Value of long non-coding RNA HAS2-AS1 as a diagnostic and prognostic marker of glioma / El valor de ARNncl HAS2-AS1 como marcador diagnóstico y pronóstico del glioma

Background: Glioma presents high incidence and poor prognosis, and therefore more effective treatments are needed. Studies have confirmed that long non-coding RNAs (lncRNAs) basically regulate various human diseases including glioma. It has been theorized that HAS2-AS1 serves as an lncRNA to exert an oncogenic role in varying cancers. This study aimed to assess the value of lncRNA HAS2-AS1 as a diagnostic and prognostic marker for glioma. Methods: The miRNA expression data and clinical data of glioma were downloaded from the TCGA database for differential analysis and survival analysis. In addition, pathological specimens and specimens of adjacent normal tissue from 80 patients with glioma were used to observe the expression of HAS2-AS1. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic ability and prognostic value of HAS2-AS1 in glioma. Meanwhile, a Kaplan–Meier survival curve was plotted to evaluate the survival of glioma patients with different HAS2-AS1 expression levels. Results: HAS2-AS1 was significantly upregulated in glioma tissues compared with normal tissue. The survival curves showed that overexpression of HAS2-AS1 was associated with poor overall survival (OS) and progression-free survival (PFS). Several clinicopathological factors of glioma patients, including tumor size and WHO grade, were significantly correlated with HAS2-AS1 expression in tissues. The ROC curve showed an area under the curve (AUC) value of 0.863, indicating that HAS2-AS1 had good diagnostic value. The ROC curve for the predicted OS showed an AUC of 0.906, while the ROC curve for predicted PFS showed an AUC of 0.88. Both suggested that overexpression of HAS2-AS1 was associated with poor prognosis.Conclusions: Normal tissues could be clearly distinguished from glioma tissues based on HAS2-AS1 expression. Moreover, overexpression of HAS2-AS1 indicated poor prognosis in glioma patients.(AU)

Introducción: Los gliomas presentan una alta incidencia y un mal pronóstico, por lo que es necesario un tratamiento más efectivo. Algunos estudios han confirmado que los ARN no codificantes de cadena larga (ARNncl) regulan diferentes enfermedades, entre las que se incluyen los gliomas. Se ha postulado que HAS2-AS1 actúa como un ARNncl, con un efecto oncogénico en diferentes tipos de cáncer. Este estudio tiene como objetivo analizar el valor del ARNncl HAS2-AS1 como marcador diagnóstico y pronóstico de glioma. Métodos: Descargamos los datos clínicos y de expresión de micro-ARN de la base de datos del Atlas del Genoma del Cáncer (TCGA) para realizar el análisis diferencial y de supervivencia. También analizamos la expresión de HAS2-AS1 en muestras patológicas y muestras de tejido adyacente normal de 80 pacientes con glioma. Para analizar la capacidad diagnóstica y el valor pronóstico de HAS2-AS1 en el glioma, recurrimos a la curva ROC. También utilizamos curvas de Kaplan-Meier para evaluar la supervivencia de los pacientes con glioma con diferentes niveles de expresión de HAS2-AS1. Resultados: La expresión de HAS2-AS1 era significativamente mayor en las muestras patológicas que en el tejido normal. Las curvas de supervivencia demostraron que la sobreexpresión de HAS2-AS1 estaba relacionada con una menor supervivencia general y supervivencia libre de progresión. Algunos factores clínico-patológicos de los pacientes con glioma, como el tamaño del tumor y su grado, según la clasificación de la OMS, mostraron una correlación significativa con la expresión de HAS2-AS1 en los tejidos afectados. La curva ROC mostró un área bajo la curva de 0,863, lo que indica que la expresión de HAS2-AS1 posee un importante valor diagnóstico. El área bajo la curva de la supervivencia general estimada fue de 0,906; para la supervivencia libre de progresión estimada, de 0,88. Ambos valores muestran que la sobreexpresión de HAS2-AS1 se asocia con un mal pronóstico...(AU)

Value of long non-coding RNA HAS2-AS1 as a diagnostic and prognostic marker of glioma.

