Glioblastoma (GBM) is the most common and lethal primary brain tumour. The prognosis for GBM patients remains poor due to rapid tumour recurrence and resistance to conventional treatments. Small Rho GTPase proteins, which regulate cell shape and motility, are critical for GBM aggressive growth and infiltration into the surrounding brain parenchyma. Hence, small-molecule inhibitors targeting them represent an appealing opportunity to hinder the infiltration behaviour of GBM. Here, a synergistic experimental and computational approach allowed us to identify an inhibitor that reduces migration in patient-derived GBM cell lines. Computational and in vitro functional assays reveal that this compound inhibits Rho GTPases function by targeting multiple allosteric sites thereby enhancing flexibility of key functional regions and hindering their interaction with protein regulators. Our research unveiled a novel hit molecule targeting Rho GTPases with significant potential to improve the treatment of GBM and other highly aggressive tumours.

Gliomas pose a significant treatment challenge due to their varied genetic makeup and clinical presentations. This study examines a unique cohort of high-grade adult type diffuse gliomas (ATDG) previously diagnosed as anaplastic astrocytoma prior to the WHO 2021 tumor classification changes. This cohort chose to undergo only surgical resection without adjuvant therapies. We provide a rare dataset of patients allowing for new insight into the natural progression of this disease with surgical treatment alone.

A retrospective review was conducted of patients who were operated on by a single surgeon from the years 2002-2022 and who were diagnosed as having a Grade III Anaplastic Astrocytoma before the WHO 2021 guidelines were published. Correcting for the criteria in the 2021 Guidelines resulted in a mixture of adult-type diffuse malignant gliomas (ATDG), including IDH-Mutant astrocytomas (Grade 3 and 4) and IDH-WT Glioblastoma. All patients included underwent surgical resection alone after declining any adjuvant therapy for various reasons.

A total of 20 patients met the inclusion criteria with an average age of 38 years. Among them, 15 had IDH-mutant (IDH-mt) Grade 3 astrocytomas (75 %), 1 had an IDH-mt Grade 4 astrocytoma (5 %), and 4 had IDH-wildtype (IDH-WT) glioblastomas (20 %). The 5-year survival rate for the entire cohort was 74.0 %. Grade 3 astrocytomas had a 5-year survival of 86.7 %, while Grade 4 astrocytomas and IDH-WT GBM patients exhibited a 5-year survival rate of 40 %. 5-year progression-free survival (PFS) rates were derived from the surgery date up until the recurrence or censorship. The collective cohort had a PFS rate of 34.3 %. Grade 3 astrocytomas achieved a 5-year PFS of 32.0 %, whereas Grade 4 astrocytomas and IDH-WT GBM reached a PFS of 40.0 %.

In our cohort study, we demonstrate that patients with ATDG can potentially achieve relative long-term survival through surgical resection alone. This unique cohort highlights the natural progression of this disease with surgery alone and provides the foundation for future more rigorous studies to evaluate the additive benefit of different adjuvant therapies. With evolving tumor classifications and variable responses to standard therapeutics, it becomes imperative to revisit and understand the additive benefits of different chemotherapeutic protocols in addition to surgical resection.

Temozolomide (TMZ) is the only one oral first-line chemotherapeutic drug for glioblastoma treatment. However, O6-methylguanine-DNA methyltransferase (MGMT) can repair the lethal O6-methylguaine (O6-MeG) lesion produced by TMZ, thus imparting resistance to TMZ. Currently, the clinical utility of small molecule covalent MGMT inhibitors is limited by the occurrence of severe hematological toxicity. Therefore, developing new strategies for overcoming MGMT-mediated resistance is highly urgent. Here, we explored the feasibility that modulating Wnt/β-catenin signaling pathway in glioblastoma to inhibit MGMT expression to overcome TMZ resistance. From eight natural products or approved drugs with inhibitory effects on Wnt/β-catenin pathway, we found thymoquinone (TQ) completely suppressed MGMT expression in glioblastoma SF763 and SF767 cell lines within 24 h. As expected, TQ exhibited synergistic killing effects with TMZ in SF763 and SF767 cells, while in MGMT-negative SF126 cells only additive effect observed. Moreover, TQ remarkably enhanced the inhibition of TMZ on cell proliferation, clone formation, invasion and migration, and promoted cell apoptosis. In resistant SF763 mice tumor xenograft model, TQ significantly increased the suppression of TMZ on tumor growth, meanwhile maintaining good biosafety. Western blotting analysis indicated that TQ significantly inhibited the nuclear translocation of β-catenin and the expression of downstream proteins Cyclin D1 and MGMT. The addition of Wnt activator LiCl reversed the nuclear translocation of β-catenin and the expression of Cyclin D1 and MGMT induced by TQ. For the first time, our findings indicate that TQ can considerably increase the sensitivity of glioblastoma to TMZ by interfering Wnt/β-catenin pathway to downregulate MGMT expression.

isocitrate dehydrogenase 1 (IDH1), a key metabolic enzyme in the cytosol, catalyzes the oxidative decarboxylation of isocitrate to produce α-ketoglutarate (α-KG) and NADPH in the TCA cycle. Pan-cancer studies have demonstrated that IDH1 exhibits a higher mutation frequency and is implicated in a broader range of cancer types, indicating its potential as a promising anti-tumor target.

We summarized patents from 2018 to the present that identify novel molecules, compounds, formulations, and methods for inhibiting mIDH1. The literature was retrieved from Web of Science and PubMed. Patent information was obtained via the State Intellectual Property Office's Patent Search and Analysis platform. Clinical data were sourced from the Cortellis Drug Discovery Intelligence database. The date of the most recent search was .

Due to multiple signaling pathway dysregulations and compensatory pathways in solid tumor, monotherapies targeting mutant IDH1 (mIDH1) often fail to achieve desired therapeutic outcomes. Consequently, the combination of mIDH1 inhibitors with other therapeutic agents can enhance the efficacy of antitumor treatments and mitigate the risk of drug resistance. Moreover, the development of novel dual or multiple inhibitors and functional molecules targeting mIDH1 May represent a more promising approach.

