Brain network topology and its cognitive impact in adult glioma survivors.

Structural brain network topology can be altered in case of a brain tumor, due to both the tumor itself and its treatment. In this study, we explored the role of structural whole-brain and nodal network metrics and their association with cognitive functioning. Fifty WHO grade 2-3 adult glioma survivors (> 1-year post-therapy) and 50 matched healthy controls underwent a cognitive assessment, covering six cognitive domains. Raw cognitive assessment scores were transformed into w-scores, corrected for age and education. Furthermore, based on multi-shell diffusion-weighted MRI, whole-brain tractography was performed to create weighted graphs and to estimate whole-brain and nodal graph metrics. Hubs were defined based on nodal strength, betweenness centrality, clustering coefficient and shortest path length in healthy controls. Significant differences in these metrics between patients and controls were tested for the hub nodes (i.e. n = 12) and non-hub nodes (i.e. n = 30) in two mixed-design ANOVAs. Group differences in whole-brain graph measures were explored using Mann-Whitney U tests. Graph metrics that significantly differed were ultimately correlated with the cognitive domain-specific w-scores. Bonferroni correction was applied to correct for multiple testing. In survivors, the bilateral putamen were significantly less frequently observed as a hub (pbonf < 0.001). These nodes' assortativity values were positively correlated with attention (r(90) > 0.573, pbonf < 0.001), and proxy IQ (r(90) > 0.794, pbonf < 0.001). Attention and proxy IQ were significantly more often correlated with assortativity of hubs compared to non-hubs (pbonf < 0.001). Finally, the whole-brain graph measures of clustering coefficient (r = 0.685), global (r = 0.570) and local efficiency (r = 0.500) only correlated with proxy IQ (pbonf < 0.001). This study demonstrated potential reorganization of hubs in glioma survivors. Assortativity of these hubs was specifically associated with cognitive functioning, which could be important to consider in future modeling of cognitive outcomes and risk classification in glioma survivors.

Growth inhibition of subcutaneous tumor with glioma cells in nude mice by silencing TLR4.

This study investigated the regulatory impact of Toll-like receptor 4 (TLR4) gene on glioma cell proliferation and apoptosis, elucidating the molecular mechanisms underlying TLR4-induced growth inhibition in vivo. U-87MG-Sh and U-87MG-NC cells, with silenced TLR4 and negative control plasmid respectively, were established. Eighteen nude mice, divided into transfection, negative control, and blank control groups, were inoculated with corresponding cells. Over four weeks, the transfection group exhibited significantly reduced tumor growth rates, smaller mass and volume, and lower growth activity compared to controls. Histological analysis revealed sparse tumor cells, increased fibrous connective tissue, and slower angiogenesis in the transfection group. Flow cytometry demonstrated a lower proliferation index and increased G0/1 cell count in the transfection group. mRNA levels of TLR4, NF-κB, and CyclinD1 were significantly lower in the transfection group. TLR4 silencing correlated with U-87MG cell proliferation regulation, growth inhibition, NF-κB and CyclinD1 modulation, and induction of cell cycle arrest and apoptosis. These findings suggest TLR4 as a potential gene therapy target for glioma.

Regulation and molecular mechanism of adiponectin on the proliferation, apoptosis, autophagy, and chemosensitivity of LN18 Glioma cell line.