BACKGROUND: Glioma presents high incidence and poor prognosis, and therefore more effective treatments are needed. Studies have confirmed that long non-coding RNAs (lncRNAs) basically regulate various human diseases including glioma. It has been theorized that HAS2-AS1 serves as an lncRNA to exert an oncogenic role in varying cancers. This study aimed to assess the value of lncRNA HAS2-AS1 as a diagnostic and prognostic marker for glioma. METHODS: The miRNA expression data and clinical data of glioma were downloaded from the TCGA database for differential analysis and survival analysis. In addition, pathological specimens and specimens of adjacent normal tissue from 80 patients with glioma were used to observe the expression of HAS2-AS1. The receiver operating characteristic (ROC) curve was used to analyze the diagnostic ability and prognostic value of HAS2-AS1 in glioma. Meanwhile, a Kaplan-Meier survival curve was plotted to evaluate the survival of glioma patients with different HAS2-AS1 expression levels. RESULTS: HAS2-AS1 was significantly upregulated in glioma tissues compared with normal tissue. The survival curves showed that overexpression of HAS2-AS1 was associated with poor overall survival (OS) and progression-free survival (PFS). Several clinicopathological factors of glioma patients, including tumor size and WHO grade, were significantly correlated with HAS2-AS1 expression in tissues. The ROC curve showed an area under the curve (AUC) value of 0.863, indicating that HAS2-AS1 had good diagnostic value. The ROC curve for the predicted OS showed an AUC of 0.906, while the ROC curve for predicted PFS showed an AUC of 0.88. Both suggested that overexpression of HAS2-AS1 was associated with poor prognosis. CONCLUSIONS: Normal tissues could be clearly distinguished from glioma tissues based on HAS2-AS1 expression. Moreover, overexpression of HAS2-AS1 indicated poor prognosis in glioma patients. Therefore, HAS2-AS1 could be used as a diagnostic and prognostic marker for glioma.

TGIF2 is a potential biomarker for diagnosis and prognosis of glioma.

Background: TGFB-induced factor homeobox 2 (TGIF2), a member of the Three-Amino-acid-Loop-Extension (TALE) superfamily, has been implicated in various malignant tumors. However, its prognostic significance in glioma, impact on tumor immune infiltration, and underlying mechanisms in glioma development remain elusive. Methods: The expression of TGIF2 in various human normal tissues, normal brain tissues, and gliomas was investigated using HPA, TCGA, GTEx, and GEO databases. The study employed several approaches, including Kaplan-Meier analysis, ROC analysis, logistic regression, Cox regression, GO analysis, KEGG analysis, and GSEA, to explore the relationship between TGIF2 expression and clinicopathologic features, prognostic value, and potential biological functions in glioma patients. The impact of TGIF2 on tumor immune infiltration was assessed through Estimate, ssGSEA, and Spearman analysis. Genes coexpressed with TGIF2 were identified, and the protein-protein interaction (PPI) network of these coexpressed genes were constructed using the STRING database and Cytoscape software. Hub genes were identified using CytoHubba plugin, and their clinical predictive value was explored. Furthermore, in vitro experiments were performed by knocking down and knocking out TGIF2 using siRNA and CRISPR/Cas9 gene editing, and the role of TGIF2 in glioma cell invasion and migration was analyzed using transwell assay, scratch wound-healing assay, RT-qPCR, and Western blot. Results: TGIF2 mRNA was found to be upregulated in 21 cancers, including glioma. High expression of TGIF2 was associated with malignant phenotypes and poor prognosis in glioma patients, indicating its potential as an independent prognostic factor. Furthermore, elevated TGIF2 expression positively correlated with cell cycle regulation, DNA synthesis and repair, extracellular matrix (ECM) components, immune response, and several signaling pathways that promote tumor progression. TGIF2 showed correlations with Th2 cells, macrophages, and various immunoregulatory genes. The hub genes coexpressed with TGIF2 demonstrated significant predictive value. Additionally, in vitro experiments revealed that knockdown and knockout of TGIF2 inhibited glioma cell invasion, migration and suppressed the epithelial-mesenchymal transition (EMT) phenotype. Conclusion: TGIF2 emerges as a potential biomarker for glioma, possibly linked to tumor immune infiltration and EMT.

The MDM2-p53 Axis Represents a Therapeutic Vulnerability Unique to Glioma Stem Cells.

