The white matter is a pro-differentiative niche for glioblastoma

Predicting glioblastoma progression using MR diffusion tensor imaging: A systematic review

BACKGROUND AND PURPOSE

Despite multimodal treatment of glioblastoma (GBM), recurrence beyond the initial tumor volume is inevitable. Moreover, conventional MRI has shortcomings that hinder the early detection of occult white matter tract infiltration by tumor, but diffusion tensor imaging (DTI) is a sensitive probe for assessing microstructural changes, facilitating the identification of progression before standard imaging. This sensitivity makes DTI a valuable tool for predicting recurrence. A systematic review was therefore conducted to investigate how DTI, in comparison to conventional MRI, can be used for predicting GBM progression.

METHODS

We queried three databases (PubMed, Web of Science, and Scopus) using the search terms: (diffusion tensor imaging OR DTI) AND (glioblastoma OR GBM) AND (recurrence OR progression). For included studies, data pertaining to the study type, number of GBM recurrence patients, treatment type(s), and DTI-related metrics of recurrence were extracted.

RESULTS

In all, 16 studies were included, from which there were 394 patients in total. Six studies reported decreased fractional anisotropy in recurrence regions, and 2 studies described the utility of connectomics/tractography for predicting tumor migratory pathways to a site of recurrence. Three studies reported evidence of tumor progression using DTI before recurrence was visible on conventional imaging.

CONCLUSIONS

These findings suggest that DTI metrics may be useful for guiding surgical and radiotherapy planning for GBM patients, and for informing long-term surveillance. Understanding the current state of the literature pertaining to these metrics' trends is crucial, particularly as DTI is increasingly used as a treatment-guiding imaging modality.

MicroRNA-124-3p targets Sp1 transcription factor to regulate glioma progression in rats

Gliomas are the most prevalent malignancies of the central nervous system (CNS). Downregulation of microRNA‑124 (miR‑124) has been identified in glioma; however, its biological functions in glioma are not yet fully understood. Specificity protein 1 (SP1) is a type of transcription factor that is involved in cancer progression. In this study, we examined the targeting of Sp1 mRNA by miR-124-3p in a rat glioma model. After confirming and selecting the binding of Sp1 to miR-124 with the help of bioinformatics methods, adult male Wistar rats were used to induce glioma by microinjection of 1 × 106 C6 cells into the striatum area of brain. The rats were divided into 3 groups; intact, sham and glioma groups. The presence of glioma was confirmed 21 days after implantation through histological analysis. The expression levels of miR-124 and SP1 genes in the experimental groups were examined using quantitative real-time polymerase chain reaction (qRT-PCR). Our data showed that the expression of miR-124 was significantly downregulated in glioma group compared to the sham and intact group, while the expression of SP1 was significantly upregulated. We found that the expression levels of miR-124 and Sp1 were decreased and increased in C6 cell line compared to the normal brain tissue cell line, respectively. The results indicated that Sp1 was identified as a direct target of miR‑124 through luciferase reporter assays. In summary, this study demonstrated for the first time that miR-124 expression is downregulated and Sp1 expression is upregulated in an animal model of glioma, which, in turn, may be involved in the development of glioma brain cancer.

Vagus nerve stimulation: Novel concept for the treatment of glioblastoma and solid cancers by cytokine (interleukin-6) reduction, attenuating the SASP, enhancing tumor immunity

Immuno-oncology, specifically immune checkpoint inhibitors (ICIs), has revolutionized cancer care with dramatic, long-term responses and increased survival, including patients with metastatic cancer to the brain. Glioblastomas, and other primary brain tumors, are refractory to ICIs as monotherapy or in combination with standard therapy. The tumor microenvironment (TME) poses multiple biological hurdles: blood-brain barrier, immune suppression, heterogeneity, and tumor infiltration. Genomic analysis of the senescence-associated secretory phenotype (SASP) and preclinical models of glioma suggest that an exciting approach would entail reprogramming of the glioma microenvironment, attenuating the pro-inflammatory, pro-tumorigenic cytokines of the SASP, especially interleukin-6 (IL-6). A testable hypothesis now proposed is to modulate the immune system by harnessing the body's 'inflammatory reflex' to reduce cytokines. Vagus nerve stimulation can activate T cell immunity by the cholinergic, α7nicotinic acetylcholine receptor agonist (α7nAchR), and suppress IL-6 systemically, as well as other pro-inflammatory cytokines of the SASP, interleukin -1β (IL-1β) and tumor necrosis factor-alpha (TNF-α). The hypothesis predicts that electrical activation of the vagus nerve, with cytokine reduction, in combination with ICIs, would convert an immune resistant ("cold") tumor to an immune responsive ("hot") tumor, and halt glioma progression. The hypothesis also envisions cancer as an immune "dysautonomia" whereby a therapeutic intervention, vagus nerve stimulation (VNS), resets the systemic and local cytokine levels. A prospective, randomized, phase II clinical trial, to confirm the hypothesis, is a logical, exigent, next step. Cytokine reduction by VNS could also be useful for other forms of human cancer, e.g., breast, colorectal, head and neck, lung, melanoma, ovarian, pancreatic, and prostate cancer, as the emerging field of "cancer neuroscience" shows a role for neural regulation of multiple tumor types. Because IL-6, and companion pro-inflammatory cytokines, participate in the initiation, progression, spread and recurrence of cancer, minimally invasive VNS could be employed to suppress glioma or cancer progression, while also mitigating depression and/or seizures, thereby enhancing quality of life. The current hypothesis reimagines glioma pathophysiology as a dysautonomia with the therapeutic objective to reset the autonomic nervous system and form an immune responsive state to halt tumor progression and prevent recurrence. VNS, as a novel method to control cancer, can be administered with ICIs, standard therapy, or in clinical trials, combined with emerging immunotherapy: dendritic cell, mRNA, or chimeric antigen receptor (CAR) T cell vaccines.

Wnt signaling in the tumor microenvironment: A driver of brain tumor dynamics

The Wnt signaling pathway is important for cell growth and development in the central nervous system and its associated vasculature. Thus, it is an interesting factor for establishing anti-brain cancer therapy. However, simply inhibiting the Wnt signaling pathway in patients with brain tumors is not an effective anti-cancer therapy. Due to their complex microenvironment, which comprises various cell types and signaling molecules, brain tumors pose significant challenges. It is important to understand the interplay between tumor cells and the microenvironment for developing effective therapeutic strategies for both benign and malignant brain tumors. Thus, this research focused on the role of the tumor microenvironment (TME) in brain tumor progression, particularly the involvement of Wnt-dependent signaling pathways. The brain parenchyma comprises neurons, glia, endothelial cells, and other extracellular matrix elements that can contribute to the TME. The TME components can secrete Wnt ligands or associated molecules, resulting in the aberrant activation of the Wnt signaling pathway, followed by tumor progression and therapeutic resistance. Therefore, it is essential to understand the intricate crosstalk between the Wnt signaling pathway and the TME in developing targeted therapies. This review aimed to elucidate the complexities of the brain TME and its interactions with the Wnt signaling pathways to improve treatment outcomes and our understanding of brain tumor biology.