This study aimed to explore the regulatory effects and associated mechanisms of adiponectin on apoptosis and proliferation in the LN18 glioma cell line through the AMPK and Akt signaling pathways. Additionally, we sought to elucidate the impact of adiponectin on the chemosensitivity of the LN18 glioma cell line to temozolomide (TMZ). The proliferation rate of glioma cells treated with adiponectin was assessed using the cholecystokinin (CCK8) assay. The Western blot analysis was employed to assess the expression of p-Akt, p-AMPK, p-mTOR, cleaved caspase3, Bax, Cyclin D1, and Cyclin B1 following adiponectin treatment. Cell apoptosis was quantified using AnnexinV/PI flow cytometry, while changes in the cell cycle were detected using PI staining flow cytometry. The findings revealed that adiponectin upregulates p-AMPK expression and downregulates p-mTOR expression in the PTEN wild-type glioma cell line LN18, with no discernible effect on p-Akt expression. Moreover, adiponectin inhibits the proliferation rate of the PTEN wild-type glioma cell line LN18, enhances the expression of cleaved caspase3 and Bax, and significantly elevates the apoptosis rate, as evidenced by AnnexinV/PI flow cytometry. Adiponectin was observed to suppress the expression of Cyclin D1 and Cyclin B1, increase the number of cells in the G1 phase, and promote autophagy. Additionally, adiponectin augments the expression of Beclin1 and the ratio of LC3II/I in the PTEN wild-type glioma cell line LN18, while decreasing p62 expression. In conclusion, this study posits that adiponectin holds therapeutic promise for glioma treatment. Furthermore, adiponectin enhances the inhibitory effect of TMZ on the proliferation rate of LN18 cells when treated with 0.1 mM and 1 mM TMZ. These results collectively suggest that adiponectin impedes proliferation, encourages apoptosis and autophagy in the LN18 glioma cell line, and heightens its sensitivity to the chemotherapeutic drug TMZ.

Factors affecting the extent of resection and neurological outcomes following transopercular resection of insular gliomas.

BACKGROUND: Surgical resection of insular gliomas is a challenge. TO resection is considered more versatile and has lower risk of vascular damage. In this study, we aimed to understand the factors that affect resection rates, ischemic changes and neurological outcomes and studied the utility of IONM in patients who underwent TO resection for IGs. METHODS: Retrospective analysis of 66 patients with IG who underwent TO resection was performed. RESULTS: Radical resection was possible in 39% patients. Involvement of zone II and the absence of contrast enhancement predicted lower resection rate. Persistent deficit rate was 10.9%. Although dominant lobe tumors increased immediate deficit and fronto-orbital operculum involvement reduced prolonged deficit rate, no tumor related factor showed significant association with persistent deficits. 45% of patients developed a postoperative infarct, 53% of whom developed deficits. Most affected vascular territory was lenticulostriate (39%). MEP changes were observed in 9/57 patients. 67% of stable TcMEPs and 74.5% of stable strip MEPs did not develop any postoperative motor deficits. Long-term deficits were seen in 3 and 6% patients with stable TcMEP and strip MEPs respectively. In contrast, 25% and 50% of patients with reversible strip MEP and Tc MEP changes respectively had persistent motor deficits. DWI changes were clinically more relevant when accompanied by MEP changes intraoperatively, with persistent deficit rates three times greater when MEP changes occurred than when MEPs were stable. CONCLUSION: Radical resection can be achieved in large, multizone IGs, with reasonable outcomes using TO approach and multimodal intraoperative strategy with IONM.

Mitochondrial RNA modification-based signature to predict prognosis of lower grade glioma: a multi-omics exploration and verification study.

Mitochondrial RNA modification (MRM) plays a crucial role in regulating the expression of key mitochondrial genes and promoting tumor metastasis. Despite its significance, comprehensive studies on MRM in lower grade gliomas (LGGs) remain unknown. Single-cell RNA-seq data (GSE89567) was used to evaluate the distribution functional status, and correlation of MRM-related genes in different cell types of LGG microenvironment. We developed an MRM scoring system by selecting potential MRM-related genes using LASSO regression analysis and the Random Survival Forest algorithm, based on multiple bulk RNA-seq datasets from TCGA, CGGA, GSE16011, and E-MTAB-3892. Analysis was performed on prognostic and immunological features, signaling pathways, metabolism, somatic mutations and copy number variations (CNVs), treatment responses, and forecasting of potential small-molecule agents. A total of 35 MRM-related genes were selected from the literature. Differential expression analysis of 1120 normal brain tissues and 529 LGGs revealed that 22 and 10 genes were upregulated and downregulated, respectively. Most genes were associated with prognosis of LGG. METLL8, METLL2A, TRMT112, and METTL2B were extensively expressed in all cell types and different cell cycle of each cell type. Almost all cell types had clusters related to mitochondrial RNA processing, ribosome biogenesis, or oxidative phosphorylation. Cell-cell communication and Pearson correlation analyses indicated that MRM may promoting the development of microenvironment beneficial to malignant progression via modulating NCMA signaling pathway and ICP expression. A total of 11 and 9 MRM-related genes were observed by LASSO and the RSF algorithm, respectively, and finally 6 MRM-related genes were used to establish MRM scoring system (TRMT2B, TRMT11, METTL6, METTL8, TRMT6, and TRUB2). The six MRM-related genes were then validated by qPCR in glioma and normal tissues. MRM score can predict the malignant clinical characteristics, abundance of immune infiltration, gene variation, clinical outcome, the enrichment of signaling pathways and metabolism. In vitro experiments demonstrated that silencing METTL8 significantly curbs glioma cell proliferation and enhances apoptosis. Patients with a high MRM score showed a better response to immunotherapies and small-molecule agents such as arachidonyl trifluoromethyl ketone, MS.275, AH.6809, tacrolimus, and TTNPB. These novel insights into the biological impacts of MRM within the glioma microenvironment underscore its potential as a target for developing precise therapies, including immunotherapeutic approaches.