Glioblastoma multiforme (GBM) is an aggressive brain tumor with poor prognosis. Recent advancements in bioinformatics have contributed to uncovering the genetic alterations that underlie the development and progression of GBM. Analysis of extensive genomic data led to the identification of significant pathways involved in GBM, such as the PI3K/AKT/mTOR and Ras/Raf/MEK/ERK signaling pathways, alongside key genes such as EGFR, TP53 and TERT. These findings have enhanced our understanding of GBM biology and led to the identification of new therapeutic targets. Bioinformatics has become an indispensable tool in pinpointing the genetic modifications that drive GBM, paving the way for innovative treatment strategies. This approach not only aids in comprehending the complexities of GBM but also holds promise for improving outcomes in patients suffering from this devastating disease. The ongoing integration of bioinformatics in GBM research continues to be vital for advancing therapeutic options.

Glioblastoma multiforme (GBM) is the most aggressive and malignant primary brain tumor, classified as grade IV by the WHO. Despite standard treatments like surgical resection, radiotherapy and chemotherapy (i.e. temozolomide), GBM's prognosis remains poor due to its heterogeneity, recurrence and the impermeability of the blood-brain barrier (BBB). The exact cause of GBM is unclear with potential factors including genetic predisposition and ionizing radiation. Innovative approaches such as nanomicelles-nanoscale, self-assembled structures made from lipids and amphiphilic polymers show promise for GBM therapy. These nanocarriers enhance drug solubility and stability, enabling targeted delivery of therapeutic agents across the BBB. This review explores the synthesis strategies, characterization and applications of nanomicelles in GBM treatment. Nanomicelles improve the delivery of both hydrophobic and hydrophilic drugs and provide non-invasive delivery options. By offering site-specific targeting, biocompatibility, and stability, nanomicelles can potentially overcome the limitations of current GBM therapies. This review highlights recent advancements in the use of nanomicelles for delivering therapeutic agents and nucleic acids addressing the critical need for advanced treatments to improve GBM patient outcomes.

Deep learning shows promise in automated brain tumour segmentation, but it depends on costly expert annotations. Recent advances in unsupervised learning offer an alternative by using synthetic data for training. However, the discrepancy between real and synthetic data limits the accuracy of the unsupervised approaches. In this paper, we propose an approach for unsupervised brain tumour segmentation on magnetic resonance (MR) images via a two-stage image synthesis strategy. This approach accounts for the domain gap between real and synthetic data and aims to generate realistic synthetic data for model training. In the first stage, we train a junior segmentation model using synthetic brain tumour images generated by hand-crafted tumour shape and intensity models, and employs a validation set with distribution shift for model selection. The trained junior model is applied to segment unlabelled real tumour images, generating pseudo labels that capture realistic tumour shape, intensity, and texture. In the second stage, realistic synthetic tumour images are generated by mixing brain images with tumour pseudo labels, closing the domain gap between real and synthetic images. The generated synthetic data is then used to train a senior model for final segmentation. In experiments on five brain imaging datasets, the proposed approach, named as SynthTumour, surpasses existing unsupervised methods and demonstrates high performance for both brain tumour segmentation and ischemic stroke lesion segmentation tasks.

Fluorine has become an essential element in the development of modern pharmaceuticals, due to its unique chemical properties that can significantly enhance the biological activity, metabolic stability, and lipophilicity of drug molecules. This review explores recent advancements in the synthesis and application of fluorine-containing drugs approved by the US Food and Drug Administration (FDA) in 2024. These novel drugs demonstrate improved efficacy and safety profiles, addressing a range of therapeutic areas including oncology, infectious diseases, metabolic disorders and genetic disorders that affect the adrenal glands. The incorporation of fluorine atoms into drug candidates has facilitated the development of molecules with optimized pharmacokinetic and pharmacodynamic properties, leading to better patient outcomes. The review further discusses the synthetic methodologies employed, the structural characteristics of these drugs, and their clinical implications, providing insights into the ongoing innovation within the pharmaceutical industry driven by fluorine chemistry.

Although IDH-mutant glioma generally has a better prognosis than their IDH-wildtype counterparts, considerable prognostic heterogeneity persists among patients with the same IDH mutation. Current study has primarily focused on the different IDH statuses or grades, while the metabolic heterogeneity within IDH-mutant gliomas remains insufficiently characterized. This study aims to identify transcriptomic metabolic subtypes and associated immune microenvironment differences to better understand survival variability and potential therapeutic targets in IDH-mutant glioma.

Patients with IDH-mutant gliomas were included from four public datasets (TCGA, n = 373; CGGA325, n = 167; CGGA693, n = 333; GLASS, n = 100), supplemented by 22 cases from Beijing Tiantan Hospital as an independent cohort. Consensus clustering was used to define novel metabolic subtypes. Clinical features were assessed using chi-square tests and Kaplan-Meier analysis. Metabolic profiles were characterized through enrichment analysis and GSVA; immune infiltration was analyzed using CIBERSORTx and ESTIMATE. Tumor samples from the independent cohort underwent untargeted metabolomics for validation. LASSO regression was applied to select metabolic signatures, and the CGP2014 drug library was used for drug screening.

Three metabolic subtypes (C1-C3) with distinct prognoses (p < 0.05) were identified. C1 exhibited enhanced carbohydrate and nucleotide metabolism; C2 displayed upregulated amino acid and lipid metabolism; and C3 demonstrated elevated lipid, nucleotide, and vitamin metabolism. These patterns were validated in the independent cohort. Subtypes were also correlated with immune infiltration. A 13-gene metabolic signature was established to stratify prognostic risk and suggest subtype-specific drug sensitivities.

Our study provided a novel metabolic subtype for IDH-mutant glioma and highlighted these patients' metabolic heterogeneity and potential therapeutic strategies.

