The neurotrophic tropomyosin receptor kinase (NTRK) genes (NTRK1, NTRK2, and NTRK3) code for three transmembrane high-affinity tyrosine-kinase receptors for nerve growth factors (TRK-A, TRK-B, and TRK-C) which are mainly involved in nervous system development. Loss of function alterations in these genes can lead to nervous system development problems; conversely, activating alterations harbor oncogenic potential, promoting cell proliferation/survival and tumorigenesis. Chromosomal rearrangements are the most clinically relevant alterations of pathological NTRK activation, leading to constitutionally active chimeric receptors. NTRK fusions have been detected with extremely variable frequencies in many pediatric and adult cancer types, including central nervous system (CNS) tumors. These alterations can be detected by different laboratory assays (e.g., immunohistochemistry, FISH, sequencing), but each of these approaches has specific advantages and limitations which must be taken into account for an appropriate use in diagnostics or research. Moreover, therapeutic targeting of this molecular marker recently showed extreme efficacy. Considering the overall lack of effective treatments for brain neoplasms, it is expected that detection of NTRK fusions will soon become a mainstay in the diagnostic assessment of CNS tumors, and thus in-depth knowledge regarding this topic is warranted.

Purpose: Current glioma diagnostic guidelines call for molecular profiling to stratify patients into prognostic and treatment subgroups. In case the tumor tissue is inaccessible, cerebrospinal fluid (CSF) has been proposed as a reliable tumor DNA source for liquid biopsy. We prospectively investigated the use of CSF for molecular characterization of newly diagnosed gliomas. Experimental Design: We recruited two cohorts of newly diagnosed patients with glioma, one (n = 45) providing CSF collected in proximity of the tumor, the other (n = 39) CSF collected by lumbar puncture (LP). Both cohorts provided tumor tissues by surgery concomitant with CSF sampling. DNA samples retrieved from CSF and matched tumors were systematically characterized and compared by comprehensive (NGS, next-generation sequencing) or targeted (ddPCR, droplet digital PCR) methodologies. Conventional and molecular diagnosis outcomes were compared. Results: We report that tumor DNA is abundant in CSF close to the tumor, but scanty and mostly below NGS sensitivity threshold in CSF from LP. Indeed, tumor DNA is mostly released by cells invading liquoral spaces, generating a gradient that attenuates by departing from the tumor. Nevertheless, in >60% of LP CSF samples, tumor DNA is sufficient to assess a selected panel of genetic alterations (IDH and TERT promoter mutations, EGFR amplification, CDKN2A/B deletion: ITEC protocol) and MGMT methylation that, combined with imaging, enable tissue-agnostic identification of main glioma molecular subtypes. Conclusions: This study shows potentialities and limitations of CSF liquid biopsy in achieving molecular characterization of gliomas at first clinical presentation and proposes a protocol to maximize diagnostic information retrievable from CSF DNA.

Background: Glioblastoma (GBM) is the most common primary brain tumor. The extent of resection (EOR) has been claimed as one of the most important prognostic factors. Fluorescent dyes aid surgeons in detecting a tumor’s borders. 5-aminolevulinic acid (5-ALA) and sodium fluorescein (SF) are the most used. Only a few studies have directly compared these two fluorophores. Methods: A single center retrospective analysis of patients treated for GBM in the period between January 2018 and January 2021 was built to find any differences in terms of EOR, Karnofsky Performance Status (KPS), and overall survival (OS) on the use of 5-ALA, SF, or both. Results: Overall, 99 patients affected by isocitrate dehydrogenase (IDH) wild-type Glioblastoma were included. 5-ALA was administered to 40 patients, SF to 44, and both to 15. No statistically significant associations were identified between the fluorophore and EOR (p = 0.783) or postoperative KPS (p = 0.270). Survival analyses did not show a selective advantage for the use of a given fluorophore (p = 0.184), although there appears to be an advantageous trend associated with the concomitant use of both dyes, particularly after stratification by MGMT (p = 0.071). Conclusions: 5-Ala and SF are equally useful in achieving gross total resection of the enhancing tumor volume. The combination of both fluorophores could lead to an OS advantage.

