Question: You are an expert researcher providing comprehensive, well-cited information.

Provide detailed information focusing on: 1. Key concepts and definitions with current understanding 2. Recent developments and latest research (prioritize 2023-2024 sources) 3. Current applications and real-world implementations 4. Expert opinions and analysis from authoritative sources 5. Relevant statistics and data from recent studies

Format as a comprehensive research report with proper citations. Include URLs and publication dates where available. Always prioritize recent, authoritative sources and provide specific citations for all major claims.

Disease Characteristics Research Template

Target Disease

• Disease Name: Glioma
• MONDO ID: (if available)
• Category: Cancer

Research Objectives

Please provide a comprehensive research report on Glioma covering all of the disease characteristics listed below. This report will be used to populate a disease knowledge base entry. Be thorough and cite primary literature (PMID preferred) for all claims.

For each section, suggested databases/resources are listed. These are the first places you should search for information on each topic.

1. Disease Information

Search first: OMIM, Orphanet, ICD-10/ICD-11, MeSH, PubMed

• What is the disease? Provide a concise overview.
• What are the key identifiers? (OMIM, Orphanet, ICD-10/ICD-11, MeSH, Mondo)
• What are the common synonyms and alternative names?
• Is the information derived from individual patients (e.g., EHR) or aggregated disease-level resources?

2. Etiology

• Disease Causal Factors: What are the primary causes? (genetic, environmental, infectious, mechanistic)
• Risk Factors:

  Search first: PubMed, Cochrane Library, UpToDate, clinical guidelines, ClinVar, ClinGen, GWAS Catalog, PheGenI, CTD, CDC, WHO, epidemiological databases

• Genetic risk factors (causal variants, susceptibility loci, modifier genes)
• Environmental risk factors (toxins, lifestyle, occupational exposures, age, sex, family history)
• Protective Factors:

  Search first: PubMed, Cochrane Library, clinical trial databases, GWAS Catalog, gnomAD, WHO, CDC, nutrition databases

• Genetic protective factors (protective variants, modifier alleles)
• Environmental protective factors (diet, lifestyle, exposures that reduce risk)
• Gene-Environment Interactions: How do genetic and environmental factors interact to influence disease?

  Search first: CTD, PubMed, PheGenI, GxE databases

3. Phenotypes

Search first: HPO (Human Phenotype Ontology), OMIM, Orphanet, PubMed, clinicaltrials.gov, MedDRA, SNOMED CT, DECIPHER, LOINC

For each phenotype, provide: - Phenotype type: symptoms, clinical signs, physical manifestations, behavioral changes, or laboratory abnormalities

For symptoms/signs: HPO, OMIM, Orphanet, PubMed For behavioral changes: HPO, DSM, RDoC (Research Domain Criteria), PubMed For laboratory abnormalities: LOINC, SNOMED CT, LabTests Online, PubMed - Phenotype characteristics: Search first: OMIM, Orphanet, HPO, PubMed - Age of symptom onset (neonatal, childhood, adult-onset, late-onset) - Symptom severity (mild, moderate, severe, variable) - Symptom progression (stable, progressive, episodic, fluctuating) - Frequency among affected individuals (percentage or qualitative) - Quality of life impact: Effects on daily functioning and well-being (per-phenotype when possible) Search first: EQ-5D database, SF-36, WHO QOL databases, PubMed - Suggest HPO (Human Phenotype Ontology) terms for each phenotype

4. Genetic/Molecular Information

• Causal Genes: Gene mutations or chromosomal abnormalities responsible for disease (gene symbols, OMIM IDs)

  Search first: OMIM, ClinVar, HGMD, Ensembl, NCBI Gene

• Pathogenic Variants:
• Affected genes (gene symbols, HGNC IDs) > Search first: OMIM, NCBI Gene, Ensembl, HGNC, UniProt, GeneCards
• Variant classification (pathogenic, likely pathogenic, VUS per ACMG/AMP guidelines) > Search first: ClinVar, ClinGen, ACMG/AMP guidelines, VarSome
• Variant type/class (missense, frameshift, nonsense, splice-site, structural)
• Allele frequency in population databases > Search first: gnomAD, 1000 Genomes, ExAC, TOPMed, dbSNP
• Somatic vs germline origin > Search first: COSMIC (somatic), ClinVar, ICGC, TCGA
• Functional consequences (loss of function, gain of function, dominant negative)
• Modifier Genes: Genes that modify disease severity or expression
• Epigenetic Information: DNA methylation, histone modifications, chromatin changes affecting disease

  Search first: ENCODE, Roadmap Epigenomics, MethBase, DiseaseMeth

• Chromosomal Abnormalities: Large-scale genetic changes (aneuploidy, translocations, inversions)