Breaking new ground: can artificial intelligence and machine learning transform papillary glioneuronal tumor diagnosis?

Papillary glioneuronal tumors (PGNTs), classified as Grade I by the WHO in 2016, present diagnostic challenges due to their rarity and potential for malignancy. Xiaodan Du et al.'s recent study of 36 confirmed PGNT cases provides critical insights into their imaging characteristics, revealing frequent presentation with headaches, seizures, and mass effect symptoms, predominantly located in the supratentorial region near the lateral ventricles. Lesions often appeared as mixed cystic and solid masses with septations or as cystic masses with mural nodules. Given these complexities, artificial intelligence (AI) and machine learning (ML) offer promising advancements for PGNT diagnosis. Previous studies have demonstrated AI's efficacy in diagnosing various brain tumors, utilizing deep learning and advanced imaging techniques for rapid and accurate identification. Implementing AI in PGNT diagnosis involves assembling comprehensive datasets, preprocessing data, extracting relevant features, and iteratively training models for optimal performance. Despite AI's potential, medical professionals must validate AI predictions, ensuring they complement rather than replace clinical expertise. This integration of AI and ML into PGNT diagnostics could significantly enhance preoperative accuracy, ultimately improving patient outcomes through more precise and timely interventions.

Ultrasound-mediated delivery of doxorubicin to the brain results in immune modulation and improved responses to PD-1 blockade in gliomas.

Given the marginal penetration of most drugs across the blood-brain barrier, the efficacy of various agents remains limited for glioblastoma (GBM). Here we employ low-intensity pulsed ultrasound (LIPU) and intravenously administered microbubbles (MB) to open the blood-brain barrier and increase the concentration of liposomal doxorubicin and PD-1 blocking antibodies (aPD-1). We report results on a cohort of 4 GBM patients and preclinical models treated with this approach. LIPU/MB increases the concentration of doxorubicin by 2-fold and 3.9-fold in the human and murine brains two days after sonication, respectively. Similarly, LIPU/MB-mediated blood-brain barrier disruption leads to a 6-fold and a 2-fold increase in aPD-1 concentrations in murine brains and peritumoral brain regions from GBM patients treated with pembrolizumab, respectively. Doxorubicin and aPD-1 delivered with LIPU/MB upregulate major histocompatibility complex (MHC) class I and II in tumor cells. Increased brain concentrations of doxorubicin achieved by LIPU/MB elicit IFN-γ and MHC class I expression in microglia and macrophages. Doxorubicin and aPD-1 delivered with LIPU/MB results in the long-term survival of most glioma-bearing mice, which rely on myeloid cells and lymphocytes for their efficacy. Overall, this translational study supports the utility of LIPU/MB to potentiate the antitumoral activities of doxorubicin and aPD-1 for GBM.

Serum beta2-microglobulin acts as a biomarker for severity and prognosis in glioma patients: a preliminary clinical study.

