Background Glioblastoma is the most common and aggressive adult brain malignancy against which conventional surgery and chemoradiation provide limited benefit. Even when a good treatment response is obtained, recurrence inevitably occurs either locally (∼80%) or distally (∼20%), driven by cancer clones that are often genomically distinct from those in the primary tumour. Glioblastoma cells display a characteristic infiltrative phenotype, invading the surrounding tissue and often spreading across the whole brain. Cancer cells responsible for relapse can reside in two compartments of residual disease that are left behind after treatment: the infiltrated normal brain parenchyma and the sub-ventricular zone. However, these two sources of residual disease in glioblastoma are understudied because of the difficulty in sampling these regions during surgery. Patient and methods Here, we present the results of whole-exome sequencing of 69 multi-region samples collected using fluorescence-guided resection from 11 patients, including the infiltrating tumour margin and the sub-ventricular zone for each patient, as well as matched blood. We used a phylogenomic approach to dissect the spatio-temporal evolution of each tumour and unveil the relation between residual disease and the main tumour mass. We also analysed two patients with paired primary-recurrence samples with matched residual disease. Results Our results suggest that infiltrative subclones can arise early during tumour growth in a subset of patients. After treatment, the infiltrative subclones may seed the growth of a recurrent tumour, thus representing the ‘missing link’ between the primary tumour and recurrent disease. Conclusions These results are consistent with recognised clinical phenotypic behaviour and suggest that more specific therapeutic targeting of cells in the infiltrated brain parenchyma may improve patient’s outcome.

Glioblastoma multiforme and other malignant cancers resulting in solid tumors continue to be devastating diseases. In order to find more effective treatments, it is necessary to cultivate a better understanding of the dynamics of tumor development in relation to both primary and secondary tumors. Although hand-held or digital caliper methods can measure tumor growth in subcutaneous xenograft models, to date, the only way to follow and monitor the progression of growing tumors in orthotopic animal models is imaging. This is not enough. To improve our knowledge of the biological characteristics that take place during tumor progression at both primary and metastatic sites, it is indispensable to develop an in vivo model which enables us to reproduce, from the beginning to the end of the cancer's natural history, what really happens in a patient affected by a solid tumor. The ideal tumor model must allow us to monitor all the stages of the tumor's development, both in the primary bulk and in secondary locations, by obtaining cells, biopsies as well as performing stainings on sections. In this paper, "the development tumor model", already proposed by the author to monitor the whole progression of the glioblastoma, is also applied to the study of all solid malignancies. It is a xenogeneic orthotopic transplantation model using human tumor-derived cells from the pre-hypoxic phase as transplanted material, which will be cultured in a neurobasal serum-free medium. By transplanting the same material at the same time (time zero) into a number of immunodeficient and genetically identical mice or rats, the model can be used to create a pool of twin animal transplant candidates under the same testing conditions. By sacrificing one animal a week (or choosing other intervals as needed) and performing multiple biopsies and stainings on sections, we can monitor the entire development of both the primary and secondary tumors. This may shed light on which specific cells and particular markers need to be focused on in order to develop innovative, valid therapeutic strategies.

The prognosis of patients affected by glioblastoma remains dismal despite many efforts have been devoted worldwide in research and therapeutic strategies. Reasons of our failure include the fact that the patient harboring a glioblastoma always has two problems inside the brain, the bulk tumor and the parenchyma microinfiltrated; the other reason is that the tumor is able to grow dynamically adapting to the mutated conditions of its growth microenvironment. This paper tries to give an interpretation to the dynamic process of the tumor growth, from the beginning to the end of its natural history, dividing it in three phases, one pre-hypoxia and two post-hypoxia, and these are then correlated with the types of cancer stem cells (CSCs) involved. Furthermore, the paper proposes an original animal model to follow glioblastoma development in only one generation of mice, both in the bulk and in the brain parenchyma.

Glioblastoma multiforme is a solid tumor with particular aspects due to its organ of origin and its development modalities. The brain is very sensitive to oxygen and glucose deprivation and it is the only organ that cannot be either transplanted or entirely removed. Furthermore, many clues and recent indirect experimental evidence indicate that the micro-infiltration of the whole brain parenchyma occurs in very early stages of tumor bulk growth or likely even before. As a consequence, the primary glioblastoma (IDH-wildtype, WHO 2016) is the only tumor where the malignant (i.e. distantly infiltrating the organ of origin) and deadly (i.e. leading cause to patient’s death) phases coincide and overlap in one single phase of its natural history. To date, the prognosis of optimally treated glioblastoma patients remains dismal despite recent fundamental progress in neurosurgical techniques which are enabling better maximal safe resection and survival outcome. Intratumor variegated heterogeneity of glioblastoma bulk due to trunk-branch evolution and very early micro-infiltration and settlement of neoplastic cells in the entire brain parenchyma are the reasons for resistance to current therapeutic treatments. With the aim of future innovative and effective therapies, this paper deals with the unique glioblastoma features, the appropriate research methods as well as the strategies to follow to overcome current causes of resistance.

