Although treatment outcomes of glioblastoma, the most malignant central nervous system (CNS) tumor, has improved in the past decades, it is still incurable, and survival has only slightly improved. Advances in molecular biology and genetics have completely transformed our understanding of glioblastoma. Multiple classifications and different diagnostic methods were made according to novel molecular markers. Discovering tumor heterogeneity only partially explains the ineffectiveness of current anti-proliferative therapies. Dynamic heterogeneity secures resistance to combined oncotherapy. As tumor growth proceeds, new therapy-resistant sub clones emerge. Liquid biopsy is a new and promising diagnostic tool that can step up with the dynamic genetic change. Getting a ’real-time’ picture of a specific tumor, anti-invasion and multi-target treatment can be designed. During invasion to the peri-tumoral brain tissue, glioma cells interact with the extracellular matrix components. The expressional levels of these matrix molecules give a characteristic pattern, the invasion spectrum, which possess vast diagnostical, predictive and prognostic information. It is a huge leap forward combating tumor heterogeneity and searching for novel therapies. Using the invasion spectrum of a tumor sample is a novel tool to distinguish between histological subtypes, specifying the tumor grades or different prognostic groups. Moreover, new therapeutic methods and their combinations are under trial. These are crucial steps towards personalized oncotherapy.

Background Glioblastoma multiforme (GBM) is the most common malignant disease of the central nervous system. Its prognosis is unfavorable, and the median overall survival of patients is 16 to 24 months. The main cause of the poor survival data are the extensive invasion of cancer cells to the neighboring parenchyma, thus leading to inevitable local recurrence. The extracellular matrix (ECM) is a known factor in tumor invasion, and differences in the ECM of nontumor brain and glioblastoma has been proven. Methods In this research, 20 invasion-related expressions of ECM components were determined in 26 GBM flash-frozen samples using quantitative reverse transcription-polymerase chain reaction and proteomic measurements. Expression data were then set against the survival data of the patients. Results Significant alterations between groups with different survival rates could not be established in the individual evaluation of the expression level of the selected molecules. However, statistical analysis of the expression pattern of invasion-related molecules revealed a correlation with prognosis. The positive predictive values of the messenger RNA (mRNA) and the proteomic expression studies were 0.85 and 0.89, respectively. The receiver operation characteristic value was 0.775 for the mRNA expression data and 0.875 for the protein expression data. Furthermore, a group of molecules, including brevican, cadherin-12, integrin β1, integrin α3, laminin α4, and laminin β1, that play a prominent role in invasion were identified. Conclusions Joint assessment of the expression of invasion-related molecules provides a specific invasion spectrum of the tumor that correlates with the survival of glioblastoma patients. Using statistical classifiers enables the adoption of an invasion spectrum as a considerably accurate prognostic factor while gaining predictive information on potential molecular oncotherapeutic targets at the same time. ^* These authors contributed equally.

Compared to rodents, inhibitory interneurons in the human neocortex exhibit high input excitability because of reduced passive ion leakage across their extracellular membrane. However, the regulation of intrinsic excitability by voltage-gated ion channels activated over a wide range of membrane potentials in human interneurons remains poorly understood. We performed whole-cell patch-clamp microelectrode recordings in mouse and human neocortical slices obtained from surgically resected non-pathological brain tissue finding that Kir channels control the electrical resistance of parvalbumin (Pvalb) neurons in an identical manner in the human and mouse. Molecular analyses revealed predominantly Kir3.1 and Kir3.2 channels in Pvalb neurons in both species. Using whole-cell recordings from synaptically connected neuron pairs and a computational model, we demonstrated that physiological Kir activation inhibits human Pvalb interneurons during postsynaptic potentials evoked by presynaptic neurogliaform cells. The similarity of Kir-mediated inhibition across species suggests that it is an archetypal property of Pvalb neurons.