Hankun Xu1, Xiaoqian Wu2, Yingfei Dou2, Wei Zheng3. 1. Departments of Neurology, Qingzhou People' s Hosptial, Shandong, Weifang, China. 2. Departments of Cardiology, Yidu Central Hosptial, Weifang, Shandong, China. 3. Departments of Neurosurgery, the Second Hospital of Shandong First Medical University, 706 Taishan Road, Taian, 271000, Shandong, China. zhijingzhi5482@163.com.
Abstract
BACKGROUND: Glioblastoma (GBM) is the most common histological type of glioma, which has the most aggressive biological characters and the worst outcome. The targeted therapy of GBM requires more progression, and new biomarkers should be identified. MATERIALS AND METHODS: In our study, we firstly retrieved the data of TCGA and compared the TPMs of all ANXAs in TCGA database. By quantitative PCR (qPCR), we detected the mRNA levels of ANXAs in 8 pairs of GBM tissues and their corresponding normal brain tissues. Moreover, we detected the expression of ANXAs in 118 cases of GBMs, and further evaluated their clinical significance by analyzing the correlation with clinicopathological factors, and estimated their prognostic significance with univariate and multivariate analyses. RESULTS: In the TCGA database, ANXA1, ANXA2, ANXA4, and ANXA5 had higher transcripts per million (TPMs) in GBM tissues compared with the normal brain tissues, while ANXA3 expression was downregulated in GBM tissues. With qPCR, ANXA1, ANXA2, and ANXA10 were verified to be the upregulated genes in GBM, but other ANXAs had no significant differences. ANXA2 and ANXA10, but not ANXA1, were correlated with poor prognosis of GBM and identified as independent prognostic biomarkers for poor outcome. CONCLUSIONS: ANXA1, ANXA2, and ANXA10 are the upregulated genes in GBM. ANXA2 and ANXA10, but not ANXA1, are independent prognostic biomarkers indicating unfavorable outcome. Our results suggest that expression profiles based on ANXA10 expression may be a new classification system to predict prognosis of GBM patients.
BACKGROUND: Glioblastoma (GBM) is the most common histological type of glioma, which has the most aggressive biological characters and the worst outcome. The targeted therapy of GBM requires more progression, and new biomarkers should be identified. MATERIALS AND METHODS: In our study, we firstly retrieved the data of TCGA and compared the TPMs of all ANXAs in TCGA database. By quantitative PCR (qPCR), we detected the mRNA levels of ANXAs in 8 pairs of GBM tissues and their corresponding normal brain tissues. Moreover, we detected the expression of ANXAs in 118 cases of GBMs, and further evaluated their clinical significance by analyzing the correlation with clinicopathological factors, and estimated their prognostic significance with univariate and multivariate analyses. RESULTS: In the TCGA database, ANXA1, ANXA2, ANXA4, and ANXA5 had higher transcripts per million (TPMs) in GBM tissues compared with the normal brain tissues, while ANXA3 expression was downregulated in GBM tissues. With qPCR, ANXA1, ANXA2, and ANXA10 were verified to be the upregulated genes in GBM, but other ANXAs had no significant differences. ANXA2 and ANXA10, but not ANXA1, were correlated with poor prognosis of GBM and identified as independent prognostic biomarkers for poor outcome. CONCLUSIONS: ANXA1, ANXA2, and ANXA10 are the upregulated genes in GBM. ANXA2 and ANXA10, but not ANXA1, are independent prognostic biomarkers indicating unfavorable outcome. Our results suggest that expression profiles based on ANXA10 expression may be a new classification system to predict prognosis of GBM patients.
Authors: Erwin G Van Meir; Costas G Hadjipanayis; Andrew D Norden; Hui-Kuo Shu; Patrick Y Wen; Jeffrey J Olson Journal: CA Cancer J Clin Date: 2010 May-Jun Impact factor: 508.702
Authors: Llara Prieto-Fernández; Sofía T Menéndez; María Otero-Rosales; Irene Montoro-Jiménez; Francisco Hermida-Prado; Juana M García-Pedrero; Saúl Álvarez-Teijeiro Journal: Front Cell Dev Biol Date: 2022-09-28