Systematic assessment of the clinical applicability of cell-free RNAs (cfRNAs), which includes broader RNA categories beyond microRNAs, for patients with brain tumors remains largely unexplored due to the lack of sensitive profiling technologies. Our study endeavors to bridge this gap by utilizing an optimized cell-free transcriptome profiling technique that we have recently developed. We comprehensively profiled the cell-free transcriptome in plasma and cerebrospinal fluid (CSF) samples from a total of 85 patients with glioma, meningioma, or tumor-free central nervous system diseases. We identified 16 cfRNA signatures in CSF with robust performance in brain tumor detection (test set AUC = 0.94; validation set AUC = 1). The integration of CSF and plasma-derived cfRNAs outperformed individual analyses using either CSF or plasma candidates for the classification of glioma (test set AUC = 0.94; validation set AUC = 0.85) and meningioma (test set AUC = 0.92; validation set AUC = 0.83). Additionally, we identified 33 CSF and 3 plasma cfRNAs with prognostic significance for postoperative patient outcomes. Multivariate analysis showed that cfRNA-based risk scores (Hazard ratio=9.9) outperformed traditional risk factors in predicting recurrence-free survival. Importantly, our findings in liquid biopsies are consistent with results from primary tumor tissues. By delving into the diagnostic and prognostic implications of cfRNA signatures in CSF and plasma, our study paves the way for improved diagnostic precision and personalized therapeutic interventions for brain tumor patients.

In healthy cells, cyclin D1 is expressed during the G1 phase of the cell cycle, where it activates CDK4 and CDK6. Its dysregulation is a well-established oncogenic driver in numerous human cancers. The cancer-related function of cyclin D1 has been primarily studied by focusing on the phosphorylation of the retinoblastoma (RB) gene product. Here, using an integrative approach combining bioinformatic analyses and biochemical experiments, we show that GTSE1 (G-Two and S phases expressed protein 1), a protein positively regulating cell cycle progression, is a previously unrecognized substrate of cyclin D1-CDK4/6 in tumor cells overexpressing cyclin D1 during G1 and subsequent phases. The phosphorylation of GTSE1 mediated by cyclin D1-CDK4/6 inhibits GTSE1 degradation, leading to high levels of GTSE1 across all cell cycle phases. Functionally, the phosphorylation of GTSE1 promotes cellular proliferation and is associated with poor prognosis within a pan-cancer cohort. Our findings provide insights into cyclin D1's role in cell cycle control and oncogenesis beyond RB phosphorylation.

Glioblastoma (GBM) is a highly malignant brain tumor with complex molecular mechanisms. Histopathological images provide valuable morphological information of tumors. This study aims to evaluate the predictive potential of quantitative histopathological image features (HIF) for molecular characteristics and overall survival (OS) in GBM patients by integrating HIF with multi-omics data.

We included 439 GBM patients with eligible histopathological images and corresponding genetic data from The Cancer Genome Atlas (TCGA). A total of 550 image features were extracted from the histopathological images. Machine learning algorithms were employed to identify molecular characteristics, with random forest (RF) models demonstrating the best predictive performance. Predictive models for OS were constructed based on HIF using RF. Additionally, we enrolled tissue microarrays of 67 patients as an external validation set. The prognostic histopathological image features (PHIF) were identified using two machine learning algorithms, and prognosis-related gene modules were discovered through WGCNA.

The RF-based OS prediction model achieved significant prognostic accuracy (5-year AUC = 0.829). Prognostic models were also developed using single-omics, the integration of HIF and single-omics (HIF + genomics, HIF + transcriptomics, HIF + proteomics), and all features (multi-omics). The multi-omics model achieved the best prediction performance (1-, 3- and 5-year AUCs of 0.820, 0.926 and 0.878, respectively).

Our study indicated a certain prognostic value of HIF, and the integrated multi-omics model may enhance the prognostic prediction of GBM, offering improved accuracy and robustness for clinical application.

Recurrence is inevitable in both IDH wild-type glioblastoma and IDH-mutant WHO grade 3 or 4 astrocytoma. While IDH-mutant astrocytomas are associated with longer survival and delayed first progression, less is known about disease course beyond initial treatment. This study examines whether IDH mutation status influences time to second recurrence and identifies additional predictors of recurrence intervals.

This retrospective, multi-institutional study included adults diagnosed with pathologically confirmed high-grade glioma (HGG) between 2015 and 2020. HGG refers to IDH-mutant WHO grade 3 or 4 astrocytomas and IDH wild-type glioblastomas, consistent with WHO CNS5 criteria. Demographics, treatment, extent of resection, and molecular markers were analyzed. Time-to-recurrence was calculated per RANO 2.0 criteria. Statistical tests included Mann‒Whitney U, Fisher's exact, and Cox regression.

Among 319 patients, 121 met inclusion criteria. Fourteen (11.6%) had IDH-mutant astrocytomas, and 107 (88.4%) had IDH wild-type glioblastomas. Mean time to first recurrence was significantly longer in IDH-mutant patients (17.5 months) than IDH wild-type (9.8 months, p = 0.0130). Mean time-to-second recurrence was not significantly different (IDH-mutant: 10.8 months, IDH wild-type: 8.1 months, p = 0.176). Multivariate analysis found IDH wild-type status (p = 0.0491) and Black race (p = 0.0238) predicted shorter time to first recurrence.

IDH mutation status significantly affects time to first but not second recurrence. This study offers insight into recurrence patterns and highlights disparities in disease progression.

Gliomas, arising from supportive glial cells in the central nervous system, present significant challenges in oncology due to their varying aggressiveness and poor prognosis, particularly in high-grade forms. Understanding the molecular pathways involved in glioma progression is essential for developing effective treatment strategies. This study aimed to develop a fatty acid metabolism (FAM)-related gene signature to better predict poor prognosis in glioma patients, thereby facilitating more targeted therapeutic approaches. We employed the Least Absolute Shrinkage and Selection Operator regression analysis to identify a gene signature associated with FAM from The Cancer Genome Atlas and Chinese Glioma Genome Atlas RNA-seq datasets. Survival analyses, including Kaplan-Meier and Cox regression analyses, were conducted to assess the prognostic value of the identified genes. A total of seven FAM-related genes were associated with survival outcomes in isocitrate dehydrogenase-1 wild-type glioblastoma. The constructed gene signature effectively stratified patients into high-risk and low-risk groups, with high-risk patients demonstrating significantly poorer survival. PTGR1 emerged as the core gene, closely linked to malignant progression and poor prognosis. The FAM-related gene signature developed in this study provides a reliable tool for predicting poor outcomes in glioma patients. PTGR1, identified as a pivotal gene within this signature, may serve as a potential target for future therapeutic interventions, offering promising avenues for enhancing patient survival.