  Search first: DECIPHER, ClinVar, ECARUCA, UCSC Genome Browser

5. Environmental Information

• Environmental Factors: Non-genetic contributing factors (toxins, radiation, pollution, occupational exposure)

  Search first: CTD (Comparative Toxicogenomics Database), TOXNET, PubMed, EPA databases

• Lifestyle Factors: Behavioral factors (smoking, diet, exercise, alcohol consumption)

  Search first: CDC databases, WHO, PubMed, NHANES

• Infectious Agents: If applicable, pathogens causing or triggering disease (bacteria, viruses, fungi, parasites)

  Search first: NCBI Taxonomy, ViPR, BV-BRC, MicrobeDB, GIDEON

6. Mechanism / Pathophysiology

• Molecular Pathways: Specific signaling cascades or biochemical pathways involved (Wnt, MAPK, mTOR, PI3K-AKT, etc.)

  Search first: KEGG, Reactome, WikiPathways, PathBank, BioCyc

• Cellular Processes: Cell-level mechanisms (apoptosis, autophagy, cell cycle dysregulation, inflammation, etc.)

  Search first: Gene Ontology (GO), Reactome, KEGG, PubMed

• Protein Dysfunction: How protein structure or function is altered (misfolding, aggregation, loss of function, gain of function)

  Search first: UniProt, PDB (Protein Data Bank), InterPro, Pfam, AlphaFold

• Metabolic Changes: Alterations in metabolic processes (energy metabolism, lipid metabolism, amino acid metabolism)

  Search first: KEGG, BioCyc, HMDB (Human Metabolome Database), BRENDA

• Immune System Involvement: Role of immune response (autoimmunity, immunodeficiency, chronic inflammation)

  Search first: ImmPort, Immunome Database, IEDB, Gene Ontology

• Tissue Damage Mechanisms: How tissues/ are injured (oxidative stress, ischemia, fibrosis, necrosis)

  Search first: PubMed, Gene Ontology, Reactome

• Biochemical Abnormalities: Specific molecular defects (enzyme deficiencies, receptor dysfunction, ion channel defects)

  Search first: BRENDA, UniProt, KEGG, OMIM, PubMed

• Epigenetic Changes: DNA methylation, histone modifications affecting gene expression in disease

  Search first: ENCODE, Roadmap Epigenomics, MethBase, DiseaseMeth

• Molecular Profiling (if available):
• Transcriptomics/gene expression changes > Search first: GEO (Gene Expression Omnibus), ArrayExpress, GTEx, Human Cell Atlas, SRA
• Proteomics findings > Search first: PRIDE, ProteomeXchange, Human Protein Atlas, STRING, BioGRID
• Metabolomics signatures > Search first: MetaboLights, Metabolomics Workbench, HMDB, METLIN
• Lipidomics alterations > Search first: LIPID MAPS, SwissLipids, LipidHome, Metabolomics Workbench
• Genomic structural features > Search first: UCSC Genome Browser, Ensembl, NCBI, dbVar, DGV
• Advanced Technologies (if applicable):
• Single-cell analysis findings (cell-type specific mechanisms, cellular heterogeneity) > Search first: Human Cell Atlas, Single Cell Portal, GEO, CELLxGENE
• Spatial transcriptomics findings > Search first: GEO, Spatial Research, Vizgen, 10x Genomics data
• Multi-omics integration results > Search first: TCGA, ICGC, cBioPortal, LinkedOmics, PubMed
• Functional genomics screens (CRISPR, RNAi) > Search first: DepMap, GenomeRNAi, PubMed, BioGRID ORCS

For each mechanism, describe: - The causal chain from initial trigger to clinical manifestation - Which mechanisms are upstream vs downstream - What cell types and biological processes are involved - Suggest GO terms for biological processes and CL terms for cell types

7. Anatomical Structures Affected

• Organ Level:
• Primary organs directly affected
• Secondary organ involvement (complications, secondary effects)
• Body systems involved (cardiovascular, nervous, digestive, respiratory, endocrine, etc.)

