Multicenter integration analysis of TRP channels revealed potential mechanisms of immunosuppressive microenvironment activation and identified a machine learning-derived signature for improving outcomes in gliomas.

AIM: This study aimed to explore the mechanisms of transient receptor potential (TRP) channels on the immune microenvironment and develop a TRP-related signature for predicting prognosis, immunotherapy response, and drug sensitivity in gliomas. METHODS: Based on the unsupervised clustering algorithm, we identified novel TRP channel clusters and investigated their biological function, immune microenvironment, and genomic heterogeneity. In vitro and in vivo experiments revealed the association between TRPV2 and macrophages. Subsequently, based on 96 machine learning algorithms and six independent glioma cohorts, we constructed a machine learning-based TRP channel signature (MLTS). The performance of the MLTS in predicting prognosis, immunotherapy response, and drug sensitivity was evaluated. RESULTS: Patients with high expression levels of TRP channel genes had worse prognoses, higher tumor mutation burden, and more activated immunosuppressive microenvironment. Meanwhile, TRPV2 was identified as the most essential regulator in TRP channels. TRPV2 activation could promote macrophages migration toward malignant cells and alleviate glioma prognosis. Furthermore, MLTS could work independently of common clinical features and present stable and superior prediction performance. CONCLUSION: This study investigated the comprehensive effect of TRP channel genes in gliomas and provided a promising tool for designing effective, precise treatment strategies.

Study on the Relationship Between MRI Functional Imaging and Multiple Immunohistochemical Features of Glioma: A Noninvasive and More Precise Glioma Management.

Objective: To investigate the performance of diffusion-tensor imaging (DTI) and hydrogen proton magnetic resonance spectroscopy (1H-MRS) parameters in predicting the immunohistochemistry (IHC) biomarkers of glioma. Methods: Patients with glioma confirmed by pathology from March 2015 to September 2019 were analyzed, the preoperative DTI and 1H-MRS images were collected, apparent diffusion coefficient (ADC) and fractional anisotropy (FA), in the lesion area were measured, the relative values relative ADC (rADC) and relative FA (rFA) were obtained by the ratio of them in the lesion area to the contralateral normal area. The peak of each metabolite in the lesion area of 1H-MRS image: N-acetylaspartate (NAA), choline (Cho), and creatine (Cr), and metabolite ratio: NAA/Cho, NAA/(Cho + Cr) were selected and calculated. The preoperative IHC data were collected including CD34, Ki-67, p53, S-100, syn, vimentin, NeuN, Nestin, and glial fibrillary acidic protein. Results: One predicting parameter of DTI was screened, the rADC of the Ki-67 positive group was lower than that of the negative group. Two parameters of 1H-MRS were found to have significant reference values for glioma grades, the NAA and Cr decreased as the grade of glioma increased, moreover, Ki-67 Li was negatively correlated with NAA and Cr. Conclusion: NAA and Cr have potential application value in predicting glioma grades and tumor proliferation activity. Only rADC has predictive value for Ki-67 expression among DTI parameters.

Prognostic relevance of high expression of kynurenine pathway markers in glioblastoma.

Glioblastoma (GBM) continues to exhibit a discouraging survival rate despite extensive research into new treatments. One factor contributing to its poor prognosis is the tumor's immunosuppressive microenvironment, in which the kynurenine pathway (KP) plays a significant role. This study aimed to explore how KP impacts the survival of newly diagnosed GBM patients. We examined tissue samples from 108 GBM patients to assess the expression levels of key KP markers-tryptophan 2,3-dioxygenase (TDO2), indoleamine 2,3-dioxygenase (IDO1/2), and the aryl hydrocarbon receptor (AhR). Using immunohistochemistry and QuPath software, three tumor cores were analyzed per patient to evaluate KP marker expression. Kaplan-Meier survival analysis and stepwise multivariate Cox regression were used to determine the effect of these markers on patient survival. Results showed that patients with high expression of TDO2, IDO1/2, and AhR had significantly shorter survival times. This finding held true even when controlling for other known prognostic variables, with a hazard ratio of 3.393 for IDO1, 2.775 for IDO2, 1.891 for TDO2, and 1.902 for AhR. We suggest that KP markers could serve as useful tools for patient stratification, potentially guiding future immunomodulating trials and personalized treatment approaches for GBM patients.

