Search Results (491)

Background: This narrative review summarizes recent progress in artificial intelligence (AI), especially radiomics and deep learning, for non-invasive diagnosis and molecular profiling of gliomas. Methodology: A thorough literature search was conducted on PubMed, Scopus, and Embase for studies published from January 2020 to July 2025, focusing on clinical and technical research. In key areas, these studies examine AI models’ predictive capabilities with multi-parametric Magnetic Resonance Imaging (MRI) and Positron Emission Tomography (PET). Results: The domains identified in the literature include the advancement of radiomic models for tumor grading and biomarker prediction, such as Isocitrate Dehydrogenase (IDH) mutation, O6-methylguanine-dna methyltransferase (MGMT) promoter methylation, and 1p/19q codeletion. The growing use of convolutional neural networks (CNNs) and generative adversarial networks (GANs) in tumor segmentation, classification, and prognosis was also a significant topic discussed in the literature. Deep learning (DL) methods are evaluated against traditional radiomics regarding feature extraction, scalability, and robustness to imaging protocol differences across institutions. Conclusions: This review analyzes emerging efforts to combine clinical, imaging, and histology data within hybrid or transformer-based AI systems to enhance diagnostic accuracy. Significant findings include the application of DL to predict cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) deletion and chemokine CCL2 expression. These highlight the expanding capabilities of imaging-based genomic inference and the importance of clinical data in multimodal fusion. Challenges such as data harmonization, model interpretability, and external validation still need to be addressed. Full article

Diffuse gliomas are the most common primary brain tumors in adults in the Western world. According to the 2021 World Health Organization (WHO) classification of central nervous system (CNS) tumors, the assessment of isocitrate dehydrogenase (IDH1/2)-mutation status is essential for accurate patient stratification. In this study, we performed a comprehensive evaluation of IDH-mutation status in the intraoperative setting using the Idylla platform. The reference cohort comprised 30 formalin-fixed paraffin-embedded (FFPE) tissue samples with known IDH status, while the exploration cohort included 35 intraoperative snap-frozen and native-tissue specimens. The results were compared with those of a standard next-generation sequencing (NGS) analysis. Our findings demonstrate that the Idylla IDH-mutation assay provides 100% concordance compared with NGS analysis for both FFPE and intraoperative tissue samples. The Idylla system delivers results within approximately 90 min, significantly outperforming NGS, which requires between 7 and 27 days. This rapid turnaround facilitates timely interdisciplinary case discussions and enables timely therapy planning, within the framework of neuro-oncological molecular tumor boards. The ultra-fast intraoperative IDH-mutation analysis using the Idylla platform, in combination with intraoperative histopathological assessment, enables rapid patient stratification and treatment planning in diffuse gliomas. Full article

Background: Wide application of genome sequencing technologies has highlighted extensive genetic diversity in Acute Myeloid Leukemia (AML), yet the specific roles of individual genes remain unclear. This systematic review and meta-analysis aims to provide robust evidence for the prognostic impact of somatic gene mutations in de novo AML patients, while also exploring the prevalence of these mutations. Methods: Eligible studies were identified from PubMed and Scopus, with a focus on those reporting the prognostic influence of somatic gene mutations on overall survival (OS) or relapse-free survival (RFS) when compared to wild-type carriers. We calculated the pooled prevalence with 95% confidence intervals to assess the frequency of these mutations, and the pooled Hazard Ratio (HR) to compare OS and RFS associated with specific gene mutations. Results: We evaluated 53 somatic gene mutations using 80 studies, involving 20,048 de novo AML patients. The analysis revealed that the most prevalent affected genes were NPM1 (27%), DNMT3A (26%), and FLT3-ITD (24%). Mutations in CSF3R, TET2, and TP53 were significantly associated with poorer OS or RFS (p < 0.05). Sensitivity analysis confirmed that ASXL1, DNMT3A, and RUNX1 mutations were consistently linked to inferior OS or RFS. In contrast, CEBPAdm mutations were associated with favorable OS [HR = 0.39 (0.30–0.50)] and RFS [HR = 0.44 (0.37–0.54)]. Subgroup analysis showed that FLT3-ITD mutations were consistently associated with worse OS or RFS across all subgroups, though no significant subgroup differences were noted. No significant impact on OS or RFS was observed for mutations in GATA2, FLT3-TKD, KRAS, NRAS, IDH1, and IDH2. Conclusions: These findings provide critical insights into AML prognosis, aiding clinical decision-making and improving risk stratification strategies. Full article

