank test, p = .03). CONCLUSIONS: The current investigation demonstrated that miR-133b level is useful for predicting the prognosis of patients with glioma.
BACKGROUND: Recently, microRNA-133b (miR-133b) dysregulation has been shown to play a key role in several humancancers, as well as glioma. In this study, we aimed to investigate the clinical significance and prognostic value of miR-133b in glioma. METHODS: Real-time quantitative PCR was employed to measure the expression level of miR-133b in tissues. Survival analysis was carried out by using the log-rank test and Kaplan-Meier method. Prognostic factors for overall survival were identified by univariate and multivariate analyses using the Cox proportional hazards regression model. RESULTS: The expression level of miR-133b was significantly lower in glioma tissues compared with matched non-cancerous brain tissues (p < .05). Its level was strongly correlated with Karnofsky Performance Scale score (p < .001) and WHO grade (p < .001). Kaplan-Meier survival and log-rank analysis indicated that the decreased expression of miR-133b was strongly correlated with shorter overall survival of patients with glioma (log-rank test, p = .03). CONCLUSIONS: The current investigation demonstrated that miR-133b level is useful for predicting the prognosis of patients with glioma.