Developing the novel bioinformatics algorithms to systematically investigate the connections among survival time, key genes and proteins for Glioblastoma multiforme.
BMC Bioinformatics
; 21(Suppl 13): 383, 2020 Sep 17.
Article
em En
| MEDLINE
| ID: mdl-32938364
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.Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Neoplasias Encefálicas
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Glioblastoma
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Biologia Computacional
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Glioma
Tipo de estudo:
Clinical_trials
Limite:
Humans
Idioma:
En
Ano de publicação:
2020
Tipo de documento:
Article