Microglia and macrophages in glioblastoma: landscapes and treatment directions

Glioblastoma is the most common primary malignant tumour of the central nervous system and remains uniformly and rapidly fatal. The tumour-associated macrophage (TAM) compartment comprises brain-resident microglia and bone marrow-derived macrophages (BMDMs) recruited from the periphery. Immune-suppressive and tumour-supportive TAM cell states predominate in glioblastoma, and immunotherapies, which have achieved striking success in other solid tumours have consistently failed to improve survival in this 'immune-cold' niche context. Hypoxic and necrotic regions in the tumour core are found to enrich, especially in anti-inflammatory and immune-suppressive TAM cell states. Microglia predominate at the invasive tumour margin and express pro-inflammatory and interferon TAM cell signatures. Depletion of TAMs, or repolarisation towards a pro-inflammatory state, are appealing therapeutic strategies and will depend on effective understanding and classification of TAM cell ontogeny and state based on new single-cell and spatial multi-omic in situ profiling. Here, we explore the application of these datasets to expand and refine TAM characterisation, to inform improved modelling approaches, and ultimately underpin the effective manipulation of function.

SOX10 mediates glioblastoma cell-state plasticity

Phenotypic plasticity is a cause of glioblastoma therapy failure. We previously showed that suppressing the oligodendrocyte-lineage regulator SOX10 promotes glioblastoma progression. Here, we analyze SOX10-mediated phenotypic plasticity and exploit it for glioblastoma therapy design. We show that low SOX10 expression is linked to neural stem-cell (NSC)-like glioblastoma cell states and is a consequence of temozolomide treatment in animal and cell line models. Single-cell transcriptome profiling of Sox10-KD tumors indicates that Sox10 suppression is sufficient to induce tumor progression to an aggressive NSC/developmental-like phenotype, including a quiescent NSC-like cell population. The quiescent NSC state is induced by temozolomide and Sox10-KD and reduced by Notch pathway inhibition in cell line models. Combination treatment using Notch and HDAC/PI3K inhibitors extends the survival of mice carrying Sox10-KD tumors, validating our experimental therapy approach. In summary, SOX10 suppression mediates glioblastoma progression through NSC/developmental cell-state transition, including the induction of a targetable quiescent NSC state. This work provides a rationale for the design of tumor therapies based on single-cell phenotypic plasticity analysis.

Attenuation coefficient as a tool to detect changes in the white matter of the rat brain caused by different types of gliomas and irradiation

In the present work, we carried out a comparative study of the attenuation coefficient of the white matter of the rat brain during the growth of glial tumors characterized by different degrees of malignancy (glioblastoma 101/8, astrocytoma 10-17-2, glioma C6) and during irradiation. We demonstrated that some tumor models cause a pronounced decrease in white matter attenuation coefficient values due to infiltration of tumor cells, myelinated fiber destruction, and edema. In contrast, other tumors cause compression of the myelinated fibers of the corpus callosum without their ruptures and prominent invasion of tumor cells, which preserved the attenuation coefficient values changeless. In addition, for the first time, the possibility of using the attenuation coefficient to detect late radiation-induced changes in white matter characterized by focal development of edema, disruption of the integrity of myelinated fibers, and a decrease in the amount of oligodendrocytes and differentiation of these areas from tumor tissue and healthy white matter has been demonstrated. The results indicate the promise of using the attenuation coefficient estimated from OCT data for in vivo assessment of the degree of destruction of peritumoral white matter or its compression, which makes this method useful not only in primary resections but also in repeated surgical interventions for recurrent tumors.

Remote Neuroinflammation in Newly Diagnosed Glioblastoma Correlates with Unfavorable Clinical Outcome

PURPOSE

Current therapy strategies still provide only limited success in the treatment of glioblastoma, the most frequent primary brain tumor in adults. In addition to the characterization of the tumor microenvironment, global changes in the brain of patients with glioblastoma have been described. However, the impact and molecular signature of neuroinflammation distant of the primary tumor site have not yet been thoroughly elucidated.

EXPERIMENTAL DESIGN

We performed translocator protein (TSPO)-PET in patients with newly diagnosed glioblastoma (n = 41), astrocytoma WHO grade 2 (n = 7), and healthy controls (n = 20) and compared TSPO-PET signals of the non-lesion (i.e., contralateral) hemisphere. Back-translation into syngeneic SB28 glioblastoma mice was used to characterize Pet alterations on a cellular level. Ultimately, multiplex gene expression analyses served to profile immune cells in remote brain.

RESULTS

Our study revealed elevated TSPO-PET signals in contralateral hemispheres of patients with newly diagnosed glioblastoma compared to healthy controls. Contralateral TSPO was associated with persisting epileptic seizures and shorter overall survival independent of the tumor phenotype. Back-translation into syngeneic glioblastoma mice pinpointed myeloid cells as the predominant source of contralateral TSPO-PET signal increases and identified a complex immune signature characterized by myeloid cell activation and immunosuppression in distant brain regions.

CONCLUSIONS

Neuroinflammation within the contralateral hemisphere can be detected with TSPO-PET imaging and associates with poor outcome in patients with newly diagnosed glioblastoma. The molecular signature of remote neuroinflammation promotes the evaluation of immunomodulatory strategies in patients with detrimental whole brain inflammation as reflected by high TSPO expression.

Macrophage-mediated myelin recycling fuels brain cancer malignancy

Tumors growing in metabolically challenged environments, such as glioblastoma in the brain, are particularly reliant on crosstalk with their tumor microenvironment (TME) to satisfy their high energetic needs. To study the intricacies of this metabolic interplay, we interrogated the heterogeneity of the glioblastoma TME using single-cell and multi-omics analyses and identified metabolically rewired tumor-associated macrophage (TAM) subpopulations with pro-tumorigenic properties. These TAM subsets, termed lipid-laden macrophages (LLMs) to reflect their cholesterol accumulation, are epigenetically rewired, display immunosuppressive features, and are enriched in the aggressive mesenchymal glioblastoma subtype. Engulfment of cholesterol-rich myelin debris endows subsets of TAMs to acquire an LLM phenotype. Subsequently, LLMs directly transfer myelin-derived lipids to cancer cells in an LXR/Abca1-dependent manner, thereby fueling the heightened metabolic demands of mesenchymal glioblastoma. Our work provides an in-depth understanding of the immune-metabolic interplay during glioblastoma progression, thereby laying a framework to unveil targetable metabolic vulnerabilities in glioblastoma.

Deep intravital brain tumor imaging enabled by tailored three-photon microscopy and analysis

Intravital 2P-microscopy enables the longitudinal study of brain tumor biology in superficial mouse cortex layers. Intravital microscopy of the white matter, an important route of glioblastoma invasion and recurrence, has not been feasible, due to low signal-to-noise ratios and insufficient spatiotemporal resolution. Here, we present an intravital microscopy and artificial intelligence-based analysis workflow (Deep3P) that enables longitudinal deep imaging of glioblastoma up to a depth of 1.2 mm. We find that perivascular invasion is the preferred invasion route into the corpus callosum and uncover two vascular mechanisms of glioblastoma migration in the white matter. Furthermore, we observe morphological changes after white matter infiltration, a potential basis of an imaging biomarker during early glioblastoma colonization. Taken together, Deep3P allows for a non-invasive intravital investigation of brain tumor biology and its tumor microenvironment at subcortical depths explored, opening up opportunities for studying the neuroscience of brain tumors and other model systems.

NKG2C/KLRC2 tumor cell expression enhances immunotherapeutic efficacy against glioblastoma

BACKGROUND

Activating and inhibitory receptors of natural killer (NK) cells such as NKp, NKG2, or CLEC are highly relevant to cold tumors including glioblastoma (GBM). Here, we aimed to characterize the expression of these receptors in GBM to gain insight into their potential role as modulators of the intratumoral microenvironment.

