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.

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.

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.

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.

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.

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.

FOSL1's Oncogene Roles in Glioma/Glioma Stem Cells and Tumorigenesis: A Comprehensive Review.

This review specifically examines the important function of the oncoprotein FOSL1 in the dimeric AP-1 transcription factor, which consists of FOS-related components. FOSL1 is identified as a crucial controller of invasion and metastatic dissemination, making it a potential target for therapeutic treatment in cancer patients. The review offers a thorough examination of the regulatory systems that govern the influence exerted on FOSL1. These include a range of changes that occur throughout the process of transcription and after the translation of proteins. We have discovered that several non-coding RNAs, such as microRNAs (miRNAs) and long non-coding RNAs (lncRNAs), play a significant role in regulating FOSL1 expression by directly interacting with its mRNA transcripts. Moreover, an investigation into the functional aspects of FOSL1 reveals its involvement in apoptosis, proliferation, and migration. This work involves a comprehensive analysis of the complex signaling pathways that support these diverse activities. Furthermore, particular importance is given to the function of FOSL1 in coordinating the activation of several cytokines, such as TGF-beta, and the commencement of IL-6 and VEGF production in tumor-associated macrophages (TAMs) that migrate into the tumor microenvironment. There is a specific emphasis on evaluating the predictive consequences linked to FOSL1. Insights are now emerging on the developing roles of FOSL1 in relation to the processes that drive resistance and reliance on specific treatment methods. Targeting FOSL1 has a strong inhibitory effect on the formation and spread of specific types of cancers. Despite extensive endeavors, no drugs targeting AP-1 or FOSL1 for cancer treatment have been approved for clinical use. Hence, it is imperative to implement innovative approaches and conduct additional verifications.

Fluorescein-guided surgery in high-grade gliomas: focusing on the eloquent and deep-seated areas.

PURPOSE: The vital function of eloquent and deep brain areas necessitates precise treatment for tumors located in these regions. Fluorescein-guided surgery (FGS) has been widely used for high-grade gliomas (HGGs) resection. Nevertheless, the safety and efficacy of utilizing this technique for resecting brain tumors located in eloquent and deep-seated areas remain uncertain. This study aims to assess the safety and extent of resection of HGGs in these challenging tumors with fluorescein and explore its impact on patient survival. METHODS: A retrospective analysis was conducted on the clinical and radiological data of 67 consecutive patients with eloquent or deep-seated HGGs who underwent surgery between January 2020 and June 2023. Lacroix functional location grade was used to determine the eloquence of the tumors. The comparison between the fluorescence-guided surgery group (FGS, n = 32) and the conventional white-light microscopic surgery group (non-FGS, n = 35) included assessments of extent of resection (EOR), rates of gross total resection (GTR, 100%) and near-total resection (NTR, 99 to 98%), postoperative Neurologic Assessment in Neuro-Oncology (NANO) scores, overall survival (OS), and progression-free survival (PFS), to evaluate the safety and efficacy of fluorescein-guided technology in tumor resection at these specific locations. RESULTS: Baseline of demographics, lesion location, and pathology showed no significant difference between the two groups. GTR of the FGS group was higher than the non-FGS group (84.4% vs. 60.0%, OR 3.60, 95% CI 1.18-10.28, p < 0.05). The FGS group also showed higher GTR + NTR (EOR ≥ 98%) than the non-FGS group (93.8% vs. 65.7%, OR 7.83, 95% CI 1.86-36.85, p < 0.01). 87.0% of eloquent tumors (Lacroix grade III) in the FGS group achieved GTR + NTR, compared to 52.2% of control group (OR 6.11, 95% CI 1.50-22.78, p < 0.05). For deep-seated tumors, the rate of GTR + NTR in the two groups were 91.7% and 53.3%, respectively (OR 9.62, 95% CI 1.05-116.50, p < 0.05). No significant difference of the preoperative NANO score of the two groups was found. The postoperative NANO score of the FGS group was significantly lower than the non-FGS group (2.56 ± 1.29 vs. 3.43 ± 1.63, p < 0.05). Median OS of the FGS group was 4.2 months longer than the non-FGS group despite no statistical difference (18.2 months vs. 14.0 months, HR 0.63, 95% CI 0.36-1.11, p = 0.112), while PSF was found significantly longer in FGS patients than those of the non-FGS group (11.2 months vs. 7.7 months, HR 0.59, 95% CI 0.35-0.99, p < 0.05). CONCLUSION: Sodium fluorescein-guided surgery for high-grade gliomas in eloquent and deep-seated brain regions enables more extensive resection while preserving neurologic function and improve patient survival.