Background: Biliary tract cancer (BTC) management has undergone tremendous changes, benefiting from the identification of highly actionable molecular alterations. Among these, IDH1 mutations and FGFR2 fusions are the most common alterations detected and are classified as ESCAT tier 1 in BTC. However, their prognostic value in real-world settings remains uncertain. Objective: To explore overall survival (OS) in patients harbouring locally advanced or metastatic BTC (mBTC) with IDH1 or FGFR2 alterations, compared to those with wild-type tumours. Methods: This retrospective, multicentre study included patients with mBTC treated between 2020 and 2023 across five French centres. Patients were categorized into two cohorts based on molecular profiling: those with IDH1 or FGFR2 alterations, and those with wild-type tumours (WT-mBTC). Results: 119 consecutive patients were included. 18 were classified as altered (IDH1 = 13; FGFR2 = 5). Sixty-four pts underwent no molecular testing. The median OS of the entire cohort was 11.9 months (10.3–14.3). The median OS was 24.2 months (12.3–NA) versus 10.8 months (7.9–12.9), p = 0.02, in the altered and WT-mBTC cohorts, respectively. The Cox regression model conducted depicted an HR for death of 0.46 (CI95%, 0.2–0.9) for IDH1 or FGFR2 alterations. There were no diffence in PFS for first-line. Conclusions: Our cohort suggests that IDH1 or FGFR2 alterations may be associated with prognostic differences in patients with metastatic BTC, although they do not appear to influence outcomes under first-line treatment. These findings are consistent with trends observed in clinical trials. Whether improved survival is solely attributable to targeted therapies remains questionable. In line with ESMO recommendations, systematic molecular profiling should be considered in patients with mBTC. Full article

Background: Fluorescence-guided surgery using 5-aminolevulinic acid (5-ALA) enables the intraoperative visualization of glioma. However, its effectiveness varies based on tumor subtype and molecular profile, posing challenges for achieving complete resection. Our systematic review aims to explore the relationship between IDH mutation status and intraoperative fluorescence visualization. Importantly, this is the first study to propose that vorasidenib, an emerging IDH-targeting agent, could enhance 5-ALA-guided surgery, marking a novel direction for translational research. Methods: A systematic literature search was conducted using the PubMed, Cochrane Library, Scopus and Web of Science databases up to May 2025, following PRISMA guidelines. The primary outcomes included fluorescence detection rates across different glioma subtypes and their correlation with IDH mutation status. Secondary outcomes comprised surgical efficacy measures such as gross total resection (GTR), overall survival (OS), and progression-free survival (PFS). Additionally, we analyzed the metabolic consequences of IDH mutations and evaluated the potential role of vorasidenib in enhancing 5-ALA-induced fluorescence. Results: Seven studies including 621 patients included in the final analysis. Fluorescence detection was nearly universal in WHO grade 4 gliomas (94–100%), but lower in grade 3 (43–85%) and rare in grade 2 (7–26%). Several cohorts reported reduced fluorescence in IDH-mutant gliomas, although this was not consistent across all studies. In high-grade gliomas, visible fluorescence correlated with higher GTR rates and, in some series, longer OS. Conversely, in lower-grade IDH-mutant gliomas, fluorescence did not increase GTR and was associated with worse PFS and OS. Conclusions: The effectiveness of 5-ALA-guided fluorescence in glioma surgery is significantly influenced by both tumor grade and IDH mutation status. Vorasidenib may represent a potential avenue for modulating tumor metabolism and enhancing intraoperative fluorescence in IDH-mutant gliomas, a hypothesis that warrants further experimental validation. Full article

