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Biomedicines
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Mechanisms and Novel Therapeutic Approaches for Gliomas
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Mechanisms and Novel Therapeutic Approaches for Gliomas

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Cancer Biology and Oncology".

Deadline for manuscript submissions: closed (31 July 2025) | Viewed by 13988

Special Issue Editor

Dr. Maria V. Chatziathanasiadou

E-Mail Website
Guest Editor
Honorary Research Associate, Department of Brain Sciences, Faculty of Medicine, Imperial College London, London, UK
Interests: glioblastoma; metabolic therapies; immunotherapies; tumour microenvironment; cancer drug discovery
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Gliomas, the most common type of primary malignant brain tumour, present significant clinical challenges. This is mainly due to their invasive nature, intratumour heterogeneity, immunosuppressive microenvironment, and the presence of the blood–brain barrier. Little progress has been achieved in glioma treatment over the last few decades, while the main therapeutic options are surgery, radiotherapy, and chemotherapy. Thus, there is an imperative need to deepen our current understanding of glioma mechanisms and develop cutting-edge therapeutic strategies.

This Special Issue aims to cover molecular and cellular glioma mechanisms, including molecular markers, signaling, tumour landscape, cell crosstalk, and immunity, as well as novel therapeutic approaches, such as metabolic therapies, immunotherapies, newly designed and repurposed drugs, and combination treatments.

We also welcome review manuscripts that present recently discovered molecular markers, therapeutic targets, tumour landscape characteristics, or innovative therapies from preclinical studies and clinical trials.

Dr. Maria V. Chatziathanasiadou
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomedicines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • glioma
  • molecular mechanisms
  • signaling
  • tumour immunity
  • tumour metabolism
  • tumour microenvironment
  • metabolic therapies
  • immunotherapies
  • combination treatment

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Related Special Issue

Published Papers (6 papers)