BACKGROUND: Gliomas are the deadliest malignant tumors of the adult central nervous system. We previously discovered that beta2-microglobulin (B2M) is abnormally upregulated in glioma tissues and that it exerts a range of oncogenic effects. Besides its tissue presence, serum B2M levels serve as biomarkers for various diseases. This study aimed to explore whether serum B2M levels can be used in the diagnosis and prognosis of gliomas. METHODS: Medical records from 246 glioma patients were retrospectively analyzed. The relationship between preoperative serum B2M levels and clinicopathological features was examined. Kaplan-Meier analysis, alongside uni- and multivariate Cox regression, assessed the association between B2M levels, systemic inflammatory markers, and glioma patient prognosis. Receiver operating characteristic (ROC) curve analysis evaluated the diagnostic significance of these biomarkers specifically for glioblastoma (GBM). RESULTS: Patients with malignant gliomas exhibited elevated preoperative serum B2M levels. Glioma patients with high serum B2M levels experienced shorter survival times. Multivariate Cox analysis determined the relationship between B2M levels (hazard ratio = 1.92, 95% confidence interval: 1.05-3.50, P = 0.034) and the overall survival of glioma patients. B2M demonstrated superior discriminatory power in distinguishing between GBM and non-GBM compared to inflammation indicators. Moreover, postoperative serum B2M levels were lower than preoperative levels in the majority of glioma patients. CONCLUSIONS: High preoperative serum B2M levels correlated with malignant glioma and a poor prognosis. Serum B2M shows promise as a novel biomarker for predicting patient prognosis and reflecting the therapeutic response.

Radiomic white matter parameters of functional integrity of the corticospinal tract in high-grade glioma.

Tractography has become a widely available tool for the planning of neurosurgical operations as well as for neuroscientific research. The absence of patient interaction makes it easily applicable. However, it leaves uncertainty about the functional relevance of the identified bundles. We retrospectively analyzed the correlation of white matter markers with their clinical function in 24 right-handed patients who underwent first surgery for high-grade glioma. Morphological affection of the corticospinal tract (CST) and grade of paresis were assessed before surgery. Tractography was performed manually with MRTrix3 and automatically with TractSeg. Median and mean fractional anisotropy (FA) from manual tractography showed a significant correlation with CST affection (p = 0.008) and paresis (p = 0.015, p = 0.026). CST affection correlated further most with energy, and surface-volume ratio (p = 0.014) from radiomic analysis. Paresis correlated most with maximum 2D column diameter (p = 0.005), minor axis length (p = 0.006), and kurtosis (p = 0.008) from radiomic analysis. Streamline count yielded no significant correlations. In conclusion, mean or median FA can be used for the assessment of CST integrity in high-grade glioma. Also, several radiomic parameters are suited to describe tract integrity and may be used to quantitatively analyze white matter in the future.

UCHL3 induces radiation resistance and acquisition of mesenchymal phenotypes by deubiquitinating POLD4 in glioma stem cells.

BACKGROUND: The high degree of intratumoral genomic heterogeneity is a major obstacle for glioblastoma (GBM) tumors, one of the most lethal human malignancies, and is thought to influence conventional therapeutic outcomes negatively. The proneural-to-mesenchymal transition (PMT) of glioma stem cells (GSCs) confers resistance to radiation therapy in glioblastoma patients. POLD4 is associated with cancer progression, while the mechanisms underlying PMT and tumor radiation resistance have remained elusive. METHOD: Expression and prognosis of the POLD family were analyzed in TCGA, the Chinese Glioma Genome Atlas (CGGA) and GEO datasets. Tumorsphere formation and in vitro limiting dilution assay were performed to investigate the effect of UCHL3-POLD4 on GSC self-renewal. Apoptosis, TUNEL, cell cycle phase distribution, modification of the Single Cell Gel Electrophoresis (Comet), γ-H2AX immunofluorescence, and colony formation assays were conducted to evaluate the influence of UCHL3-POLD4 on GSC in ionizing radiation. Coimmunoprecipitation and GST pull-down assays were performed to identify POLD4 protein interactors. In vivo, intracranial xenograft mouse models were used to investigate the molecular effect of UCHL3, POLD4 or TCID on GCS. RESULT: We determined that POLD4 was considerably upregulated in MES-GSCs and was associated with a meagre prognosis. Ubiquitin carboxyl terminal hydrolase L3 (UCHL3), a DUB enzyme in the UCH protease family, is a bona fide deubiquitinase of POLD4 in GSCs. UCHL3 interacted with, depolyubiquitinated, and stabilized POLD4. Both in vitro and in vivo assays indicated that targeted depletion of the UCHL3-POLD4 axis reduced GSC self-renewal and tumorigenic capacity and resistance to IR treatment by impairing homologous recombination (HR) and nonhomologous end joining (NHEJ). Additionally, we proved that the UCHL3 inhibitor TCID induced POLD4 degradation and can significantly enhance the therapeutic effect of IR in a gsc-derived in situ xenograft model. CONCLUSION: These findings reveal a new signaling axis for GSC PMT regulation and highlight UCHL3-POLD4 as a potential therapeutic target in GBM. TCID, targeted for reducing the deubiquitinase activity of UCHL3, exhibited significant synergy against MES GSCs in combination with radiation.

