The spectrum of morphological findings in pediatric central nervous system MN1-fusion-positive neuroepithelial tumors.

PURPOSE: Central nervous system high-grade neuroepithelial tumor with MN1 alteration (CNS-HGNET-MN1) is a rare entity defined by its DNA methylation pattern and pathologically considered to be high-grade with mixed patterns, stromal hyalinization, and with astrocytic differentiation. Our aim was to present six pediatric cases to contribute to the characterization of this group of tumors. MATERIAL AND METHODS: Six female patients aged 4 to 12 years with CNS tumors with MN1 alteration identified using genome-wide methylation arrays and/or RT-PCR were included. Clinicopathological, morphological, immunohistochemical, and molecular findings were analyzed. RESULTS: Tumor location was the parietal lobe in four and the intramedullary spinal cord in two. Two were morphologically diagnosed as ependymomas, one as gliofibroma, one as a HGNET-MN1 altered and the other two were difficult to classify. All were well-defined tumors, with a cystic component in three. Only two tumors had extensive stromal hyalinization, three had pseudopapillary formations, and four had other patterns. Multinucleated, clear, and rhabdoid cells were present. Necrosis and histiocyte clusters were also observed. Proliferative index was >10 in four. GFAP, EMA, CK, and SYN were variable, while Olig2 staining was mostly positive. Four of six patients with supratentorial tumors and complete resections were alive and tumor free after 2 to 10 years of follow-up. The two cases with medullary involvement and incomplete resections were alive and undergoing treatment 2 years after surgery. CONCLUSION: Neuroepithelial-MN1 tumors are challenging and suspicion requires molecular confirmation. Our pediatric data contribute to the knowledge for accurate diagnosis. Although further studies with a larger number of cases should be conducted in order to draw more robust conclusions regarding clinico-pathological features, here we present valuable pediatric data to increase the knowledge that may lead to the accurate management of this group of tumors.

[Neurology and COVID-19: Case Series of Neurological Complications in 96 patients Admitted at a University Hospital]. / Neurología hospitalaria y COVID-19: serie de 96 pacientes evaluados en un hospital universitario.

BACKGROUND: There are multisystemic consequences secondary to SARS- CoV-2 infection. AIM: To characterize neurological complications in patients admitted due to SARS-CoV-2 infection. METHODS: Review of medical records of patients aged over 15 years with COVID-19 evaluated by the neurology team between April and August 2020 at a university hospital. Severity of the infection, referral reasons, neurological diagnoses and laboratory results were registered. The diagnoses were defined by consensus among the members of the hospital neurology group. Cerebrovascular and inflammatory diseases of the central and peripheral nervous system were defined as "probably associated" or "possibly associated" to COVID-19. RESULTS: Ninety-six patients had at least 1 new neu- rological complication. 74% were admitted due to pneumonia and 20% due to a neurological disease. The most common reasons for neurological referral were impaired consciousness (39%), focal neurological deficit (24%), headache (9%) and seizures (5%). The most relevant neurological diagnoses were delirium in 48 patients, stroke in 24, critical illness polyneuropathy and myopathy in 17, seizures in 14, brachial plexopathy in 3, compressive neuropathies in 5, encephalitis in 1, possible vasculitis in 1 and Guillain-Barré syndrome in 1. Stroke and epilepsy were associated with increased length of hospital stay, but without differences in mortality. CONCLUSIONS: The spectrum of neurological complications of COVID-19 is wide. There are clinical entities typical of critically ill patients and also diseases associated directly and indirectly with the SARS-CoV2 infection.

[Human papillomavirus testing in cervical cancer screening at a public health service of Santiago, Chile]. / Examen de detección de virus papiloma humano en el tamizaje de cáncer cervicouterino en un Servicio de Salud de Santiago, Chile.