The prevention of tumor recurrence by the successful targeting of glioma stem cells endowed with a tumor-initiating capacity is deemed the key to the long-term survival of glioblastoma patients. Glioma stem cells are characterized by their marked therapeutic resistance; however, recent evidence suggests that they have unique vulnerabilities that may be therapeutically targeted. We investigated MDM2 expression levels in glioma stem cells and their non-stem cell counterparts and the effects of the genetic and pharmacological inhibition of MDM2 on the viability of these cells as well as downstream molecular pathways. The results obtained showed that MDM2 expression was substantially higher in glioma stem cells than in their non-stem cell counterparts and also that the inhibition of MDM2, either genetically or pharmacologically, induced a more pronounced activation of the p53 pathway and apoptotic cell death in the former than in the latter. Specifically, the inhibition of MDM2 caused a p53-dependent increase in the expression of BAX and PUMA and a decrease in the expression of survivin, both of which significantly contributed to the apoptotic death of glioma stem cells. The present study identified the MDM2-p53 axis as a novel therapeutic vulnerability, or an Achilles' heel, which is unique to glioma stem cells. Our results, which suggest that non-stem, bulk tumor cells are less sensitive to MDM2 inhibitors, may help guide the selection of glioblastoma patients suitable for MDM2 inhibitor therapy.

Transmembrane Protein TMEM230, Regulator of Glial Cell Vascular Mimicry and Endothelial Cell Angiogenesis in High-Grade Heterogeneous Infiltrating Gliomas and Glioblastoma.

High-grade gliomas (HGGs) and glioblastoma multiforme (GBM) are characterized by a heterogeneous and aggressive population of tissue-infiltrating cells that promote both destructive tissue remodeling and aberrant vascularization of the brain. The formation of defective and permeable blood vessels and microchannels and destructive tissue remodeling prevent efficient vascular delivery of pharmacological agents to tumor cells and are the significant reason why therapeutic chemotherapy and immunotherapy intervention are primarily ineffective. Vessel-forming endothelial cells and microchannel-forming glial cells that recapitulate vascular mimicry have both infiltration and destructive remodeling tissue capacities. The transmembrane protein TMEM230 (C20orf30) is a master regulator of infiltration, sprouting of endothelial cells, and microchannel formation of glial and phagocytic cells. A high level of TMEM230 expression was identified in patients with HGG, GBM, and U87-MG cells. In this study, we identified candidate genes and molecular pathways that support that aberrantly elevated levels of TMEM230 play an important role in regulating genes associated with the initial stages of cell infiltration and blood vessel and microchannel (also referred to as tumor microtubule) formation in the progression from low-grade to high-grade gliomas. As TMEM230 regulates infiltration, vascularization, and tissue destruction capacities of diverse cell types in the brain, TMEM230 is a promising cancer target for heterogeneous HGG tumors.

Pathway-based stratification of gliomas uncovers four subtypes with different TME characteristics and prognosis.

Increasing evidences have found that the interactions between hypoxia, immune response and metabolism status in tumour microenvironment (TME) have clinical importance of predicting clinical outcomes and therapeutic efficacy. This study aimed to develop a reliable molecular stratification based on these key components of TME. The TCGA data set (training cohort) and two independent cohorts from CGGA database (validation cohort) were enrolled in this study. First, the enrichment score of 277 TME-related signalling pathways was calculated by gene set variation analysis (GSVA). Then, consensus clustering identified four stable and reproducible subtypes (AFM, CSS, HIS and GLU) based on TME-related signalling pathways, which were characterized by differences in hypoxia and immune responses, metabolism status, somatic alterations and clinical outcomes. Among the four subtypes, HIS subtype had features of immunosuppression, oxygen deprivation and active energy metabolism, resulting in a worst prognosis. Thus, for better clinical application of this acquired stratification, we constructed a risk signature by using the LASSO regression model to identify patients in HIS subtype accurately. We found that the risk signature could accurately screen out the patients in HIS subtype and had important reference value for individualized treatment of glioma patients. In brief, the definition of the TME-related subtypes was a valuable tool for risk stratification in gliomas. It might serve as a reliable prognostic classifier and provide rational design of individualized treatment, and follow-up scheduling for patients with gliomas.

The plasma miRNome and venous thromboembolism in high-grade glioma: miRNA Sequencing of a nested case-control cohort.

Patients with high-grade gliomas are at high risk of venous thromboembolism (VTE). MicroRNAs (miRNAs) are small non-coding RNAs with multiple roles in tumour biology, haemostasis and platelet function. Their association with VTE risk in high-grade glioma has not been comprehensively mapped so far. We thus conducted a nested case-control study within 152 patients with WHO grade IV glioma that had been part of a prospective cohort study on VTE risk factors. At inclusion a single blood draw was taken, and patients were thereafter followed for a maximum of 2 years. During that time, 24 patients (16%) developed VTE. Of the other 128 patients, we randomly selected 24 age- and sex-matched controls. After quality control, the final group size was 21 patients with VTE during follow-up and 23 without VTE. Small RNA next-generation sequencing of plasma was performed. We observed that hsa-miR-451a was globally the most abundant miRNA. Notably, 51% of all miRNAs showed a correlation with platelet count. The analysis of miRNAs differentially regulated in VTE patients-with and without platelet adjustment-identified potential VTE biomarker candidates such as has-miR-221-3p. Therewith, we here provide one of the largest and deepest peripheral blood miRNA datasets of high-grade glioma patients so far, in which we identified first VTE biomarker candidates that can serve as the starting point for future research.