The m6A reader HNRNPC promotes glioma progression by enhancing the stability of IRAK1 mRNA through the MAPK pathway.

Glioma is the most common and aggressive type of primary malignant brain tumor. The N6-methyladenosine (m6A) modification widely exists in eukaryotic cells and plays an important role in the occurrence and development of human tumors. However, the function and mechanism of heterogeneous nuclear ribonucleoprotein C (HNRNPC), an RNA-binding protein and m6A reader in gliomas remains to be comprehensively and extensively explored. Herein, we found that HNRNPC mRNA and protein overexpression were associated with a poor prognosis for patients with gliomas, based on the data from TCGA, the CGGA, and the TMAs. Biologically, HNRNPC knockdown markedly repressed malignant phenotypes of glioma in vitro and in vivo, whereas ectopic HNRNPC expression had the opposite effect. Integrative RNA sequencing and MeRIP sequencing analyses identified interleukin-1 receptor-associated kinase 1 (IRAK1) as a downstream target of HNRNPC. The glioma public datasets and tissue microarrays (TMAs) data indicated that IRAK1 overexpression was associated with poor prognosis, and IRAK1 knockdown significantly repressed malignant biological behavior in vitro. Mechanistically, HNRNPC maintains the mRNA stability of IRAK1 in an m6A-dependent manner, resulting in activation of the mitogen-activated protein kinase (MAPK) signaling pathway, which was necessary for the malignant behavior of glioma. Our findings demonstrate the HNRNPC-IRAK1-MAPK axis as a crucial carcinogenic factor for glioma and the novel underlying mechanism of IRAK1 upregulation, which provides a rationale for therapeutically targeting epitranscriptomic modulators in glioma.

CLEC7A regulates M2 macrophages to suppress the immune microenvironment and implies poorer prognosis of glioma.

Background: Gliomas constitute a category of malignant tumors originating from brain tissue, representing the majority of intracranial malignancies. Previous research has demonstrated the pivotal role of CLEC7A in the progression of various cancers, yet its specific implications within gliomas remain elusive. The primary objective of this study was to investigate the prognostic significance and immune therapeutic potential of CLEC7A in gliomas through the integration of bioinformatics and clinical pathological analyses. Methods: This investigation involved examining and validating the relationship between CLEC7A and glioma using samples from Hospital, along with data from TCGA, GEO, GTEx, and CGGA datasets. Subsequently, we explored its prognostic value, biological functions, expression location, and impact on immune cells within gliomas. Finally, we investigated its potential impact on the chemotaxis and polarization of macrophages. Results: The expression of CLEC7A is upregulated in gliomas, and its levels escalate with the malignancy of tumors, establishing it as an independent prognostic factor. Functional enrichment analysis revealed a significant correlation between CLEC7A and immune function. Subsequent examination of immune cell differential expression demonstrated a robust association between CLEC7A and M2 macrophages. This conclusion was further substantiated through single-cell analysis, immunofluorescence, and correlation studies. Finally, the knockout of CLEC7A in M2 macrophages resulted in a noteworthy reduction in macrophage chemotaxis and polarization factors. Conclusion: CLEC7A expression is intricately linked to the pathology and molecular characteristics of gliomas, establishing its role as an independent prognostic factor for gliomas and influencing macrophage function. It could be a promising target for immunotherapy in gliomas.

Machine learning-based identification of a cell death-related signature associated with prognosis and immune infiltration in glioma.