METHODS

We performed a transcriptomic analysis of several NK receptors with a focus on the activating receptor encoded by KLRC2, NKG2C, among bulk and single-cell RNA sequencing GBM data sets. We also evaluated the effects of KLRC2-overexpressing GL261 cells in mice treated with or without programmed cell death protein-1 (PD-1) monoclonal antibody (mAb). Finally, we analyzed samples from two clinical trials evaluating PD-1 mAb effects in patients with GBM to determine the potential of NKG2C to serve as a biomarker of response.

RESULTS

We observed significant expression of several inhibitory NK receptors on GBM-infiltrating NK and T cells, which contrasts with the strong expression of KLRC2 on tumor cells, mainly at the infiltrative margin. Neoplastic KLRC2 expression was associated with a reduction in the number of myeloid-derived suppressor cells and with a higher level of tumor-resident lymphocytes. A stronger antitumor activity after PD-1 mAb treatment was observed in NKG2Chigh-expressing tumors both in mouse models and patients with GBM whereas the expression of inhibitory NK receptors showed an inverse association.

CONCLUSIONS

This study explored the role of neoplastic NKG2C/KLRC2 expression in shaping the immune profile of GBM and suggests that it is a predictive biomarker for positive responses to immune checkpoint inhibitor treatment in patients with GBM. Future studies could further validate this finding in prospective trials.

Diffusion tensor imaging in detecting gliomas sub-regions of infiltration, local and remote recurrences: a systematic review

Given that glioma cells tend to infiltrate and migrate along WM tracts, leading to demyelination and axonal injuries, Diffusion Tensor Imaging (DTI) emerged as a promising tool for identifying major "high-risk areas" of recurrence within the peritumoral brain zone (PBZ) or at a distance throughout the adjacents white matter tracts. Of our systematic review is to answer the following research question: In patients with brain tumor, is DTI able to recognizes within the peri-tumoral brain zone (PBZ) areas more prone to local (near the surgical cavity) or remote recurrence compared to the conventional imaging techniques?. We conducted a comprehensive literature search to identify relevant studies in line with the PRISMA-P (Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols) guidelines. 15 papers were deemed compatible with our research question and included. To enhance the paper's readability, we have categorized our findings into two distinct groups: the first delves into the role of DTI in detecting PBZ sub-regions of infiltration and local recurrences (n = 8), while the second group explores the feasibility of DTI in detecting white matter tract infiltration and remote recurrences (n = 7). DTI values and, within a broader framework, radiomics investigations can provide precise, voxel-by-voxel insights into the state of PBZ and recurrences. Better defining the regions at risk for potential recurrence within the PBZ and along WM bundles will allow targeted therapy.

Diffusion Tensor Imaging Identifies Cervical Spondylosis, Myelitis, and Spinal Cord Tumors

BACKGROUND

Diffusion tensor imaging (DTI) has been increasingly recognized for its capability to study microstructural changes in the neuropathology of brain diseases. However, the optimal DTI metric and its diagnostic utility for a variety of spinal cord diseases are still under investigation.

PURPOSE

To evaluate the diagnostic efficacy of DTI metrics for differentiating between cervical spondylosis, myelitis, and spinal tumors.

METHODS

This retrospective study analyzed DTI scans from 68 patients (22 with cervical spondylosis, 23 with myelitis, and 23 with spinal tumors). DTI indicators, including fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD), were calculated. The Kruskal-Wallis test was used to compare these indicators, followed by Receiver Operating Characteristic (ROC) curve analysis, to evaluate the diagnostic efficacy of each indicator across disease pairs. Additionally, we explored the correlations of DTI indicators with specific clinical measurements.

RESULTS

FA values were significantly lower in tumor patients compared to those with cervical spondylosis (p < 0.0001) and myelitis (p < 0.05). Additionally, tumor patients exhibited significantly elevated MD and RD values relative to the spondylosis and myelitis groups. ROC curve analysis underscored FA's superior discriminative performance, with an area under the curve (AUC) of 0.902 for differentiating tumors from cervical spondylosis, and an AUC of 0.748 for distinguishing cervical myelitis from spondylosis. Furthermore, a significant negative correlation was observed between FA values and Expanded Disability Status Scores (EDSSs) in myelitis patients (r = -0.62, p = 0.002), as well as between FA values and Ki-67 scores in tumor patients (r = -0.71, p = 0.0002).

CONCLUSION

DTI indicators, especially FA, have the potential in distinguishing spondylosis, myelitis, and spinal cord tumors. The significant correlation between FA values and clinical indicators highlights the value of FA in the clinical assessment and prognosis of spinal diseases and may be applied in diagnostic protocols in the future.

Distinct roles of TREM2 in central nervous system cancers and peripheral cancers

Glioblastomas (GBM) are incurable central nervous system (CNS) cancers characterized by substantial myeloid cell infiltration. Whether myeloid cell-directed therapeutic targets identified in peripheral non-CNS cancers are applicable to GBM requires further study. Here, we identify that the critical immunosuppressive target in peripheral cancers, triggering receptor expressed on myeloid cells-2 (TREM2), is immunoprotective in GBM. Genetic or pharmacological TREM2 deficiency promotes GBM progression in vivo. Single-cell and spatial sequencing reveals downregulated TREM2 in GBM-infiltrated myeloid cells. TREM2 negatively correlates with immunosuppressive myeloid and T cell exhaustion signatures in GBM. We further demonstrate that during GBM progression, CNS-enriched sphingolipids bind TREM2 on myeloid cells and elicit antitumor responses. Clinically, high TREM2 expression in myeloid cells correlates with better survival in GBM. Adeno-associated virus-mediated TREM2 overexpression impedes GBM progression and synergizes with anti-PD-1 therapy. Our results reveal distinct functions of TREM2 in CNS cancers and support organ-specific myeloid cell remodeling in cancer immunotherapy.

Non-Tumor Cells within the Tumor Microenvironment-The "Eminence Grise" of the Glioblastoma Pathogenesis and Potential Targets for Therapy

Glioblastoma (GBM) is the most common malignancy of the central nervous system in adults. GBM has high levels of therapy failure and its prognosis is usually dismal. The phenotypic heterogeneity of the tumor cells, dynamic complexity of non-tumor cell populations within the GBM tumor microenvironment (TME), and their bi-directional cross-talk contribute to the challenges of current therapeutic approaches. Herein, we discuss the etiology of GBM, and describe several major types of non-tumor cells within its TME, their impact on GBM pathogenesis, and molecular mechanisms of such an impact. We also discuss their value as potential therapeutic targets or prognostic biomarkers, with reference to the most recent works on this subject. We conclude that unless all "key player" populations of non-tumor cells within the TME are considered, no breakthrough in developing treatment for GBM can be achieved.

Radiotherapy-Induced Astrocyte Senescence Promotes an Immunosuppressive Microenvironment in Glioblastoma to Facilitate Tumor Regrowth

Accumulating evidence suggests that changes in the tumor microenvironment caused by radiotherapy are closely related to the recurrence of glioma. However, the mechanisms by which such radiation-induced changes are involved in tumor regrowth have not yet been fully investigated. In the present study, how cranial irradiation-induced senescence in non-neoplastic brain cells contributes to glioma progression is explored. It is observed that senescent brain cells facilitated tumor regrowth by enhancing the peripheral recruitment of myeloid inflammatory cells in glioblastoma. Further, it is identified that astrocytes are one of the most susceptible senescent populations and that they promoted chemokine secretion in glioma cells via the senescence-associated secretory phenotype. By using senolytic agents after radiotherapy to eliminate these senescent cells substantially prolonged survival time in preclinical models. The findings suggest the tumor-promoting role of senescent astrocytes in the irradiated glioma microenvironment and emphasize the translational relevance of senolytic agents for enhancing the efficacy of radiotherapy in gliomas.