BACKGROUND: Molecular techniques for human papillomavirus (HPV) detection have a good performance as screening tests and could be included in cervical cancer early detection programs. We conducted a population-based trial comparing HPV detection and Papanicolaou as primary screening tests, in a public health service in Santiago, Chile. AIM: To describe the experience of implementing this new molecular test and present the main results of the study. MATERIAL AND METHODS: Women aged 25 to 64 enrolled in three public health centers were invited to participate. In all women, samples were collected for Papanicolaou and HPV DNA testing, and naked-eye visual inspection of the cervix with acetic acid was performed. Women with any positive screening test were referred to the local area hospital for diagnostic confirmation with colposcopy and biopsy of suspicious lesions. RESULTS: Screening results were obtained for 8265 women, of whom 931 (11.3%) were positive to any test. The prevalence of cervical intraepithelial neoplasia grade 2 or worse (CIN2+) was 1.1%; nine women had invasive cervical cancer. Sensitivities for the detection of CIN2+ were 22.1% (95% confidence interval (CI) 16.4-29.2) for Papanicolaou and 92.7% (95% CI 84.4-96.8) for HPV testing; specificities were 98.9% (95% CI 98.7-99.0) and 92.0% (95% CI 91.4-92.6) respectively. CONCLUSION: This experience showed that the implementation of a molecular test for cervical cancer screening is not a major challenge in Chile: it was well accepted by both the health team and the participants, and it may improve the effectiveness of the screening program.

Enhanced CRAd activity using enhancer motifs driven by a nucleosome positioning sequence.

Cancer development involves changes driven by the epigenetic machinery, including nucleosome positioning. Recently, the concept that adenoviral replication may be driven by tumor specific promoters (TSPs) gained support, and several conditionally replicative adenoviruses (CRAd) exhibited therapeutic efficacy in clinical trials. Here, we show for the first time that placing a nucleosome positioning sequence (NPS) upstream of a TSP combined with Wnt-responsive motifs (pART enhancer) enhanced the TSP transcriptional activity and increased the lytic activity of a CRAd. pART enhanced the transcriptional activity of the gastrointestinal cancer (GIC)-specific REG1A promoter (REG1A-pr); moreover, pART also increased the in vitro lytic activity of a CRAd whose replication was driven by REG1A-Pr. The pART enhancer effect in vitro and in vivo was strictly dependent on the presence of the NPS. Indeed, deletion of the NPS was strongly deleterious for the in vivo antitumor efficacy of the CRAd on orthotopically established pancreatic xenografts. pART also enhanced the specific activity of other heterologous promoters; moreover, the NPS was also able to enhance the responsiveness of hypoxia- and NFκB-response elements. We conclude that NPS could be useful for gene therapy approaches in cancer as well as other diseases.

Deep Learning-Based Glucose Prediction Models: A Guide for Practitioners and a Curated Dataset for Improved Diabetes Management.

Accurate short- and mid-term blood glucose predictions are crucial for patients with diabetes struggling to maintain healthy glucose levels, as well as for individuals at risk of developing the disease. Consequently, numerous efforts from the scientific community have focused on developing predictive models for glucose levels. This study harnesses physiological data collected from wearable sensors to construct a series of data-driven models based on deep learning approaches. We systematically compare these models to offer insights for practitioners and researchers venturing into glucose prediction using deep learning techniques. Key questions addressed in this work encompass the comparison of various deep learning architectures for this task, determining the optimal set of input variables for accurate glucose prediction, comparing population-wide, fine-tuned, and personalized models, and assessing the impact of an individual's data volume on model performance. Additionally, as part of our outcomes, we introduce a meticulously curated dataset inclusive of data from both healthy individuals and those with diabetes, recorded in free-living conditions. This dataset aims to foster research in this domain and facilitate equitable comparisons among researchers.

Exploiting the therapeutic vulnerability of IDH-mutant gliomas with zotiraciclib.

Isocitrate dehydrogenase (IDH)-mutant gliomas have distinctive metabolic and biological traits that may render them susceptible to targeted treatments. Here, by conducting a high-throughput drug screen, we pinpointed a specific susceptibility of IDH-mutant gliomas to zotiraciclib (ZTR). ZTR exhibited selective growth inhibition across multiple IDH-mutant glioma in vitro and in vivo models. Mechanistically, ZTR at low doses suppressed CDK9 and RNA Pol II phosphorylation in IDH-mutant cells, disrupting mitochondrial function and NAD+ production, causing oxidative stress. Integrated biochemical profiling of ZTR kinase targets and transcriptomics unveiled that ZTR-induced bioenergetic failure was linked to the suppression of PIM kinase activity. We posit that the combination of mitochondrial dysfunction and an inability to adapt to oxidative stress resulted in significant cell death upon ZTR treatment, ultimately increasing the therapeutic vulnerability of IDH-mutant gliomas. These findings prompted a clinical trial evaluating ZTR in IDH-mutant gliomas towards precision medicine ( NCT05588141 ). Highlights: Zotiraciclib (ZTR), a CDK9 inhibitor, hinders IDH-mutant glioma growth in vitro and in vivo . ZTR halts cell cycle, disrupts respiration, and induces oxidative stress in IDH-mutant cells.ZTR unexpectedly inhibits PIM kinases, impacting mitochondria and causing bioenergetic failure.These findings led to the clinical trial NCT05588141, evaluating ZTR for IDH-mutant gliomas.