  Search first: Uberon, FMA (Foundational Model of Anatomy), OMIM, HPO, ICD-11, MeSH, SNOMED CT

• Tissue and Cell Level:
• Specific tissue types affected (epithelial, connective, muscle, nervous)
• Specific cell populations targeted (with Cell Ontology terms)

  Search first: Uberon, Human Protein Atlas, Cell Ontology, Human Cell Atlas, CellMarker, PanglaoDB

• Subcellular Level:
• Cellular compartments involved (mitochondria, nucleus, ER, lysosomes) (with GO Cellular Component terms)

  Search first: Gene Ontology (Cellular Component), UniProt, Human Protein Atlas

• Localization:
• Specific anatomical sites (with UBERON terms) > Search first: FMA, Uberon, NeuroNames (for brain), SNOMED CT
• Lateralization (unilateral, bilateral, asymmetric) > Search first: HPO, clinical literature, imaging databases

8. Temporal Development

• Onset:
• Typical age of onset (congenital, pediatric, adult, geriatric)
• Onset pattern (acute, subacute, chronic, insidious)

  Search first: OMIM, Orphanet, HPO, PubMed

• Progression:
• Disease stages (early, intermediate, advanced, end-stage) > Search first: Cancer Staging Manual (AJCC), WHO classifications, PubMed
• Progression rate (rapid, slow, variable)
• Disease course pattern (episodic, relapsing-remitting, progressive, stable)
• Disease duration (self-limited, chronic lifelong)

  Search first: Disease registries, longitudinal cohort databases, natural history studies, PubMed, Orphanet, OMIM

• Patterns:
• Remission patterns (spontaneous, treatment-induced) > Search first: Clinical trial databases, disease registries, PubMed
• Critical periods (time windows of vulnerability or opportunity for intervention) > Search first: PubMed, developmental biology databases, clinical guidelines

9. Inheritance and Population

• Epidemiology:
• Prevalence (cases per 100,000 at given time)
• Incidence (new cases per 100,000 per year)

  Search first: Orphanet, CDC, WHO, GBD (Global Burden of Disease), national registries, SEER, disease registries

• For Genetic Etiology:
• Inheritance pattern (AD, AR, X-linked, mitochondrial, multifactorial, polygenic) > Search first: OMIM, Orphanet, ClinVar, GTR (Genetic Testing Registry)
• Penetrance (complete, incomplete, age-dependent) > Search first: ClinVar, OMIM, PubMed, ClinGen
• Expressivity (variable, consistent) > Search first: OMIM, ClinVar, PubMed
• Genetic anticipation (increasing severity in successive generations) > Search first: OMIM, PubMed (especially for repeat expansion disorders)
• Germline mosaicism > Search first: ClinVar, OMIM, genetic counseling literature, PubMed
• Founder effects (population-specific mutations) > Search first: gnomAD, population genetics databases, PubMed
• Consanguinity role > Search first: OMIM, population studies, genetic counseling resources
• Carrier frequency > Search first: gnomAD, carrier screening databases, GeneReviews, GTR
• Population Demographics:
• Affected populations (ethnic or demographic groups with higher prevalence) > Search first: gnomAD, 1000 Genomes, PAGE Study, PubMed, population registries
• Geographic distribution (endemic areas, regional variation) > Search first: WHO, CDC, GBD, Orphanet, geographic epidemiology databases
• Geographic distribution of specific variants
• Sex ratio (male:female) > Search first: Disease registries, OMIM, PubMed, epidemiological databases
• Age distribution of affected individuals > Search first: CDC, disease registries, SEER, Orphanet

10. Diagnostics

• Clinical Tests:
• Laboratory tests (blood, urine, tissue chemistry, specific enzyme assays) > Search first: LOINC, LabTests Online, PubMed
• Biomarkers (proteins, metabolites, genetic markers, circulating biomarkers) > Search first: FDA Biomarker List, BEST (Biomarkers, EndpointS, and other Tools), PubMed
• Imaging studies (X-ray, CT, MRI, PET, ultrasound) > Search first: RadLex, DICOM, Radiopaedia, imaging databases
• Functional tests (pulmonary function, cardiac stress tests) > Search first: LOINC, clinical guidelines, PubMed
• Electrophysiology (EEG, EMG, ECG, nerve conduction studies) > Search first: LOINC, clinical neurophysiology databases, PubMed
• Biopsy findings (histopathology, immunohistochemistry) > Search first: SNOMED CT, College of American Pathologists resources, PubMed
• Pathology findings (microscopic examination) > Search first: SNOMED CT, Digital Pathology databases, PubMed
• Genetic Testing:

  Search first: GTR (Genetic Testing Registry), GeneReviews, ClinGen

• Overview of recommended genetic testing approach
• Whole genome sequencing (WGS) utility > Search first: GTR, ClinVar, GEL (Genomics England), gnomAD
• Whole exome sequencing (WES) utility > Search first: GTR, ClinVar, OMIM, GeneMatcher
• Gene panels (which panels, which genes) > Search first: GTR, ClinVar, laboratory-specific databases
• Single gene testing > Search first: GTR, ClinVar, OMIM, GeneReviews
• Chromosomal microarray (CMA) > Search first: DECIPHER, ClinVar, dbVar, ECARUCA
• Karyotyping > Search first: Chromosome Abnormality Database, ClinVar, cytogenetics resources
• FISH > Search first: ClinVar, cytogenetics databases, PubMed
• Mitochondrial DNA testing > Search first: MITOMAP, MSeqDR, ClinVar, GTR
• Repeat expansion testing > Search first: GTR, ClinVar, repeat expansion databases, PubMed
• Omics-Based Diagnostics (if applicable):
• RNA sequencing / transcriptomics > Search first: GEO, ArrayExpress, GTEx, RNA-seq databases
• Proteomics > Search first: PRIDE, ProteomeXchange, FDA Biomarker database
• Metabolomics > Search first: MetaboLights, Metabolomics Workbench, HMDB
• Epigenomics > Search first: GEO, ENCODE, Roadmap Epigenomics, MethBase
• Liquid biopsy > Search first: COSMIC, ClinVar, liquid biopsy databases, PubMed
• Clinical Criteria:
• Standardized diagnostic criteria (DSM, ICD, society guidelines) > Search first: DSM-5, ICD-11, clinical society guidelines, UpToDate
• Differential diagnosis (other conditions to rule out, with distinguishing features) > Search first: DynaMed, UpToDate, clinical decision support systems
• Screening:
• Screening methods for asymptomatic individuals (newborn screening, carrier screening, cascade screening) > Search first: ACMG recommendations, CDC newborn screening, GTR

11. Outcome/Prognosis

• Survival and Mortality:
• Survival rate (5-year, 10-year, overall) > Search first: SEER, cancer registries, disease-specific registries, PubMed
• Life expectancy (with and without treatment if applicable) > Search first: Orphanet, disease registries, actuarial databases, PubMed
• Mortality rate > Search first: CDC, WHO, GBD, national mortality databases
• Disease-specific mortality (deaths directly attributable to disease) > Search first: Disease registries, CDC Wonder, GBD, PubMed
• Morbidity and Function:
• Morbidity (disease-related disability and health impacts) > Search first: GBD, WHO, disability databases, PubMed
• Disability outcomes (long-term functional impairments) > Search first: ICF (International Classification of Functioning), disability registries
• Quality of life measures (EQ-5D, SF-36, PROMIS, disease-specific tools) > Search first: EQ-5D database, SF-36, PROMIS, PubMed
• Disease Course:
• Complications (secondary problems: infections, organ failure, etc.) > Search first: ICD codes, disease registries, clinical databases, PubMed
• Recovery potential (likelihood and extent of recovery, with vs without treatment) > Search first: Natural history studies, rehabilitation databases, PubMed
• Prediction:
• Prognostic factors (age, disease severity, biomarkers, treatment response) > Search first: Prognostic models databases, clinical calculators, PubMed
• Prognostic biomarkers (molecular markers predicting disease course) > Search first: FDA Biomarker database, PubMed, cancer prognostic databases

12. Treatment

• Pharmacotherapy:
• Pharmacological treatments (drug names, drug classes, mechanisms of action) > Search first: DrugBank, RxNorm, ATC classification, DailyMed, FDA databases
• Pharmacogenomics (how genetic variants affect drug metabolism, efficacy, toxicity) > Search first: PharmGKB, CPIC (Clinical Pharmacogenetics), FDA Table of PGx Biomarkers
• Advanced Therapeutics:
• Gene therapy (viral vectors, CRISPR, gene replacement, gene editing) > Search first: ClinicalTrials.gov, FDA gene therapy database, ASGCT resources
• Cell therapy (stem cell transplant, CAR-T, cellular therapeutics) > Search first: ClinicalTrials.gov, FDA cell therapy database, FACT standards
• RNA-based therapies (ASOs, siRNA, mRNA therapies) > Search first: ClinicalTrials.gov, FDA approvals, PubMed
• Targeted therapies (treatments directed at specific molecular targets) > Search first: My Cancer Genome, OncoKB, ClinicalTrials.gov, FDA approvals
• Immunotherapies (checkpoint inhibitors, monoclonal antibodies) > Search first: Cancer Immunotherapy Database, FDA approvals, ClinicalTrials.gov
• Surgical and Interventional:
• Surgical interventions (types of surgery, timing, outcomes) > Search first: CPT codes, surgical registries, clinical guidelines, PubMed
• Supportive and Rehabilitative:
• Supportive care (symptom management, pain control, nutrition) > Search first: Clinical guidelines, Cochrane Library, PubMed
• Rehabilitation (physical therapy, occupational therapy, speech therapy) > Search first: Rehabilitation medicine databases, clinical guidelines, PubMed
• Experimental:
• Experimental treatments in clinical trials (with NCT identifiers if available) > Search first: ClinicalTrials.gov, EU Clinical Trials Register, WHO ICTRP
• Treatment Outcomes:
• Treatment response rates > Search first: Clinical trial databases, FDA reviews, systematic reviews, PubMed
• Side effects and adverse events > Search first: FDA Adverse Event Reporting System (FAERS), MedWatch, PubMed
• Treatment Strategy:
• Treatment algorithms (clinical pathways, decision trees) > Search first: Clinical practice guidelines, NCCN Guidelines, UpToDate
• Combination therapies > Search first: ClinicalTrials.gov, treatment guidelines, PubMed
• Personalized medicine approaches (genotype-guided treatment) > Search first: My Cancer Genome, CIViC, PharmGKB, precision medicine databases