Temozolomide (TMZ) remains the primary oral chemotherapeutic agent for glioblastoma, but its efficacy is hampered by resistance mechanisms involving O6-methylguanine-DNA methyltransferase (MGMT). MGMT repairs the TMZ-induced lethal O6-methylguanine (O6-MeG) lesions, leading to treatment resistance. Current small molecule covalent MGMT inhibitors have limited clinical application due to severe hematological toxicity when used with TMZ. Therefore, alternative strategies to overcome MGMT-mediated resistance are critically needed. Targeting the Wnt/β-catenin signaling pathway to suppress MGMT expression presents a promising approach. We synthesized and discovered that a novel Wnt inhibitor, DK419 (6-chloro-2-(trifluoromethyl)-N-(4-(trifluoromethyl)phenyl)-1H -benzimidazole-4-carboxamide), effectively suppressed MGMT expression within 12 h in TMZ-resistant SF763 and SF767 cell lines. DK419 demonstrated synergistic cytotoxic effects with TMZ in these cell lines, while only an additive effect was observed in MGMT-negative SF126 cells. Furthermore, DK419 significantly enhanced TMZ's inhibitory effects on cell proliferation, colony formation, invasion, and migration, while also promoting apoptosis. In a resistant mouse tumor xenograft model, DK419 significantly boosted TMZ's tumor growth suppression, maintaining good biosafety. Western blot analysis revealed that DK419 markedly inhibited the nuclear translocation of β-catenin and decreased the expression of its downstream targets, Cyclin D1 and MGMT. The addition of the Wnt activator LiCl reversed DK419-induced effects on β-catenin nuclear translocation and Cyclin D1 and MGMT expression. For the first time, our findings demonstrate that DK419 can significantly enhance glioblastoma sensitivity to TMZ by modulating the Wnt/β-catenin pathway to downregulate MGMT expression.

Cancer progression and therapeutic resistance are closely linked to a stemness phenotype. Here, we introduce a protein-expression-based stemness index (PROTsi) to evaluate oncogenic dedifferentiation in relation to histopathology, molecular features, and clinical outcomes. Utilizing datasets from the Clinical Proteomic Tumor Analysis Consortium across 11 tumor types, we validate PROTsi's effectiveness in accurately quantifying stem-like features. Through integration of PROTsi with multi-omics, including protein post-translational modifications, we identify molecular features associated with stemness and proteins that act as active nodes within transcriptional networks, driving tumor aggressiveness. Proteins highly correlated with stemness were identified as potential drug targets, both shared and tumor specific. These stemness-associated proteins demonstrate predictive value for clinical outcomes, as confirmed by immunohistochemistry in multiple samples. The findings emphasize PROTsi's efficacy as a valuable tool for selecting predictive protein targets, a crucial step in customizing anti-cancer therapy and advancing the clinical development of cures for cancer patients.

Glioblastoma (GBM) is an aggressive Grade IV brain tumor with a poor prognosis. It results from genetic mutations, epigenetic changes, and factors within the tumor microenvironment (TME). Traditional treatments like surgery, radiotherapy, and chemotherapy provide limited survival benefits due to the tumor's heterogeneity and resistance mechanisms. This review examines novel approaches for treating GBM, focusing on repurposing existing medications such as antipsychotics, antidepressants, and statins for their potential anti-GBM effects. Advances in molecular profiling, including next-generation sequencing, artificial intelligence (AI), and nanotechnology-based drug delivery, are transforming GBM diagnosis and treatment. The TME, particularly GBM stem cells and immune evasion, plays a key role in therapeutic resistance. Integrating multi-omics data and applying precision medicine show promise, especially in combination therapies and immunotherapies, to enhance clinical outcomes. Addressing challenges such as drug resistance, targeting GBM stem cells, and crossing the blood-brain barrier is essential for improving treatment efficacy. While current treatments offer limited benefits, emerging strategies such as immunotherapies, precision medicine, and drug repurposing show significant potential. Technologies like liquid biopsies, AI-powered diagnostics, and nanotechnology could help overcome obstacles like the blood-brain barrier and GBM stem cells. Ongoing research into combination therapies, targeted drug delivery, and personalized treatments is crucial. Collaborative efforts and robust clinical trials are necessary to translate these innovations into effective therapies, offering hope for improved survival and quality of life for GBM patients.

Glioblastoma (GBM) is an exceedingly aggressive primary brain tumor defined by rapid growth, extensive infiltration, and resistance to standard therapies. A central factor driving these malignancies is the subpopulation of glioblastoma stem cells (GSCs), which possess self-renewal capacity, multipotency, and the ability to regenerate tumor heterogeneity. GSCs contribute to key hallmarks of GBM pathobiology, including relentless progression, resistance to chemotherapy and radiotherapy, and inevitable recurrence. GSCs exhibit distinct molecular signatures, enhanced DNA repair, and metabolic adaptations that protect them against conventional treatments. Moreover, they reside within specialized niches-such as perivascular or hypoxic microenvironments-that sustain stemness, promote immunosuppression, and facilitate angiogenesis. Recent discoveries highlight signaling pathways like Notch, Wnt/β-catenin, Hedgehog, STAT3-PARN, and factors such as TFPI2 and HML-2 as critical regulators of GSC maintenance, plasticity, and immune evasion. These findings underscore the complexity of GSC biology and their pivotal role in driving GBM heterogeneity and therapeutic failure. Emerging therapeutic strategies aim to target GSCs through multiple avenues, including surface markers, immunotherapeutics (e.g., CAR T cells), metabolic vulnerabilities, and combination regimens. Advances in patient-derived organoids, single-cell omics, and 3D co-culture models enable more accurate representation of the tumor ecosystem and personalized therapeutic approaches. Ultimately, improved understanding of GSC-specific targets and the tumor microenvironment promises more effective interventions, paving the way toward better clinical outcomes for GBM patients.

