TY  - JOUR
A1  - Salvucci, Manuela
A1  - Zakaria, Zaitun
A1  - Carberry, Steven
A1  - Tivnan, Amanda
A1  - Seifert, Volker
A1  - Kögel, Donat
A1  - Murphy, Brona M.
A1  - Prehn, Jochen H. M.
T1  - System-based approaches as prognostic tools for glioblastoma
T2  - BMC cancer
N2  - Background: The evasion of apoptosis is a hallmark of cancer. Understanding this process holistically and overcoming apoptosis resistance is a goal of many research teams in order to develop better treatment options for cancer patients. Efforts are also ongoing to personalize the treatment of patients. Strategies to confirm the therapeutic efficacy of current treatments or indeed to identify potential novel additional options would be extremely beneficial to both clinicians and patients. In the past few years, system medicine approaches have been developed that model the biochemical pathways of apoptosis. These systems tools incorporate and analyse the complex biological networks involved. For their successful integration into clinical practice, it is mandatory to integrate systems approaches with routine clinical and histopathological practice to deliver personalized care for patients.
Results: We review here the development of system medicine approaches that model apoptosis for the treatment of cancer with a specific emphasis on the aggressive brain cancer, glioblastoma.
Conclusions: We discuss the current understanding in the field and present new approaches that highlight the potential of system medicine approaches to influence how glioblastoma is diagnosed and treated in the future.
KW  - Apoptosis
KW  - Computational model
KW  - Glioblastoma
KW  - Molecular signatures
KW  - Network model
KW  - Numerical simulation
KW  - Precision oncology
KW  - Prognostic biomarker
KW  - Systems biology
KW  - Systems medicine
Y1  - 2019
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/53326
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-533265
SN  - 1471-2407
N1  - Open Access: This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
VL  - 19
IS  - 1, Art. 1092
SP  - 1
EP  - 17
PB  - BioMed Central ; Springer
CY  - London ; Berlin ; Heidelberg
ER  -