Despite the multidisciplinary management in the treatment of glioblastomas, the average survival of GBM patients is still 15 months. In recent years, molecular biomarkers have gained more and more importance both in the diagnosis and therapy of glial tumors. At the same time, it has become clear that non neoplastic cells, which constitute about 30% of glioma mass, dramatically influence tumor growth, spread, and recurrence. This is the main reason why, in recent years, scientific research has been focused on understanding the function and the composition of tumor microenvironment and its role in gliomagenesis and recurrence. The aim of this review is to summarize the most recent discovery about resident microglia, tumor-associated macrophages, lymphocytes, and the role of extracellular vesicles and their bijective interaction with glioma cells. Moreover, we reported the most recent updates about new therapeutic strategies targeting immune system receptors and soluble factors. Understanding how glioma cells interact with non-neoplastic cells in tumor microenvironment is an essential step to comprehend mechanisms at the base of disease progression and to find new therapeutic strategies for GBM patients. However, no significant results have yet been obtained in studies targeting single molecules/pathways; considering the complex microenvironment, it is likely that only by using multiple therapeutic agents acting on multiple molecular targets can significant results be achieved.

Objective: Clinical and surgical decisions for glioblastoma patients depend on a tumor imaging-based evaluation. Artificial Intelligence (AI) can be applied to magnetic resonance imaging (MRI) assessment to support clinical practice, surgery planning and prognostic predictions. In a real-world context, the current obstacles for AI are low-quality imaging and postoperative reliability. The aim of this study is to train an automatic algorithm for glioblastoma segmentation on a clinical MRI dataset and to obtain reliable results both pre- and post-operatively. Methods: The dataset used for this study comprises 237 (71 preoperative and 166 postoperative) MRIs from 71 patients affected by a histologically confirmed Grade IV Glioma. The implemented U-Net architecture was trained by transfer learning to perform the segmentation task on postoperative MRIs. The training was carried out first on BraTS2021 dataset for preoperative segmentation. Performance is evaluated using DICE score (DS) and Hausdorff 95% (H95). Results: In preoperative scenario, overall DS is 91.09 (± 0.60) and H95 is 8.35 (± 1.12), considering tumor core, enhancing tumor and whole tumor (ET and edema). In postoperative context, overall DS is 72.31 (± 2.88) and H95 is 23.43 (± 7.24), considering resection cavity (RC), gross tumor volume (GTV) and whole tumor (WT). Remarkably, the RC segmentation obtained a mean DS of 63.52 (± 8.90) in postoperative MRIs. Conclusions: The performances achieved by the algorithm are consistent with previous literature for both pre-operative and post-operative glioblastoma’s MRI evaluation. Through the proposed algorithm, it is possible to reduce the impact of low-quality images and missing sequences.

Glioblastoma (GBM) is the most common and aggressive central nervous system tumor, requiring multimodal management. Due to its malignant behavior and infiltrative growth pattern, GBM is one of the most difficult tumors to treat and gross total resection is still considered to be the first crucial step. The deep understanding of GBM microenvironment and the possibility of manipulating the patient’s innate and adaptive immune system to fight the neoplasm represent the base of immunotherapeutic strategies that currently express the future for the fight against GBM. Despite the immunotherapeutic approach having been successfully adopted in several solid and haematologic neoplasms, immune resistance and the immunosuppressive environment make the use of these strategies challenging in GBM treatment. We describe the most recent updates regarding new therapeutic strategies that target the immune system, immune checkpoint inhibitors, chimeric antigen receptor T cell therapy, peptide and oncolytic vaccines, and the relevant mechanism of immune resistance. However, no significant results have yet been obtained in studies targeting single molecules/pathways. The future direction of GBM therapy will include a combined approach that, in contrast to the inescapable current treatment modality of maximal resection followed by chemo- and radiotherapy, may combine a multifaceted immunotherapy treatment with the dual goals of directly killing tumor cells and activating the innate and adaptive immune response.