Pediatric-type high-grade gliomas with PDGFRA amplification in adult patients with Li-Fraumeni syndrome: clinical and molecular characterization of three cases.

Li-Fraumeni syndrome (LFS) is an autosomal dominant tumor predisposition syndrome caused by heterozygous germline mutations or deletions in the TP53 tumor suppressor gene. Central nervous system tumors, such as choroid plexus tumors, medulloblastomas, and diffuse gliomas, are frequently found in patients with LFS. Although molecular profiles of diffuse gliomas that develop in pediatric patients with LFS have been elucidated, those in adults are limited. Recently, diffuse gliomas have been divided into pediatric- and adult-type gliomas, based on their distinct molecular profiles. In the present study, we investigated the molecular profiles of high-grade gliomas in three adults with LFS. These tumors revealed characteristic histopathological findings of high-grade glioma or glioblastoma and harbored wild-type IDH1/2 according to whole exome sequencing (WES). However, these tumors did not exhibit the key molecular alterations of glioblastoma, IDH-wildtype such as TERT promoter mutation, EGFR amplification, or chromosome 7 gain and 10 loss. Although WES revealed no other characteristic gene mutations or copy number alterations in high-grade gliomas, such as those in histone H3 genes, PDGFRA amplification was found in all three cases together with uniparental disomy of chromosome 17p, where the TP53 gene is located. DNA methylation analyses revealed that all tumors exhibited DNA methylation profiles similar to those of pediatric-type high-grade glioma H3-wildtype and IDH-wildtype (pHGG H3-/IDH-wt), RTK1 subtype. These data suggest that high-grade gliomas developed in adult patients with LFS may be involved in pHGG H3-/IDH-wt. PDGFRA and homozygous alterations in TP53 may play pivotal roles in the development of this type of glioma in adult patients with LFS.

GRIK1 promotes glioblastoma malignancy and is a novel prognostic factor of poor prognosis.

Primary tumors of the central nervous system (CNS) are classified into over 100 different histological types. The most common type of glioma is derived from astrocytes, and the most invasive glioblastoma (WHO IV) accounts for over 57% of these tumors. Glioblastoma (GBM) is the most common and fatal tumor of the CNS, with strong growth and invasion capabilities, which makes complete surgical resection almost impossible. Despite various treatment methods such as surgery, radiotherapy, and chemotherapy, glioma is still an incurable disease, and the median survival time of patients with GBM is shorter than 15 months. Thus, molecular mechanisms of GBM characteristic invasive growth need to be clarified to improve the poor prognosis. Glutamate ionotropic receptor kainate type subunit 1 (GRIK1) is essential for brain function and is involved in many mental and neurological diseases. However, GRIK1's pathogenic roles and mechanisms in GBM are still unknown. Single-nuclear RNA sequencing of primary and recurrent GBM samples revealed that GRIK1 expression was noticeably higher in the recurrent samples. Moreover, immunohistochemical staining of an array of GBM samples showed that high levels of GRIK1 correlated with poor prognosis of GBM, consistent with The Cancer Genome Atlas database. Knockdown of GRIK1 retarded GBM cells growth, migration, and invasion. Taken together, these findings show that GRIK1 is a unique and important component in the development of GBM and may be considered as a biomarker for the diagnosis and therapy in individuals with GBM.

[MiR-26-3p regulates proliferation, migration, invasion and apoptosis of glioma cells by targeting CREB1].