Silencing UBE2K inhibits the growth of glioma cells by inducing the autophagy-related apoptosis.

Glioma is a central nervous system (CNS) malignant tumor with high heterogeneity and mortality, which severely threatens the health of patients. The overall survival of glioma patients is relatively short and it is critical to identify new molecular targets for developing effective treatment strategies. UBE2K is a ubiquitin conjugating enzyme with oncogenic function in several malignant tumors. However, whether UBE2K participates in gliomas remains unknown. Herein, in glioma cells, UBE2K was found highly expressed in U87 and U251 cells. Subsequently, U87 and U251 cells were transfected with si-UBE2K to silence UBE2K, with the si-NC transfection as the negative control. In both U87 and U251 cells, the cell viability was sharply reduced by transfecting si-UBE2K for 48 and 72 h. Markedly decreased colony number, reduced number of migrated cells and invaded cells, and declined relative wound healing rate were observed in si-UBE2K transfected U87 and U251 cells. Moreover, the Bcl-2 level was markedly reduced, while the Bax and cleaved-caspase-3 levels were sharply increased in U87 and U251 cells after the si-UBE2K transfection. Furthermore, the p62 level was signally declined, while the Beclin-1 and LC-3 II/I levels were greatly increased in U87 and U251 cells by the si-UBE2K transfection. Furthermore, the facilitating effect of si-UBE2K on the apoptosis and autophagy in U87 and U251 cells was abolished by the coculture of 3-MA, an inhibitor of autophagy. Collectively, UBE2K facilitated the in vitro growth of glioma cells, possibly by inhibiting the autophagy-related apoptosis, which might be a promising target for treating glioma.

Classification of brain tumor types through MRIs using parallel CNNs and firefly optimization.

Image segmentation is a critical and challenging endeavor in the field of medicine. A magnetic resonance imaging (MRI) scan is a helpful method for locating any abnormal brain tissue these days. It is a difficult undertaking for radiologists to diagnose and classify the tumor from several pictures. This work develops an intelligent method for accurately identifying brain tumors. This research investigates the identification of brain tumor types from MRI data using convolutional neural networks and optimization strategies. Two novel approaches are presented: the first is a novel segmentation technique based on firefly optimization (FFO) that assesses segmentation quality based on many parameters, and the other is a combination of two types of convolutional neural networks to categorize tumor traits and identify the kind of tumor. These upgrades are intended to raise the general efficacy of the MRI scan technique and increase identification accuracy. Using MRI scans from BBRATS2018, the testing is carried out, and the suggested approach has shown improved performance with an average accuracy of 98.6%.

Matrix metalloproteinase 9 expression and glioblastoma survival prediction using machine learning on digital pathological images.

This study aimed to apply pathomics to predict Matrix metalloproteinase 9 (MMP9) expression in glioblastoma (GBM) and investigate the underlying molecular mechanisms associated with pathomics. Here, we included 127 GBM patients, 78 of whom were randomly allocated to the training and test cohorts for pathomics modeling. The prognostic significance of MMP9 was assessed using Kaplan-Meier and Cox regression analyses. PyRadiomics was used to extract the features of H&E-stained whole slide images. Feature selection was performed using the maximum relevance and minimum redundancy (mRMR) and recursive feature elimination (RFE) algorithms. Prediction models were created using support vector machines (SVM) and logistic regression (LR). The performance was assessed using ROC analysis, calibration curve assessment, and decision curve analysis. MMP9 expression was elevated in patients with GBM. This was an independent prognostic factor for GBM. Six features were selected for the pathomics model. The area under the curves (AUCs) of the training and test subsets were 0.828 and 0.808, respectively, for the SVM model and 0.778 and 0.754, respectively, for the LR model. The C-index and calibration plots exhibited effective estimation abilities. The pathomics score calculated using the SVM model was highly correlated with overall survival time. These findings indicate that MMP9 plays a crucial role in GBM development and prognosis. Our pathomics model demonstrated high efficacy for predicting MMP9 expression levels and prognosis of patients with GBM.

MicroRNAs as the pivotal regulators of Temozolomide resistance in glioblastoma.