Peritumoral brain zone in glioblastoma: biological, clinical and mechanical features

Glioblastoma is a highly aggressive and invasive tumor that affects the central nervous system (CNS). With a five-year survival rate of only 6.9% and a median survival time of eight months, it has the lowest survival rate among CNS tumors. Its treatment consists of surgical resection, subsequent fractionated radiotherapy and concomitant and adjuvant chemotherapy with temozolomide. Despite the implementation of clinical interventions, recurrence is a common occurrence, with over 80% of cases arising at the edge of the resection cavity a few months after treatment. The high recurrence rate and location of glioblastoma indicate the need for a better understanding of the peritumor brain zone (PBZ). In this review, we first describe the main radiological, cellular, molecular and biomechanical tissue features of PBZ; and subsequently, we discuss its current clinical management, potential local therapeutic approaches and future prospects.

Identification of EMT-associated prognostic features among grade II/III gliomas

Grade II/III gliomas have a highly heterogeneous clinical course. Identifying prognostic biomarkers in grade II/III gliomas is essential to guide clinical management. We explored epithelial-mesenchymal transition (EMT)-related genes to uncover prognostic features in grade II/III gliomas. Consensus cluster analysis of 200 EMT-related genes classified 512 grade II/III glioma samples into two molecular subtypes, C1 and C2. The C1 subtype had significantly worse overall survival compared to the C2 subtype. Pathway analysis revealed C1 tumors were highly associated with tumor progression pathways and demonstrated higher immune cell infiltration scores. Differential expression analysis identified four genes (ACTN1, AQP1, LAMC3, NRM) that discriminated the two subtypes. Validation in external datasets confirmed that high expression of this four-gene signature predicted poor prognosis in grade II/III gliomas. Cellular experiments showed ACTN1, AQP1 and NRM promoted glioma cell proliferation, migration and invasion. We examined correlations of the signature genes with T cell exhaustion markers and found ACTN1 expression had the strongest association. Immunohistochemistry analysis further demonstrated that ACTN1 protein expression in grade II/III gliomas was negatively correlated with patient overall survival. In summary, our study identified a concise four-gene signature that robustly predicts grade II/III gliomas prognosis across multiple datasets. The signature provides clinical relevance in distinguishing more aggressive grade II/III glioma tumors. Targeting the ACTN1, AQP1 and NRM genes may offer new therapeutic opportunities to improve grade II/III gliomas patient outcomes.

Glioma stem cells remodel immunotolerant microenvironment in GBM and are associated with therapeutic advancements

Glioma is the most common primary tumor of the central nervous system (CNS). Glioblastoma (GBM) is incurable with current treatment strategies. Additionally, the treatment of recurrent GBM (rGBM) is often referred to as terminal treatment, necessitating hospice-level care and management. The presence of the blood-brain barrier (BBB) gives GBM a more challenging or "cold" tumor microenvironment (TME) than that of other cancers and gloma stem cells (GSCs) play an important role in the TME remodeling, occurrence, development and recurrence of giloma. In this review, our primary focus will be on discussing the following topics: niche-associated GSCs and macrophages, new theories regarding GSC and TME involving pyroptosis and ferroptosis in GBM, metabolic adaptations of GSCs, the influence of the cold environment in GBM on immunotherapy, potential strategies to transform the cold GBM TME into a hot one, and the advancement of GBM immunotherapy and GBM models.

Advanced diffusion imaging reveals microstructural characteristics of primary CNS lymphoma, allowing differentiation from glioblastoma

Background

Primary CNS lymphoma (PCNSL) and glioblastoma (GBM) both represent frequent intracranial malignancies with differing clinical management. However, distinguishing PCNSL from GBM with conventional MRI can be challenging when atypical imaging features are present. We employed advanced dMRI for noninvasive characterization of the microstructure of PCNSL and differentiation from GBM as the most frequent primary brain malignancy.

Methods

Multiple dMRI metrics including Diffusion Tensor Imaging, Neurite Orientation Dispersion and Density Imaging, and Diffusion Microstructure Imaging were extracted from the contrast-enhancing tumor component in 10 PCNSL and 10 age-matched GBM on 3T MRI. Imaging findings were correlated with cell density and axonal markers obtained from histopathology.

Results

We found significantly increased intra-axonal volume fractions (V-intra and intracellular volume fraction) and microFA in PCNSL compared to GBM (all P < .001). In contrast, mean diffusivity (MD), axial diffusivity (aD), and microADC (all P < .001), and also free water fractions (V-CSF and V-ISO) were significantly lower in PCNSL (all P < .01). Receiver-operating characteristic analysis revealed high predictive values regarding the presence of a PCNSL for MD, aD, microADC, V-intra, ICVF, microFA, V-CSF, and V-ISO (area under the curve [AUC] in all >0.840, highest for MD and ICVF with an AUC of 0.960). Comparative histopathology between PCNSL and GBM revealed a significantly increased cell density in PCNSL and the presence of axonal remnants in a higher proportion of samples.

Conclusions

Advanced diffusion imaging enables the characterization of the microstructure of PCNSL and reliably distinguishes PCNSL from GBM. Both imaging and histopathology revealed a relatively increased cell density and a preserved axonal microstructure in PCNSL.

Brain tumour genetic network signatures of survival

Tumour heterogeneity is increasingly recognized as a major obstacle to therapeutic success across neuro-oncology. Gliomas are characterized by distinct combinations of genetic and epigenetic alterations, resulting in complex interactions across multiple molecular pathways. Predicting disease evolution and prescribing individually optimal treatment requires statistical models complex enough to capture the intricate (epi)genetic structure underpinning oncogenesis. Here, we formalize this task as the inference of distinct patterns of connectivity within hierarchical latent representations of genetic networks. Evaluating multi-institutional clinical, genetic and outcome data from 4023 glioma patients over 14 years, across 12 countries, we employ Bayesian generative stochastic block modelling to reveal a hierarchical network structure of tumour genetics spanning molecularly confirmed glioblastoma, IDH-wildtype; oligodendroglioma, IDH-mutant and 1p/19q codeleted; and astrocytoma, IDH-mutant. Our findings illuminate the complex dependence between features across the genetic landscape of brain tumours and show that generative network models reveal distinct signatures of survival with better prognostic fidelity than current gold standard diagnostic categories.

Exosomal non-coding RNAs in glioma progression: insights into tumor microenvironment dynamics and therapeutic implications

Gliomas are the most common and deadly types of brain tumors, known for their extensive genetic and epigenetic variability, which poses considerable challenges for pharmacological treatment. Glioma heterogeneity is also related to their intricate and dynamic tumor microenvironment (TME), which comprises a diverse array of cell types, including immune cells, vascular cells, glial cells, and neural precursors, collectively influencing tumor behavior and progression. A pivotal aspect of this intercellular communication relies on the exchange of extracellular vesicles (EVs), which contain and transfer complex molecular cargoes typical of their cells of origin, such as proteins, lipids, carbohydrates, metabolites, and non-coding RNAs (ncRNAs), that encompass microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). Glioma cells actively release EVs loaded with specific ncRNAs that can target genes and other ncRNAs in recipient cells residing within the TME. Among these recipient cells, prominent players include tumor-associated macrophages and microglia (TAMs), non-neoplastic astrocytes and endothelial cells. The intricate interplay between EVs derived from glioma cells and these recipient cells significantly contributes to the establishment of a tumor-permissive microenvironment, promoting tumor cell proliferation, migration, angiogenesis, and invasion, by targeting various downstream pathways. This review critically examines the current understanding of the intricate interplay between glioma, exosomal ncRNAs, and various components of the glioma TME. By shedding light on the roles of ncRNAs in mediating intercellular communication, this review underscores their significance in orchestrating TME transformation and highlights their potential as novel therapeutic targets for effectively tackling glioma progression.