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Research

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18 pages, 2121 KB  
Article
Gender- and Grade-Dependent Activation of Androgen Receptor Signaling in Adult-Type Diffuse Gliomas: Epigenetic Insights from a Retrospective Cohort Study
by Lidia Gatto, Sofia Asioli, Luca Morandi, Enrico Di Oto, Vincenzo Di Nunno, Alicia Tosoni, Marta Aprile, Stefania Bartolini, Lucia Griva, Sofia Melotti, Francesca Gentilini, Giuseppe Pinto, Francesco Casadei, Maria Pia Foschini, Caterina Tonon, Raffaele Lodi and Enrico Franceschi
Biomedicines 2025, 13(10), 2379; https://doi.org/10.3390/biomedicines13102379 - 28 Sep 2025
Viewed by 385
Abstract
Background: The androgen receptor (AR) is a ligand-dependent transcription factor of the nuclear steroid receptor superfamily, implicated in the pathogenesis of various solid tumors. The AR gene, located on chromosome Xq11–12, is accompanied by several X-linked genes that modulate AR expression and [...] Read more.
Background: The androgen receptor (AR) is a ligand-dependent transcription factor of the nuclear steroid receptor superfamily, implicated in the pathogenesis of various solid tumors. The AR gene, located on chromosome Xq11–12, is accompanied by several X-linked genes that modulate AR expression and function, including FLNA, UXT, and members of the melanoma antigen gene (MAGE) family (MAGEA1, MAGEA11, MAGEC1, MAGEC2). While the AR has been investigated in multiple tumor types, its role in adult-type diffuse gliomas remains largely unexplored. Here, we characterized AR protein expression and the promoter methylation status of the AR and associated regulatory genes in adult-type diffuse gliomas. Methods: A retrospective analysis was conducted on 50 patients with adult-type diffuse gliomas, including IDH-mutant gliomas (grades 2–4) and IDH-wildtype glioblastomas (GBMs), classified according to the 2021 WHO criteria. AR nuclear expression was assessed by immunohistochemistry (IHC). Methylation-specific PCR and quantitative DNA methylation analyses were employed to evaluate promoter methylation of the AR and selected co-regulatory genes. Results: AR nuclear positivity correlated significantly with male sex (p = 0.04) and higher tumor grade, with the highest expression in IDH-wildtype GBMs (p = 0.04). In IDH-mutant gliomas, AR immunoreactivity was more prevalent in astrocytomas than in 1p/19q codeleted oligodendrogliomas (p = 0.02). AR expression was associated with unmethylated MGMT promoter status (p = 0.02). DNA methylation analysis revealed AR gene hypomethylation in tumors displaying nuclear AR positivity and in IDH-wildtype GBMs (Kruskal–Wallis p < 0.05). Additionally, methylation patterns of AR co-regulators located on the X chromosome suggest epigenetic regulation of AR signaling in gliomas. Conclusions: The findings reveal distinct AR pathway activation patterns in adult-type diffuse gliomas, particularly IDH-wildtype GBMs, suggesting that further exploration of antiandrogen therapies is warranted. Full article
(This article belongs to the Special Issue Mechanisms and Novel Therapeutic Approaches for Gliomas)
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14 pages, 5518 KB  
Article
NOD2 Promotes Glioblastoma Progression Through Effects on Epithelial–Mesenchymal Transition and Cancer Stemness
by Eshrat Jahan, Shubhash Chandra Chaudhary, S M Abdus Salam, Eun-Jung Ahn, Nah Ihm Kim, Tae-Young Jung, Jong-Hwan Park, Sung Sun Kim, Ji Young Lee, Kyung-Hwa Lee and Kyung-Sub Moon
Biomedicines 2025, 13(8), 2041; https://doi.org/10.3390/biomedicines13082041 - 21 Aug 2025
Viewed by 3904
Abstract
Background: Glioblastoma multiforme (GBM) represents one of the most aggressive and lethal primary brain malignancies, characterized by rapid proliferation, extensive invasiveness, and a dismal prognosis. Emerging evidence implicates nucleotide-binding oligomerization domain-containing protein 2 (NOD2), an intracellular pattern recognition receptor, as [...] Read more.
Background: Glioblastoma multiforme (GBM) represents one of the most aggressive and lethal primary brain malignancies, characterized by rapid proliferation, extensive invasiveness, and a dismal prognosis. Emerging evidence implicates nucleotide-binding oligomerization domain-containing protein 2 (NOD2), an intracellular pattern recognition receptor, as a potential driver of GBM progression. This study investigates NOD2’s role in promoting glioblastoma through its effects on the epithelial–mesenchymal transition (EMT) and cancer stem cell (CSC) markers. Methods: NOD2 expression levels and survival outcomes were assessed using TCGA data from GBM tumor samples (n = 153) and normal brain tissues (n = 5). NOD2 protein expression was validated in glioma cell lines using Western blot and immunofluorescence analyses. Functional studies employed siRNA-mediated NOD2 knockdown to evaluate effects on cellular proliferation, migration, invasion, and colony formation, while correlations between NOD2 and EMT/CSC markers were assessed. Results: The analysis of TCGA data revealed a significantly elevated NOD2 expression in GBM tumors compared to normal brain tissue, with a high NOD2 expression correlating with a reduced disease-free survival in GBM patients. All tested glioma cell lines demonstrated robust NOD2 expression. Functional analyses demonstrated that NOD2 depletion substantially impaired cellular proliferation, migration, invasion, and the colony-forming capacity. Mechanistically, siRNA-mediated NOD2 knockdown significantly decreased the expression of EMT (Snail, SLUG, Vimentin) and CSC markers (CD44, CD133) at both protein and mRNA levels. Conclusions: Our results indicate that NOD2 contributes to GBM progression by influencing EMT and CSC pathways. These findings suggest NOD2’s potential as a therapeutic target in glioblastoma, highlighting the need for further mechanistic studies and therapeutic exploration. Full article
(This article belongs to the Special Issue Mechanisms and Novel Therapeutic Approaches for Gliomas)
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Review