Glioblastoma (GBM) is an aggressive nervous system tumor with a poor prognosis. Although, surgery, radiation therapy, and chemotherapy are the current standard protocol for GBM patients, there is still a poor prognosis in these patients. Temozolomide (TMZ) as a first-line therapeutic agent in GBM can easily cross from the blood-brain barrier to inhibit tumor cell proliferation. However, there is a high rate of TMZ resistance in GBM patients. Since, there are limited therapeutic choices for GBM patients who develop TMZ resistance; it is required to clarify the molecular mechanisms of chemo resistance to introduce the novel therapeutic targets. MicroRNAs (miRNAs) regulate chemo resistance through regulation of drug metabolism, absorption, DNA repair, apoptosis, and cell cycle. In the present review we discussed the role of miRNAs in TMZ response of GBM cells. It has been reported that miRNAs mainly induced TMZ sensitivity by regulation of signaling pathways and autophagy in GBM cells. Therefore, miRNAs can be used as the reliable diagnostic/prognostic markers in GBM patients. They can also be used as the therapeutic targets to improve the TMZ response in GBM cells.

The cuproptosis-related signature predicts the prognosis and immune microenvironments of primary diffuse gliomas: a comprehensive analysis.

BACKGROUND: Evidence has revealed a connection between cuproptosis and the inhibition of tumor angiogenesis. While the efficacy of a model based on cuproptosis-related genes (CRGs) in predicting the prognosis of peripheral organ tumors has been demonstrated, the impact of CRGs on the prognosis and the immunological landscape of gliomas remains unexplored. METHODS: We screened CRGs to construct a novel scoring tool and developed a prognostic model for gliomas within the various cohorts. Afterward, a comprehensive exploration of the relationship between the CRG risk signature and the immunological landscape of gliomas was undertaken from multiple perspectives. RESULTS: Five genes (NLRP3, ATP7B, SLC31A1, FDX1, and GCSH) were identified to build a CRG scoring system. The nomogram, based on CRG risk and other signatures, demonstrated a superior predictive performance (AUC of 0.89, 0.92, and 0.93 at 1, 2, and 3 years, respectively) in the training cohort. Furthermore, the CRG score was closely associated with various aspects of the immune landscape in gliomas, including immune cell infiltration, tumor mutations, tumor immune dysfunction and exclusion, immune checkpoints, cytotoxic T lymphocyte and immune exhaustion-related markers, as well as cancer signaling pathway biomarkers and cytokines. CONCLUSION: The CRG risk signature may serve as a robust biomarker for predicting the prognosis and the potential viability of immunotherapy responses. Moreover, the key candidate CRGs might be promising targets to explore the underlying biological background and novel therapeutic interventions in gliomas.

Risk factors for nausea and vomiting requiring the daily administration of 5-HT3 receptor antagonists in radiotherapy combined with temozolomide for high-grade glioma.

Radiotherapy combined with temozolomide (TMZ+RT) is the primary treatment for high-grade glioma. TMZ is classified as a moderate emetic risk agent and, thus, supportive care for nausea and vomiting is important. In Nagoya University Hospital, all patients are treated with a 5-hydroxy-tryptamine 3 receptor antagonist (5-HT3RA) for the first 3 days. The daily administration of 5-HT3RA is resumed after the 4th day based on the condition of patients during TMZ+RT. Therefore, the present study investigated risk factors for nausea and vomiting in patients requiring the daily administration of 5-HT3RA. Patients with high-grade glioma who received TMZ+RT between January 2014 and December 2019 at our hospital were included. Patients were divided into two groups: a control group (patients who did not resume 5-HT3RA) and resuming 5-HT3RA group (patients who resumed 5-HT3RA after the 4th day), and both groups were compared to identify risk factors for nausea and vomiting during TMZ+RT. There were 78 patients in the control group (68%) and 36 in the resuming 5-HT3RA group (32%). A multivariate analysis of patient backgrounds in the two groups identified age <18 years, PS 2 or more, and occipital lobe tumors as risk factors for nausea and vomiting. Nausea and vomiting were attenuated in 30 patients (83%) in the resuming 5-HT3RA group following the resumption of 5-HT3RA. The results obtained highlight the importance of extracting patients with these risk factors before the initiation of therapy and the early resumption or daily administration of 5-HT3RA according to the condition of each patient.

