Zhi-Cheng He1, Yi-Fang Ping1, Sen-Lin Xu1, Yong Lin1, Shi-Cang Yu1, Hsiang-Fu Kung1, Xiu-Wu Bian1. 1. Institute of Pathology and Southwest Cancer Center, Southwest Hospital, Third Military Medical UniversityChongqing 400038, China; Key Laboratory of Tumor Immunopathology of Ministry of Education of China, Third Military Medical UniversityChongqing 400038, China.
Abstract
OBJECTIVE: To investigate the expression and significance of MGMT in different molecular subtypes of glioblastoma (GBM), and to evaluate the important role of MGMT and P53 in predicting the prognosis of GBM patients. METHODS: MGMT expression was detected by immunohistochemical staining in 72 cases of GBM which had been classified as three molecular subtypes. The relationship between MGMT and P53, an important molecule for identification of proneural-like GBM, were further analyzed. The association between MGMT and patients' prognosis was analyzed with Kaplan-Meier method, which was further validated by the data from 513 cases of GBM in the TCGA database. RESULTS: MGMT expression was lower in proneural-like subtype in 72 GBM cases (p < 0.001), and was negatively correlated with P53 (r=-0. 6203, p < 0.001). This results was also verified by a validation group of 87 GBM cases (r=-0. 2950, p < 0.001). Interestingly, low expression of MGMT predicted a better outcome in proneurallike subtype or P53 high-expression group (p < 0.05) but not in non-proneural-like subtype and P53 low-expression group. All of these results were verified by the data from TCGA database. CONCLUSION: MGMT can be used as an independent prognostic factor and plays an important role in molecular typing and diagnosis of GBM by combination with proneural-like subtype marker P53.
OBJECTIVE: To investigate the expression and significance of MGMT in different molecular subtypes of glioblastoma (GBM), and to evaluate the important role of MGMT and P53 in predicting the prognosis of GBM patients. METHODS:MGMT expression was detected by immunohistochemical staining in 72 cases of GBM which had been classified as three molecular subtypes. The relationship between MGMT and P53, an important molecule for identification of proneural-like GBM, were further analyzed. The association between MGMT and patients' prognosis was analyzed with Kaplan-Meier method, which was further validated by the data from 513 cases of GBM in the TCGA database. RESULTS:MGMT expression was lower in proneural-like subtype in 72 GBM cases (p < 0.001), and was negatively correlated with P53 (r=-0. 6203, p < 0.001). This results was also verified by a validation group of 87 GBM cases (r=-0. 2950, p < 0.001). Interestingly, low expression of MGMT predicted a better outcome in proneurallike subtype or P53 high-expression group (p < 0.05) but not in non-proneural-like subtype and P53 low-expression group. All of these results were verified by the data from TCGA database. CONCLUSION:MGMT can be used as an independent prognostic factor and plays an important role in molecular typing and diagnosis of GBM by combination with proneural-like subtype marker P53.
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