Unlocking the Code: The Role of Molecular and Genetic Profiling in Revolutionizing Glioblastoma Treatment DOI Creative Commons
Moustafa Mansour,

Ahmed M Kamer-Eldawla,

Reem W Malaeb

et al.

Cancer Treatment and Research Communications, Journal Year: 2024, Volume and Issue: 43, P. 100881 - 100881

Published: Jan. 1, 2024

Glioblastoma (GBM) is the most aggressive primary brain cancer, characterized by profound molecular and cellular heterogeneity, which contributes to its resistance conventional therapies poor prognosis. Despite multimodal treatments including surgical resection, radiation, chemotherapy, median survival remains approximately 15 months. Recent advances in genetic profiling have elucidated key alterations subtypes of GBM, such as EGFR amplification, PTEN ATRX loss, TP53 alterations, significant prognostic therapeutic implications. These discoveries spurred development targeted aimed at disrupting aberrant signaling pathways like RTK/RAS/PI3K TP53. However, treatment a formidable challenge, driven tumor complex microenvironment (TME), intrinsic adaptive mechanisms. Emerging approaches aim address these challenges, use immunotherapies immune checkpoint inhibitors CAR T-cell therapies, target specific antigens but face hurdles due immunosuppressive TME. Additionally, novel strategies biopolymer-based interstitial focused ultrasound for blood-brain barrier disruption, nanoparticle-based drug delivery systems show promise enhancing efficacy precision GBM treatments. This review explores evolving landscape therapy, emphasizing importance personalized medicine through profiling, potential combination need innovative overcome resistance. Continued research into GBM's biology modalities offers hope improving patient outcomes.

Language: Английский

A Radiologist's Guide to IDH-Wildtype Glioblastoma for Efficient Communication With Clinicians: Part I-Essential Information on Preoperative and Immediate Postoperative Imaging DOI
Philipp Kickingereder, Philipp Karschnia, Felix Sahm

et al.

Korean Journal of Radiology, Journal Year: 2025, Volume and Issue: 26(3), P. 246 - 246

Published: Jan. 1, 2025

The paradigm of isocitrate dehydrogenase (IDH)-wildtype glioblastoma is rapidly evolving, reflecting clinical, pathological, and imaging advancements. Thus, it remains challenging for radiologists, even those who are dedicated to neuro-oncology imaging, keep pace with this progressing field provide useful updated information clinicians. Based on current knowledge, radiologists can play a significant role in managing patients IDH-wildtype by providing accurate preoperative diagnosis as well postoperative treatment planning including delineation the residual tumor. Through active communication clinicians, extending far beyond confines radiology reading room, impact clinical decision making. This Part 1 review provides an overview about neuropathological understand past, present, upcoming revisions World Health Organization classification. findings that noteworthy while communicating clinicians immediate glioblastomas will be summarized.

Language: Английский

Citations

1
Immunity/metabolism dual-regulation via an acidity-triggered bioorthogonal assembly nanoplatform enhances glioblastoma immunotherapy by targeting CXCL12/CXCR4 and adenosine-A2AR pathways DOI
Ruili Wei,

Kunfeng Xie,

Tao Li

et al.

Biomaterials, Journal Year: 2025, Volume and Issue: 319, P. 123216 - 123216

Published: Feb. 26, 2025

Language: Английский

Citations

1
Clinical research framework proposal for ketogenic metabolic therapy in glioblastoma DOI Creative Commons
Tomás Duraj,

Miriam Kalamian,

Giulio Zuccoli

et al.

BMC Medicine, Journal Year: 2024, Volume and Issue: 22(1)

Published: Dec. 5, 2024

Abstract Glioblastoma (GBM) is the most aggressive primary brain tumor in adults, with a universally lethal prognosis despite maximal standard therapies. Here, we present consensus treatment protocol based on metabolic requirements of GBM cells for two major fermentable fuels: glucose and glutamine. Glucose source carbon ATP synthesis growth through glycolysis, while glutamine provides nitrogen, carbon, glutaminolysis. As no can grow without anabolic substrates or energy, simultaneous targeting glycolysis glutaminolysis expected to reduce proliferation if not all cells. Ketogenic therapy (KMT) leverages diet-drug combinations that inhibit glutaminolysis, signaling shifting energy metabolism therapeutic ketosis. The glucose-ketone index (GKI) standardized biomarker assessing biological compliance, ideally via real-time monitoring. KMT aims increase substrate competition normalize microenvironment GKI-adjusted ketogenic diets, calorie restriction, fasting, also glycolytic glutaminolytic flux using specific inhibitors. Non-fermentable fuels, such as ketone bodies, fatty acids, lactate, are comparatively less efficient supporting long-term bioenergetic biosynthetic demands cancer cell proliferation. proposed strategy may be implemented synergistic priming baseline well other tumors driven by regardless their residual mitochondrial function. Suggested best practices provided guide future research oncology, offering shared, evidence-driven framework observational interventional studies.

