Pediatric Hemispheric High-Grade Gliomas and H3.3-G34 Mutation: A Review of the Literature on Biological Features and New Therapeutic Strategies DOI Open Access

Marta Bonada,

Matilde Pittarello,

Emerson De Fazio

et al.

Genes, Journal Year: 2024, Volume and Issue: 15(8), P. 1038 - 1038

Published: Aug. 6, 2024

Pediatric high-grade glioma (pHGG) encompasses a wide range of gliomas with different genomic, epigenomic, and transcriptomic features. Almost 50% pHGGs present mutation in genes coding for histone 3, including the subtype harboring H3.3-G34 mutation. In this context, mutations are frequently associated

Language: Английский

Immunotherapeutic Strategies for the Treatment of Glioblastoma: Current Challenges and Future Perspectives DOI Open Access
Ilaria Salvato, Antonio Marchini

Cancers, Journal Year: 2024, Volume and Issue: 16(7), P. 1276 - 1276

Published: March 25, 2024

Despite decades of research and the best up-to-date treatments, grade 4 Glioblastoma (GBM) remains uniformly fatal with a patient median overall survival less than 2 years. Recent advances in immunotherapy have reignited interest utilizing immunological approaches to fight cancer. However, current immunotherapies so far not met anticipated expectations, achieving modest results their journey from bench bedside for treatment GBM. Understanding intrinsic features GBM is crucial importance development effective antitumoral strategies improve life expectancy conditions. In this review, we provide comprehensive overview distinctive characteristics that significantly influence conventional therapies immune-based approaches. Moreover, present an immunotherapeutic currently undergoing clinical evaluation treatment, specific emphasis on those advancing phase 3 studies. These encompass immune checkpoint inhibitors, adoptive T cell therapies, vaccination (i.e., RNA-, DNA-, peptide-based vaccines), virus-based Finally, explore novel innovative future prospects field

Language: Английский

Citations

19
AS1411 aptamer/RGD dual functionalized theranostic chitosan-PLGA nanoparticles for brain cancer treatment and imaging DOI
Mahima Chauhan,

Sonali,

Saurabh Shekhar

et al.

Biomaterials Advances, Journal Year: 2024, Volume and Issue: 160, P. 213833 - 213833

Published: March 21, 2024

Language: Английский

Citations

7
Isobolographic interactions of cannabidiol and AM 1172 with cisplatin in human neuroblastoma and glioblastoma cell lines: an in vitro study DOI
Katarzyna Załuska-Ogryzek, Paula Wróblewska-Łuczka, Agnieszka Góralczyk

et al.

Chemico-Biological Interactions, Journal Year: 2025, Volume and Issue: unknown, P. 111392 - 111392

Published: Jan. 1, 2025

Language: Английский

Citations

1
Glioblastoma and Immune Checkpoint Inhibitors: A Glance at Available Treatment Options and Future Directions DOI Open Access

Silvia Mara Baez Rodriguez,

Ligia Gabriela Tătăranu,

A. El Kamel

et al.

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(19), P. 10765 - 10765

Published: Oct. 7, 2024

Glioblastoma is known to be one of the most aggressive and fatal human cancers, with a poor prognosis resistance standard treatments. In last few years, many solid tumor treatments have been revolutionized help immunotherapy. However, this type treatment has failed improve results in glioblastoma patients. Effective immunotherapeutic strategies may developed after understanding how achieves tumor-mediated immune suppression both local systemic landscapes. Biomarkers identify patients likely benefit from treatment. review, we discuss use immunotherapy glioblastoma, an emphasis on checkpoint inhibitors factors that influence clinical response. A Pubmed data search was performed for all existing information regarding used glioblastoma. All evaluating ongoing trials involving ICIs either as monotherapy or combination other drugs compiled analyzed.

Language: Английский

Citations

3
Selectively expressed RNA molecules as a versatile tool for functionalized cell targeting DOI Creative Commons
Frederik Rastfeld, Marco Hoffmann,

Sylvie Krüger

et al.

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: Jan. 6, 2025

Abstract Targeting of diseased cells is one the most urgently needed prerequisites for a next generation potent pharmaceuticals. Different approaches pursued fail mainly due to lack specific surface markers. Developing an RNA-based methodology, we can now ensure precise cell targeting combined with selective expression effector proteins therapy, diagnostics or steering. The combination molecular properties antisense technology and mRNA therapy functional RNA secondary structures allowed us develop selectively expressed molecules medical applications. These seRNAs remain inactive in non-target induce translation by partial degradation only preselected types interest. Cell specificity type functionalization are easily adaptable based on modular system. In proof-of-concept studies use as platform highly targeting. We effectively treat breast tumor clusters mixed systems shrink early U87 glioblastoma brain male mice without detectable side effects. Our data open up potential avenues various therapeutic

Language: Английский

Citations

0
It’s all downstream from here: RTK/Raf/MEK/ERK pathway resistance mechanisms in glioblastoma DOI Creative Commons

Rebeca Yakubov,

Ramneet Kaloti,

Phooja Persaud

et al.