Epigenetic Reprogramming of Autophagy Drives Mutant IDH1 Glioma Progression and Response to Radiation.

Mutant isocitrate dehydrogenase 1 (mIDH1; IDH1 R132H ) exhibits a gain of function mutation enabling 2-hydroxyglutarate (2HG) production. 2HG inhibits DNA and histone demethylases, inducing epigenetic reprogramming and corresponding changes to the transcriptome. We previously demonstrated 2HG-mediated epigenetic reprogramming enhances DNA-damage response and confers radioresistance in mIDH1 gliomas harboring p53 and ATRX loss of function mutations. In this study, RNA-seq and ChIP-seq data revealed human and mouse mIDH1 glioma neurospheres have downregulated gene ontologies related to mitochondrial metabolism and upregulated autophagy. Further analysis revealed that the decreased mitochondrial metabolism was paralleled by a decrease in glycolysis, rendering autophagy as a source of energy in mIDH1 glioma cells. Analysis of autophagy pathways showed that mIDH1 glioma cells exhibited increased expression of pULK1-S555 and enhanced LC3 I/II conversion, indicating augmented autophagy activity. This dependence is reflected by increased sensitivity of mIDH1 glioma cells to autophagy inhibition. Blocking autophagy selectively impairs the growth of cultured mIDH1 glioma cells but not wild-type IDH1 (wtIDH1) glioma cells. Targeting autophagy by systemic administration of synthetic protein nanoparticles packaged with siRNA targeting Atg7 (SPNP-siRNA-Atg7) sensitized mIDH1 glioma cells to radiation-induced cell death, resulting in tumor regression, long-term survival, and immunological memory, when used in combination with IR. Our results indicate autophagy as a critical pathway for survival and maintenance of mIDH1 glioma cells, a strategy that has significant potential for future clinical translation. One Sentence Summary: The inhibition of autophagy sensitizes mIDH1 glioma cells to radiation, thus creating a promising therapeutic strategy for mIDH1 glioma patients. Graphical abstract: Our genetically engineered mIDH1 mouse glioma model harbors IDH1 R132H in the context of ATRX and TP53 knockdown. The production of 2-HG elicited an epigenetic reprogramming associated with a disruption in mitochondrial activity and an enhancement of autophagy in mIDH1 glioma cells. Autophagy is a mechanism involved in cell homeostasis related with cell survival under energetic stress and DNA damage protection. Autophagy has been associated with radio resistance. The inhibition of autophagy thus radio sensitizes mIDH1 glioma cells and enhances survival of mIDH1 glioma-bearing mice, representing a novel therapeutic target for this glioma subtype with potential applicability in combined clinical strategies.

Screening trial of human papillomavirus for early detection of cervical cancer in Santiago, Chile.

Cervical cancer mortality in Chile is four times higher than in developed countries. We compared the accuracy of human papillomavirus (HPV) DNA testing and conventional Papanicolaou (Pap) testing to detect prevalent precancerous and cancerous lesions in the routine clinical practice of the public health system. Women aged 25 years and older residing in the area covered by three primary care centers of Santiago, Chile, were invited to participate. Eligible women received both HPV DNA (Hybrid Capture 2) and Pap testing. Women positive by either test (Pap: ASCUS+, HC2: RLU/CO ≥ 1.0) underwent colposcopy and biopsy, as did a sample of double-negative women with an abnormal cervix at visual inspection or with risk factors for cervical lesions. Crude and verification bias-corrected sensitivities and specificities were estimated. In total, 8,265 women (98.8% of eligible) had complete screening results. Of these, 10.7% were HPV positive, 1.7% were Pap positive and 1.1% were positive by both tests. In all, 931 (11.3%) women were screen-positive, of whom 94.3% attended colposcopy. Additionally, 295 control women were invited for colposcopy, of whom 78% attended. In all, 42 CIN2, 45 CIN3 and 9 cancers were identified. Verification bias-corrected sensitivity for CIN2+ (95% confidence interval) was 92.7% (84.4-96.8) for HPV and 22.1% (16.4-29.2) for Pap; corresponding specificities were 92.0% (91.4-92.6) and 98.9% (98.7-99.0). In conclusion, in routine clinical practice in a developing country, HPV testing was four times more sensitive for CIN2+ than Pap testing, identifying three times more CIN2+ lesions; HPV testing was easily implemented in our established cervical cancer prevention program.