Language: Английский

Citations

6
V-ATPase in glioma stem cells: a novel metabolic vulnerability DOI Creative Commons
Alessandra Maria Storaci, Irene Bertolini, Cristina Martelli

et al.

Journal of Experimental & Clinical Cancer Research, Journal Year: 2025, Volume and Issue: 44(1)

Published: Jan. 17, 2025

Glioblastoma (GBM) is a lethal brain tumor characterized by the glioma stem cell (GSC) niche. The V-ATPase proton pump has been described as crucial factor in sustaining GSC viability and tumorigenicity. Here we studied how patients-derived GSCs rely on activity to sustain mitochondrial bioenergetics growth. cultures was modulated using Bafilomycin A1 (BafA1) metabolic traits were analyzed live assays. GBM orthotopic xenografts used vivo models of disease. Cell extracts, proximity-ligation assay advanced microscopy analyze subcellular presence proteins. A metabolomic screening performed Biocrates p180 kit, whereas transcriptomic analysis Nanostring panels. Perturbation reduces growth vitro vivo. In there pool that localize mitochondria. At functional level, inhibition induces ROS production, damage, while hindering oxidative phosphorylation reducing protein synthesis. This rewiring accompanied higher glycolytic rate intracellular lactate accumulation, which not exploited for biosynthetic or survival purposes. critical metabolism Targeting may be novel potential vulnerability glioblastoma treatment.

Language: Английский

Citations

0
MRI transformer deep learning and radiomics for predicting IDH wild type TERT promoter mutant gliomas DOI Creative Commons

Wenju Niu,

Junyu Yan,

Min Hao

et al.

npj Precision Oncology, Journal Year: 2025, Volume and Issue: 9(1)

Published: March 27, 2025

This study aims to predict IDH wt with TERTp-mut gliomas using multiparametric MRI sequences through a novel fusion model, while matching model classification metrics patient risk stratification aids in crafting personalized diagnostic and prognosis evaluations.Preoperative T1CE T2FLAIR from 1185 glioma patients were analyzed. A MultiChannel_2.5D_DL 2D DL both based on the cross-scale attention vision transformer (CrossFormer) neural network, along Radiomics developed. These integrated via ensemble learning into stacking model. The outperformed 2D_DL models, AUCs of 0.806-0.870. achieved highest AUC (0.855-0.904) across validation sets. Patients stratified high-risk low-risk groups scores, significant survival differences observed Kaplan–Meier analysis log-rank tests. effectively identifies TERTp-mutant stratifies risk, aiding prognosis.

Language: Английский

Citations

0
MRI-based habitat imaging predicts high-risk molecular subtypes and early risk assessment of lower-grade gliomas DOI Creative Commons
Xiangli Yang,

Wenju Niu,

Kai Wu

et al.

Cancer Imaging, Journal Year: 2025, Volume and Issue: 25(1)

Published: March 28, 2025

In lower-grade gliomas (LrGGs, histological grades 2-3), there exist a minority of high-risk molecular subtypes with malignant transformation potential, associated unfavorable clinical outcomes and shorter survival prognosis. Identifying early in LrGGs conducting preoperative prognostic evaluations are crucial for precise diagnosis treatment. We retrospectively collected data from 345 patients comprehensively screened key markers. Based on MRI sequences (CE-T1WI/T2-FLAIR), we employed seven classifiers to construct models based habitat, radiomics, combined. Eventually, identified Extra Trees habitat features as the optimal predictive model identifying LrGGs. Moreover, developed prediction radiomics score (Radscore) assess outlook utilized Kaplan-Meier (KM) analysis alongside log-rank test discern variations probabilities among low-risk cohorts. The concordance index was gauge efficacy clinical, amalgamated prognosis models. Calibration curves were appraise congruence between anticipated probability actual projected by predicting LrGGs, achieved AUCs 0.802, 0.771, 0.768 training set, internal external respectively. Comparison combined revealed that exhibited highest performance (C-index = 0.781 C-index 0.778 0.743 set), followed 0.749 0.716 0.707 while performed worst 0.717 0.687 0.649 set). Furthermore, calibration satisfactory alignment when forecasting 1-year, 2-year, 3-year MRI-based simultaneously achieves objectives non-invasive assessment This has incremental value warning risk-stratified management.