OBJECTIVE: To investigate the regulatory role of miR-26b-3p in proliferation, migration and invasion of glioma. METHODS: The expressions of miR-26b-3p and cAMP-responsive element binding protein 1 (CREB1) in gliomas of different pathological grades were detected with RT-qPCR and Western blotting. Bioinformatic methods were used to analyze the target sequence of miRNA-26b-3p binding to CREB1, and dual luciferase gene reporter experiment was performed to explore the mechanism for targeted regulation of CREB1 by miR-26b-3p. Glioma U251 cells were treated with miR-26b-3p mimic or inhibitor, and the changes in CREB1 expression and cell proliferation, migration, invasion and apoptosis were determined with Western blotting, CCK-8 assay, wound healing assay, Transwell assay, and flow cytometry. RESULTS: The expression of miR-26b-3p decreased while CREB1 expression increased significantly as the pathological grade of gliomas increased (P < 0.05). Dual luciferase gene reporter experiment confirmed that CREB1 was a downstream target of miR-26b-3p. Inhibition of miR-26b-3p significantly upregulated the expression of CERB1, suppressed apoptosis and promoted proliferation and invasion of glioma cells, and overexpression of miR-26b-3p produced the opposite effects (P < 0.05). CONCLUSION: MiR-26b-3p regulates CREB1 expression to modulate apoptosis, proliferation, migration and invasion of glioma cells, thereby participating in tumorigenesis and progression of glioma.

Abnormal expression of long non­coding RNA LINC01270 in glioma and its correlation with X­ray computed tomography signs.

This study focused on the association of LINC01270 and computed tomography (CT) signs with glioma development, to evaluate their potential in the early detection of glioma. Serum LINC01270 was evaluated in glioma patients and healthy individuals using PCR. The involvement of LINC01270 in glioma onset and development was evaluated by ROC and chi­square test. The association of LINC01270 with the CT signs and their combined effects in the diagnosis in glioma were also estimated. Serum LINC01270 was significantly elevated in glioma patients, which was closely associated with patients' advanced WHO grades and lower KPS. Both LINC01270 upregulation and CT findings showed significant potential in diagnosing glioma, and LINC01270 correlated significantly with the invasion risk and metastasis indicated on CT. The combination of LINC01270 expression and CT findings significantly improved the sensitivity and specificity of glioma diagnosis. Upregulated LINC01270 in glioma is associated with malignant and severe disease development and has significant diagnostic value. Combined detection of LINC01270 and CT findings could improve the diagnostic efficacy in glioma cases, thus optimizing clinical diagnosis.

Dual-space disentangled-multimodal network (DDM-net) for glioma diagnosis and prognosis with incomplete pathology and genomic data.

Objective. Effective fusion of histology slides and molecular profiles from genomic data has shown great potential in the diagnosis and prognosis of gliomas. However, it remains challenging to explicitly utilize the consistent-complementary information among different modalities and create comprehensive representations of patients. Additionally, existing researches mainly focus on complete multi-modality data and usually fail to construct robust models for incomplete samples.Approach. In this paper, we propose adual-space disentangled-multimodal network (DDM-net)for glioma diagnosis and prognosis. DDM-net disentangles the latent features generated by two separate variational autoencoders (VAEs) into common and specific components through a dual-space disentangled approach, facilitating the construction of comprehensive representations of patients. More importantly, DDM-net imputes the unavailable modality in the latent feature space, making it robust to incomplete samples.Main results. We evaluated our approach on the TCGA-GBMLGG dataset for glioma grading and survival analysis tasks. Experimental results demonstrate that the proposed method achieves superior performance compared to state-of-the-art methods, with a competitive AUC of 0.952 and a C-index of 0.768.Significance. The proposed model may help the clinical understanding of gliomas and can serve as an effective fusion model with multimodal data. Additionally, it is capable of handling incomplete samples, making it less constrained by clinical limitations.

SIRPB1 regulates inflammatory factor expression in the glioma microenvironment via SYK: functional and bioinformatics insights.

BACKGROUND: SIRPB1 expression is upregulated in various tumor types, including gliomas, and is known to contribute to tumor progression; nevertheless, its function in the immune milieu of gliomas is still mainly unknown. METHODS: This study, we analyzed 1152 normal samples from the GTEx database and 670 glioma samples from the TCGA database to investigate the relationship between the expression of SIRPB1 and clinicopathological features. Moreover, SIRPB1 gene knockout THP-1 cell lines were constructed using CRISPR/Cas9 and were induced into a co-culture of macrophages and glioma cells in vitro to learn more about the role of SIRPB1 in the glioma immune milieu. Lastly, we established a prognostic model to predict the effect of SIRPB1 on prognosis. RESULTS: Significantly higher levels of SIRPB1 expression were found in gliomas, which had an adverse effect on the immune milieu and correlated poorly with patient survival. SIRPB1 activation with certain antibodies results in SYK phosphorylation and the subsequent activation of calcium, MAPK, and NF-κB signaling pathways. This phenomenon is primarily observed in myeloid-derived cells as opposed to glioma cells. In vitro co-culture demonstrated that macrophages with SIRPB1 knockout showed decreased IL1RA, CCL2, and IL-8, which were recovered upon ectopic expression of SIRPB1 but reduced again following treatment with SYK inhibitor GS9973. Critically, a lower overall survival rate was linked to increased SIRPB1 expression. Making use of SIRPB1 expression along with additional clinicopathological variables, we established a nomogram that showed a high degree of prediction accuracy. CONCLUSIONS: Our study demonstrates that glioma cells can be activated by macrophages via SIRPB1, subsequently reprogramming the TME, suggesting that SIRPB1 could serve as a promising therapeutic target for gliomas.