Dissecting Intra-tumor Heterogeneity in the Glioblastoma Microenvironment Using Fluorescence-Guided Multiple Sampling

The treatment of the most aggressive primary brain tumor in adults, glioblastoma (GBM), is challenging due to its heterogeneous nature, invasive potential, and poor response to chemo- and radiotherapy. As a result, GBM inevitably recurs and only a few patients survive 5 years post-diagnosis. GBM is characterized by extensive phenotypic and genetic heterogeneity, creating a diversified genetic landscape and a network of biological interactions between subclones, ultimately promoting tumor growth and therapeutic resistance. This includes spatial and temporal changes in the tumor microenvironment, which influence cellular and molecular programs in GBM and therapeutic responses. However, dissecting phenotypic and genetic heterogeneity at spatial and temporal levels is extremely challenging, and the dynamics of the GBM microenvironment cannot be captured by analysis of a single tumor sample. In this review, we discuss the current research on GBM heterogeneity, in particular, the utility and potential applications of fluorescence-guided multiple sampling to dissect phenotypic and genetic intra-tumor heterogeneity in the GBM microenvironment, identify tumor and non-tumor cell interactions and novel therapeutic targets in areas that are key for tumor growth and recurrence, and improve the molecular classification of GBM.

The tumour ecology of quiescence: Niches across scales of complexity

Quiescence is a state of cell cycle arrest, allowing cancer cells to evade anti-proliferative cancer therapies. Quiescent cancer stem cells are thought to be responsible for treatment resistance in glioblastoma, an aggressive brain cancer with poor patient outcomes. However, the regulation of quiescence in glioblastoma cells involves a myriad of intrinsic and extrinsic mechanisms that are not fully understood. In this review, we synthesise the literature on quiescence regulatory mechanisms in the context of glioblastoma and propose an ecological perspective to stemness-like phenotypes anchored to the contemporary concepts of niche theory. From this perspective, the cell cycle regulation is multiscale and multidimensional, where the niche dimensions extend to extrinsic variables in the tumour microenvironment that shape cell fate. Within this conceptual framework and powered by ecological niche modelling, the discovery of microenvironmental variables related to hypoxia and mechanosignalling that modulate proliferative plasticity and intratumor immune activity may open new avenues for therapeutic targeting of emerging biological vulnerabilities in glioblastoma.

Glioblastoma cell fate is differentially regulated by the microenvironments of the tumor bulk and infiltrative margin

Glioblastoma (GBM) recurrence originates from invasive margin cells that escape surgical debulking, but to what extent these cells resemble their bulk counterparts remains unclear. Here, we generated three immunocompetent somatic GBM mouse models, driven by subtype-associated mutations, to compare matched bulk and margin cells. We find that, regardless of mutations, tumors converge on common sets of neural-like cellular states. However, bulk and margin have distinct biology. Injury-like programs associated with immune infiltration dominate in the bulk, leading to the generation of lowly proliferative injured neural progenitor-like cells (iNPCs). iNPCs account for a significant proportion of dormant GBM cells and are induced by interferon signaling within T cell niches. In contrast, developmental-like trajectories are favored within the immune-cold margin microenvironment resulting in differentiation toward invasive astrocyte-like cells. These findings suggest that the regional tumor microenvironment dominantly controls GBM cell fate and biological vulnerabilities identified in the bulk may not extend to the margin residuum.

macroH2A2 antagonizes epigenetic programs of stemness in glioblastoma

Self-renewal is a crucial property of glioblastoma cells that is enabled by the choreographed functions of chromatin regulators and transcription factors. Identifying targetable epigenetic mechanisms of self-renewal could therefore represent an important step toward developing effective treatments for this universally lethal cancer. Here we uncover an epigenetic axis of self-renewal mediated by the histone variant macroH2A2. With omics and functional assays deploying patient-derived in vitro and in vivo models, we show that macroH2A2 shapes chromatin accessibility at enhancer elements to antagonize transcriptional programs of self-renewal. macroH2A2 also sensitizes cells to small molecule-mediated cell death via activation of a viral mimicry response. Consistent with these results, our analyses of clinical cohorts indicate that high transcriptional levels of this histone variant are associated with better prognosis of high-grade glioma patients. Our results reveal a targetable epigenetic mechanism of self-renewal controlled by macroH2A2 and suggest additional treatment approaches for glioblastoma patients.

Diet suppresses glioblastoma initiation in mice by maintaining quiescence of mutation-bearing neural stem cells

Glioblastoma is thought to originate from neural stem cells (NSCs) of the subventricular zone that acquire genetic alterations. In the adult brain, NSCs are largely quiescent, suggesting that deregulation of quiescence maintenance may be a prerequisite for tumor initiation. Although inactivation of the tumor suppressor p53 is a frequent event in gliomagenesis, whether or how it affects quiescent NSCs (qNSCs) remains unclear. Here, we show that p53 maintains quiescence by inducing fatty-acid oxidation (FAO) and that acute p53 deletion in qNSCs results in their premature activation to a proliferative state. Mechanistically, this occurs through direct transcriptional induction of PPARGC1a, which in turn activates PPARα to upregulate FAO genes. Dietary supplementation with fish oil containing omega-3 fatty acids, natural PPARα ligands, fully restores quiescence of p53-deficient NSCs and delays tumor initiation in a glioblastoma mouse model. Thus, diet can silence glioblastoma driver mutations, with important implications for cancer prevention.

Injury primes mutation-bearing astrocytes for dedifferentiation in later life

Despite their latent neurogenic potential, most normal parenchymal astrocytes fail to dedifferentiate to neural stem cells in response to injury. In contrast, aberrant lineage plasticity is a hallmark of gliomas, and this suggests that tumor suppressors may constrain astrocyte dedifferentiation. Here, we show that p53, one of the most commonly inactivated tumor suppressors in glioma, is a gatekeeper of astrocyte fate. In the context of stab-wound injury, p53 loss destabilized the identity of astrocytes, priming them to dedifferentiate in later life. This resulted from persistent and age-exacerbated neuroinflammation at the injury site and EGFR activation in periwound astrocytes. Mechanistically, dedifferentiation was driven by the synergistic upregulation of mTOR signaling downstream of p53 loss and EGFR, which reinstates stemness programs via increased translation of neurodevelopmental transcription factors. Thus, our findings suggest that first-hit mutations remove the barriers to injury-induced dedifferentiation by sensitizing somatic cells to inflammatory signals, with implications for tumorigenesis.

Data-driven spatio-temporal modelling of glioblastoma

Mathematical oncology provides unique and invaluable insights into tumour growth on both the microscopic and macroscopic levels. This review presents state-of-the-art modelling techniques and focuses on their role in understanding glioblastoma, a malignant form of brain cancer. For each approach, we summarize the scope, drawbacks and assets. We highlight the potential clinical applications of each modelling technique and discuss the connections between the mathematical models and the molecular and imaging data used to inform them. By doing so, we aim to prime cancer researchers with current and emerging computational tools for understanding tumour progression. By providing an in-depth picture of the different modelling techniques, we also aim to assist researchers who seek to build and develop their own models and the associated inference frameworks. Our article thus strikes a unique balance. On the one hand, we provide a comprehensive overview of the available modelling techniques and their applications, including key mathematical expressions. On the other hand, the content is accessible to mathematicians and biomedical scientists alike to accommodate the interdisciplinary nature of cancer research.