Statistical analysis of the pulse-coupled synchronization strategy for wireless sensor networks.

Pulse-coupled synchronization is attracting increased attention in the sensor network community. Yet its properties have not been fully investigated. Using statistical analysis, we prove analytically that by controlling the number of connections at each node, synchronization can be guaranteed for generally pulse-coupled oscillators even in the presence of a refractory period. The approach does not require the initial phases to reside in half an oscillation cycle, which improves existing results. We also find that a refractory period can be strategically included to reduce idle listening at nearly no sacrifice to the synchronization probability. Given that reduced idle listening leads to higher energy efficiency in the synchronization process, the strategically added refractory period makes the synchronization scheme appealing to cheap sensor nodes, where energy is a precious system resource. We also analyzed the pulse-coupled synchronization in the presence of unreliable communication links and obtained similar results. QualNet experimental results are given to confirm the effectiveness of the theoretical predictions.

A Probabilistic Approach to Blood Glucose Prediction in Type 1 Diabetes Under Meal Uncertainties.

Currently, most reliable and commercialized artificial pancreas systems for type 1 diabetes are hybrid closed-loop systems, which require the user to announce every meal and its size. However, estimating the amount of carbohydrates in a meal and announcing each and every meal is an error-prone process that introduces important uncertainties to the problem, which when not considered, lead to sub-optimal outcomes of the controller. To address this problem, we propose a novel deep-learning-based model for probabilistic glucose prediction, called the Input and State Recurrent Kalman Network (ISRKN), which consists in the incorporation of an input and state Kalman filter in the latent space of a deep neural network so that the posterior distributions can be computed in closed form and the uncertainty can be propagated using the Kalman equations. In addition, the proposed architecture allows explicit estimation of the meal uncertainty distribution, whose parameters are encoded in the filter parameters. Results using the UVA/Padova simulator and data from a clinical trial show that the proposed model outperforms other probabilistic models using several probabilistic metrics across different degrees of distributional shifts.

Impact of epigenetic reprogramming on antitumor immune responses in glioma.

Epigenetic remodeling is a molecular hallmark of gliomas, and it has been identified as a key mediator of glioma progression. Epigenetic dysregulation contributes to gliomagenesis, tumor progression, and responses to immunotherapies, as well as determining clinical features. This epigenetic remodeling includes changes in histone modifications, chromatin structure, and DNA methylation, all of which are driven by mutations in genes such as histone 3 genes (H3C1 and H3F3A), isocitrate dehydrogenase 1/2 (IDH1/2), α-thalassemia/mental retardation, X-linked (ATRX), and additional chromatin remodelers. Although much of the initial research primarily identified how the epigenetic aberrations impacted glioma progression by solely examining the glioma cells, recent studies have aimed at establishing the role of epigenetic alterations in shaping the tumor microenvironment (TME). In this review, we discuss the mechanisms by which these epigenetic phenomena in glioma remodel the TME and how current therapies targeting epigenetic dysregulation affect the glioma immune response and therapeutic outcomes. Understanding the link between epigenetic remodeling and the glioma TME provides insights into the implementation of epigenetic-targeting therapies to improve the antitumor immune response.

H3.3-G34R Mutation-Mediated Epigenetic Reprogramming Leads to Enhanced Efficacy of Immune Stimulatory Gene Therapy in Pediatric High-Grade Gliomas.