Background: Blood-based comprehensive genomic profiling (CGP), a form of liquid biopsy, is often used for biliary tract cancer (BTC) when tissue-based CGP (tissue CGP) is unavailable, despite lower detection rates. This study explored factors linked to detecting actionable genomic alterations to optimize its use. Methods: We retrospectively analyzed BTC cases in Japan’s C-CAT (June 2019–January 2025), restricting panel comparisons to FoundationOne^® CDx (F1; n = 5019) and FoundationOne^® Liquid CDx (F1L; n = 1550). Missing covariates were handled by multiple imputations (m = 20). Between-panel balance used 1:1 propensity-score matching (caliper 0.2). Outcomes were modeled with logistic regression. Targets included MSI-H, TMB-H, FGFR2/RET/NTRK fusions, BRAF V600E, KRAS G12C, IDH1 mutations, and ERBB2 amplification. An exploratory analysis stratified results by the number of prespecified enrichment factors (0–4). Liquid biopsy was performed using plasma-based comprehensive genomic profiling assays (FoundationOne^® Liquid). Results: Missingness was low; after matching (n = 1549 per group) covariates were well balanced (all|SMD|≤0.05). Detection of any actionable alteration was lower with F1L than F1 (16.8% vs. 24.8%; OR 0.61, 95% CI 0.49–0.75; p < 0.001). F1L also had lower TMB-H (OR 0.62, 0.43–0.90; p = 0.01) and ERBB2 amplification (OR 0.42, 0.31–0.57; p < 0.001), with no significant differences for MSI-H, IDH1, KRAS G12C, or BRAF V600E. Within F1L, non-perihilar location (OR 2.05), liver (1.90), lymph-node (1.41), and lung metastases (1.52) predicted detection of actionable genomic alterations. F1L detection increased from 5.8% (zero factors) to 32.8% (four factors), approximating tissue at three factors. Conclusions: The utility of liquid biopsy can be maximized by carefully selecting samples on the basis of conditions that increase the detection rate. Full article

Background: Cholangiocarcinoma (CCA) is a highly heterogeneous malignancy arising from the biliary epithelium, with an increasing incidence and poor prognosis worldwide. Recent advances in next-generation sequencing have revealed a variety of genomic alterations―such as FGFR2 fusions, IDH1 mutations, and ERBB2 amplification―that may serve as therapeutic targets. However, the influence of underlying etiologic factors, including chronic liver and biliary diseases, on the molecular landscape of CCA remains unclear. Objective: This review aimed to synthesize the current knowledge on the genomic and molecular alterations of CCA in the context of diverse etiologic factors, including hepatitis B virus, hepatitis C virus, primary sclerosing cholangitis (PSC), primary biliary cholangitis, metabolic dysfunction-associated steatotic liver disease (MASLD), alcohol-related liver disease (ALD), and liver fluke infection. Main findings: Certain backgrounds, such as PSC and liver fluke infection, are associated with distinct molecular signatures (e.g., TP53, SMAD4, KRAS, and ERBB2 alterations), whereas others, such as MASLD or ALD, show limited and inconsistent genomic data. Targetable alterations―including FGFR2 fusions, IDH1 mutations, and ERBB2 amplification―are heterogeneously distributed across etiologies and anatomical subtypes. Molecular targeted therapies such as FGFR and IDH1 inhibitors have shown clinical benefits in selected patients. Conclusions: A better understanding of how chronic liver and biliary diseases shape the genomic landscape of CCA will inform the development of personalized treatments, surveillance strategies, and preventive approaches. Large-scale etiology-stratified genomic studies integrating multiomics and real-world clinical data are urgently needed to advance precision oncology in CCA. Full article