Tumor Microenvironment in Gliomas: A Treatment Hurdle or an Opportunity to Grab?

Gliomas are the most frequent central nervous system (CNS) primary tumors. The prognosis and clinical outcomes of these malignancies strongly diverge according to their molecular alterations and range from a few months to decades. The tumor-associated microenvironment involves all cells and connective tissues surrounding tumor cells. The composition of the microenvironment as well as the interactions with associated neoplastic mass, are both variables assuming an increasing interest in these last years. This is mainly because the microenvironment can mediate progression, invasion, dedifferentiation, resistance to treatment, and relapse of primary gliomas. In particular, the tumor microenvironment strongly diverges from isocitrate dehydrogenase (IDH) mutated and wild-type (wt) tumors. Indeed, IDH mutated gliomas often show a lower infiltration of immune cells with reduced angiogenesis as compared to IDH wt gliomas. On the other hand, IDH wt tumors exhibit a strong immune infiltration mediated by several cytokines and chemokines, including CCL2, CCL7, GDNF, CSF-1, GM-CSF, etc. The presence of several factors, including Sox2, Oct4, PD-L1, FAS-L, and TGF β2, also mediate an immune switch toward a regulatory inhibited immune system. Other important interactions are described between IDH wt glioblastoma cells and astrocytes, neurons, and stem cells, while these interactions are less elucidated in IDH-mutated tumors. The possibility of targeting the microenvironment is an intriguing perspective in terms of therapeutic drug development. In this review, we summarized available evidence related to the glioma microenvironment, focusing on differences within different glioma subtypes and on possible therapeutic development.

Nondestructive label-free detection of peritumoral white matter damage using cross-polarization optical coherence tomography

Introduction

To improve the quality of brain tumor resections, it is important to differentiate zones with myelinated fibers destruction from tumor tissue and normal white matter. Optical coherence tomography (OCT) is a promising tool for brain tissue visualization and in the present study, we demonstrate the ability of cross-polarization (CP) OCT to detect damaged white matter and differentiate it from normal and tumor tissues.

Materials and methods

The study was performed on 215 samples of brain tissue obtained from 57 patients with brain tumors. The analysis of the obtained OCT data included three stages: 1) visual analysis of structural OCT images; 2) quantitative assessment based on attenuation coefficients estimation in co- and cross-polarizations; 3) building of color-coded maps with subsequent visual analysis. The defining characteristics of structural CP OCT images and color-coded maps were determined for each studied tissue type, and then two classification tests were passed by 8 blinded respondents after a training.

Results

Visual assessment of structural CP OCT images allows detecting white matter areas with damaged myelinated fibers and differentiate them from normal white matter and tumor tissue. Attenuation coefficients also allow distinguishing all studied brain tissue types, while it was found that damage to myelinated fibers leads to a statistically significant decrease in the values of attenuation coefficients compared to normal white matter. Nevertheless, the use of color-coded optical maps looks more promising as it combines the objectivity of optical coefficient and clarity of the visual assessment, which leads to the increase of the diagnostic accuracy of the method compared to visual analysis of structural OCT images.

Conclusions

Alteration of myelinated fibers causes changes in the scattering properties of the white matter, which gets reflected in the nature of the received CP OCT signal. Visual assessment of structural CP OCT images and color-coded maps allows differentiating studied tissue types from each other, while usage of color-coded maps demonstrates higher diagnostic accuracy values in comparison with structural images (F-score = 0.85-0.86 and 0.81, respectively). Thus, the results of the study confirm the potential of using OCT as a neuronavigation tool during resections of brain tumors.

The landscape of tumor cell states and spatial organization in H3-K27M mutant diffuse midline glioma across age and location

Histone 3 lysine27-to-methionine (H3-K27M) mutations most frequently occur in diffuse midline gliomas (DMGs) of the childhood pons but are also increasingly recognized in adults. Their potential heterogeneity at different ages and midline locations is vastly understudied. Here, through dissecting the single-cell transcriptomic, epigenomic and spatial architectures of a comprehensive cohort of patient H3-K27M DMGs, we delineate how age and anatomical location shape glioma cell-intrinsic and -extrinsic features in light of the shared driver mutation. We show that stem-like oligodendroglial precursor-like cells, present across all clinico-anatomical groups, display varying levels of maturation dependent on location. We reveal a previously underappreciated relationship between mesenchymal cancer cell states and age, linked to age-dependent differences in the immune microenvironment. Further, we resolve the spatial organization of H3-K27M DMG cell populations and identify a mitotic oligodendroglial-lineage niche. Collectively, our study provides a powerful framework for rational modeling and therapeutic interventions.

Injury programs shape glioblastoma

Glioblastoma is the most common and aggressive primary brain cancer in adults and is almost universally fatal due to its stark therapeutic resistance. During the past decade, although survival has not substantially improved, major advances have been made in our understanding of the underlying biology. It has become clear that these devastating tumors recapitulate features of neurodevelopmental hierarchies which are influenced by the microenvironment. Emerging evidence also highlights a prominent role for injury responses in steering cellular phenotypes and contributing to tumor heterogeneity. This review highlights how the interplay between injury and neurodevelopmental programs impacts on tumor growth, invasion, and treatment resistance, and discusses potential therapeutic considerations in view of these findings.

Roles of Chromatin Remodelling and Molecular Heterogeneity in Therapy Resistance in Glioblastoma

Cancer stem cells (CSCs) represent a therapy-resistant reservoir in glioblastoma (GBM). It is now becoming clear that epigenetic and chromatin remodelling programs link the stemlike behaviour of CSCs to their treatment resistance. New evidence indicates that the epigenome of GBM cells is shaped by intrinsic and extrinsic factors, including their genetic makeup, their interactions and communication with other neoplastic and non-neoplastic cells, including immune cells, and their metabolic niche. In this review, we explore how all these factors contribute to epigenomic heterogeneity in a tumour and the selection of therapy-resistant cells. Lastly, we discuss current and emerging experimental platforms aimed at precisely understanding the epigenetic mechanisms of therapy resistance that ultimately lead to tumour relapse. Given the growing arsenal of drugs that target epigenetic enzymes, our review addresses promising preclinical and clinical applications of epidrugs to treat GBM, and possible mechanisms of resistance that need to be overcome.

Efficient Bayesian inference for stochastic agent-based models

The modelling of many real-world problems relies on computationally heavy simulations of randomly interacting individuals or agents. However, the values of the parameters that underlie the interactions between agents are typically poorly known, and hence they need to be inferred from macroscopic observations of the system. Since statistical inference rests on repeated simulations to sample the parameter space, the high computational expense of these simulations can become a stumbling block. In this paper, we compare two ways to mitigate this issue in a Bayesian setting through the use of machine learning methods: One approach is to construct lightweight surrogate models to substitute the simulations used in inference. Alternatively, one might altogether circumvent the need for Bayesian sampling schemes and directly estimate the posterior distribution. We focus on stochastic simulations that track autonomous agents and present two case studies: tumour growths and the spread of infectious diseases. We demonstrate that good accuracy in inference can be achieved with a relatively small number of simulations, making our machine learning approaches orders of magnitude faster than classical simulation-based methods that rely on sampling the parameter space. However, we find that while some methods generally produce more robust results than others, no algorithm offers a one-size-fits-all solution when attempting to infer model parameters from observations. Instead, one must choose the inference technique with the specific real-world application in mind. The stochastic nature of the considered real-world phenomena poses an additional challenge that can become insurmountable for some approaches. Overall, we find machine learning approaches that create direct inference machines to be promising for real-world applications. We present our findings as general guidelines for modelling practitioners.