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Glioblastoma development should be subdivided in three phases, one prehypoxic and two post-hypoxic phases. The pre-hypoxic phase, ranging from 10% to 5% oxygen (normal brain oxygen levels), should be characterized only by CD133-cells, and these cells are inevitably also those that first conquer and microinfiltrate the brain parenchyma. In some areas of the bulk, the oxygen concentration falls to about 5% or less, and hypoxia develops. The second phase ranges from about 5% to about 1% oxygen concentration. This phase of mild and severe hypoxia is regulated by the epigenetic shift driven by HIF2a, which is expressed only in cancer stem cells (CSCs) and is correlated with CD133 expression. When oxygen levels fall in certain regions of the tumor to about 1% or less, the third phase of very severe hypoxia begins. This phase is driven by HIF1a, which is expressed both by CSCs and committed cells. To date, the only way to monitor the development of the growing tumor in animal model is imaging. However, in order to reproduce what really happens in a human patient affected by a glioblastoma, we need a model that allows cells, biopsies, and sections to be obtained throughout tumor development. I recently proposed an original animal model that can enable us to study and monitor the entire development of the glioblastoma in only one generation of mice. The model allows the creation of a pool of twin transplanted animals in the same condition and the study of glioblastoma development, both in the bulk and in the brain parenchyma. This is done by taking multiple biopsies and by performing multiple stainings on sections. Through parenchymal biopsies and stainings on sections, we have four means to identify the CSCs microinfiltrated in the brain with the possibility of targeting them.

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PURPOSE: Discrimination between glioblastoma (GB) and radiation necrosis (RN) remains challenging using conventional MRI. However, a correct diagnosis is important for patient management. We hypothesised that based on differences in vascular properties, such as vascular density, vascular permeability, blood flow, composition of the extracellular and extravascular space and interstitial pressure, dynamic contrast-enhanced (DCE) MRI would allow to distinguish GB from RN. As such, in this study, the potential of semi-quantitative and quantitative analysis of DCE-MRI was investigated to differentiate GB from RN in rats. PROCEDURES: F98 GB cells were inoculated in the rat brain. GB growth was seen on follow-up MRI 8-23 days post-inoculation (n=15). RN lesions developed 6-8 months post-irradiation (n=10). DCE-MRI was acquired using a fast low angle shot (FLASH) sequence. Regions of interest (ROIs) encompassed peripheral contrast-enhancement in GB (n=15) and RN (n=10) as well as central necrosis within these lesions (GB (n=4), RN (n=3)). DCE-MRI data were fitted to determine 4 function variables (amplitude A, offset from zero C, wash-in rate k and wash-out rate D) as well as maximal intensity (Imax F ) and time-to-peak (TTP F ). Secondly, maps of semi-quantitative and quantitative parameters (extended Tofts model) were created using Olea sphere ( O ). Semi-quantitative DCE-MRI parameters included wash-in O , wash-out O , area under the curve (AUC O ), maximal intensity (Imax O ) and time-topeak (TTP O ). Quantitative parameters included the rate constant plasma to extravascular-extracellular space (EES) (K trans ), the rate constant EES to plasma (K ep ), plasma volume (V p ) and EES volume (V e ). All (semi-)quantitative parameters were compared between GB and RN using the MannWhitney U test and ROC analysis was performed. RESULTS: Wash-in rates (k and wash-in O ) were significantly higher in GB compared to RN (p=0.016 and p=0.041, respectively). Wash-out rate (D) was only significantly higher in GB using curve fitting (p=0.014). TTP F and TTP O were significantly lower in GB compared to RN (p=0.001 and p < 0.001, respectively). The highest sensitivity (93%) and specificity (90%) was obtained for TTP O by applying a threshold of 415 s. K trans , K ep , V p and V e were not significantly different between GB and RN. CONCLUSIONS: Based on our results in a rat model, DCE-MRI may be useful to discriminate GB from RN. Wash-in rates (k and wash-in O ), TTP F and TTP O , which can be derived from a 5-min DCE-MRI acquisition, are able to distinguish GB from RN while other quantitative and semi-quantitative parameters are not. Whether DCE-MRI will also be able to differentiate GB from RN in humans must be further explored. P08.04 "THE DEVELOPMENT TUMOR MODEL" USED TO BIOLOGICALLY AND SPATIOTEMPORALLY FOLLOW AND UNDERSTAND GLIOBLASTOMA EVOLUTION IN THE WHOLE BRAIN AND TO TEST AND MONITOR NEW THERAPIESE. Brognaro; S. Maria della Misericordia Hospital, Rovigo, Italy.To date, "The development tumor model" (TDTM) is the only precli...