Developing the novel bioinformatics algorithms to systematically investigate the connections among survival time, key genes and proteins for Glioblastoma multiforme

Abstract

Abstract Background Glioblastoma multiforme (GBM) is one of the most common malignant brain tumors and its average survival time is less than 1 year after diagnosis. Results Firstly, this study aims to develop the novel survival analysis algorithms to explore the key genes and proteins related to GBM. Then, we explore the significant correlation between AEBP1 upregulation and increased EGFR expression in primary glioma, and employ a glioma cell line LN229 to identify relevant proteins and molecular pathways through protein network analysis. Finally, we identify that AEBP1 exerts its tumor-promoting effects by mainly activating mTOR pathway in Glioma. Conclusions We summarize the whole process of the experiment and discuss how to expand our experiment in the future.

Keywords

• Glioblastoma multiforme (GBM)
• Survival analysis
• Adipocyte enhancer-binding protein 1 (AEBP1)
• Data mining
• mTOR pathway