Amide proton transfer weighted and diffusion weighted imaging based radiomics classification algorithm for predicting 1p/19q co-deletion status in low grade gliomas.

BACKGROUND: 1p/19q co-deletion in low-grade gliomas (LGG, World Health Organization grade II and III) is of great significance in clinical decision making. We aim to use radiomics analysis to predict 1p/19q co-deletion in LGG based on amide proton transfer weighted (APTw), diffusion weighted imaging (DWI), and conventional MRI. METHODS: This retrospective study included 90 patients histopathologically diagnosed with LGG. We performed a radiomics analysis by extracting 8454 MRI-based features form APTw, DWI and conventional MR images and applied a least absolute shrinkage and selection operator (LASSO) algorithm to select radiomics signature. A radiomics score (Rad-score) was generated using a linear combination of the values of the selected features weighted for each of the patients. Three neuroradiologists, including one experienced neuroradiologist and two resident physicians, independently evaluated the MR features of LGG and provided predictions on whether the tumor had 1p/19q co-deletion or 1p/19q intact status. A clinical model was then constructed based on the significant variables identified in this analysis. A combined model incorporating both the Rad-score and clinical factors was also constructed. The predictive performance was validated by receiver operating characteristic curve analysis, DeLong analysis and decision curve analysis. P < 0.05 was statistically significant. RESULTS: The radiomics model and the combined model both exhibited excellent performance on both the training and test sets, achieving areas under the curve (AUCs) of 0.948 and 0.966, as well as 0.909 and 0.896, respectively. These results surpassed the performance of the clinical model, which achieved AUCs of 0.760 and 0.766 on the training and test sets, respectively. After performing Delong analysis, the clinical model did not significantly differ in predictive performance from three neuroradiologists. In the training set, both the radiomic and combined models performed better than all neuroradiologists. In the test set, the models exhibited higher AUCs than the neuroradiologists, with the radiomics model significantly outperforming resident physicians B and C, but not differing significantly from experienced neuroradiologist. CONCLUSIONS: Our results suggest that our algorithm can noninvasively predict the 1p/19q co-deletion status of LGG. The predictive performance of radiomics model was comparable to that of experienced neuroradiologist, significantly outperforming the diagnostic accuracy of resident physicians, thereby offering the potential to facilitate non-invasive 1p/19q co-deletion prediction of LGG.

EGFR/CEP7 high polysomy is separate and distinct from EGFR amplification in glioblastoma as determined by fluorescence in situ hybridization.

EGFR amplification in gliomas is commonly defined by an EGFR/CEP7 ratio of ≥2. In testing performed at a major reference laboratory, a small subset of patients had ≥5 copies of both EGFR and CEP7 yet were not amplified by the EGFR/CEP7 ratio and were designated high polysomy cases. To determine whether these tumors are more closely related to traditionally defined EGFR-amplified or nonamplified gliomas, a retrospective search identified 22 out of 1143 (1.9%) gliomas with an average of ≥5 copies/cell of EGFR and CEP7 with an EGFR/CEP7 ratio of <2 displaying high polysomy. Of these cases, 4 had insufficient clinicopathologic data to include in additional analysis, 15 were glioblastomas, 2 were IDH-mutant astrocytomas, and 1 was a high-grade glial neoplasm, NOS. Next-generation sequencing available on 3 cases demonstrated one with a TERT promoter mutation, TP53 mutations in all cases, and no EGFR mutations or amplifications, which most closely matched the nonamplified cases. The median overall survival times were 42.86, 66.07, and 41.14 weeks for amplified, highly polysomic, and nonamplified, respectively, and were not significantly different (p = 0.3410). High chromosome 7 polysomic gliomas are rare but our data suggest that they may be biologically similar to nonamplified gliomas.

