胶质母细胞瘤
生物信息学
癌症
破译
体内
医学
疾病
计算生物学
生物信息学
计算机科学
癌症研究
生物
病理
内科学
基因
生物技术
生物化学
作者
Mariam‐Eleni Oraiopoulou,Eleftheria Tzamali,Joseph Papamatheakis,Vangelis Sakkalis
出处
期刊:IEEE Reviews in Biomedical Engineering
[Institute of Electrical and Electronics Engineers]
日期:2023-01-01
卷期号:16: 456-471
被引量:8
标识
DOI:10.1109/rbme.2021.3111744
摘要
The main reason why therapeutic schemes fail in Glioblastoma lies on its own peculiarities as a cancer and on our failure to fully decipher them. Fast tumor evolution, invasiveness and incomplete surgical resection contribute to disease recurrence, therapy resistance and high mortality. More faithful models must be developed to address Glioblastoma biology and better clinical guidance. Research studies are discussed in this review that: i) improve understanding and assessment of the growth mechanisms of Glioblastoma and ii) develop preclinical models ( in vitro-in vivo-in silico ) that mimic patient's tumor (phenocopying) in order to provide better prediction of response to therapies.
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