Glutamate and glutamine are critical metabolites in gliomas, each serving distinct roles in tumor biology. Separate quantification of these metabolites using in vivo MR spectroscopy (MRS) at clinical field strengths (≤ 3T) is hindered by their molecular similarity, resulting in overlapping, hence indistinguishable, spectral peaks.

To develop an MRS imaging (MRSI) protocol to map glutamate and glutamine separately at 3T within clinically feasible time, using J-modulation to enhance spectral differentiation, demonstrate its reliability/reproducibility, and quantify the metabolites in glioma subregions.

Prospective.

Phantoms, 5 healthy subjects, and 30 patients with suspected glioma. IDH wild-type glioblastoma cases were evaluated to establish a uniform group.

3T, Research protocol: 2D 1H sLASER MRSI (40 and 120 ms TE) with water reference, 3D T1-weighted and 2D T2-weighted. Trial-screening process: T1-weighted, T1-weighted contrast-enhanced, T2-weighted, FLAIR.

Spectral simulations and phantom measurements were performed to design and validate the protocol. Spectral quality/fitting parameters for scan-rescan measurements were obtained using LCModel. The proposed long-TE data were compared with short-TE data. BraTS Toolkit was employed for fully automated tumor segmentation.

Scan-rescan comparison was performed using Bland-Altman analysis. LCModel coefficient of modeling covariance (CMC) between glutamate and glutamine was mapped to evaluate their model interactions for each spectral fitting. Metabolite levels in tumor subregions were compared using one-way ANOVA and Kruskal-Wallis. A p value < 0.05 was considered statistically significant.

Spectral quality/fitting parameters and metabolite levels were highly consistent between scan-rescan measurements. A negative association between glutamate and glutamine models at short TE (CMC = -0.16 ± 0.06) was eliminated at long TE (0.01 ± 0.05). Low glutamate in tumor subregions (non-enhancing-tumor-core: 5.35 ± 4.45 mM, surrounding-non-enhancing-FLAIR-hyperintensity: 7.39 ± 2.62 mM, and enhancing-tumor: 7.60 ± 4.16 mM) was found compared to contralateral (10.84 ± 2.94 mM), whereas glutamine was higher in surrounding-non-enhancing-FLAIR-hyperintensity (9.17 ± 6.84 mM) and enhancing-tumor (7.20 ± 4.42 mM), but not in non-enhancing-tumor-core (4.92 ± 3.38 mM, p = 0.18) compared to contralateral (2.94 ± 1.35 mM).

The proposed MRSI protocol (~12 min) enables separate mapping of glutamate and glutamine reliably along with other MRS-detectable standard metabolites in glioma subregions at 3T.

1 TECHNICAL EFFICACY: Stage 3.

Recurrent isocitrate dehydrogenase (IDH) mutations catalyze nicotinamide adenine dinucleotide phosphate (NADPH)-dependent production of oncometabolite (R)-2-hydroxyglutarate (R-2HG) for tumorigenesis. IDH inhibition provides clinical response in a subset of acute myeloid leukemia (AML) cases; however, most patients develop resistance, highlighting the need for more effective IDH-targeting therapies. By comparing transcriptomic alterations in isogenic leukemia cells harboring CRISPR base-edited IDH mutations, we identify the activation of adhesion molecules including CD44, a transmembrane glycoprotein, as a shared feature of IDH-mutant leukemia, consistent with elevated CD44 expression in IDH-mutant AML patients. CD44 is indispensable for IDH-mutant leukemia cells through activating pentose phosphate pathway and inhibiting glycolysis by phosphorylating glucose-6-phosphate dehydrogenase and pyruvate kinase muscle isozyme M2, respectively. This metabolic rewiring ensures efficient NADPH generation for mutant IDH-catalyzed R-2HG production. Combining IDH inhibition with CD44 blockade enhances the elimination of IDH-mutant leukemia cells. Hence, we describe an oncogenic feedforward pathway involving CD44-mediated metabolic rewiring for oncometabolite production, representing a potentially targetable dependency of IDH-mutant malignancies.

In-vivo magnetic resonance spectroscopy (MRS) of 2-hydroxyglutarate (2HG) may provide diagnostic and monitoring biomarkers in isocitrate dehydrogenase (IDH)-mutated glioma. A previous meta-analysis has shown good diagnostic accuracy of TE-optimized PRESS for IDH-mutated glioma, but most studies feature IDH-wildtype glioma as a comparison. However, when considering newly identified brain lesions that may mimic glioma, full characterization of its diagnostic utility should also consider the accuracy of 2HG measurement in non-tumor tissue. Therefore, we tested how well TE-optimized 2HG levels distinguish between IDH-mutated glioma and non-tumor tissue, in this case, normal-appearing brain. We further examined the impact of different spectral modeling strategies (baseline stiffness, macromolecule inclusion, and basis set composition).

48 patients with diagnosed/suspected IDH-mutated glioma were enrolled. 3T MRS data were acquired from tumor and contralateral non-tumor tissue with PRESS localization (TE = 97 ms, optimized for 2HG detection) and analyzed with 'LCModel' software. Receiver operating characteristic analysis evaluated 2HG estimates' ability to distinguish IDH-mutated glioma from non-tumor brain tissue. Modeling interactions between 2HG and other metabolites were evaluated to identify reasons for potential false-positive 2HG detection.

TE-optimized PRESS distinguished IDH-mutated glioma from non-tumor tissue with lower sensitivity (range 0.76-0.62) and specificity (0.85-0.78) than literature suggests for IDH-mutated vs. IDH-wildtype glioma. Strong negative correlations between gamma-aminobutyric acid (GABA) and 2HG persisted across all modeling strategies and may lead to false-positive 2HG detection in non-tumor tissue. We further present a cautionary example from a patient on a ketogenic diet, showing that the ketone body acetone can interfere with 2HG detection.

Spectral overlap with GABA and acetone can lead to false-positive 2HG detection in non-tumor tissue. Clinicians need to be mindful of these pitfalls when interpreting 2HG estimates.