Global research trends and hotspots on glioma stem cells

Background

Glioma stem cells (GSCs) are a sub-population of cancer stem cells with capacity of self-renewal and differentiation. Accumulated evidence has revealed that GSCs were shown to contribute to gliomagenesis, distant metastasis as well as the resistance to radiotherapy and chemotherapy. As a result, GSCs were regarded as a promising therapeutic target in human glioma. The purpose of our study is to identify current state and hotspots of GSCs research by analyzing scientific publications through bibliometric methods.

Methods

All relevant publications on GSCs during 2003-2021 were extracted from the Science Citation Index Expanded of Web of Science Core Collection (WoSCC), and related information was collected and analyzed using Microsoft Excel 2016, GraphPad Prism 8 and VOSviewer software.

Results

A total of 4990 papers were included. The United States accounted for the largest number of publications (1852), the second average citations per item (ACI) value (67.54) as well as the highest H-index (157). Cancer Research was the most influential journal in this field. The most contributive institution was League of European Research Universities. RICH JN was the author with the most publications (109) and the highest H-index (59). All studies were clustered into 3 groups: “glioma stem cell properties”, “cell biological properties” and “oncology therapy”. The keywords “identification”, “CD133” and “side population” appeared earlier with the smaller average appearing years (AAY), and the keywords”radiotherapy” and “chemotherapy” had the latest AAY. The analysis of top cited articles showed that “temozolomide”, “epithelial-mesenchymal transition”, and “immunotherapy” emerged as new focused issues.

Conclusion

There has been a growing number of researches on GSCs. The United States has always been a leading player in this domain. In general, the research focus has gradually shifted from basic cellular biology to the solutions of clinical concerns. “Temozolomide resistance”, “epithelial-mesenchymal transition”, and “immunotherapy” should be given more attention in the future.

Brain cancer stem cells: resilience through adaptive plasticity and hierarchical heterogeneity

Malignant brain tumours are complex ecosystems containing neoplastic and stromal components that generate adaptive and evolutionarily driven aberrant tissues in the central nervous system. Brain cancers are cultivated by a dynamic population of stem-like cells that enforce intratumoural heterogeneity and respond to intrinsic microenvironment or therapeutically guided insults through proliferation, plasticity and restructuring of neoplastic and stromal components. Far from a rigid hierarchy, heterogeneous neoplastic populations transition between cellular states with differential self-renewal capacities, endowing them with powerful resilience. Here we review the biological machinery used by brain tumour stem cells to commandeer tissues in the intracranial space, evade immune responses and resist chemoradiotherapy. Through recent advances in single-cell sequencing, improved models to investigate the role of the tumour microenvironment and a deeper understanding of the fundamental role of the immune system in cancer biology, we are now better equipped to explore mechanisms by which these processes can be exploited for therapeutic benefit.

PDPN marks a subset of aggressive and radiation-resistant glioblastoma cells

Treatment-resistant glioma stem cells are thought to propagate and drive growth of malignant gliomas, but their markers and our ability to target them specifically are not well understood. We demonstrate that podoplanin (PDPN) expression is an independent prognostic marker in gliomas across multiple independent patient cohorts comprising both high- and low-grade gliomas. Knockdown of PDPN radiosensitized glioma cell lines and glioma-stem-like cells (GSCs). Clonogenic assays and xenograft experiments revealed that PDPN expression was associated with radiotherapy resistance and tumor aggressiveness. We further demonstrate that knockdown of PDPN in GSCs in vivo is sufficient to improve overall survival in an intracranial xenograft mouse model. PDPN therefore identifies a subset of aggressive, treatment-resistant glioma cells responsible for radiation resistance and may serve as a novel therapeutic target.

Tumor-Associated Microenvironment of Adult Gliomas: A Review

The glioma-associated tumor microenvironment involves a multitude of different cells ranging from immune cells to endothelial, glial, and neuronal cells surrounding the primary tumor. The interactions between these cells and glioblastoma (GBM) have been deeply investigated while very little data are available on patients with lower-grade gliomas. In these tumors, it has been demonstrated that the composition of the microenvironment differs according to the isocitrate dehydrogenase status (mutated/wild type), the presence/absence of codeletion, and the expression of specific alterations including H3K27 and/or other gene mutations. In addition, mechanisms by which the tumor microenvironment sustains the growth and proliferation of glioma cells are still partially unknown. Nonetheless, a better knowledge of the tumor-associated microenvironment can be a key issue in the optic of novel therapeutic drug development.

Machine learning-based prediction of motor status in glioma patients using diffusion MRI metrics along the corticospinal tract

Along tract statistics enables white matter characterization using various diffusion MRI metrics. These diffusion models reveal detailed insights into white matter microstructural changes with development, pathology and function. Here, we aim at assessing the clinical utility of diffusion MRI metrics along the corticospinal tract, investigating whether motor glioma patients can be classified with respect to their motor status. We retrospectively included 116 brain tumour patients suffering from either left or right supratentorial, unilateral World Health Organization Grades II, III and IV gliomas with a mean age of 53.51 ± 16.32 years. Around 37% of patients presented with preoperative motor function deficits according to the Medical Research Council scale. At group level comparison, the highest non-overlapping diffusion MRI differences were detected in the superior portion of the tracts’ profiles. Fractional anisotropy and fibre density decrease, apparent diffusion coefficient axial diffusivity and radial diffusivity increase. To predict motor deficits, we developed a method based on a support vector machine using histogram-based features of diffusion MRI tract profiles (e.g. mean, standard deviation, kurtosis and skewness), following a recursive feature elimination method. Our model achieved high performance (74% sensitivity, 75% specificity, 74% overall accuracy and 77% area under the curve). We found that apparent diffusion coefficient, fractional anisotropy and radial diffusivity contributed more than other features to the model. Incorporating the patient demographics and clinical features such as age, tumour World Health Organization grade, tumour location, gender and resting motor threshold did not affect the model’s performance, revealing that these features were not as effective as microstructural measures. These results shed light on the potential patterns of tumour-related microstructural white matter changes in the prediction of functional deficits.

Real-time evaluation of glioblastoma growth in patient-specific zebrafish xenografts

BACKGROUND

Patient-derived xenograft (PDX) models of glioblastoma (GBM) are a central tool for neuro-oncology research and drug development, enabling the detection of patient-specific differences in growth, and in vivo drug response. However, existing PDX models are not well suited for large-scale or automated studies. Thus, here, we investigate if a fast zebrafish-based PDX model, supported by longitudinal, AI-driven image analysis, can recapitulate key aspects of glioblastoma growth and enable case-comparative drug testing.

METHODS

We engrafted 11 GFP-tagged patient-derived GBM IDH wild-type cell cultures (PDCs) into 1-day-old zebrafish embryos, and monitored fish with 96-well live microscopy and convolutional neural network analysis. Using light-sheet imaging of whole embryos, we analyzed further the invasive growth of tumor cells.