Language: Английский

Citations

0
Contrast-enhanced ultrasound can differentiate the level of glioma infiltration and correlate it with biological behavior: a study based on local pathology DOI
Xing Hu, Gaobo Zhang, Rong Xie

et al.

Journal of Ultrasound, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 4, 2024

Language: Английский

Citations

0
Predicting the Molecular Subtypes of 2021 WHO Grade 4 Glioma by a Multiparametric MRI-Based Machine Learning Model DOI Creative Commons
Wenji Xu, Yangyang Li, Jie Zhang

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 11, 2024

Abstract Purpose: To develop and validate a machine learning (ML) model using multiparametric MRI for the preoperative differentiation of 2021 World Health Organization (WHO) grade 4 astrocytoma glioblastoma (GBM) (Task 1), to stratify distinguish isocitrate dehydrogenase-mutant (IDH-mut) from IDH-wild-type (IDH-wt) 2). Additionally, evaluate model’s prognostic value. Materials methods: We retrospectively analyzed 320 glioma patients three hospitals. Cases were randomly divided into training validation sets with 7:3 ratio. Features extracted tumor edema on contrast-enhanced T1-weighted imaging (CE-T1WI) T2 fluid-attenuated inversion recovery (T2-FLAIR). Extreme gradient boosting (XGBoost) was utilized constructing ML, clinical, combined models. Model performance evaluated receiver operating characteristic (ROC) curves, decision calibration curves. Stability six additional classifiers. Kaplan-Meier (KM) survival analysis log-rank test assessed Results: In Task 1 (grade vs GBM) 2 (IDH-mut IDH-wt 4), (AUC = 0.911 0.854, 0.902 0.909) optimal ML 0.855, 0.904 0.895) significantly outperformed clinical 0.671 0.656, 0.619 0.605) in both sets. Survival showed performed similarly molecular subtype tasks (P 0.966 P 0.793). Conclusion: The effectively distinguished GBM differentiated IDH-mut astrocytoma. provides reliable stratification various subtypes.

Language: Английский

Citations

0
Unlocking the Code: The Role of Molecular and Genetic Profiling in Revolutionizing Glioblastoma Treatment DOI Creative Commons
Moustafa Mansour,

Ahmed M Kamer-Eldawla,

Reem W Malaeb

et al.

Cancer Treatment and Research Communications, Journal Year: 2024, Volume and Issue: 43, P. 100881 - 100881

Published: Jan. 1, 2024

Glioblastoma (GBM) is the most aggressive primary brain cancer, characterized by profound molecular and cellular heterogeneity, which contributes to its resistance conventional therapies poor prognosis. Despite multimodal treatments including surgical resection, radiation, chemotherapy, median survival remains approximately 15 months. Recent advances in genetic profiling have elucidated key alterations subtypes of GBM, such as EGFR amplification, PTEN ATRX loss, TP53 alterations, significant prognostic therapeutic implications. These discoveries spurred development targeted aimed at disrupting aberrant signaling pathways like RTK/RAS/PI3K TP53. However, treatment a formidable challenge, driven tumor complex microenvironment (TME), intrinsic adaptive mechanisms. Emerging approaches aim address these challenges, use immunotherapies immune checkpoint inhibitors CAR T-cell therapies, target specific antigens but face hurdles due immunosuppressive TME. Additionally, novel strategies biopolymer-based interstitial focused ultrasound for blood-brain barrier disruption, nanoparticle-based drug delivery systems show promise enhancing efficacy precision GBM treatments. This review explores evolving landscape therapy, emphasizing importance personalized medicine through profiling, potential combination need innovative overcome resistance. Continued research into GBM's biology modalities offers hope improving patient outcomes.

Language: Английский

Citations

0