OBJECTIVE: Neuroepithelial-transforming protein 1 is a member of the guanine nucleotide exchange factor family, a group of proteins which are known to activate and thereby regulate Rho family members. Deregulation of neuroepithelial-transforming protein 1 expression has been found in certain types of human tumors. To investigate its prognostic value in human gliomas, which is currently unknown, we examined the correlation between neuroepithelial-transforming protein 1 expression and prognosis in patients with gliomas. METHODS: Immunohistochemical staining was performed to detect neuroepithelial-transforming protein 1 expression patterns in the biopsies from 96 patients with primary gliomas. Kaplan-Meier survival and Cox's regression analyses were performed to evaluate the prognosis of patients. RESULTS: Immunohistochemical analysis with anti-neuroepithelial-transforming protein 1 antibody revealed that neuroepithelial-transforming protein 1 was significantly associated with the Karnofsky performance scale score and World Health Organization grades of patients with gliomas. Especially, the positive expression rates of neuroepithelial-transforming protein 1 were significantly higher in patients with higher grade (P = 0.001) and lower Karnofsky's performance scale score (P = 0.005). The median survival of patients with high neuroepithelial-transforming protein 1 expression was significantly shorter than that with low expression and without expression (316, 892 and 1180 days, respectively). Cox's multifactor analysis showed that the Karnofsky performance scale (P = 0.01), World Health Organization grade (P = 0.008) and neuroepithelial-transforming protein 1 (P = 0.006) were independent prognosis factors for human glioma. CONCLUSIONS: Taken together, our study indicates for the first time that neuroepithelial-transforming protein 1 status may be a highly sensitive marker for glioma prognosis and suggest that the expression patterns of neuroepithelial-transforming protein 1 might be a potent tool for predicting the clinical prognosis of glioma patients.
OBJECTIVE: Neuroepithelial-transforming protein 1 is a member of the guanine nucleotide exchange factor family, a group of proteins which are known to activate and thereby regulate Rho family members. Deregulation of neuroepithelial-transforming protein 1 expression has been found in certain types of humantumors. To investigate its prognostic value in humangliomas, which is currently unknown, we examined the correlation between neuroepithelial-transforming protein 1 expression and prognosis in patients with gliomas. METHODS: Immunohistochemical staining was performed to detect neuroepithelial-transforming protein 1 expression patterns in the biopsies from 96 patients with primary gliomas. Kaplan-Meier survival and Cox's regression analyses were performed to evaluate the prognosis of patients. RESULTS: Immunohistochemical analysis with anti-neuroepithelial-transforming protein 1 antibody revealed that neuroepithelial-transforming protein 1 was significantly associated with the Karnofsky performance scale score and World Health Organization grades of patients with gliomas. Especially, the positive expression rates of neuroepithelial-transforming protein 1 were significantly higher in patients with higher grade (P = 0.001) and lower Karnofsky's performance scale score (P = 0.005). The median survival of patients with high neuroepithelial-transforming protein 1 expression was significantly shorter than that with low expression and without expression (316, 892 and 1180 days, respectively). Cox's multifactor analysis showed that the Karnofsky performance scale (P = 0.01), World Health Organization grade (P = 0.008) and neuroepithelial-transforming protein 1 (P = 0.006) were independent prognosis factors for humanglioma. CONCLUSIONS: Taken together, our study indicates for the first time that neuroepithelial-transforming protein 1 status may be a highly sensitive marker for glioma prognosis and suggest that the expression patterns of neuroepithelial-transforming protein 1 might be a potent tool for predicting the clinical prognosis of gliomapatients.
Authors: Meghan M Wyse; Silvia Goicoechea; Rafael Garcia-Mata; Andrea L Nestor-Kalinoski; Kathryn M Eisenmann Journal: Biochem Biophys Res Commun Date: 2017-01-21 Impact factor: 3.575