Isocitrate dehydrogenase IDH1 and IDH2, key enzymes in central and energy metabolism, are frequently mutated in acute myeloid leukemia (AML). They catalyze the production of the oncometabolite R-2-hydroxyglurate, which plays a key role in leukemogenesis and relapse of patients after standard AML treatments. Although the recent introduction of selective inhibitors of IDH1 (ivosidenib) and IDH2 (enasidenib) has improved the prognosis of patients with IDH1- and IDH2-mutant AML, several mechanisms of resistance to these treatments have already been identified, including metabolic reprogramming. The study of these mechanisms has opened up new therapeutic opportunities for the monitoring and treatment of patients with this subtype of AML.

Quantitative blood oxygenation level-dependent (qBOLD) technique can be applied to detect tissue damage and changes in hemodynamic in gliomas. It is not known whether qBOLD-based radiomics approaches can improve the prediction of isocitrate dehydrogenase-1 (IDH-1) mutation.

To establish a qBOLD-based clinical radiomics-integrated model for predicting IDH-1 mutation in gliomas.

A total of 125 patients of grade II-IV glioma (IDH1 mutation: IDH1 wild-type = 50:75) were divided into a training group (n = 87) and a validation group (n = 38). Contrast enhanced T1-weighted (CE-T1W), T2-weighted (T2W), and 3D multi-gradient-recalled-echo (MGRE) images were acquired. Radiomics features were extracted from the region of interests of each image. The feature selection and support vector machine radiomics models were established for each sequence. A clinical radiomics-integrated model was finally constructed combining the best radiomics model with age. The predictive effectiveness of the models was evaluated by area under the receiver operating characteristic curve (AUC). Brier score was used to assess overall predictive performance. Decision curve analysis and calibration curve were also conducted.

The best radiomics model was CE-T1W + T2W + qBOLD with AUCs of 0.823 (95% confidence interval [CI]: 0.743-0.831) in the training group and 0.751 (95% CI: 0.655-0.794) in the validation group, respectively. The clinical radiomics-integrated model, incorporating the best radiomics model with age, showed the best predictive effectiveness with AUCs of 0.851 (95% CI 0.759-0.918) in the training group and 0.786 (95% CI 0.622-0.902) in the validation group.

A clinical radiomics-integrated model that combined qBOLD parametric maps, CE-T1W, and T2W images with age achieved promising performance for predicting IDH1 mutation in glioma patients.

Enzymes are critical biological catalysts involved in maintaining the intricate balance of metabolic processes within living organisms. Mutations in enzymes can result in disruptions to their functionality that may lead to a range of diseases. This review focuses on computational studies that investigate the effects of disease-associated mutations in various enzymes. Through molecular dynamics simulations, multiscale calculations, and machine learning approaches, computational studies provide detailed insights into how mutations impact enzyme structure, dynamics, and catalytic activity. This review emphasizes the increasing impact of computational simulations in understanding molecular mechanisms behind enzyme (dis)function by highlighting the application of key computational methodologies to selected enzyme examples, aiding in the prediction of mutation effects and the development of therapeutic strategies.

Iron metabolism is a critical factor in tumorigenesis and development. Although TP53 mutations are prevalent in glioblastoma (GBM), the mechanisms by which TP53 regulates iron metabolism remain elusive. We reveal an imbalance iron homeostasis in GBM via TCGA database analysis. TP53 mutations disrupted iron homeostasis in GBM, characterized by elevated total iron levels and reduced ferritin (FTH). The gain-of-function effect triggered by TP53 mutations upregulates itchy E3 ubiquitin-protein ligase (ITCH) protein expression in astrocytes, leading to FTH degradation and an increase in free iron levels. TP53-mut astrocytes were more tolerant to the high iron environment induced by exogenous ferric ammonium citrate (FAC), but the increase in intracellular free iron made them more sensitive to Erastin-induced ferroptosis. Interestingly, we found that Erastin combined with FAC treatment significantly increased ferroptosis. These findings provide new insights for drug development and therapeutic modalities for GBM patients with TP53 mutations from iron metabolism perspectives.

Isocitrate dehydrogenase (IDH)-mutant astrocytomas show a peak incidence in young and middle-aged adults and have relatively favorable outcomes. In patients with these tumors ≥55 years at diagnosis, clinical, histopathologic, and prognostic characteristics are less clear. Here, we compared histopathological, immunohistochemical, molecular, and overall survival of 34 patients aged ≥55 years with a group of 84 patients aged 19-54 years; all had IDH mutant astrocytomas. The older cohort had 14 World Health Organization (WHO) grade 2, 7 WHO grade 3, and 13 WHO grade 4 tumors versus 24, 32, and 28 WHO grade 2, 3, and 4 tumors in the younger group. Comparing equal-grade tumors in both cohorts, Kaplan-Meyer survival analysis revealed that patients ≥55 years of age showed worse prognosis despite receiving comparable treatment regimens (Stupp protocol). Roughly equal numbers of noncanonical IDH mutations were seen in both groups (11.76% in ≥55 vs 19.04% in <55). Older patients were more likely to show retention of nuclear protein alpha-thalassemia and mental retardation X-linked syndrome (ATRX) and/or absence of strong P53 staining by immunohistochemistry. Although patients ≥55 years of age with astrocytomas, IDH-mutant, had worse overall survival, many, particularly those with low-grade tumors, had 5 years or greater survival. Employing parallel treatment regimens with chemotherapy, radiation, and maximum safe resection may improve survival of older patients with IDH mutant gliomas.

Reliable estimates for the number of cancer patients with a specific mutation can help quantify the size of the population that could potentially benefit from a targeted therapy. We adapt our previously developed approach for estimating gene-level mutation abundances to estimate mutation-specific (e.g., KRAS G12C) abundances by combining United States cancer epidemiology and genomic data. We demonstrate the approach by obtaining population-level estimates for all acquired somatic missense mutations that create a de novo cysteine residue. We find that approximately 14% of non-epidemiological informed estimates are more than twice the epidemiological informed estimate. Non-epidemiologically informed pan-cancer estimation of mutation rates may not be representative of the number of cancer patients with a specific mutation. Our study suggests that epidemiological and genomic information should be combined when estimating the population level abundance of specific pathogenic mutations.