Comprehensive application of AI algorithms with TCR NGS data for glioma diagnosis.

T-cell receptor (TCR) detection can examine the extent of T-cell immune responses. Therefore, the article analyzed characteristic data of glioma obtained by DNA-based TCR high-throughput sequencing, to predict the disease with fewer biomarkers and higher accuracy. We downloaded data online and obtained six TCR-related diversity indices to establish a multidimensional classification system. By comparing actual presence of the 602 correlated sequences, we obtained two-dimensional and multidimensional datasets. Multiple classification methods were utilized for both datasets with the classification accuracy of multidimensional data slightly less to two-dimensional datasets. This study reduced the TCR ß sequences through feature selection methods like RFECV (Recursive Feature Elimination with Cross-Validation). Consequently, using only the presence of these three sequences, the classification AUC value of 96.67% can be achieved. The combination of the three correlated TCR clones obtained at a source data threshold of 0.1 is: CASSLGGNTEAFF_TRBV12_TRBJ1-1, CASSYSDTGELFF_TRBV6_TRBJ2-2, and CASSLTGNTEAFF_TRBV12_TRBJ1-1. At 0.001, the combination is: CASSLGETQYF_TRBV12_TRBJ2-5, CASSLGGNQPQHF_TRBV12_TRBJ1-5, and CASSLSGNTIYF_TRBV12_TRBJ1-3. This method can serve as a potential diagnostic and therapeutic tool, facilitating diagnosis and treatment of glioma and other cancers.

Positive feedback loop of c-myc/XTP6/NDH2/NF-κB to promote malignant progression in glioblastoma.

BACKGROUND: Recent studies have highlighted the significant role of the NF-κB signaling pathway in the initiation and progression of cancer. Furthermore, long noncoding RNAs (lncRNAs) have been identified as pivotal regulators in sustaining the NF-κB signaling pathway's functionality. Despite these findings, the underlying molecular mechanisms through which lncRNAs influence the NF-κB pathway remain largely unexplored. METHODS: Bioinformatic analyses were utilized to investigate the differential expression and prognostic significance of XTP6. The functional roles of XTP6 were further elucidated through both in vitro and in vivo experimental approaches. To estimate the interaction between XTP6 and NDH2, RNA pulldown and RNA Immunoprecipitation (RIP) assays were conducted. The connection between XTP6 and the IκBα promoter was examined using Chromatin Isolation by RNA Purification (ChIRP) assays. Additionally, Chromatin Immunoprecipitation (ChIP) assays were implemented to analyze the binding affinity of c-myc to the XTP6 promoter, providing insights into the regulatory mechanisms at play. RESULTS: XTP6 was remarkedly upregulated in glioblastoma multiforme (GBM) tissues and was connected with adverse prognosis in GBM patients. Our investigations revealed that XTP6 can facilitate the malignant progression of GBM both in vitro and in vivo. Additionally, XTP6 downregulated IκBα expression by recruiting NDH2 to the IκBα promoter, which resulted in elevated levels of H3K27me3, thereby reducing the transcriptional activity of IκBα. Moreover, the progression of GBM was further driven by the c-myc-mediated upregulation of XTP6, establishing a positive feedback loop with IκBα that perpetuated the activation of the NF-κB signaling pathway. Notably, the application of an inhibitor targeting the NF-κB signaling pathway effectively inhibited the continuous activation induced by XTP6, leading to a significant reduction in tumor formation in vivo. CONCLUSION: The results reveal that XTP6 unveils an innovative epigenetic mechanism instrumental in the sustained activation of the NF-κB signaling pathway, suggesting a promising therapeutic target for the treatment of GBM.

Evaluation of secretome biomarkers in glioblastoma cancer stem cells: A bioinformatics analysis.

