학술논문

Phenocopying Glioblastoma: A Review
Document Type
Periodical
Source
IEEE Reviews in Biomedical Engineering IEEE Rev. Biomed. Eng. Biomedical Engineering, IEEE Reviews in. 16:456-471 2023
Subject
Bioengineering
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Communication, Networking and Broadcast Technologies
Tumors
Cancer
Three-dimensional displays
Predictive models
Mathematical model
In vivo
In vitro
Animal models
brain cancer
cancer predictive algorithms
glioblastoma
imaging cancer pathophysiology
mathematical modeling
precision medicine
primary cell cultures
translational biomarkers
xenografts
Language
ISSN
1937-3333
1941-1189
Abstract
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.