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System-based approaches as prognostic tools for glioblastoma
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 patien...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6852738/ https://www.ncbi.nlm.nih.gov/pubmed/31718568 http://dx.doi.org/10.1186/s12885-019-6280-2 |
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author | Salvucci, Manuela Zakaria, Zaitun Carberry, Steven Tivnan, Amanda Seifert, Volker Kögel, Donat Murphy, Brona M. Prehn, Jochen H. M. |
author_facet | Salvucci, Manuela Zakaria, Zaitun Carberry, Steven Tivnan, Amanda Seifert, Volker Kögel, Donat Murphy, Brona M. Prehn, Jochen H. M. |
author_sort | Salvucci, Manuela |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-6852738 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-68527382019-11-20 System-based approaches as prognostic tools for glioblastoma Salvucci, Manuela Zakaria, Zaitun Carberry, Steven Tivnan, Amanda Seifert, Volker Kögel, Donat Murphy, Brona M. Prehn, Jochen H. M. BMC Cancer Review 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. BioMed Central 2019-11-12 /pmc/articles/PMC6852738/ /pubmed/31718568 http://dx.doi.org/10.1186/s12885-019-6280-2 Text en © The Author(s). 2019 Open AccessThis 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. |
spellingShingle | Review Salvucci, Manuela Zakaria, Zaitun Carberry, Steven Tivnan, Amanda Seifert, Volker Kögel, Donat Murphy, Brona M. Prehn, Jochen H. M. System-based approaches as prognostic tools for glioblastoma |
title | System-based approaches as prognostic tools for glioblastoma |
title_full | System-based approaches as prognostic tools for glioblastoma |
title_fullStr | System-based approaches as prognostic tools for glioblastoma |
title_full_unstemmed | System-based approaches as prognostic tools for glioblastoma |
title_short | System-based approaches as prognostic tools for glioblastoma |
title_sort | system-based approaches as prognostic tools for glioblastoma |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6852738/ https://www.ncbi.nlm.nih.gov/pubmed/31718568 http://dx.doi.org/10.1186/s12885-019-6280-2 |
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