Pediatric high-grade gliomas (pHGGs) are diffuse and highly aggressive CNS tumors which remain incurable, with a 5-year overall survival of less than 20%. Within glioma, mutations in the genes encoding the histones H3.1 and H3.3 have been discovered to be age-restricted and specific of pHGGs. This work focuses on the study of pHGGs harboring the H3.3-G34R mutation. H3.3-G34R tumors represent the 9-15% of pHGGs, are restricted to the cerebral hemispheres, and are found predominantly in the adolescent population (median 15.0 years). We have utilized a genetically engineered immunocompetent mouse model for this subtype of pHGG generated via the Sleeping Beauty-transposon system. The analysis of H3.3-G34R genetically engineered brain tumors by RNA-Sequencing and ChIP-Sequencing revealed alterations in the molecular landscape associated to H3.3-G34R expression. In particular, the expression of H3.3-G34R modifies the histone marks deposited at the regulatory elements of genes belonging to the JAK/STAT pathway, leading to an increased activation of this pathway. This histone G34R-mediated epigenetic modifications lead to changes in the tumor immune microenvironment of these tumors, towards an immune-permissive phenotype, making these gliomas susceptible to TK/Flt3L immune-stimulatory gene therapy. The application of this therapeutic approach increased median survival of H3.3-G34R tumor bearing animals, while stimulating the development of anti-tumor immune response and immunological memory. Our data suggests that the proposed immune-mediated gene therapy has potential for clinical translation for the treatment of patients harboring H3.3-G34R high grade gliomas.

Zinc Finger MYND-Type Containing 8 (ZMYND8) Is Epigenetically Regulated in Mutant Isocitrate Dehydrogenase 1 (IDH1) Glioma to Promote Radioresistance.

PURPOSE: Mutant isocitrate dehydrogenase 1 (mIDH1) alters the epigenetic regulation of chromatin, leading to a hypermethylation phenotype in adult glioma. This work focuses on identifying gene targets epigenetically dysregulated by mIDH1 to confer therapeutic resistance to ionizing radiation (IR). EXPERIMENTAL DESIGN: We evaluated changes in the transcriptome and epigenome in a radioresistant mIDH1 patient-derived glioma cell culture (GCC) following treatment with an mIDH1-specific inhibitor, AGI-5198. We identified Zinc Finger MYND-Type Containing 8 (ZMYND8) as a potential target of mIDH1 reprogramming. We suppressed ZMYND8 expression by shRNA knockdown and genetic knockout (KO) in mIDH1 glioma cells and then assessed cellular viability to IR. We assessed the sensitivity of mIDH1 GCCS to pharmacologic inhibition of ZMYND8-interacting partners: HDAC, BRD4, and PARP. RESULTS: Inhibition of mIDH1 leads to an upregulation of gene networks involved in replication stress. We found that the expression of ZMYND8, a regulator of DNA damage response, was decreased in three patient-derived mIDH1 GCCs after treatment with AGI-5198. Knockdown of ZMYND8 expression sensitized mIDH1 GCCs to radiotherapy marked by decreased cellular viability. Following IR, mIDH1 glioma cells with ZMYND8 KO exhibit significant phosphorylation of ATM and sustained γH2AX activation. ZMYND8 KO mIDH1 GCCs were further responsive to IR when treated with either BRD4 or HDAC inhibitors. PARP inhibition further enhanced the efficacy of radiotherapy in ZMYND8 KO mIDH1 glioma cells. CONCLUSIONS: These findings indicate the impact of ZMYND8 in the maintenance of genomic integrity and repair of IR-induced DNA damage in mIDH1 glioma. See related commentary by Sachdev et al., p. 1648.

Energy-efficient pulse-coupled synchronization strategy design for wireless sensor networks through reduced idle listening.

Synchronization is crucial to wireless sensor networks due to their decentralized structure. We propose an energy-efficient pulse-coupled synchronization strategy to achieve this goal. The basic idea is to reduce idle listening by intentionally introducing a large refractory period in the sensors' cooperation. The large refractory period greatly reduces idle listening in each oscillation period, and is analytically proven to have no influence on the time to synchronization. Hence, it significantly reduces the total energy consumption in a synchronization process. A topology control approach tailored for pulse-coupled synchronization is given to guarantee a k-edge strongly connected interaction topology, which is tolerant to communication-link failures. The topology control approach is totally decentralized and needs no information exchange among sensors, and it is applicable to dynamic network topologies as well. This facilitates a completely decentralized implementation of the synchronization strategy. The strategy is applicable to mobile sensor networks, too. QualNet case studies confirm the effectiveness of the synchronization strategy.