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.

The Clinical Utility of a Tiered Approach to Pediatric Glioma Molecular Characterization for Resource-Limited Settings.

PURPOSE: Molecular characterization is key to optimally diagnose and manage cancer. The complexity and cost of routine genomic analysis have unfortunately limited its use and denied many patients access to precision medicine. A possible solution is to rationalize use-creating a tiered approach to testing which uses inexpensive techniques for most patients and limits expensive testing to patients with the highest needs. Here, we tested the utility of this approach to molecularly characterize pediatric glioma in a cost- and time-sensitive manner. METHODS: We used a tiered testing pipeline of immunohistochemistry (IHC), customized fusion panels or fluorescence in situ hybridization (FISH), and targeted RNA sequencing in pediatric gliomas. Two distinct diagnostic algorithms were used for low- and high-grade gliomas (LGGs and HGGs). The percentage of driver alterations identified, associated testing costs, and turnaround time (TAT) are reported. RESULTS: The tiered approach successfully characterized 96% (95 of 99) of gliomas. For 82 LGGs, IHC, targeted fusion panel or FISH, and targeted RNA sequencing solved 35% (29 of 82), 29% (24 of 82), and 30% (25 of 82) of cases, respectively. A total of 64% (53 of 82) of samples were characterized without targeted RNA sequencing. Of 17 HGG samples, 13 were characterized by IHC and four were characterized by targeted RNA sequencing. The average cost per sample was more affordable when using the tiered approach as compared with up-front targeted RNA sequencing in LGG ($405 US dollars [USD] v $745 USD) and HGGs ($282 USD v $745 USD). The average TAT per sample was also shorter using the tiered approach (10 days for LGG, 5 days for HGG v 14 days for targeted RNA sequencing). CONCLUSION: Our tiered approach molecularly characterized 96% of samples in a cost- and time-sensitive manner. Such an approach may be feasible in neuro-oncology centers worldwide, particularly in resource-limited settings.

Knockdown of trem2 promotes proinflammatory microglia and inhibits glioma progression via the JAK2/STAT3 and NF-κB pathways.

BACKGROUND: In the tumor immune microenvironment (TIME), triggering receptor expressed on myeloid cells 2 (trem2) is widely considered to be a crucial molecule on tumor-associated macrophages(TAMs). Multiple studies have shown that trem2 may function as an immune checkpoint in various malignant tumors, mediating tumor immune evasion. However, its specific molecular mechanisms, especially in glioma, remain elusive. METHODS: Lentivirus was transfected to establish cells with stable knockdown of trem2. A Transwell system was used for segregated coculture of glioma cells and microglia. Western blotting, quantitative real-time polymerase chain reaction (qRT‒PCR), and immunofluorescence (IF) were used to measure the expression levels of target proteins. The proliferation, invasion, and migration of cells were detected by colony formation, cell counting kit-8 (CCK8), 5-ethynyl-2'-deoxyuridine (EdU) and transwell assays. The cell cycle, apoptosis rate and reactive oxygen species (ROS) level of cells were assessed using flow cytometry assays. The comet assay and tube formation assay were used to detect DNA damage in glioma cells and angiogenesis activity, respectively. Gl261 cell lines and C57BL/6 mice were used to construct the glioma orthotopic transplantation tumor model. RESULTS: Trem2 was highly overexpressed in glioma TAMs. Knocking down trem2 in microglia suppressed the growth and angiogenesis activity of glioma cells in vivo and in vitro. Mechanistically, knockdown of trem2 in microglia promoted proinflammatory microglia and inhibited anti-inflammatory microglia by activating jak2/stat1 and inhibiting the NF-κB p50 signaling pathway. The proinflammatory microglia produced high concentrations of nitric oxide (NO) and high levels of the proinflammatory cytokines TNF-α, IL-6, and IL-1ß, and caused further DNA damage and promoted the apoptosis rate of tumor cells. CONCLUSIONS: Our findings revealed that trem2 in microglia plays a significant role in the TIME of gliomas. Knockdown of trem2 in microglia might help to improve the efficiency of inhibiting glioma growth and delaying tumor progression and provide new ideas for further treatment of glioma.