Accumulating evidence suggests that a wide variety of cell deaths are deeply involved in cancer immunity. However, their roles in glioma have not been explored. We employed a logistic regression model with the shrinkage regularization operator (LASSO) Cox combined with seven machine learning algorithms to analyse the patterns of cell death (including cuproptosis, ferroptosis, pyroptosis, apoptosis and necrosis) in The Cancer Genome Atlas (TCGA) cohort. The performance of the nomogram was assessed through the use of receiver operating characteristic (ROC) curves and calibration curves. Cell-type identification was estimated by using the cell-type identification by estimating relative subsets of known RNA transcripts (CIBERSORT) and single sample gene set enrichment analysis methods. Hub genes associated with the prognostic model were screened through machine learning techniques. The expression pattern and clinical significance of MYD88 were investigated via immunohistochemistry (IHC). The cell death score represents an independent prognostic factor for poor outcomes in glioma patients and has a distinctly superior accuracy to that of 10 published signatures. The nomogram performed well in predicting outcomes according to time-dependent ROC and calibration plots. In addition, a high-risk score was significantly related to high expression of immune checkpoint molecules and dense infiltration of protumor cells, these findings were associated with a cell death-based prognostic model. Upregulated MYD88 expression was associated with malignant phenotypes and undesirable prognoses according to the IHC. Furthermore, high MYD88 expression was associated with poor clinical outcomes and was positively related to CD163, PD-L1 and vimentin expression in the in-horse cohort. The cell death score provides a precise stratification and immune status for glioma. MYD88 was found to be an outstanding representative that might play an important role in glioma.

Understanding the immunosuppressive microenvironment of glioma: mechanistic insights and clinical perspectives.

Glioblastoma (GBM), the predominant and primary malignant intracranial tumor, poses a formidable challenge due to its immunosuppressive microenvironment, thereby confounding conventional therapeutic interventions. Despite the established treatment regimen comprising surgical intervention, radiotherapy, temozolomide administration, and the exploration of emerging modalities such as immunotherapy and integration of medicine and engineering technology therapy, the efficacy of these approaches remains constrained, resulting in suboptimal prognostic outcomes. In recent years, intensive scrutiny of the inhibitory and immunosuppressive milieu within GBM has underscored the significance of cellular constituents of the GBM microenvironment and their interactions with malignant cells and neurons. Novel immune and targeted therapy strategies have emerged, offering promising avenues for advancing GBM treatment. One pivotal mechanism orchestrating immunosuppression in GBM involves the aggregation of myeloid-derived suppressor cells (MDSCs), glioma-associated macrophage/microglia (GAM), and regulatory T cells (Tregs). Among these, MDSCs, though constituting a minority (4-8%) of CD45+ cells in GBM, play a central component in fostering immune evasion and propelling tumor progression, angiogenesis, invasion, and metastasis. MDSCs deploy intricate immunosuppressive mechanisms that adapt to the dynamic tumor microenvironment (TME). Understanding the interplay between GBM and MDSCs provides a compelling basis for therapeutic interventions. This review seeks to elucidate the immune regulatory mechanisms inherent in the GBM microenvironment, explore existing therapeutic targets, and consolidate recent insights into MDSC induction and their contribution to GBM immunosuppression. Additionally, the review comprehensively surveys ongoing clinical trials and potential treatment strategies, envisioning a future where targeting MDSCs could reshape the immune landscape of GBM. Through the synergistic integration of immunotherapy with other therapeutic modalities, this approach can establish a multidisciplinary, multi-target paradigm, ultimately improving the prognosis and quality of life in patients with GBM.

State of the Art in Low-Grade Glioma Management: Insights From Isocitrate Dehydrogenase and Beyond.