BACKGROUND: Glioblastoma (GBM) is a malignant brain tumor that frequently occurs alongside other central nervous system (CNS) conditions. The secretome of GBM cells contains a diverse array of proteins released into the extracellular space, influencing the tumor microenvironment. These proteins can serve as potential biomarkers for GBM due to their involvement in key biological processes, exploring the secretome biomarkers in GBM research represents a cutting-edge strategy with significant potential for advancing diagnostic precision, treatment monitoring, and ultimately improving outcomes for patients with this challenging brain cancer. AIM: This study was aimed to investigate the roles of secretome biomarkers and their pathwayes in GBM through bioinformatics analysis. METHODS AND RESULTS: Using data from the Gene Expression Omnibus and the Cancer Genome Atlas datasets-where both healthy and cancerous samples were analyzed-we used a quantitative analytical framework to identify differentially expressed genes (DEGs) and cell signaling pathways that might be related to GBM. Then, we performed gene ontology studies and hub protein identifications to estimate the roles of these DEGs after finding disease-gene connection networks and signaling pathways. Using the GEPIA Proportional Hazard Model and the Kaplan-Meier estimator, we widened our analysis to identify the important genes that may play a role in both progression and the survival of patients with GBM. In total, 890 DEGs, including 475 and 415 upregulated and downregulated were identified, respectively. Our results revealed that SQLE, DHCR7, delta-1 phospholipase C (PLCD1), and MINPP1 genes are highly expressed, and the Enolase 2 (ENO2) and hexokinase-1 (HK1) genes are low expressions. CONCLUSION: Hence, our findings suggest novel mechanisms that affect the occurrence of GBM development, growth, and/or establishment and may also serve as secretory biomarkers for GBM prognosis and possible targets for therapy. So, continued research in this field may uncover new avenues for therapeutic interventions and contribute to the ongoing efforts to combat GBM effectively.

Evaluating soluble Axl as a biomarker for glioblastoma: A pilot study.

With current imaging, discriminating tumor progression from treatment effect following immunotherapy or oncolytic virotherapy of glioblastoma (GBM) is challenging. A blood based diagnostic biomarker would therefore be helpful. Axl is a receptor tyrosine kinase that is highly expressed by many cancers including GBM. Axl expression is regulated through enzymatic cleavage of its extracellular domain. The resulting fragment can be detected in serum as soluble Axl (sAxl). sAxl levels can distinguish patients with melanoma, hepatocellular carcinoma, and pancreatic ductal adenocarcinoma from healthy controls. This is a pilot study to determine if sAxl is a candidate biomarker for GBM. The sAxl levels in the serum of 40 healthy volunteers and 20 GBM patients were determined using an enzyme-linked immunosorbent assay (ELISA). Pre- and post- operative sAxl levels were obtained. Volumetric MRI evaluation provided GBM tumor volume metrics. There was no significant difference in the sAxl levels of the volunteers (30.16±1.88 ng/ml) and GBM patients (30.74±1.96 ng/ml) p = 0.27. The postoperative sAxl levels were significantly higher than preoperative levels (32.32±2.26 ng/ml vs 30.74±1.96 ng/ml, p = 0.03). We found no correlation between tumor volume and sAxl levels. Axl expression was low or absent in 6 of 11 (55%) patient derived GBM cell lines. Given the wide range of Axl expression by GBM tumors, sAxl may not be a reliable indicator of GBM. However, given the small sample size in this study, a larger study may be considered.

Inhibition of the TCF12/VSIG4 axis by palbociclib diminishes the proliferation and migration of glioma cells and decreases the M2 polarization of glioma-associated microglia.

The CDK4/CDK6 inhibitor palbociclib has shown the encouraging promise in the treatment of glioma. Here, we elucidated how palbociclib exerts suppressive functions in the M2 polarization of glioma-related microglia and the progression of glioma. Xenograft experiments were used to evaluate the function in vivo. The mRNA levels of transcription factor 12 (TCF12) and VSIG4 were detected by RT-qPCR, and their protein levels were assessed by immunoblotting. Cell migration was tested by wound-healing assay. Cell cycle distribution and M1/M2 microglia phenotype analysis were performed by flow cytometry. The levels of IFN-γ, TNF-α, IL-6，and TGF-ß were measured by ELISA. The TCF12/VSIG4 association was verified by luciferase reporter and chromatin immunoprecipitation (ChIP) assays. In U251 and LN229 glioma cells, TCF12 and VSIG4 were overexpressed, and palbociclib reduced their expression levels. TCF12 upregulation enhanced the proliferation and migration of glioma cells and the M2 polarization of glioma-associated microglia in vitro as well as the tumorigenicity of U251 glioma cells in vivo, which could be reversed by palbociclib. Mechanistically, TCF12 could enhance VSIG4 transcription and expression by binding to the VSIG4 promoter. TCF12 deficiency led to repression in glioma cell proliferation and migration as well as microglia M2 polarization, which could be abolished by increased VSIG4 expression. Our study reveals the novel TCF12/VSIG4 axis responsible for the efficacy of palbociclib in combating glioma, offering a rationale for the application of palbociclib in glioma treatment.