For each treatment, suggest MAXO (Medical Action Ontology) terms where applicable.

13. Prevention

• Prevention Levels:
• Primary prevention (preventing disease occurrence: vaccination, risk factor modification) > Search first: CDC, WHO, USPSTF recommendations, Cochrane Library
• Secondary prevention (early detection and treatment: screening programs, early intervention) > Search first: USPSTF, CDC screening guidelines, WHO
• Tertiary prevention (preventing complications in those with disease) > Search first: Clinical guidelines, disease management protocols, PubMed
• Immunization: Vaccine strategies (if applicable)

  Search first: CDC vaccine schedules, WHO immunization, FDA vaccine database

• Screening and Early Detection:
• Screening programs (population-based: newborn screening, cancer screening) > Search first: CDC screening programs, USPSTF, cancer screening databases
• Genetic screening (carrier screening, preimplantation genetic diagnosis, prenatal testing) > Search first: ACMG recommendations, ACOG guidelines, GTR
• Risk stratification (identifying high-risk individuals for targeted prevention) > Search first: Risk prediction models, clinical calculators, PubMed
• Behavioral Interventions: Lifestyle modifications to reduce risk

  Search first: CDC, WHO, behavioral intervention databases, Cochrane Library

• Counseling: Genetic counseling (risk assessment, family planning guidance)

  Search first: NSGC resources, ACMG guidelines, GeneReviews

• Public Health:
• Public health interventions (sanitation, vector control, health education) > Search first: CDC, WHO, public health databases, PubMed
• Environmental interventions (reducing environmental risk factors) > Search first: EPA databases, WHO environmental health, PubMed
• Prophylaxis: Preventive medications or procedures

  Search first: Clinical guidelines, FDA approvals, PubMed

14. Other Species / Natural Disease

• Taxonomy: Species affected (with NCBI Taxon identifiers)

  Search first: NCBI Taxonomy

• Breed: Specific breeds affected (with VBO identifiers if applicable)

  Search first: VBO (Vertebrate Breed Ontology)

• Gene: Orthologous genes in other species (with NCBI Gene IDs)

  Search first: NCBI Gene

• Natural Disease:
• Naturally occurring disease in other species (companion animals, wildlife) > Search first: OMIA (Online Mendelian Inheritance in Animals), VetCompass, PubMed
• Veterinary relevance and importance in animal health > Search first: OMIA, veterinary databases, PubMed
• Comparative Biology:
• Comparative pathology (similarities and differences across species) > Search first: OMIA, comparative pathology databases, PubMed
• Evolutionary conservation of disease mechanisms > Search first: HomoloGene, OrthoMCL, Alliance of Genome Resources
• Transmission (if applicable):
• Zoonotic potential > Search first: CDC zoonotic diseases, WHO zoonoses, GIDEON
• Cross-species susceptibility > Search first: NCBI Taxonomy, veterinary databases, PubMed

15. Model Organisms

• Model Types:
• Model organism type (mammalian, invertebrate, cellular, in vitro) > Search first: Alliance of Genome Resources, model organism databases
• Specific model systems (mouse, rat, zebrafish, Drosophila, C. elegans, yeast, cell lines, organoids, iPSCs) > Search first: MGI, RGD, ZFIN, FlyBase, WormBase, SGD, ATCC, Cellosaurus
• Induced models (drug treatment, surgical intervention, environmental manipulation) > Search first: MGI, model organism databases, PubMed
• Genetic Models:
• Types available (knockout, knock-in, transgenic, conditional, humanized) > Search first: MGI, IMPC, KOMP, EuMMCR, IMSR
• Model Characteristics:
• Phenotype recapitulation (how well model reproduces human disease features) > Search first: Model organism databases, comparative studies, PubMed
• Model limitations (aspects of human disease not captured) > Search first: Model organism databases, PubMed, review articles
• Applications:
• Research applications (what aspects of disease can be studied) > Search first: Model organism databases, PubMed
• Resources:
• Model databases > Search first: MGI, RGD, ZFIN, FlyBase, WormBase, IMSR, EMMA, MMRRC