Isocitrate dehydrogenase 1 (IDH1) mutations are key drivers of glioma biology, influencing tumor aggressiveness and treatment response. To elucidate their molecular impact, we performed proteome analysis on patient-derived (PD) and U87MG glioma cell models with either mutant or wild-type IDH1. We quantified over 6000 protein groups per model, identifying 1594 differentially expressed proteins in PD-AS (IDH1_MUT) vs. PD-GB (IDH1_WT) and 904 in U87_MUT vs. U87_WT. Both IDH1_MUT models exhibited enhanced MHC antigen presentation and interferon signaling, indicative of an altered immune microenvironment. However, metabolic alterations were model-dependent: PD-AS cells shifted toward glycolysis and purine salvage, while U87_MUT cells retained oxidative phosphorylation, potentially due to D2-hydroxyglutarate (2OHG)-mediated HIF1A stabilization. We also observed a predominance of downregulated DNA repair proteins in IDH1_MUT models, particularly those involved in homologous recombination. In contrast, RB1 and ASMTL were strongly upregulated in both IDH1_MUT models, implicating them in DNA repair and cellular stress responses. We also found distinct expression patterns of proteins regulating histone methylation in IDH1_MUT cells, favoring increased methylation of H3K4, H3K9, and H3K36. A key driver of this may be the upregulation of SETD2 in PD-AS, an H3K4 and H3K36 trimethyltransferase linked to the recruitment of HIF1A as well as DNA mismatch repair proteins. This study uncovers candidate biomarkers and pathways relevant to glioma progression and therapeutic targeting, but also underscores the complexity of predicting glioma pathogenesis and treatment responses based on IDH1 mutation status. While proteome profiling provides valuable insights, a comprehensive understanding of IDH1_MUT gliomas will likely require integrative multi-omics approaches, including DNA/RNA methylation profiling, histone and protein post-translational modification analyses, and targeted DNA damage and repair assays. Full article

The development of molecular profiling approaches for AML patients such as whole genome sequencing, whole exome sequencing and transcriptomic sequencing have greatly contributed to better understanding of leukemia development, progression and treatment responsiveness/resistance. These studies have generated a new knowledge about driver events operating in AML that can be translated into clinics, thus favoring the mutations; using this approach, more than 50% of older AML patients display molecular alterations, such as IDH1, IDH2, FLT3 (FLT3-TKD and FLT3-ITD), NPM1 and KMT2A rearrangements that can be targeted by specific drugs. Preclinical and clinical studies have supported the use of drugs targeting these molecular alterations as first-line therapy in association with induction chemotherapy in chemotherapy-fit patients or with a hypomethylating agent in association with a Bcl-2 inhibitor (Venetoclax) in chemotherapy-unfit patients. These studies have shown promising results that need to be confirmed through randomized clinical studies specifically involving the enrollment of older AML patients. Full article

Background: Gliomas are among the most complex and lethal primary brain tumors, necessitating precise evaluation of both anatomical subregions and molecular alterations for effective clinical management. Methods: To find a solution to the disconnected nature of current bioimage analysis pipelines, where anatomical segmentation based on MRI and molecular biomarker prediction are done as separate tasks, we use here Molecular-Genomic and Multi-Task (MGMT-Net), a one deep learning scheme that carries out the task of the multi-modal MRI data without any conversion. MGMT-Net incorporates a novel Cross-Modality Attention Fusion (CMAF) module that dynamically integrates diverse imaging sequences and pairs them with a hybrid Transformer–Convolutional Neural Network (CNN) encoder to capture both global context and local anatomical detail. This architecture supports dual-task decoders, enabling concurrent voxel-wise tumor delineation and subject-level classification of key genomic markers, including the IDH gene mutation, the 1p/19q co-deletion, and the TERT gene promoter mutation. Results: Extensive validation on the Brain Tumor Segmentation (BraTS 2024) dataset and the combined Cancer Genome Atlas/Erasmus Glioma Database (TCGA/EGD) datasets demonstrated high segmentation accuracy and robust biomarker classification performance, with strong generalizability across external institutional cohorts. Ablation studies further confirmed the importance of each architectural component in achieving overall robustness. Conclusions: MGMT-Net presents a scalable and clinically relevant solution that bridges radiological imaging and genomic insights, potentially reducing diagnostic latency and enhancing precision in neuro-oncology decision-making. By integrating spatial and genetic analysis within a single model, this work represents a significant step toward comprehensive, AI-driven glioma assessment. Full article