Low-grade gliomas present a formidable challenge in neuro-oncology because of the challenges imposed by the blood-brain barrier, predilection for the young adult population, and propensity for recurrence. In the past two decades, the systematic examination of genomic alterations in adults and children with primary brain tumors has uncovered profound new insights into the pathogenesis of these tumors, resulting in more accurate tumor classification and prognostication. It also identified several common recurrent genomic alterations that now define specific brain tumor subtypes and have provided a new opportunity for molecularly targeted therapeutic intervention. Adult-type diffuse low-grade gliomas are frequently associated with mutations in isocitrate dehydrogenase 1 and 2 (IDH1/2), resulting in production of 2-hydroxyglutarate, an oncometabolite important for tumorigenesis. Recent studies of IDH inhibitors have yielded promising results in patients at early stages of disease with prolonged progression-free survival (PFS) and delayed time to radiation and chemotherapy. Pediatric-type gliomas have high rates of alterations in BRAF, including BRAF V600E point mutations or BRAF-KIAA1549 rearrangements. BRAF inhibitors, often combined with MEK inhibitors, have resulted in radiographic response and improved PFS in these patients. This article reviews emerging approaches to the treatment of low-grade gliomas, including a discussion of targeted therapies and how they integrate with the current treatment modalities of surgical resection, chemotherapy, and radiation.

The Father of Wisdom: "The Influence of Surgical Experience on Overall Survival in Patients with Malignant Gliomas".

BACKGROUND: The role of surgery in the management of malignant gliomas has been feverishly deliberated after the publication of the first expansive case series, the last two decades reinvigorating the discussion regarding the value of total removal in improving survivability. Despite numerous technologies being implemented to increase the resection rates of malignant gliomas, the role of surgical experience has been largely overlooked. This article aims to discuss the importance of a single surgeon's experience in treating high-grade gliomas over a period of 20 years. MATERIAL AND METHODS: In order to demonstrate the role of surgical experience, we divided the patients operated by a single neurosurgeon into two distinct intervals: between 2000 and 2009 and between 2012 and 2020, respectively. Only cases with subsequent adjuvant radio-chemotherapy were included. For objective reasons, no technologies that could assist the extent of resection (EOR) such as intraoperative MRI (iMRI) or 5-ALA could be used in the country of our study. Gross total resection was the main goal whenever possible, whereas subtotal removal was defined as a clear remnant on contrasted MRI or CT performed 24-48 h postoperatively. Using the Kaplan-Meier method, we analyzed the survival and disease-free interval of our patients according to age, pathology, and degree of resection. RESULTS: In the 20-year interval of our retrospective study, the main author (ISF) operated 1591 cases of gliomas in a total of 1878 surgeries, including recurrences. The number of high-grade glioma (HGG) patients was 909 (57.10%), 495 of which were male (54.5%) and 414 (45.5%) female. The mean age of the HGG population was 51.9 years. The most common type of HGG subtype were glioblastomas with a total number 620 cases (68.2%). Regarding overall survival (OS), average survival at 12 months was better by 1.6%, and 12.1% improved at 18 months and 17.8% longer at 24 months in the 2012-2020 interval. The mean OS in the earlier interval was 11.00 months compared to the second when it reached 13.441 months (CI, 12.642-14.24). CONCLUSION: Surgical treatment represents a critical step in the multimodal treatment of malignant gliomas. According to our results, surgical experience improves not only overall survival in a manner equivalent to adjuvant chemotherapy but also the quality of life. As such, a special qualification in neurooncology may prove necessary in offering these patients a second chance at life.

Metabolic models predict fotemustine and the combination of eflornithine/rifamycin and adapalene/cannabidiol for the treatment of gliomas.

Gliomas are the most common type of malignant brain tumors, with glioblastoma multiforme (GBM) having a median survival of 15 months due to drug resistance and relapse. The treatment of gliomas relies on surgery, radiotherapy and chemotherapy. Only 12 anti-brain tumor chemotherapies (AntiBCs), mostly alkylating agents, have been approved so far. Glioma subtype-specific metabolic models were reconstructed to simulate metabolite exchanges, in silico knockouts and the prediction of drug and drug combinations for all three subtypes. The simulations were confronted with literature, high-throughput screenings (HTSs), xenograft and clinical trial data to validate the workflow and further prioritize the drug candidates. The three subtype models accurately displayed different degrees of dependencies toward glutamine and glutamate. Furthermore, 33 single drugs, mainly antimetabolites and TXNRD1-inhibitors, as well as 17 drug combinations were predicted as potential candidates for gliomas. Half of these drug candidates have been previously tested in HTSs. Half of the tested drug candidates reduce proliferation in cell lines and two-thirds in xenografts. Most combinations were predicted to be efficient for all three glioma types. However, eflornithine/rifamycin and cannabidiol/adapalene were predicted specifically for GBM and low-grade glioma, respectively. Most drug candidates had comparable efficiency in preclinical tests, cerebrospinal fluid bioavailability and mode-of-action to AntiBCs. However, fotemustine and valganciclovir alone and eflornithine and celecoxib in combination with AntiBCs improved the survival compared to AntiBCs in two-arms, phase I/II and higher glioma clinical trials. Our work highlights the potential of metabolic modeling in advancing glioma drug discovery, which accurately predicted metabolic vulnerabilities, repurposable drugs and combinations for the glioma subtypes.