Increasing sync rate of pulse-coupled oscillators via phase response function design: theory and application to wireless networks.

This paper addresses the synchronization rate of weakly connected pulse-coupled oscillators (PCOs). We prove that besides coupling strength, the phase response function is also a determinant of synchronization rate. Inspired by the result, we propose to increase the synchronization rate of PCOs by designing the phase response function. This has important significance in PCO-based clock synchronization of wireless networks. By designing the phase response function, synchronization rate is increased even under a fixed transmission power. Given that energy consumption in synchronization is determined by the product of synchronization time and transformation power, the new strategy reduces energy consumption in clock synchronization. QualNet experiments confirm the theoretical results.

H3.3-G34 mutations impair DNA repair and promote cGAS/STING-mediated immune responses in pediatric high-grade glioma models.

Pediatric high-grade gliomas (pHGGs) are the leading cause of cancer-related deaths in children in the USA. Sixteen percent of hemispheric pediatric and young adult HGGs encode Gly34Arg/Val substitutions in the histone H3.3 (H3.3-G34R/V). The mechanisms by which H3.3-G34R/V drive malignancy and therapeutic resistance in pHGGs remain unknown. Using a syngeneic, genetically engineered mouse model (GEMM) and human pHGG cells encoding H3.3-G34R, we demonstrate that this mutation led to the downregulation of DNA repair pathways. This resulted in enhanced susceptibility to DNA damage and inhibition of the DNA damage response (DDR). We demonstrate that genetic instability resulting from improper DNA repair in G34R-mutant pHGG led to the accumulation of extrachromosomal DNA, which activated the cyclic GMP-AMP synthase/stimulator of IFN genes (cGAS/STING) pathway, inducing the release of immune-stimulatory cytokines. We treated H3.3-G34R pHGG-bearing mice with a combination of radiotherapy (RT) and DNA damage response inhibitors (DDRi) (i.e., the blood-brain barrier-permeable PARP inhibitor pamiparib and the cell-cycle checkpoint CHK1/2 inhibitor AZD7762), and these combinations resulted in long-term survival for approximately 50% of the mice. Moreover, the addition of a STING agonist (diABZl) enhanced the therapeutic efficacy of these treatments. Long-term survivors developed immunological memory, preventing pHGG growth upon rechallenge. These results demonstrate that DDRi and STING agonists in combination with RT induced immune-mediated therapeutic efficacy in G34-mutant pHGG.

Circadian Phase Prediction From Non-Intrusive and Ambulatory Physiological Data.

Chronotherapy aims to treat patients according to their endogenous biological rhythms and requires, therefore, knowing their circadian phase. Circadian phase is partially determined by genetics and, under natural conditions, is normally entrained by environmental signals (zeitgebers), predominantly by light. Physiological data such as melatonin concentration and core body temperature (CBT) have been used to estimate circadian phase. However, due to their expensive and intrusive obtention, other physiological variables that also present circadian rhythmicity, such as heart rate variability, skin temperature, activity, and body position, have recently been proposed in several studies to estimate circadian phase. This study aims to predict circadian phase using minimally intrusive ambulatory physiological data modeled with machine learning techniques. Two approaches were considered; first, time-series were used to train artificial neural networks (ANNs) that predict CBT and melatonin dynamics and, second, a novel approach that uses scalar variables to build regression models that predict the time of the minimum CBT and the dim light melatonin onset (DLMO). ANNs require less than 48 hours of minimally intrusive data collection to predict circadian phase with an accuracy of less than one hour. On the other hand, regression models that use only three variables (body mass index, activity, and heart rate) are simpler and show higher accuracy with less than one minute of error, although they require longer times of data collection. This is a promising approach that should be validated in further studies considering a broader population and a wider range of conditions, including circadian misalignment.

Uncovering Spatiotemporal Heterogeneity of High-Grade Gliomas: From Disease Biology to Therapeutic Implications.