Citation Requirements

• Cite primary literature (PMID preferred) for all mechanistic and clinical claims
• Prioritize recent reviews and landmark papers
• Include direct quotes from abstracts where possible to support key statements
• Distinguish evidence source types: human clinical, model organism, in vitro, computational

Output Format

Structure your response as a comprehensive narrative organized by the sections above. For each section, provide: - Factual content with specific details (numbers, percentages, gene names, variant nomenclature) - Ontology term suggestions (HPO, GO, CL, UBERON, CHEBI, MAXO, MONDO) where applicable - Evidence citations with PMIDs - Direct quotes from abstracts to support key claims - Clear indication when information is not available or not applicable for this disease

This report will be used to populate a disease knowledge base entry with: - Pathophysiology descriptions with causal chains - Gene/protein annotations (HGNC, GO terms) - Phenotype associations (HP terms) with frequencies - Cell type involvement (CL terms) - Anatomical locations (UBERON terms) - Chemical entities (CHEBI terms) - Treatment annotations (MAXO terms) - Evidence items with PMIDs and exact abstract quotes - Epidemiology, prognosis, diagnostic, and prevention information - Animal model descriptions with phenotype recapitulation details

Glioma (Cancer) — Disease Characteristics Research Report (WHO CNS5 / 2023–2024 prioritized)

1. Disease information

1.1 Overview / definition

Glioma is an umbrella term for primary central nervous system (CNS) tumors with glial or glial‑precursor lineage features; modern classification is based on integrated diagnosis combining histopathology with molecular alterations rather than morphology alone. (osborn2022the2021world pages 1-3, mcnamara20222021whoclassification pages 1-6)

In WHO CNS5 (5th edition, published 2021), adult-type diffuse gliomas were simplified into three principal, molecularly defined types: (i) astrocytoma, IDH-mutant; (ii) oligodendroglioma, IDH-mutant and 1p/19q-codeleted; (iii) glioblastoma, IDH-wildtype, with grading embedded within type (“within-type grading”). (reuss2023updatesonthe pages 1-2, mcnamara20222021whoclassification pages 6-9, osborn2022the2021world pages 1-3)

WHO CNS5 also emphasizes layered reporting, where the “integrated diagnosis” is presented as the top line, followed by histologic diagnosis, WHO grade, and the key molecular information supporting the classification. (osborn2022the2021world pages 1-3)

1.2 Key identifiers (available from retrieved sources)

• WHO classification standard: WHO Classification of Tumors of the Central Nervous System, 5th edition (WHO CNS5), summarized in Neuro-Oncology (June 2021; DOI: https://doi.org/10.1093/neuonc/noab106). (reuss2023updatesonthe pages 1-2)
• MONDO ID: Not retrieved from the tool evidence in this run (therefore not asserted).
• ICD/MeSH/OMIM/Orphanet: Not retrieved from the tool evidence in this run (therefore not asserted).

1.3 Synonyms / alternative names

Key terminology changes affect how older literature maps onto WHO CNS5. Notably, “glioblastoma” is reserved for IDH‑wildtype diffuse astrocytic tumors; tumors historically called “IDH‑mutant glioblastoma” are now astrocytoma, IDH‑mutant, CNS WHO grade 4. (reuss2023updatesonthe pages 1-2, mcnamara20222021whoclassification pages 6-9)

Table: This table summarizes key WHO CNS5 glioma concepts, including current terminology, common legacy names, and the molecular features that define each entity. It is useful for normalizing disease names and aligning older literature with current integrated CNS tumor classification.

1.4 Evidence provenance

This report primarily synthesizes aggregated disease-level resources (WHO CNS5, CBTRUS population registry report) and cohort/registry studies, plus selected clinical guidelines and trials. (reuss2023updatesonthe pages 1-2, price2024cbtrusstatisticalreport pages 2-3, hainfellner2024glioblastomainthe pages 1-3)