Trans-temporal trans-choroidal resection of thalamic and thalamopeduncular tumors: how I do it.

BACKGROUND:  Surgical resection is the cornerstone of treatment for low-grade tumors, albeit total excision is beneficial. As the thalamus is surrounded by vital neurovascular system, lesions here present a surgical challenge. METHOD: This article aims to demonstrate the trans-temporal, trans-choroidal fissure approach's effective surgical therapy on patients with thalamic lesions. With this approach, we were able to remove the tumor completely in three patients and almost completely in six more. Here we discuss a few technical details and potential hazards of the procedure with an operative video. CONCLUSION: This approach  provides excellent access to the deep areas of brain.

Characterizing the Linkage of Systemic Hypoxia and Angiogenesis in High-Grade Glioma to Define the Changes in Tumor Microenvironment for Predicting Prognosis.

High-grade gliomas (HGG) comprising WHO grades 3 and 4 have a poor overall survival (OS) that has not improved in the past decade. Herein, markers representing four components of the tumor microenvironment (TME) were identified to define their linked expression in TME and predict the prognosis in HGG, namely, interleukin6 (IL6, inflammation), inducible nitric oxide synthase(iNOS), heat shock protein-70 (HSP70, hypoxia), vascular endothelial growth receptor (VEGF), and endothelin1 (ET1) (angiogenesis) and matrix metalloprotease-14 (MMP14) and intercellular adhesion molecule1 (ICAM1, extracellular matrix). To establish a non-invasive panel of biomarkers for precise prognostication in HGG. Eighty-six therapy-naive HGG patients with 45 controls were analyzed for the defined panel. Systemic expression of extracellular/secretory biomarkers was screened dot-immune assay (DIA), quantified by ELISA, and validated by immunocytochemistry (ICC). Expression of iNOS, HSP70, IL-6, VEGF, ET1, MMP14, and ICAM1 was found to be positively associated with grade. Quantification of circulating levels of the markers by ELISA and ICC presented a similar result. The biomarkers were observed to negatively correlate with OS (p < 0.0001). Cox-regression analysis yielded all biomarkers as good prognostic indicators and independent of confounders. On applying combination statistics, the biomarker panel achieved higher sensitivity than single markers to define survival. The intra-association of all seven biomarkers was significant, hinting of a cross-talk between the TME components and a hypoxia driven systemic inflammation upregulating the expression of other components. This is a first ever experimental study of a marker panel that can distinguish between histopathological grades and also delineate differential survival using liquid biopsy, suggesting that markers of hypoxia can be a cornerstone for personalized therapy. The panel of biomarkers of iNOS, HSP70, IL-6, VEGF, ET1, MMP14, and ICAM1 holds promise for prognostication in HGG.

Role of Machine Learning in Liquid Biopsy of Brain Tumours.

Liquid biopsy has multiple benefits and is used extensively in other fields of oncology, but its role in neuro-oncology has been limited so far. Multiple tumour-derived materials like circulating tumour cells (CTCs), tumour-educated platelets (TEPs), cell-free DNA (cfDNA), circulating tumour DNA (ctDNA), and miRNA are studied in CSF, blood (plasma, serum) or urine. Large and complex amounts of data from liquid biopsy can be simplified by machine learning using various algorithms. By using this technique, we can diagnose brain tumours and differentiate low versus highgrade glioma and true progression from pseudo-progression. The potential of liquid biopsy in brain tumours has not been extensively studied, but it has a bright future in the coming years. Here, we present a literature review on the role of machine learning in liquid biopsy of brain tumours.

Lysyl oxidase-like 1 predicts the prognosis of patients with primary glioblastoma and promotes tumor invasion via EMT pathway.