BCOR::CREBBP fusion in malignant neuroepithelial tumor of CNS expands the spectrum of methylation class CNS tumor with BCOR/BCOR(L1)-fusion.

Methylation class "CNS tumor with BCOR/BCOR(L1)-fusion" was recently defined based on methylation profiling and tSNE analysis of a series of 21 neuroepithelial tumors with predominant presence of a BCOR fusion and/or characteristic CNV breakpoints at chromosome 22q12.31 and chromosome Xp11.4. Clear diagnostic criteria are still missing for this tumor type, specially that BCOR/BCOR(L1)-fusion is not a consistent finding in these tumors despite being frequent and that none of the Heidelberger classifier versions is able to clearly identify these cases, in particular tumors with alternative fusions other than those involving BCOR, BCORL1, EP300 and CREBBP. In this study, we introduce a BCOR::CREBBP fusion in an adult patient with a right temporomediobasal tumor, for the first time in association with methylation class "CNS tumor with BCOR/BCOR(L1)-fusion" in addition to 35 cases of CNS neuroepithelial tumors with molecular and histopathological characteristics compatible with "CNS tumor with BCOR/BCOR(L1)-fusion" based on a comprehensive literature review and data mining in the repository of 23 published studies on neuroepithelial brain Tumors including 7207 samples of 6761 patients. Based on our index case and the 35 cases found in the literature, we suggest the archetypical histological and molecular features of "CNS tumor with BCOR/BCOR(L1)-fusion". We also present four adult diffuse glioma cases including GBM, IDH-Wildtype and Astrocytoma, IDH-Mutant with CREBBP fusions and describe the necessity of complementary molecular analysis in "CNS tumor with BCOR/BCOR(L1)-alterations for securing a final diagnosis.

GPR27 expression correlates with prognosis and tumor progression in gliomas.

Backgrounds: Glioma is a highly aggressive type of brain tumor, and its prognosis is still poor despite recent progress in treatment strategies. G protein-coupled receptor 27 (GPR27) is a member of the G protein-coupled receptor family and has been reported to be involved in various cellular processes, including tumor progression. Nevertheless, the clinical potential and tumor-related role of GPR27 in glioma remain unknown. Here we aimed to explore the function and role of GPR27 in gliomas. Methods: In the current study, we evaluated the expression and clinical significance of GPR27 in gliomas using data from The Cancer Genome Atlas (TCGA) datasets. We also conducted cellular experiments to evaluate the functional role of GPR27 in glioma cell growth. Results: We found that GPR27 expression level was closely associated with disease status of glioma. Of note, GPR27 was negatively correlated with WHO grade, with grade IV samples showing the lowest GPR27 levels, while grade II samples showed the highest levels. Patients with IDH mutation or 1p/19q co-deletion exhibited higher GPR27 levels. In addition, lower GPR27 levels were correlated with higher death possibilities. In cellular experiments, we confirmed that GPR27 inhibited glioma cell growth. Conclusions: Our results indicate that GPR27 may function as a potential prognostic biomarker and therapeutic target in gliomas. Further studies are needed to illustrate the signaling mechanism and clinical implications of GPR27 in gliomas.

Demographic bias in misdiagnosis by computational pathology models.

Despite increasing numbers of regulatory approvals, deep learning-based computational pathology systems often overlook the impact of demographic factors on performance, potentially leading to biases. This concern is all the more important as computational pathology has leveraged large public datasets that underrepresent certain demographic groups. Using publicly available data from The Cancer Genome Atlas and the EBRAINS brain tumor atlas, as well as internal patient data, we show that whole-slide image classification models display marked performance disparities across different demographic groups when used to subtype breast and lung carcinomas and to predict IDH1 mutations in gliomas. For example, when using common modeling approaches, we observed performance gaps (in area under the receiver operating characteristic curve) between white and Black patients of 3.0% for breast cancer subtyping, 10.9% for lung cancer subtyping and 16.0% for IDH1 mutation prediction in gliomas. We found that richer feature representations obtained from self-supervised vision foundation models reduce performance variations between groups. These representations provide improvements upon weaker models even when those weaker models are combined with state-of-the-art bias mitigation strategies and modeling choices. Nevertheless, self-supervised vision foundation models do not fully eliminate these discrepancies, highlighting the continuing need for bias mitigation efforts in computational pathology. Finally, we demonstrate that our results extend to other demographic factors beyond patient race. Given these findings, we encourage regulatory and policy agencies to integrate demographic-stratified evaluation into their assessment guidelines.

Multi-omics technologies and molecular biomarkers in brain tumor-related epilepsy.

