Therapy Optimization in Glioblastoma: An integrative human data-based approach using mathematical models
Glioblastoma is the deadliest human primary brain tumor. Therapeutic advances in recent years have been marginal, in spite of many ideas being explored. We intend to add the mathematical dimension to these efforts to provide a new perspective on these problems. To do so, high-quality data are necessary. Thus, this collaborative activity aims to create a cooperative framework to bring together a broad range of human data of glioblastoma patients: multimodal imaging, omics, immunohistochemical and molecular biology characterization of tumor cells, etc. It also requires the development of pilot experiments to validate ideas coming from mathematical models.
Mathematical models are used in Science and Engineering to create conceptual frameworks in order to understand Nature and provide solutions to real-world problems. A broad variety of human data will be available through the project. The conceptual frameworks provided by mathematical models, when fed by the project data, may allow us to get a “big picture” of the disease’s natural history and so understand and predict its response to therapies, which may lead to improved glioblastoma treatments.
The TOG project is an open initiative coordinated by MOLAB. Many hospitals have approved the protocol, are providing data and participating in the discussions, including Hospital 12 de Octubre (Madrid), MD Anderson Cancer Center (Madrid), Erasme Hospital (Brussels), Hospital Virgen de la Salud de Toledo, Hospital Regional Universitario de Málaga, Hospital General Universitario de Albacete, Hospital de Manises, Instituto Valenciano de Oncología and Bern University Hospital (Switzerland).
Several biomedical research groups are performing pilot experiments including groups from Carlos III Health Institute, Center of Research in Cancer and Immunology at Nantes, the Aragon Institute of Engineering Research and the Institute for Biological problems at Belgrade.
Researchers from Bern, Kiev and Berlin are helping with the image and data processing and mathematicians from Paris, Bordeaux and Warsaw are also involved in the analysis.
Beyond this project
The approach under development in the problem could be used to find novel biomarkers and to design personalized optimal strategies for other cancer types for which a similar amount of data can be obtained in the clinical practice.