RESULTS

Our pipeline enables automatic and robust longitudinal observation of tumor growth and survival of individual fish. The 11 PDCs expressed growth, invasion and survival heterogeneity, and tumor initiation correlated strongly with matched mouse PDX counterparts (Spearman R = 0.89, p < 0.001). Three PDCs showed a high degree of association between grafted tumor cells and host blood vessels, suggesting a perivascular invasion phenotype. In vivo evaluation of the drug marizomib, currently in clinical trials for GBM, showed an effect on fish survival corresponding to PDC in vitro and in vivo marizomib sensitivity.

CONCLUSIONS

Zebrafish xenografts of GBM, monitored by AI methods in an automated process, present a scalable alternative to mouse xenograft models for the study of glioblastoma tumor initiation, growth, and invasion, applicable to patient-specific drug evaluation.

Glioblastoma Stem Cells-Useful Tools in the Battle against Cancer

Glioblastoma stem cells (GSCs) are cells with a self-renewal ability and capacity to initiate tumors upon serial transplantation that have been linked to tumor cell heterogeneity. Most standard treatments fail to completely eradicate GSCs, causing the recurrence of the disease. GSCs could represent one reason for the low efficacy of cancer therapy and for the short relapse time. Nonetheless, experimental data suggest that the presence of therapy-resistant GSCs could explain tumor recurrence. Therefore, to effectively target GSCs, a comprehensive understanding of their biology and the survival and developing mechanisms during treatment is mandatory. This review provides an overview of the molecular features, microenvironment, detection, and targeting strategies of GSCs, an essential information required for an efficient therapy. Despite the outstanding results in oncology, researchers are still developing novel strategies, of which one could be targeting the GSCs present in the hypoxic regions and invasive edge of the glioblastoma.

White Matter Tracts and Diffuse Lower-Grade Gliomas: The Pivotal Role of Myelin Plasticity in the Tumor Pathogenesis, Infiltration Patterns, Functional Consequences and Therapeutic Management

For many decades, interactions between diffuse lower-grade glioma (LGG) and brain connectome were neglected. However, the neoplasm progression is intimately linked to its environment, especially the white matter (WM) tracts and their myelin status. First, while the etiopathogenesis of LGG is unclear, this tumor seems to appear during the adolescence, and it is mostly located within anterior and associative cerebral areas. Because these structures correspond to those which were myelinated later in the brain maturation process, WM myelination could play a role in the development of LGG. Second, WM fibers and the myelin characteristics also participate in LGG diffusion, since glioma cells migrate along the subcortical pathways, especially when exhibiting a demyelinated phenotype, which may result in a large invasion of the parenchyma. Third, such a migratory pattern can induce functional (neurological, cognitive and behavioral) disturbances, because myelinated WM tracts represent the main limitation of neuroplastic potential. These parameters are critical for tailoring an individualized therapeutic strategy, both (i) regarding the timing of active treatment(s) which must be proposed earlier, before a too wide glioma infiltration along the WM bundles, (ii) and regarding the anatomic extent of surgical resection and irradiation, which should take account of the subcortical connectivity. Therefore, the new science of connectomics must be integrated in LGG management, based upon an improved understanding of the interplay across glioma dissemination within WM and reactional neural networks reconfiguration, in order to optimize long-term oncological and functional outcomes. To this end, mechanisms of activity-dependent myelin plasticity should be better investigated.

Glioblastoma Microenvironment: From an Inviolable Defense to a Therapeutic Chance

Glioblastoma is an aggressive tumor and is associated with a dismal prognosis. The availability of few active treatments as well as the inexorable recurrence after surgery are important hallmarks of the disease. The biological behavior of glioblastoma tumor cells reveals a very complex pattern of genomic alterations and is partially responsible for the clinical aggressiveness of this tumor. It has been observed that glioblastoma cells can recruit, manipulate and use other cells including neurons, glial cells, immune cells, and endothelial/stromal cells. The final result of this process is a very tangled net of interactions promoting glioblastoma growth and progression. Nonetheless, recent data are suggesting that the microenvironment can also be a niche in which glioblastoma cells can differentiate into glial cells losing their tumoral phenotype. Here we summarize the known interactions between micro-environment and glioblastoma cells highlighting possible therapeutic implications.

Glioma invasion along white matter tracts: A dilemma for neurosurgeons

Invasive growth along white matter (WM) tracts is one of the most prominent clinicopathological features of glioma and is also an important reason for surgical treatment failure in glioma patients. A full understanding of relevant clinical features and mechanisms is of great significance for finding new therapeutic targets and developing new treatment regimens and strategies. Herein, we review the imaging and histological characteristics of glioma patients with WM tracts invasion and summarize the possible molecular mechanism. On this basis, we further discuss the correlation between glioma molecular typing, radiotherapy and tumor treating fields (TTFields) and the invasion of glioma along WM tracts.

Magnetic Nanoparticles Used in Oncology

Recently, magnetic nanoparticles (MNPs) have more and more often been used in experimental studies on cancer treatments, which have become one of the biggest challenges in medical research. The main goal of this research is to treat and to cure advanced or metastatic cancer with minimal side effects through nanotechnology. Drug delivery approaches take into account the fact that MNPs can be bonded to chemotherapeutical drugs, nucleic acids, synthetized antibodies or radionuclide substances. MNPs can be guided, and different treatment therapies can be applied, under the influence of an external magnetic field. This paper reviews the main MNPs’ synthesis methods, functionalization with different materials and highlight the applications in cancer therapy. In this review, we describe cancer cell monitorization based on different types of magnetic nanoparticles, chemotherapy, immunotherapy, magnetic hyperthermia, gene therapy and ferroptosis. Examples of applied treatments on murine models or humans are analyzed, and glioblastoma cancer therapy is detailed in the review. MNPs have an important contribution to diagnostics, investigation, and therapy in the so called theranostics domain. The main conclusion of this paper is that MNPs are very useful in different cancer therapies, with limited side effects, and they can increase the life expectancy of patients with cancer drug resistance.

Old Stars and New Players in the Brain Tumor Microenvironment

In recent years, the direct interaction between cancer cells and tumor microenvironment (TME) has emerged as a crucial regulator of tumor growth and a promising therapeutic target. The TME, including the surrounding peritumoral regions, is dynamically modified during tumor progression and in response to therapies. However, the mechanisms regulating the crosstalk between malignant and non-malignant cells are still poorly understood, especially in the case of glioma, an aggressive form of brain tumor. The presence of unique brain-resident cell types, namely neurons and glial cells, and an exceptionally immunosuppressive microenvironment pose additional important challenges to the development of effective treatments targeting the TME. In this review, we provide an overview on the direct and indirect interplay between glioma and neuronal and glial cells, introducing new players and mechanisms that still deserve further investigation. We will focus on the effects of neural activity and glial response in controlling glioma cell behavior and discuss the potential of exploiting these cellular interactions to develop new therapeutic approaches with the aim to preserve proper brain functionality.

Modulating cell differentiation in cancer models

Cancer has been traditionally viewed as a disease characterised by excessive and uncontrolled proliferation, leading to the development of cytotoxic therapies against highly proliferating malignant cells. However, tumours frequently relapse due to the presence of slow-cycling cancer stem cells eluding chemo and radiotherapy. Since these malignant stem cells are largely undifferentiated, inducing their lineage commitment has been proposed as a potential intervention strategy to deplete tumours from their most resistant components. Pro-differentiation approaches have thus far yielded clinical success in the reversion of acute promyelocytic leukaemia (APL), and new developments are fast widening their therapeutic applicability to solid carcinomas. Recent advances in cancer differentiation discussed here highlight the potential and outstanding challenges of differentiation-based approaches.