Practical implications of integrated glioma classification according to the World Health Organization classification of tumors of the central nervous system 2016

Glioma: experimental models and reality

In theory, in vitro and in vivo models for human gliomas have great potential to not only enhance our understanding of glioma biology, but also to facilitate the development of novel treatment strategies for these tumors. For reliable prediction and validation of the effects of different therapeutic modalities, however, glioma models need to comply with specific and more strict demands than other models of cancer, and these demands are directly related to the combination of genetic aberrations and the specific brain micro-environment gliomas grow in. This review starts with a brief introduction on the pathological and molecular characteristics of gliomas, followed by an overview of the models that have been used in the last decades in glioma research. Next, we will discuss how these models may play a role in better understanding glioma development and especially in how they can aid in the design and optimization of novel therapies. The strengths and weaknesses of the different models will be discussed in light of genotypic, phenotypic and metabolic characteristics of human gliomas. The last part of this review provides some examples of how therapy experiments using glioma models can lead to deceptive results when such characteristics are not properly taken into account.

Milestones of the last 10 years: CNS cancer

For neuro-oncologists, much was accomplished in the last decade, including the establishment of the first standard of care (SOC) in this field of oncology. New treatment options boosted research in the whole field of neuro-oncology, as well clinical trials, translational and basic research. Accumulated data on molecular-genetic subgroups with distinct clinical outcomes in disease entities led to the establishment of new biomarkers and to the collaborative formulation of a new WHO classification of central nervous system tumors.