Three-dimensional(3D) cell culture systems provide a larger space for cell proliferation, which is crucial for simulating cellular behavior and drug responses in the tumor microenvironment. In this study, we developed a novel 3D co-culture system for cell interactions, utilizing a commercialized bioreactor-microcarrier system. Mesenchymal stem cells (MSCs) were extracted via enzymatic digestion, and markers CD105 and CD31 were identified. Cell growth was observed using AO and immunofluorescence staining. No significant differences in Ki67 and GFAP expression were found between 2D and 3D cultures, though the 3D system offered more space for proliferation and reduced contact inhibition. Therefore, this 3D culture system may represent the tumor microenvironment more accurately than 2D cultures and will facilitate the investigation of the characteristics and functions of exosomes derived from this system. Exosomes are nanoscale vesicles that mediate intercellular communication by transferring molecules such as miRNAs between cells. Exosomes from 3D cultures were collected via ultra-high-speed centrifugation and characterized using nano-flow cytometry, transmission electron microscopy, and western blotting for markers CD9, Alix, and TSG101. PKH26 staining revealed peak exosome uptake by tumor cells at 24 h and complete metabolism by 72 h. Exosomes from 3D cultures inhibited GBM cell proliferation, migration, and invasion. Lastly, miRNA sequencing of exosomes was performed. This study emphasizes the importance of creating 3D co-culture systems to advance cancer research and offers a helpful tool for studying the complex cell interaction environment of GBM and other malignancies.

Glioma is a prevalent form of primary malignant central nervous system tumor, characterized by its cellular invasiveness, rapid growth, and the presence of the blood-brain barrier (BBB)/blood-brain tumor barrier (BBTB). Current therapeutic approaches, such as chemotherapy and radiotherapy, have shown limited efficacy in achieving significant antitumor effects. Therefore, there is an urgent demand for new treatments. Therapeutic peptides represent an innovative class of pharmaceutical agents with lower immunogenicity and toxicity. They are easily modifiable via chemical means and possess deep tissue penetration capabilities which reduce side effects and drug resistance. These unique pharmacokinetic characteristics make peptides a rapidly growing class of new therapeutics that have demonstrated significant progress in glioma treatment. This review outlines the efforts and accomplishments in peptide-based therapeutic strategies for glioma. These therapeutic peptides can be classified into four types based on their anti-tumor function: tumor-homing peptides, inhibitor/antagonist peptides targeting cell surface receptors, interference peptides, and peptide vaccines. Furthermore, we briefly summarize the results from clinical trials of therapeutic peptides in glioma, which shows that peptide-based therapeutic strategies exhibit great potential as multifunctional players in glioma therapy.

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

Cancer and cardiovascular disease (CVD) are the 2 biggest killers worldwide. Specific treatments have been developed for the 2 diseases. However, mutual therapeutic targets should be considered because of the overlap of cellular and molecular mechanisms. Cancer research has grown at a fast pace, leading to an increasing number of new mechanistic treatments. Some of these drugs could prove useful for treating CVD, which realizes the concept of cancer drug repurposing. This review provides a comprehensive outline of the shared hallmarks of cancer and CVD, primarily ischemic heart disease and heart failure. We focus on chronic inflammation, altered immune response, stromal and vascular cell activation, and underlying signaling pathways causing pathological tissue remodeling. There is an obvious scope for targeting those shared mechanisms, thereby achieving reciprocal preventive and therapeutic benefits. Major attention is devoted to illustrating the logic, advantages, challenges, and viable examples of drug repurposing and discussing the potential influence of sex, gender, age, and ethnicity in realizing this approach. Artificial intelligence will help to refine the personalized application of drug repurposing for patients with CVD. SIGNIFICANCE STATEMENT: Cancer and cardiovascular disease (CVD), the 2 biggest killers worldwide, share several underlying cellular and molecular mechanisms. So far, specific therapies have been developed to tackle the 2 diseases. However, the development of new cardiovascular drugs has been slow compared with cancer drugs. Understanding the intersection between pathological mechanisms of the 2 diseases provides the basis for repurposing cancer therapeutics for CVD treatment. This approach could allow the rapid development of new drugs for patients with CVDs.

Carcinomatosis is one of the leading threats to human public fitness. HNF1B is a critical transcription element in vertebrate proliferation and oncogenesis, which has been shown to play roles in reactive oxygen species (ROS) metabolism. Our previous results have identified HNF1B as a tumor suppressor that could inhibit the malignant progression of prostate cancer. Yet there is no pan-carcinomatosis analysis of HNF1B, which could help us better understand common and unique underlying mechanisms in mankind knubs to enhance novel and competent treatment. Here, in our research, we evaluated the utterance pattern and explored the function of HNF1B in 33 knub categories using the data from the Cancer Genome Atlas Program (TCGA), Gene Expression Omnibus (GEO), and CLNICAL PROTEOMICTUMOR ANALYSIS CONSORTIUM (CPTAC) dataset. We found different HNF1B roles in various cancer types. HNF1B was upregulated in CHOL, STAD, KIRP, and THCA, and was downregulated in GBM, KICH, COAD, KIRC, LUSC, SARC, PAAD, and TGCT. Prognostic analyses indicated that higher HNF1B displayed better illness outcomes in BLCA, READ, and PRAD, while poorer outcomes in LUSC and THYM. HNF1B mutation was most frequent in endometrial cancer but was not associated with disease prognosis. It was discovered that HNF1B utterance relevant to endothelial cell penetration status in BLCA, ESCA, LUAD, LUSC, and TGCT, and carcinomatosis-associated fibroblast infiltration was observed in ESCA, KIRC, LIHC, and TGCT. Moreover, functional enrichment analysis disclosed that metabolism-related functions were implicated in the function of HNF1B. Taken together, our pan- carcinomatosis analysis showed the complicated roles of HNF1B in a variety of carcinomatoses, being able to improve the extensive comprehension of HNF1B's role in tumorigenesis.

Precision medicine for pituitary neuroendocrine tumors (PitNETs) is limited by the lack of reliable research models.

To generate patient-derived organoids (PDOs), which could serve as a platform for personalized drug screening for PitNET patients.