Background/Objectives: Lower-grade glioma (LGG) is a type of brain tumor with a relatively better prognosis than glioblastoma. However, identifying therapeutic targets for LGGs remains elusive. To uncover the molecular features of LGGs, functional genomics data have been investigated. Methods: Using public transcriptomics data of LGGs (The Cancer Genome Atlas and GSE107850), differentially expressed genes (DEGs) and differentially co-expressed (DCE) gene pairs between IDH mutation statuses were determined. Gene set enrichment analysis identified the molecular mechanisms of isocitrate dehydrogenase (IDH) mutation in LGGs. Furthermore, the identified DEGs and DCE gene pairs were used for drug repurposing analysis. Results: Two public datasets revealed an overlap of 1527 DEGs. Whereas only seven gene pairs showed significant differential co-expression in both datasets, 1016 genes were simultaneously involved in differential co-expression. Gene set enrichment revealed that biological processes related to neuronal tissue formation were significantly associated with the DEGs. Using drug repurposing analysis, it was found that NVP-TAE684 and bisindolylmaleimide were possible chemical compounds for the LGG treatment. Conclusions: Using transcriptomics data, molecular mechanisms associated with LGG prognosis were identified. This work provides clues for future research on LGG treatment. Full article

B-cell acute lymphoblastic leukemia (B-ALL) remains a major clinical challenge in hematologic oncology, characterized by a continuous evolution of molecular drivers that shape its heterogeneity across the age spectrum. Pediatric B-ALL is generally associated with high cure rates, while adult forms of the disease are often more aggressive and less responsive to treatment. This review examines the age-specific genetic and epigenetic landscapes that contribute to this disparity, revealing how the nature and timing of molecular alterations point to fundamentally different leukemogenic processes. Favorable genetic aberrations, such as ETV6::RUNX1 and hyperdiploidy, are predominant in children, whereas adults more frequently present with high-risk features, including BCR::ABL1 fusions and IKZF1 deletions. Epigenetic distinctions are similarly age-dependent, involving divergent patterns of DNA methylation, histone modifications, and non-coding RNA expression. For example, pediatric B-ALL frequently harbors mutations in epigenetic regulators like SETD2 and CREBBP, while adult B-ALL is more commonly affected by alterations in TET2 and IDH1/2. These molecular differences are not only prognostic but also mechanistic, reflecting distinct developmental trajectories and vulnerabilities. Understanding these age-driven transitions is essential for improving risk stratification and developing precision therapies tailored to the unique biology of B-ALL across the lifespan. Full article

Acute Myeloid Leukemia (AML) is a genetically and clinically heterogeneous malignancy marked by poor prognosis and limited therapeutic options, especially in older patients. While conventional treatments such as the “7 + 3” chemotherapy regimen and allogeneic stem cell transplantation remain standard care options, the advent of next-generation sequencing (NGS) has transformed our understanding of AML’s molecular complexity. Among the emerging hallmarks of AML, metabolic reprogramming has gained increasing attention for its role in supporting leukemic cell proliferation, survival, and therapy resistance. Distinct AML subtypes—shaped by specific genetic alterations, including FLT3, NPM1, and IDH mutations—exhibit unique metabolic phenotypes that reflect their underlying molecular landscapes. Notably, FLT3-ITD mutations are associated with enhanced reactive oxygen species (ROS) production and altered energy metabolism, contributing to disease aggressiveness and poor clinical outcomes. This review highlights the interplay between metabolic plasticity and genetic heterogeneity in AML, with a particular focus on FLT3-driven metabolic rewiring. We discuss recent insights into how these metabolic dependencies may be exploited therapeutically, offering a rationale for the development of metabolism-targeted strategies in the treatment of FLT3-mutated AML. Full article