Vasorin promotes endothelial differentiation of glioma stem cells via stimulating the transcription of VEGFR2.

Gliomas are highly vascularized malignancies, but current anti-angiogenic treatments have not demonstrated practical improvements in patient survival. Studies have suggested that glioma-derived endothelial cell (GdEC) formed by glioma stem cell (GSC) differentiation may contribute to the failure of this treatment. However, the molecular mechanisms involved in GSC endothelial differentiation remain poorly understood. We previously reported that vasorin (VASN) is highly expressed in glioma and promotes angiogenesis. Here, we show that VASN expression positively correlates with GdEC signatures in glioma patients. VASN promotes the endothelial differentiation capacity of GSC in vitro and participates in the formation of GSC-derived vessels in vivo. Mechanistically, vascular endothelial growth factor receptor 2 (VEGFR2) is a critical factor that mediates the regulation of VASN on GSC endothelial differentiation. Separation of cell chromatin fractionation and chromatin immunoprecipitation-sequencing analysis show that VASN interacts with Notch1 and co-translocates into the cell nuclei, where VASN binds to the VEGFR2 gene promoter to stimulate its transcription during the progression of GSC differentiation into GdEC. Together, these findings elucidate the role and mechanisms of VASN in promoting the endothelial differentiation of GSC and suggest VASN as a potential target for anti-angiogenic therapy based on intervention in GdEC formation in gliomas.

Neutrophils in glioma microenvironment: from immune function to immunotherapy.

Glioma is a malignant tumor of the central nervous system (CNS). Currently, effective treatment options for gliomas are still lacking. Neutrophils, as an important member of the tumor microenvironment (TME), are widely distributed in circulation. Recently, the discovery of cranial-meningeal channels and intracranial lymphatic vessels has provided new insights into the origins of neutrophils in the CNS. Neutrophils in the brain may originate more from the skull and adjacent vertebral bone marrow. They cross the blood-brain barrier (BBB) under the action of chemokines and enter the brain parenchyma, subsequently migrating to the glioma TME and undergoing phenotypic changes upon contact with tumor cells. Under glycolytic metabolism model, neutrophils show complex and dual functions in different stages of cancer progression, including participation in the malignant progression, immune suppression, and anti-tumor effects of gliomas. Additionally, neutrophils in the TME interact with other immune cells, playing a crucial role in cancer immunotherapy. Targeting neutrophils may be a novel generation of immunotherapy and improve the efficacy of cancer treatments. This article reviews the molecular mechanisms of neutrophils infiltrating the central nervous system from the external environment, detailing the origin, functions, classifications, and targeted therapies of neutrophils in the context of glioma.

Detection of In Vivo-like Cells by a Biosensor Chip Based on Metamaterials in Terahertz Regime.

Early diagnosis of diseases, especially cancer, is critical for effective treatment. The unique properties of terahertz technology have attracted attention in this field. However, current terahertz bio-detection methods face challenges due to differences between the test environment and the actual in vivo conditions. In this study, a novel method is proposed for detecting in vivo-like cells using a biosensor chip composed of metamaterials and a cavity. The cavity has a thickness of ~50 µm. The structure can protect cells from damage and provides a liquid environment like an in vivo state. Through simulation analysis, the metamaterials sensor exhibits a theoretical sensitivity of 0.287 THz/RIU (Refractive Index Unit) with a 50 µm thick analyte. The detection method is experimentally validated using the apoptosis of glioma cells and various cell types. The biosensor investigates the apoptosis of glioma cells under the impact of temozolomide, and the trend of the results was consistent with the Cell Counting Kit-8 method. Furthermore, at a concentration of ~5200 cells/cm2, the experimental results demonstrate that the sensor can distinguish between neurons and glioma cells with a resonance frequency difference of approximately 30 GHz. This research has significant potential for detecting glioma cells and offers an alternative approach to in vivo-like cell detection.