From July 2019 to May 2022, a total of 32 human PitNET specimens were collected for the establishment of organoids with an optimized culture protocol.

This study was conducted at Sun Yat-Sen University Cancer Center.

PitNET patients who were pathologically confirmed were enrolled in this study.

Histological staining and whole-exome sequencing were utilized to confirm the pathologic and genomic features of PDOs. A drug response assay on PDOs was also performed.

PDOs retained key genetic and morphological features of their parental tumors.

PDOs were successfully established from various types of PitNET samples with an overall success rate of 87.5%. Clinical nonfunctioning PitNETs-derived organoids (22/23, 95.7%) showed a higher likelihood of successful generation compared to those from functioning PitNETs (6/9, 66.7%). Preservation of cellular structure, subtype-specific neuroendocrine profiles, mutational features, and tumor microenvironment heterogeneity from parental tumors was observed. A distinctive response profile in drug tests was observed among the organoids from patients with different subtypes of PitNETs. With the validation of key characteristics from parental tumors in histological, genomic, and microenvironment heterogeneity consistency assays, we demonstrated the predictive value of the PDOs in testing individual drugs.

The established PDOs, retaining typical features of parental tumors, indicate a translational significance in innovating personalized treatment for refractory PitNETs.

Glioma is the most aggressive primary malignant tumor of the central nervous system, characterized by high recurrence rates and resistance to chemoradiotherapy, making therapeutic resistance a major challenge in neuro-oncology. Recent research emphasizes the role of the tumor microenvironment (TME) and immune modulation in glioma progression and resistance. Despite these advances, a comprehensive bibliometric analysis of research trends in glioma chemoradiotherapy resistance over the past two decades is lacking. This study aims to systematically evaluate the research landscape, identify emerging hotspots, and provide guidance for future investigations.

Articles on glioma chemoradiotherapy resistance published between 2003 and 2023 were retrieved from the Web of Science Core Collection, resulting in 4,528 publications. Bibliometric tools, including VOSviewer, CiteSpace, and R packages such as bibliometrix and ggplot2, were used to analyze co-authorship networks, keyword evolution, and citation bursts to identify collaboration patterns, thematic developments, and influential contributions.

Publication output increased significantly between 2013 and 2022, peaking at 650 articles in 2022. Over 1,000 institutions from 88 countries contributed to this research. The United States, Switzerland, and Germany showed the highest citation impact, while China led in publication volume but demonstrated relatively lower citation influence. The research focus has shifted from traditional topics such as the "MGMT gene" to emerging areas including the "tumor microenvironment," "immune infiltration," and "nanoparticles." The androgen receptor was identified as a promising but underexplored therapeutic target.

Research on glioma chemoradiotherapy resistance has seen substantial growth, with increasing emphasis on immune modulation, the tumor microenvironment, and novel therapeutic targets such as the androgen receptor. This study represents the first comprehensive bibliometric analysis of this field, providing a detailed overview of research trends and potential directions for future studies. The findings highlight the need for strengthened international collaboration and multidisciplinary approaches to address the challenges of therapeutic resistance in glioma.

Craniofacial development gives rise to the complex structures of the face and involves the interplay of diverse cell types. Despite its importance, our understanding of human-specific craniofacial developmental mechanisms and their genetic underpinnings remains limited. Here, we present a comprehensive single-nucleus RNA sequencing (snRNA-seq) atlas of human craniofacial development from craniofacial tissues of 24 embryos that span six key time points during the embryonic period (4-8 post-conception weeks). This resource resolves the transcriptional dynamics of seven major cell types and uncovers distinct major cell types, including muscle progenitors and cranial neural crest cells (CNCCs), as well as dozens of subtypes of ectoderm and mesenchyme. Comparative analyses reveal substantial conservation of major cell types, alongside human biased differences in gene expression programs. CNCCs, which play a crucial role in craniofacial morphogenesis, exhibit the lowest marker gene conservation, underscoring their evolutionary plasticity. Spatial transcriptomics further localizes cell populations, providing a detailed view of their developmental roles and anatomical context. We also link these developmental processes to genetic variation, identifying cell type-specific enrichments for common variants associated with facial morphology and rare variants linked to orofacial clefts. Intriguingly, Neanderthal-introgressed sequences are enriched near genes with biased expression in cartilage and specialized ectodermal subtypes, suggesting their contribution to modern human craniofacial features. This atlas offers unprecedented insights into the cellular and genetic mechanisms shaping the human face, highlighting conserved and distinctly human aspects of craniofacial biology. Our findings illuminate the developmental origins of craniofacial disorders, the genetic basis of facial variation, and the evolutionary legacy of ancient hominins. This work provides a foundational resource for exploring craniofacial biology, with implications for developmental genetics, evolutionary biology, and clinical research into congenital anomalies.

Glioblastoma (GBM) is defined by heterogeneous and resilient cell populations that closely reflect neurodevelopmental cell types. Although it is clear that GBM echoes early and immature cell states, identifying the specific developmental programmes disrupted in these tumours has been hindered by a lack of high-resolution trajectories of glial and neuronal lineages. Here we delineate the course of human astrocyte maturation to uncover discrete developmental stages and attributes mirrored by GBM. We generated a transcriptomic and epigenomic map of human astrocyte maturation using cortical organoids maintained in culture for nearly 2 years. Through this approach, we chronicled a multiphase developmental process. Our time course of human astrocyte maturation includes a molecularly distinct intermediate period that serves as a lineage commitment checkpoint upstream of mature quiescence. This intermediate stage acts as a site of developmental deviation separating IDH-wild-type neoplastic astrocyte-lineage cells from quiescent astrocyte populations. Interestingly, IDH1-mutant tumour astrocyte-lineage cells are the exception to this developmental perturbation, where immature properties are suppressed as a result of D-2-hydroxyglutarate oncometabolite exposure. We propose that this defiance is a consequence of IDH1-mutant-associated epigenetic dysregulation, and we identified biased DNA hydroxymethylation (5hmC) in maturation genes as a possible mechanism. Together, this study illustrates a distinct cellular state aberration in GBM astrocyte-lineage cells and presents developmental targets for experimental and therapeutic exploration.