Objectives: To investigate the correlation between intraoperative conventional ultrasound, SWE, and SMI ultrasound manifestations of glioma and the expression of immunohistochemical markers. Methods: Patients with single superficial supratentorial glioma scheduled for brain tumor resection in our neurosurgery department from October 2020 to October 2022 were prospectively included. High-grade glioma (HGG) and low-grade glioma (LGG) were classified by pathological histological grading, and the differences in conventional ultrasound, SWE Young’s modulus, and SMI intratumoral and peritumoral blood flow architecture between HGG and LGG were analyzed, and the SWE diagnostic cut-off value was calculated by the Youdon index. Logistic regression models were used to analyze the independent predictive ultrasound signs associated with the diagnosis of HGG. HGG and LGG were classified by pathological histological grading. IDH1 expression was measured by immunohistochemical methods to analyze the correlation between IDH1 expression in glioma and clinical and ultrasound characteristics. Results: Forty-eight patients with glioma admitted to our hospital from October 2020 to October 2022 were included in this study, including 30 (62.5%) with HGG and 18 (37.5%) with LGG. For conventional ultrasound, HGG was often associated with severe peritumoral edema compared with LGG (p = 0.048). The sensitivity of HGG was 88.9%, the specificity was 86.7%, and the AUC was 0.855 (95% confidence interval: 0.741–0.968, p = 0.001) using Young’s mode 13.90 kPa as the threshold. Logistic analysis showed that SWE Young’s modulus values, and peritumoral and intratumoral SMI blood flow structures, were associated with the diagnosis of HGG. Among the 48 gliomas, 22 (45.8%) were IDH1-positive and 26 (54.2%) were IDH1-negative, with no statistical difference in age between the two groups and a statistical difference in histological grading (p < 0.05). There was a statistical difference between IDH1 mutant and wild type in terms of peritumoral edema and SMI intratumoral and peritumoral tissue vascular architecture. Logistic regression models showed that intratumoral and peritumoral tissue SMI vascular architecture was a valid predictor of IDH1 positivity, with a classification accuracy of 81.3%, sensitivity of 90.9%, and specificity of 73.1%. Further group analysis of mutant Young’s modulus values in LGG were higher than wild-type Young’s modulus values (p = 0.031). Conclusions: Peritumoral and intratumoral tissue SMI vascular architecture was a valid predictor of IDH1 positivity. Based on intraoperative ultrasound multimodality images, we can preoperatively determine the expression of molecular markers of lesions, which is of clinical significance for optimizing surgical strategies and predicting prognosis. Full article

Background/Objectives: Astrocytoma, IDH-mutant, CNS WHO grade 3, is a diffuse glioma with poor prognosis, molecularly defined by IDH mutations and frequently co-occurring TP53 and ATRX alterations. This study aimed to delineate the genomic landscape and identify clinically relevant molecular features of astrocytoma, IDH-mutant, CNS WHO grade 3 using this resource. Methods: Patients in the American Association for Cancer Research Project Genomics Evidence Neoplasia Information Exchange (AACR Project GENIE) database were selected based on histological diagnosis of “anaplastic astrocytoma”, confirmed IDH1/2 mutation, and exclusion of CDKN2A/B homozygous deletions. We analyzed frequencies of somatic mutations, copy number alterations (CNAs), structural variants (SVs), assessed co-occurrence/exclusivity patterns, and explored associations with available demographic and limited survival data. Results: The most common somatic mutations were in IDH1 (98.0%), TP53 (94.8%), and ATRX (55.2%). The observed ATRX mutation frequency was lower than some historical reports (e.g., ~86%). Other recurrent alterations included phosphatidylinositol-4,5-bisphosphate 3-kinase catalytic subunit alpha (PIK3CA) (6.9%), Notch receptor 1 (NOTCH1) (6.9%), and platelet-derived growth factor receptor alpha (PDGFRA) (mutations 4.3%; CNAs also observed). Conclusions: This study provides a comprehensive genomic characterization of astrocytoma, IDH-mutant, CNS WHO grade 3 using the AACR GENIE database, confirming core mutational signatures while also highlighting potential variations in alteration frequencies, such as for ATRX. The findings establish a valuable real-world genomic benchmark for this tumor type, while promoting the need for continued data integration with robust clinical outcomes to identify actionable prognostic and therapeutic targets. Full article