Glioblastomas (GBM) are the most common and aggressive tumors of the central nervous system. Rapid tumor growth and diffuse infiltration into healthy brain tissue, along with high intratumoral heterogeneity, challenge therapeutic efficacy and prognosis. A better understanding of spatiotemporal tumor heterogeneity at the histological, cellular, molecular, and dynamic levels would accelerate the development of novel treatments for this devastating brain cancer. Histologically, GBM is characterized by nuclear atypia, cellular pleomorphism, necrosis, microvascular proliferation, and pseudopalisades. At the cellular level, the glioma microenvironment comprises a heterogeneous landscape of cell populations, including tumor cells, non-transformed/reactive glial and neural cells, immune cells, mesenchymal cells, and stem cells, which support tumor growth and invasion through complex network crosstalk. Genomic and transcriptomic analyses of gliomas have revealed significant inter and intratumoral heterogeneity and insights into their molecular pathogenesis. Moreover, recent evidence suggests that diverse dynamics of collective motion patterns exist in glioma tumors, which correlate with histological features. We hypothesize that glioma heterogeneity is not stochastic, but rather arises from organized and dynamic attributes, which favor glioma malignancy and influences treatment regimens. This review highlights the importance of an integrative approach of glioma histopathological features, single-cell and spatially resolved transcriptomic and cellular dynamics to understand tumor heterogeneity and maximize therapeutic effects.

Current Approaches for Glioma Gene Therapy and Virotherapy.

Glioblastoma (GBM) is the most common and aggressive primary brain tumor in the adult population and it carries a dismal prognosis. Inefficient drug delivery across the blood brain barrier (BBB), an immunosuppressive tumor microenvironment (TME) and development of drug resistance are key barriers to successful glioma treatment. Since gliomas occur through sequential acquisition of genetic alterations, gene therapy, which enables to modification of the genetic make-up of target cells, appears to be a promising approach to overcome the obstacles encountered by current therapeutic strategies. Gene therapy is a rapidly evolving field with the ultimate goal of achieving specific delivery of therapeutic molecules using either viral or non-viral delivery vehicles. Gene therapy can also be used to enhance immune responses to tumor antigens, reprogram the TME aiming at blocking glioma-mediated immunosuppression and normalize angiogenesis. Nano-particles-mediated gene therapy is currently being developed to overcome the BBB for glioma treatment. Another approach to enhance the anti-glioma efficacy is the implementation of viro-immunotherapy using oncolytic viruses, which are immunogenic. Oncolytic viruses kill tumor cells due to cancer cell-specific viral replication, and can also initiate an anti-tumor immunity. However, concerns still remain related to off target effects, and therapeutic and transduction efficiency. In this review, we describe the rationale and strategies as well as advantages and disadvantages of current gene therapy approaches against gliomas in clinical and preclinical studies. This includes different delivery systems comprising of viral, and non-viral delivery platforms along with suicide/prodrug, oncolytic, cytokine, and tumor suppressor-mediated gene therapy approaches. In addition, advances in glioma treatment through BBB-disruptive gene therapy and anti-EGFRvIII/VEGFR gene therapy are also discussed. Finally, we discuss the results of gene therapy-mediated human clinical trials for gliomas. In summary, we highlight the progress, prospects and remaining challenges of gene therapies aiming at broadening our understanding and highlighting the therapeutic arsenal for GBM.

Genetic Alterations in Gliomas Remodel the Tumor Immune Microenvironment and Impact Immune-Mediated Therapies.

High grade gliomas are malignant brain tumors that arise in the central nervous system, in patients of all ages. Currently, the standard of care, entailing surgery and chemo radiation, exhibits a survival rate of 14-17 months. Thus, there is an urgent need to develop new therapeutic strategies for these malignant brain tumors. Currently, immunotherapies represent an appealing approach to treat malignant gliomas, as the pre-clinical data has been encouraging. However, the translation of the discoveries from the bench to the bedside has not been as successful as with other types of cancer, and no long-lasting clinical benefits have been observed for glioma patients treated with immune-mediated therapies so far. This review aims to discuss our current knowledge about gliomas, their molecular particularities and the impact on the tumor immune microenvironment. Also, we discuss several murine models used to study these therapies pre-clinically and how the model selection can impact the outcomes of the approaches to be tested. Finally, we present different immunotherapy strategies being employed in clinical trials for glioma and the newest developments intended to harness the immune system against these incurable brain tumors.