From Theory to Practice: Implementing the WHO 2021 Classification of Adult Diffuse Gliomas in Neuropathology Diagnosis

Martin, K K; Ma, Crystal; Yip, Stephen

doi:10.3390/brainsci13050817

Cited by 6 publications

(2 citation statements)

References 104 publications

(125 reference statements)

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“…Diffusely infiltrating gliomas are the most common primary CNS malignancies affecting the adult population and are classified into three distinct entities based on histopathology [8]. Characteristically, these neoplasms exhibit infiltrative growth, with tumor cells invading normal CNS tissues, thereby giving rise to recurrence and complicating conventional treatments [62,63]. Since the fifth edition of the WHO classification, the characterization of diffuse gliomas has heavily incorporated molecular alterations, which are crucial for defining both entity grades [64].…”

Section: Discussionmentioning

confidence: 99%

MUC1andMUC4expression are inversely correlated and trigger immunological response and transport pathways in gliomas

Machado,

Ferrer

2024

Preprint

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Diffuse gliomas are tumors that arise from glial or glial progenitor cells. They are currently classified as astrocytoma isocitrate dehydrogenase (IDH)-mutant or oligodendroglioma IDH-mutant, and chromosome arms 1p/19q-codeleted, both slower-growing tumors, or glioblastoma (GBM), a more aggressive tumor. Despite advances in the diagnosis and treatment of gliomas, the median survival time after diagnosis of GBM remains low, approximately 15 months, with a 5-year overall survival rate of only 6.8%. Therefore, new biomarkers and therapy targets that could support better prognosis of these tumors would be of great value. MUC1 and MUC4, membrane-bound mucins, has been identified as a potential biomarker in several tumors. However, the role of these mucins in adult gliomas has not yet been well explored. Here, we show for the first time, in a retrospective study and byin silicoanalysis, the relevance and correlation of these genes in adult gliomas. Analysis of adult diffuse glioma patient cohorts revealed differential methylation and expression patterns of MUC1 and MUC4 across GBM and non-GBM subtypes. GBM patients exhibited decreased MUC1 methylation and elevated expression (r-0.25, p < 0.0001) whereas increased MUC4 methylation and its lower expression (r-0.13, p = 0.1344). Conversely, in non-GBM patients, MUC1 showed higher methylation levels and low expression (r-0.27, p < 0.0001) whereas MUC4 showed lower methylation levels and high expression (r-0.32, p < 0.0001). The expression levels of these genes influenced overall survival (OS) in gliomas patients (p = 0.0344), with high MUC1 and low MUC4 expression associated with worse OS. MUC1 and MUC4 correlated with MUC20 in both GBM (r = 0.54) and non-GBM (r = 0.53) patients (p < 0.0001). Functional enrichment analysis revealed distinct biological roles for co-expressed genes with MUC1 involvement in innate immunity, antigen processing, pro-inflammatory responses in both non-GBM and GBM cohorts, and integrin-based signaling pathways in GBM patients. MUC4 co-expressed genes were involved in ion transport in GBM patients. Using molecular docking, we observed that MUC1 has domains that are physically capable of interacting with immune response-related proteins such as Receptor for Advanced Glycation End-products (RAGE), Major Histocompatibility Complex II (MHCII), and extracellular matrix receptor integrin alpha 2 (ITGA2). These findings shed light on the molecular mechanisms underlying glioma progression and highlight MUC1 and MUC4 as potential prognostic markers and therapeutic targets in glioma management.

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Section: Discussionmentioning

confidence: 99%

MUC1andMUC4expression are inversely correlated and trigger immunological response and transport pathways in gliomas

Machado,

Ferrer

2024

Preprint

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“…Examples in adults are IDH mutant astrocytoma; IDH mutant oligodendroglioma and codeletions 1p/19q; glioblastoma, IDH-wild-type. In children, the examples are as follows: diffuse hemispheric glioma with H3 G34R mutation and HGGs with wild-type H3 and IDH genes [133,134]. Alongside molecular investigations on tissues and tumor cells, the advancement of tumor imaging techniques contributes to the identification and typing of lesions, the prediction of metastasis and, ultimately, the prognosis of patient survival.…”

Section: Modelling the Diagnosis Of Hggmentioning

confidence: 99%

Advancements in Image-Based Models for High-Grade Gliomas Might Be Accelerated

Frosina

2024

Cancers

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The first half of 2022 saw the publication of several major research advances in image-based models and artificial intelligence applications to optimize treatment strategies for high-grade gliomas, the deadliest brain tumors. We review them and discuss the barriers that delay their entry into clinical practice; particularly, the small sample size and the heterogeneity of the study designs and methodologies used. We will also write about the poor and late palliation that patients suffering from high-grade glioma can count on at the end of life, as well as the current legislative instruments, with particular reference to Italy. We suggest measures to accelerate the gradual progress in image-based models and end of life care for patients with high-grade glioma.

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Comparative Morphological and Molecular Genetic Characteristics of Cell and Tissue Strains of Experimental Rat Glioma 10-17-2 (Astrid-17)

Alekseeva,

Kudelkina,

Khalansky

et al. 2024

Bull Exp Biol Med

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From Theory to Practice: Implementing the WHO 2021 Classification of Adult Diffuse Gliomas in Neuropathology Diagnosis

Cited by 6 publications

References 104 publications

MUC1andMUC4expression are inversely correlated and trigger immunological response and transport pathways in gliomas

MUC1andMUC4expression are inversely correlated and trigger immunological response and transport pathways in gliomas

Advancements in Image-Based Models for High-Grade Gliomas Might Be Accelerated

Comparative Morphological and Molecular Genetic Characteristics of Cell and Tissue Strains of Experimental Rat Glioma 10-17-2 (Astrid-17)

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