Background: Lysyl oxidase enzymes (LOXs), as extracellular matrix (ECM) protein regulators, play vital roles in tumor progression by remodeling the tumor microenvironment. However, their roles in glioblastoma (GBM) have not been fully elucidated. Methods: The genetic alterations and prognostic value of LOXs were investigated via cBioPortal. The correlations between LOXs and biological functions/molecular tumor subtypes were explored in The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA). After Kaplan‒Meier and Cox survival analyses, a Loxl1-based nomogram and prognostic risk score model (PRSM) were constructed and evaluated by time-dependent receiver operating characteristic curves, calibration curves, and decision curve analyses. Tumor enrichment pathways and immune infiltrates were explored by single-cell RNA sequencing and TIMER. Loxl1-related changes in tumor viability/proliferation and invasion were further validated by CCK-8, western blot, wound healing, and Transwell invasion assays. Results: GBM patients with altered LOXs had poor survival. Upregulated LOXs were found in IDH1-wildtype and mesenchymal (not Loxl1) GBM subtypes, promoting ECM receptor interactions in GBM. The Loxl1-based nomogram and the PRSM showed high accuracy, reliability, and net clinical benefits. Loxl1 expression was related to tumor invasion and immune infiltration (B cells, neutrophils, and dendritic cells). Loxl1 knockdown suppressed GBM cell proliferation and invasion by inhibiting the EMT pathway (through the downregulation of N-cadherin/Vimentin/Snai1 and the upregulation of E-cadherin). Conclusion: The Loxl1-based nomogram and PRSM were stable and individualized for assessing GBM patient prognosis, and the invasive role of Loxl1 could provide a promising therapeutic strategy.

Multi-scale signaling and tumor evolution in high-grade gliomas.

Although genomic anomalies in glioblastoma (GBM) have been well studied for over a decade, its 5-year survival rate remains lower than 5%. We seek to expand the molecular landscape of high-grade glioma, composed of IDH-wildtype GBM and IDH-mutant grade 4 astrocytoma, by integrating proteomic, metabolomic, lipidomic, and post-translational modifications (PTMs) with genomic and transcriptomic measurements to uncover multi-scale regulatory interactions governing tumor development and evolution. Applying 14 proteogenomic and metabolomic platforms to 228 tumors (212 GBM and 16 grade 4 IDH-mutant astrocytoma), including 28 at recurrence, plus 18 normal brain samples and 14 brain metastases as comparators, reveals heterogeneous upstream alterations converging on common downstream events at the proteomic and metabolomic levels and changes in protein-protein interactions and glycosylation site occupancy at recurrence. Recurrent genetic alterations and phosphorylation events on PTPN11 map to important regulatory domains in three dimensions, suggesting a central role for PTPN11 signaling across high-grade gliomas.

Unraveling morphology, methylation profiling, and diagnostic challenges in BRAF-Mutant pediatric glial and glioneuronal tumors.

OBJECTIVES: To elucidate the relationship between DNA methylation profiling (DMP) and pathological diagnosis (PD) in pediatric glial and glioneuronal tumors with B-Raf proto-oncogene, serine/threonine kinase (BRAF) mutations, addressing their diagnostic challenges. METHODS: This retrospective study, conducted in Saudi Arabia, analyzed 47 cases from the Children's Brain Tumor Network online database using scanned images, next-generation sequencing data, and methylation profiles processed using the Heidelberg methylation brain tumor classifiers v12.5 and v12.8. The data was last access on 10 November 2023. RESULTS: The highest prevalence of BRAF mutations was observed in pilocytic astrocytoma and ganglioglioma. The DMP was consistent with PD in 23 cases, but discrepancies emerged in others, including diagnostic changes in diffuse leptomeningeal glioneuronal tumor and polymorphous low-grade neuroepithelial tumor of the young. A key inconsistency appeared between a pilocytic astrocytoma MC and a glioneuronal tumor PD. Two high-grade astrocytomas were misclassified as pleomorphic xanthoastrocytomas. Additionally, low variant allelic frequency in gangliogliomas likely contributed to misclassifications as control in 5 cases. CONCLUSION: This study emphasized the importance of integrating DMP with PD in diagnosing pediatric glial and glioneuronal tumors with BRAF mutations. Although DMP offers significant diagnostic insights, its limitations, particularly in cases with low tumor content, necessitate cautious interpretation, as well as its use as a complementary diagnostic tool, rather than a definitive method.