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30 pages, 3101 KB  
Review
Artificial Intelligence in the Diagnosis and Treatment of Brain Gliomas
by Kyriacos Evangelou, Ioannis Kotsantis, Aristotelis Kalyvas, Anastasios Kyriazoglou, Panagiota Economopoulou, Georgios Velonakis, Maria Gavra, Amanda Psyrri, Efstathios J. Boviatsis and Lampis C. Stavrinou
Biomedicines 2025, 13(9), 2285; https://doi.org/10.3390/biomedicines13092285 - 17 Sep 2025
Viewed by 985
Abstract
Brain gliomas are highly infiltrative and heterogenous tumors, whose early and accurate detection as well as therapeutic management are challenging. Artificial intelligence (AI) has the potential to redefine the landscape in neuro-oncology and can enhance glioma detection, imaging segmentation, and non-invasive molecular characterization [...] Read more.
Brain gliomas are highly infiltrative and heterogenous tumors, whose early and accurate detection as well as therapeutic management are challenging. Artificial intelligence (AI) has the potential to redefine the landscape in neuro-oncology and can enhance glioma detection, imaging segmentation, and non-invasive molecular characterization better than conventional diagnostic modalities through deep learning-driven radiomics and radiogenomics. AI algorithms have been shown to predict genotypic and phenotypic glioma traits with remarkable accuracy and facilitate patient-tailored therapeutic decision-making. Such algorithms can be incorporated into surgical planning to optimize resection extent while preserving eloquent cortical structures through preoperative imaging fusion and intraoperative augmented reality-assisted navigation. Beyond resection, AI may assist in radiotherapy dose distribution optimization, thus ensuring maximal tumor control while minimizing surrounding tissue collateral damage. AI-guided molecular profiling and treatment response prediction models can facilitate individualized chemotherapy regimen tailoring, especially for glioblastomas with MGMT promoter methylation. Applications in immunotherapy are emerging, and research is focusing on AI to identify tumor microenvironment signatures predictive of immune checkpoint inhibition responsiveness. AI-integrated prognostic models incorporating radiomic, histopathologic, and clinical variables can additionally improve survival stratification and recurrence risk prediction remarkably, to refine follow-up strategies in high-risk patients. However, data heterogeneity, algorithmic transparency concerns, and regulatory challenges hamstring AI implementation in neuro-oncology despite its transformative potential. It is therefore imperative for clinical translation to develop interpretable AI frameworks, integrate multimodal datasets, and robustly validate externally. Future research should prioritize the creation of generalizable AI models, combine larger and more diverse datasets, and integrate multimodal imaging and molecular data to overcome these obstacles and revolutionize AI-assisted patient-specific glioma management. Full article
(This article belongs to the Special Issue Mechanisms and Novel Therapeutic Approaches for Gliomas)
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19 pages, 507 KB  
Review
Radiomics and Radiogenomics in Differentiating Progression, Pseudoprogression, and Radiation Necrosis in Gliomas
by Sohil Reddy, Tyler Lung, Shashank Muniyappa, Christine Hadley, Benjamin Templeton, Joel Fritz, Daniel Boulter, Keshav Shah, Raj Singh, Simeng Zhu, Jennifer K. Matsui and Joshua D. Palmer
Biomedicines 2025, 13(7), 1778; https://doi.org/10.3390/biomedicines13071778 - 21 Jul 2025
Cited by 2 | Viewed by 2241
Abstract
Over recent decades, significant advancements have been made in the treatment and imaging of gliomas. Conventional imaging techniques, such as MRI and CT, play critical roles in glioma diagnosis and treatment but often fail to distinguish between tumor pseudoprogression (Psp) and radiation necrosis [...] Read more.
Over recent decades, significant advancements have been made in the treatment and imaging of gliomas. Conventional imaging techniques, such as MRI and CT, play critical roles in glioma diagnosis and treatment but often fail to distinguish between tumor pseudoprogression (Psp) and radiation necrosis (RN) versus true progression (TP). Emerging fields like radiomics and radiogenomics are addressing these challenges by extracting quantitative features from medical images and correlating them with genomic data, respectively. This article will discuss several studies that show how radiomic features (RFs) can aid in better patient stratification and prognosis. Radiogenomics, particularly in predicting biomarkers such as MGMT promoter methylation and 1p/19q codeletion, shows potential in non-invasive diagnostics. Radiomics also offers tools for predicting tumor recurrence (rBT), essential for treatment management. Further research is needed to standardize these methods and integrate them into clinical practice. This review underscores radiomics and radiogenomics’ potential to revolutionize glioma management, marking a significant shift towards precision neuro-oncology. Full article
(This article belongs to the Special Issue Mechanisms and Novel Therapeutic Approaches for Gliomas)
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15 pages, 1415 KB  
Review
Amino Acid Deprivation in Glioblastoma: The Role in Survival and the Tumour Microenvironment—A Narrative Review
by Keven Du, Leila Grocott, Giulio Anichini, Kevin O’Neill and Nelofer Syed
Biomedicines 2024, 12(11), 2481; https://doi.org/10.3390/biomedicines12112481 - 29 Oct 2024
Cited by 4 | Viewed by 2543
Abstract
Background: Glioblastoma is the most common and aggressive primary brain tumour, characterised by its invasive nature and complex metabolic profile. Emerging research highlights the role of amino acids (AAs) in glioblastoma metabolism, influencing tumour growth and the surrounding microenvironment. Methods: This narrative review [...] Read more.
Background: Glioblastoma is the most common and aggressive primary brain tumour, characterised by its invasive nature and complex metabolic profile. Emerging research highlights the role of amino acids (AAs) in glioblastoma metabolism, influencing tumour growth and the surrounding microenvironment. Methods: This narrative review synthesises recent pre-clinical studies focusing on the metabolic functions of AAs in glioblastoma. Key areas include the effects of AA deprivation on tumour growth, adaptive mechanisms, and the tumour microenvironment. Results: The effects related to arginine, glutamine, methionine, and cysteine deprivation have been more extensively reported. Arginine deprivation in arginine-auxotrophic glioblastomas induces apoptosis and affects cell adhesion, while glutamine deprivation disrupts metabolic pathways and enhances autophagy. Methionine and cysteine deprivation impact lipid metabolism and ferroptosis. Tumour adaptive mechanisms present challenges, and potential compensatory responses have been identified. The response of the microenvironment to AA deprivation, including immune modulation, is critical to determining therapeutic outcomes. Conclusions: Targeting AA metabolism offers a promising approach for glioblastoma treatment, with potential targeted drugs showing clinical promise. However, the complexity of tumour adaptive mechanisms and their impact on the microenvironment necessitates further research to optimise combination therapies and improve therapeutic efficacy. Full article
(This article belongs to the Special Issue Mechanisms and Novel Therapeutic Approaches for Gliomas)
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Other

