System-based approaches as prognostic tools for glioblastoma

• Main Authors: Manuela Salvucci, Zaitun Zakaria, Steven Carberry, Amanda Tivnan, Volker Seifert, Donat Kögel, Brona M. Murphy, Jochen H. M. Prehn
• Format: Article
• Language: English
• Published: BMC 2019-11-01
• Series: BMC Cancer
• Subjects: Apoptosis; Computational model; Glioblastoma; Molecular signatures; Network model; Numerical simulation
• Online Access: http://link.springer.com/article/10.1186/s12885-019-6280-2

Abstract 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.