BACKGROUND: Brain tumors are one of the leading causes of epilepsy, and brain tumor-related epilepsy (BTRE) is recognized as the major cause of intractable epilepsy, resulting in huge treatment cost and burden to patients, their families, and society. Although optimal treatment regimens are available, the majority of patients with BTRE show poor resolution of symptoms. BTRE has a very complex and multifactorial etiology, which includes several influencing factors such as genetic and molecular biomarkers. Advances in multi-omics technologies have enabled to elucidate the pathophysiological mechanisms and related biomarkers of BTRE. Here, we reviewed multi-omics technology-based research studies on BTRE published in the last few decades and discussed the present status, development, opportunities, challenges, and prospects in treating BTRE. METHODS: First, we provided a general review of epilepsy, BTRE, and multi-omics techniques. Next, we described the specific multi-omics (including genomics, transcriptomics, epigenomics, proteomics, and metabolomics) techniques and related molecular biomarkers for BTRE. We then presented the associated pathogenetic mechanisms of BTRE. Finally, we discussed the development and application of novel omics techniques for diagnosing and treating BTRE. RESULTS: Genomics studies have shown that the BRAF gene plays a role in BTRE development. Furthermore, the BRAF V600E variant was found to induce epileptogenesis in the neuronal cell lineage and tumorigenesis in the glial cell lineage. Several genomics studies have linked IDH variants with glioma-related epilepsy, and the overproduction of D2HG is considered to play a role in neuronal excitation that leads to seizure occurrence. The high expression level of Forkhead Box O4 (FOXO4) was associated with a reduced risk of epilepsy occurrence. In transcriptomics studies, VLGR1 was noted as a biomarker of epileptic onset in patients. Several miRNAs such as miR-128 and miRNA-196b participate in BTRE development. miR-128 might be negatively associated with the possibility of tumor-related epilepsy development. The lncRNA UBE2R2-AS1 inhibits the growth and invasion of glioma cells and promotes apoptosis. Quantitative proteomics has been used to determine dynamic changes of protein acetylation in epileptic and non-epileptic gliomas. In another proteomics study, a high expression of AQP-4 was detected in the brain of GBM patients with seizures. By using quantitative RT-PCR and immunohistochemistry assay, a study revealed that patients with astrocytomas and oligoastrocytomas showed high BCL2A1 expression and poor seizure control. By performing immunohistochemistry, several studies have reported the relationship between D2HG overproduction and seizure occurrence. Ki-67 overexpression in WHO grade II gliomas was found to be associated with poor postoperative seizure control. According to metabolomics research, the PI3K/AKT/mTOR pathway is associated with the development of glioma-related epileptogenesis. Another metabolomics study found that SV2A, P-gb, and CAD65/67 have the potential to function as biomarkers for BTRE. CONCLUSIONS: Based on the synthesized information, this review provided new research perspectives and insights into the early diagnosis, etiological factors, and personalized treatment of BTRE.

Whole brain morphologic features improve the predictive accuracy of IDH status and VEGF expression levels in gliomas.

Glioma is a systemic disease that can induce micro and macro alternations of whole brain. Isocitrate dehydrogenase and vascular endothelial growth factor are proven prognostic markers and antiangiogenic therapy targets in glioma. The aim of this study was to determine the ability of whole brain morphologic features and radiomics to predict isocitrate dehydrogenase status and vascular endothelial growth factor expression levels. This study recruited 80 glioma patients with isocitrate dehydrogenase wildtype and high vascular endothelial growth factor expression levels, and 102 patients with isocitrate dehydrogenase mutation and low vascular endothelial growth factor expression levels. Virtual brain grafting, combined with Freesurfer, was used to compute morphologic features including cortical thickness, LGI, and subcortical volume in glioma patient. Radiomics features were extracted from multiregional tumor. Pycaret was used to construct the machine learning pipeline. Among the radiomics models, the whole tumor model achieved the best performance (accuracy 0.80, Area Under the Curve 0.86), while, after incorporating whole brain morphologic features, the model had a superior predictive performance (accuracy 0.82, Area Under the Curve 0.88). The features contributed most in predicting model including the right caudate volume, left middle temporal cortical thickness, first-order statistics, shape, and gray-level cooccurrence matrix. Pycaret, based on morphologic features, combined with radiomics, yielded highest accuracy in predicting isocitrate dehydrogenase mutation and vascular endothelial growth factor levels, indicating that morphologic abnormalities induced by glioma were associated with tumor biology.