Journal of Neuro-Oncology, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 16, 2025

The receptor tyrosine kinase (RTK)/Ras/Raf/MEK/ERK signaling pathway is one of the most tumorigenic pathways in cancer, with its hyperactivation strongly linked to aggressive nature glioblastoma (GBM). Although extensive research has focused on developing therapeutics targeting this pathway, clinical success remains elusive due emergence resistance mechanisms. This review investigates how inhibition RTK/Ras/Raf/MEK/ERK alters transcription factors, contributing acquired mechanisms GBM. It also highlights critical role factor dysregulation therapeutic resistance. Findings from key studies GBM were synthesized explore targeted therapies, radiation, and chemotherapy. that factors undergo significant following inhibition, Transcription are promising targets for overcoming treatment GBM, cotreatment strategies combining inhibitors factor-targeted therapies presenting a novel approach. Despite challenges complex structures interactions, advancements drug development precision technologies hold great potential. Continued essential refine these improve outcomes other cancers.

Language: Английский

Citations

0
A clinically relevant model and method to study necrosis as a driving force in glioma restructuring and progression DOI Creative Commons
Jiabo Li, Ling-Kai Shih, Steven M. Markwell

et al.

Proceedings of the National Academy of Sciences, Journal Year: 2025, Volume and Issue: 122(7)

Published: Feb. 13, 2025

All glioblastoma (GBM) molecular subsets share the common trait of accelerated progression following necrosis, which cannot be adequately explained by cellular proliferation arising from accumulated genetic alterations. Counter to dogma that “cancer outgrows its blood supply,” we suggest development necrosis is not merely a consequence aggressive neoplastic growth but could contributing force causing tumor microenvironment (TME) restructuring and biologic progression. Mechanisms related necrotic contributions are poorly understood due lack methods study as primary variable. To reveal spatiotemporal changes directly, developed mouse model methodology designed induce clinically relevant thrombotic vaso-occlusion within GBMs in an immunocompetent RCAS/tv-a TME intravital microscopy demonstrate impact on glioma Diffuse high-grade gliomas generated introducing RCAS-PDGFB-RFP RCAS-Cre Nestin/tv-a; TP53 fl/fl PTEN background mouse. We then photoactivate Rose Bengal specific, targeted vessels thrombosis, hypoxia, necrosis. Following induced undergo rapid radial expansion, with immunosuppressive bone marrow–derived, tumor-associated macrophages (TAMs) stem cells (GSCs) increasing dramatically perinecrotic niche. Collectively, this introduces variable captures dynamics manner will facilitate therapeutic antagonize these mechanisms

Language: Английский

Citations

0
Evolution of Preclinical Models for Glioblastoma Modelling and Drug Screening DOI Creative Commons
Grace Thomas, Ruman Rahman

Current Oncology Reports, Journal Year: 2025, Volume and Issue: unknown

Published: April 4, 2025

Language: Английский

Citations

0
Understanding the IDH1 missense SNPs on expression of genes involved in Glioblastoma multiforme DOI
Ganesh S. Kakde, Tikam Chand Dakal, Pawan Kumar Maurya

et al.

Computational Biology and Chemistry, Journal Year: 2025, Volume and Issue: 118, P. 108487 - 108487

Published: April 25, 2025

Language: Английский

Citations

0
Radiomics-Based Machine Learning with Natural Gradient Boosting for Continuous Survival Prediction in Glioblastoma DOI Open Access
Mert Karabacak,

Shiv Patil,

Zachary Charles Gersey

et al.

Cancers, Journal Year: 2024, Volume and Issue: 16(21), P. 3614 - 3614

Published: Oct. 26, 2024

(1) Background: Glioblastoma (GBM) is the most common primary malignant brain tumor in adults, with an aggressive disease course that requires accurate prognosis for individualized treatment planning. This study aims to develop and evaluate a radiomics-based machine learning (ML) model estimate overall survival (OS) patients GBM using pre-treatment multi-parametric magnetic resonance imaging (MRI). (2) Methods: The MRI data of 865 were assessed, comprising 499 from UPENN-GBM dataset 366 UCSF-PDGM dataset. A total 14,598 radiomic features extracted T1, T1 contrast, T2, FLAIR sequences PyRadiomics. was used development (70%) internal validation (30%), while served as external test set. NGBoost Survival developed generate continuous probability estimates well predictions 6-, 12-, 18-, 24-month OS. (3) Results: successfully predicted survival, achieving C-index 0.801 on 0.725 validation. For 6-month OS, attained AUROC 0.791 (95% CI: 0.742–0.832) 0.708 0.654–0.748) validation, respectively. (4) Conclusions: ML demonstrates potential improve prediction OS GBM.

Language: Английский

Citations

3