Comparison of two region-of-interest placement methods for histogram analysis of apparent diffusion coefficient maps for glioma grading.

Objectives: We assessed the value of histogram analysis (HA) of apparent diffusion coefficient (ADC) maps for grading low-grade (LGG) and high-grade (HGG) gliomas. Methods: We compared the diagnostic performance of two region-of-interest (ROI) placement methods (ROI 1: the entire tumor; ROI 2: the tumor excluding cystic and necrotic portions). We retrospectively evaluated 54 patients with supratentorial gliomas (18 LGG and 36 HGG). All subjects underwent standard 3T contrast-enhanced magnetic resonance imaging. Histogram parameters of ADC maps calculated with the two segmentation methods comprised mean, median, maxi-mum, minimum, kurtosis, skewness, entropy, standard deviation (sd), mean of positive pixels (mpp), uniformity of positive pixels, and their ratios (r) between lesion and normal white matter. They were compared using the independent t-test, chi-square test, or Mann-Whitney U test. For statistically significant results, receiver operating characteristic curves were constructed, and the optimal cutoff value, sensitivity, and specificity were determined by maximizing Youden's index. Results: The ROI 1 method resulted in significantly higher rADC mean, rADC median, and rADC mpp for LGG than for HGG; these parameters had value for predicting the histological glioma grade with a cutoff (sensitivity, specificity) of 1.88 (77.8%, 61.1%), 2.25 (44.4%, 97.2%), and 1.88 (77.8%, 63.9%), respectively. The ROI 2 method resulted in significantly higher ADC mean, ADC median, ADC mpp, ADC sd, ADC max, rADC median, rADC mpp, rADC mean, rADC sd, and rADC max for LGG than for HGG, while skewness was lower for LGG than for HGG (0.27 [0.98] vs 0.91 [0.81], p = 0.014). In ROI 2, ADC median, ADC mpp, ADC mean, rADC median, rADC mpp, and rADC mean performed well in differentiating glioma grade with cutoffs (sensitivity, specificity) of 1.28 (77.8%, 88.9%), 1.28 (77.8%, 88.9%), 1.25 (77.8%, 91.7%), 1.81 (83.3%, 91.7%), 1.74 (83.3%, 91.7%), and 1.81 (83.3%, 91.7%), respectively. Conclusions: HA parameters had value for grading gliomas. Ex-cluding cystic and necrotic portions of the tumor for measuring HA parameters was preferable to using the entire tumor as the ROI. In this segmentation, rADC median showed the highest performance in predicting histological glioma grade, followed by rADC mpp, rADC mean, ADC median, ADC mpp, and ADC mean.

Identification of cancer risk groups through multi-omics integration using autoencoder and tensor analysis.

Identifying cancer risk groups by multi-omics has attracted researchers in their quest to find biomarkers from diverse risk-related omics. Stratifying the patients into cancer risk groups using genomics is essential for clinicians for pre-prevention treatment to improve the survival time for patients and identify the appropriate therapy strategies. This study proposes a multi-omics framework that can extract the features from various omics simultaneously. The framework employs autoencoders to learn the non-linear representation of the data and applies tensor analysis for feature learning. Further, the clustering method is used to stratify the patients into multiple cancer risk groups. Several omics were included in the experiments, namely methylation, somatic copy-number variation (SCNV), micro RNA (miRNA) and RNA sequencing (RNAseq) from two cancer types, including Glioma and Breast Invasive Carcinoma from the TCGA dataset. The results of this study are promising, as evidenced by the survival analysis and classification models, which outperformed the state-of-the-art. The patients can be significantly (p-value<0.05) divided into risk groups using extracted latent variables from the fused multi-omics data. The pipeline is open source to help researchers and clinicians identify the patients' risk groups using genomics.