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18 pages, 1782 KB  
Systematic Review
Current Applications of Raman Spectroscopy in Intraoperative Neurosurgery
by Daniel Rivera, Tirone Young, Akhil Rao, Jack Y. Zhang, Cole Brown, Lily Huo, Tyree Williams, Benjamin Rodriguez and Alexander J. Schupper
Biomedicines 2024, 12(10), 2363; https://doi.org/10.3390/biomedicines12102363 - 16 Oct 2024
Cited by 1 | Viewed by 2817
Abstract
Background: Neurosurgery demands exceptional precision due to the brain’s complex and delicate structures, necessitating precise targeting of pathological targets. Achieving optimal outcomes depends on the surgeon’s ability to accurately differentiate between healthy and pathological tissues during operations. Raman spectroscopy (RS) has emerged as [...] Read more.
Background: Neurosurgery demands exceptional precision due to the brain’s complex and delicate structures, necessitating precise targeting of pathological targets. Achieving optimal outcomes depends on the surgeon’s ability to accurately differentiate between healthy and pathological tissues during operations. Raman spectroscopy (RS) has emerged as a promising innovation, offering real-time, in vivo non-invasive biochemical tissue characterization. This literature review evaluates the current research on RS applications in intraoperative neurosurgery, emphasizing its potential to enhance surgical precision and patient outcomes. Methods: Following PRISMA guidelines, a comprehensive systematic review was conducted using PubMed to extract relevant peer-reviewed articles. The inclusion criteria focused on original research discussing real-time RS applications with human tissue samples in or near the operating room, excluding retrospective studies, reviews, non-human research, and other non-relevant publications. Results: Our findings demonstrate that RS significantly improves tumor margin delineation, with handheld devices achieving high sensitivity and specificity. Stimulated Raman Histology (SRH) provides rapid, high-resolution tissue images comparable to traditional histopathology but with reduced time to diagnosis. Additionally, RS shows promise in identifying tumor types and grades, aiding precise surgical decision-making. RS techniques have been particularly beneficial in enhancing the accuracy of glioma surgeries, where distinguishing between tumor and healthy tissue is critical. By providing real-time molecular data, RS aids neurosurgeons in maximizing the extent of resection (EOR) while minimizing damage to normal brain tissue, potentially improving patient outcomes and reducing recurrence rates. Conclusions: This review underscores the transformative potential of RS in neurosurgery, advocating for continued innovation and research to fully realize its benefits. Despite its substantial potential, further research is needed to validate RS’s clinical utility and cost-effectiveness. Full article
(This article belongs to the Special Issue Mechanisms and Novel Therapeutic Approaches for Gliomas)
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