2. Etiology

2.1 Causal factors (mechanistic / genetic)

WHO CNS5 frames adult diffuse glioma causation and taxonomy around canonical molecular alterations. For example: * Astrocytoma, IDH‑mutant is defined by IDH1/IDH2 mutation and is commonly associated with TP53 and ATRX alterations (astrocytic lineage) and generally more favorable outcomes than IDH‑wildtype tumors. (reuss2023updatesonthe pages 1-2) * Oligodendroglioma, IDH‑mutant and 1p/19q-codeleted is defined by the combination of IDH mutation and whole-arm 1p/19q codeletion (often alongside TERT promoter mutation, CIC, FUBP1), and tends to be the most favorable‑prognosis adult diffuse glioma category. (reuss2023updatesonthe pages 1-2, gue2024the2021world pages 19-21) * Glioblastoma, IDH‑wildtype can be diagnosed by classic histology or by glioblastoma‑defining molecular features (e.g., TERT promoter mutation, EGFR amplification, or combined +7/−10), even when histologic hallmarks are absent. (mcnamara20222021whoclassification pages 6-9, osborn2022the2021world pages 1-3)

2.2 Risk factors

2.2.1 Genetic predisposition (germline)

A 2023 single-institution paired tumor/normal sequencing series of 152 adult-type diffuse glioma patients reported pathogenic germline variants in 9.8% (15/152), with higher prevalence in glioblastoma, IDH‑wildtype (13.1%) than in IDH‑mutant astrocytoma (7.1%) or oligodendroglioma (3.8%). (mcdonald2023prevalenceofpathogenic pages 1-2, mcdonald2023prevalenceofpathogenic pages 5-7)

Most frequent germline pathogenic variants in that cohort were BRCA2, MUTYH, and CHEK2 (each 20% of pathogenic variants), with additional variants in BRCA1, ATM, NF1, MSH2, MSH3. (mcdonald2023prevalenceofpathogenic pages 1-2, mcdonald2023prevalenceofpathogenic pages 5-7)

Implementation gap: only 40% of patients with pathogenic germline variants were referred to genetics, despite potential implications for surveillance and family cascade testing. (mcdonald2023prevalenceofpathogenic pages 2-3, mcdonald2023prevalenceofpathogenic pages 5-7)

For pediatric CNS tumors (including glioma subtypes within the broader category), an AACR Cancer Predisposition Working Group update states that germline predisposition incidence “continues to grow” and that ~50% of patients may be the first in a family identified to have a predisposition; identification enables cascade testing and early tumor surveillance and can impact management. (hansford2024updateoncancer pages 1-2)

2.2.2 Environmental / lifestyle

No high-quality, specific environmental or protective factors were retrieved with tool evidence in this run; therefore, none are asserted.

2.3 Protective factors

No evidence was retrieved in this run for protective factors in glioma risk; therefore, none are asserted.

2.4 Gene–environment interactions

No gene–environment interaction evidence was retrieved in this run; therefore, none are asserted.

3. Phenotypes

3.1 Common clinical phenotypes (symptoms/signs) and QoL impact

Clinical guideline evidence emphasizes that neurologic symptoms can substantially impair quality of life in high-grade glioma. A SEOM-GEINO guideline notes common symptoms including seizures, cognitive deficits, drowsiness, dysphagia, headache, confusion, aphasia, motor deficits, fatigue, and dyspnea, varying with tumor size, location, and edema. (segura2023seomgeinoclinicalguidelines pages 2-4)

Supportive care priorities include management of brain edema (e.g., dexamethasone) and seizures (levetiracetam first-line monotherapy; prophylactic antiepileptic use generally not recommended), with attention to neurocognitive impairment as a frequent disabling complication. (segura2023seomgeinoclinicalguidelines pages 7-8, segura2023seomgeinoclinicalguidelines pages 8-9)

3.2 Suggested HPO terms (non-exhaustive; mapping guidance)

• Seizures — HP:0001250
• Headache — HP:0002315
• Aphasia — HP:0002381
• Cognitive impairment — HP:0100543
• Fatigue — HP:0012378
• Motor weakness — HP:0001324
• Dysphagia — HP:0002015

(These HPO IDs are provided as standard ontology mappings; this run did not retrieve HPO source documents, so they are presented as ontology suggestions rather than evidence-derived claims.)

4. Genetic / molecular information

4.1 Core disease-defining genes and alterations (adult-type diffuse gliomas)

WHO CNS5/related reviews emphasize the following diagnostic anchors: * IDH1/IDH2 mutations define IDH-mutant astrocytoma and oligodendroglioma categories; TP53/ATRX alterations support astrocytic lineage, while 1p/19q codeletion supports oligodendroglial lineage. (reuss2023updatesonthe pages 1-2, mcnamara20222021whoclassification pages 6-9) * Glioblastoma, IDH-wildtype may be defined molecularly by TERT promoter mutation, EGFR amplification, +7/−10 copy-number pattern. (mcnamara20222021whoclassification pages 6-9)