Structural- and DTI- MRI enable automated prediction of IDH Mutation Status in CNS WHO Grade 2-4 glioma patients: a deep Radiomics Approach.

BACKGROUND: The role of isocitrate dehydrogenase (IDH) mutation status for glioma stratification and prognosis is established. While structural magnetic resonance image (MRI) is a promising biomarker, it may not be sufficient for non-invasive characterisation of IDH mutation status. We investigated the diagnostic value of combined diffusion tensor imaging (DTI) and structural MRI enhanced by a deep radiomics approach based on convolutional neural networks (CNNs) and support vector machine (SVM), to determine the IDH mutation status in Central Nervous System World Health Organization (CNS WHO) grade 2-4 gliomas. METHODS: This retrospective study analyzed the DTI-derived fractional anisotropy (FA) and mean diffusivity (MD) images and structural images including fluid attenuated inversion recovery (FLAIR), non-enhanced T1-, and T2-weighted images of 206 treatment-naïve gliomas, including 146 IDH mutant and 60 IDH-wildtype ones. The lesions were manually segmented by experienced neuroradiologists and the masks were applied to the FA and MD maps. Deep radiomics features were extracted from each subject by applying a pre-trained CNN and statistical description. An SVM classifier was applied to predict IDH status using imaging features in combination with demographic data. RESULTS: We comparatively assessed the CNN-SVM classifier performance in predicting IDH mutation status using standalone and combined structural and DTI-based imaging features. Combined imaging features surpassed stand-alone modalities for the prediction of IDH mutation status [area under the curve (AUC) = 0.846; sensitivity = 0.925; and specificity = 0.567]. Importantly, optimal model performance was noted following the addition of demographic data (patients' age) to structural and DTI imaging features [area under the curve (AUC) = 0.847; sensitivity = 0.911; and specificity = 0.617]. CONCLUSIONS: Imaging features derived from DTI-based FA and MD maps combined with structural MRI, have superior diagnostic value to that provided by standalone structural or DTI sequences. In combination with demographic information, this CNN-SVM model offers a further enhanced non-invasive prediction of IDH mutation status in gliomas.

A multicenter proof-of-concept study on deep learning-based intraoperative discrimination of primary central nervous system lymphoma.

Accurate intraoperative differentiation of primary central nervous system lymphoma (PCNSL) remains pivotal in guiding neurosurgical decisions. However, distinguishing PCNSL from other lesions, notably glioma, through frozen sections challenges pathologists. Here we sought to develop and validate a deep learning model capable of precisely distinguishing PCNSL from non-PCNSL lesions, especially glioma, using hematoxylin and eosin (H&E)-stained frozen whole-slide images. Also, we compared its performance against pathologists of varying expertise. Additionally, a human-machine fusion approach integrated both model and pathologic diagnostics. In external cohorts, LGNet achieved AUROCs of 0.965 and 0.972 in distinguishing PCNSL from glioma and AUROCs of 0.981 and 0.993 in differentiating PCNSL from non-PCNSL lesions. Outperforming several pathologists, LGNet significantly improved diagnostic performance, further augmented to some extent by fusion approach. LGNet's proficiency in frozen section analysis and its synergy with pathologists indicate its valuable role in intraoperative diagnosis, particularly in discriminating PCNSL from glioma, alongside other lesions.

Exchangeable leaders of collectively migrating glioma abuse N-cadherin trafficking.

Collectively migrating cells consist of leaders and followers with different features. In this issue, Kim et al. (https://doi.org/10.1083/jcb.202401057) characterize the leader and follower cells in collective glioma migration and uncover important roles of YAP1/TAZ-mediated regulation of N-cadherin in the leader cells.