4.2 Epigenetics and methylation profiling

DNA methylation profiling is increasingly important for CNS tumor diagnosis and subgrouping. A 2024 review characterizes methylation profiling as a key diagnostic tool, with classifier matching scores ≥0.9 in ~50–65% of samples and “diagnostic impact” in ~10–20% of cases. (bertero2024molecularneuropathologyan pages 3-4)

4.3 Multi-omics and functional genomics (recent developments)

In pediatric low-grade glioma diagnostics, a 2023 international registry analysis (LOGGIC) reported that adding RNA-seq increased driver detection from 75% to 97% (121/125), with 27/125 (22%) having drivers detected only by RNA-seq (22 actionable), supporting routine RNA-seq integration when standard approaches are unrevealing. (hardin2023loggiccorebioclinical pages 1-2, hardin2023loggiccorebioclinical pages 3-5)

5. Environmental information

No high-confidence environmental toxin/lifestyle/infectious causal evidence was retrieved in this run for glioma; therefore, no specific environmental claims are made.

6. Mechanism / pathophysiology

6.1 Core mechanistic concepts (WHO CNS5 perspective)

WHO CNS5 frames glioma biology around canonical molecular alterations and their downstream phenotypes. Key upstream-to-downstream relationships emphasized in the retrieved evidence include: * IDH mutation status as a primary biological divider associated with prognostic differences and correlated molecular programs (IDH-mutant generally more favorable than IDH-wildtype). (reuss2023updatesonthe pages 1-2) * Copy-number and oncogenic alterations (e.g., EGFR amplification, TERT promoter mutation, +7/−10) serving as glioblastoma-defining markers, reflecting aggressive tumor biology independent of morphology. (mcnamara20222021whoclassification pages 6-9)

6.2 Suggested GO biological process terms (examples; ontology suggestions)

• Cell proliferation — GO:0008283
• DNA repair — GO:0006281
• Regulation of cell cycle — GO:0051726
• Angiogenesis — GO:0001525

(Provided as ontology suggestions; GO source documents were not retrieved in this run.)

6.3 Suggested Cell Ontology (CL) terms (examples; ontology suggestions)

• Astrocyte — CL:0000127
• Oligodendrocyte — CL:0000128
• Microglial cell — CL:0000129

7. Anatomical structures affected

Gliomas are CNS tumors affecting brain and spinal cord structures; adult diffuse gliomas are typically infiltrative within brain parenchyma. Adult diffuse glioma registry analyses report frequent localization in cerebral regions (“cerebrum” predominance in SEER-based analyses cited within registry context). (zhao2024emergingtrendsin pages 11-14)

Suggested UBERON terms (examples; ontology suggestions): * Brain — UBERON:0000955 * Cerebrum — UBERON:0001869

8. Temporal development

8.1 Onset

In a Belgian population registry cohort of adult-type diffuse glioma (2017–2019), median age at diagnosis was 64 years, consistent with adult-onset predominance for diffuse adult-type gliomas in population data. (pinson2024epidemiologyandsurvival pages 1-2)

8.2 Progression

Diffuse gliomas are infiltrative and often recur/progress despite therapy; WHO CNS5 emphasizes molecular classification and grading to better predict progression risk. (mcnamara20222021whoclassification pages 6-9, osborn2022the2021world pages 1-3)

9. Inheritance and population

9.1 Epidemiology (recent)

The CBTRUS Statistical Report (US; diagnosed 2017–2021; published Oct 2024) reports: * Gliomas accounted for 22.9% of all primary brain/CNS tumors. * Glioblastoma accounted for 14.0% of all tumors and 51.5% of malignant tumors. * Malignant brain/CNS tumor incidence: 6.89 per 100,000 overall; 8.06 per 100,000 in males vs 5.84 per 100,000 in females. * Malignant brain/CNS tumor mortality: 4.41 per 100,000, with 87,053 deaths during 2017–2021. * 5-year relative survival for malignant brain/CNS tumors overall: 35.7%. (price2024cbtrusstatisticalreport pages 2-3)

A Belgian national cancer registry analysis of adult-type diffuse gliomas (2017–2019; published Aug 2024) estimated an age-standardized incidence rate of 8.55 per 100,000 person-years for diffuse adult-type glioma and 6.72 per 100,000 person-years for grade 4 lesions. (pinson2024epidemiologyandsurvival pages 1-2)

Table: This table compiles recent population-level glioma epidemiology and survival figures from the 2024 CBTRUS report and a 2024 Belgian molecular-era registry. It is useful for contrasting broad U.S. CNS tumor statistics with subtype-resolved real-world outcomes for adult-type diffuse gliomas.

9.2 Inheritance patterns

Most adult diffuse gliomas are sporadic, but a clinically meaningful minority show germline pathogenic variants; a 2023 cohort found ~10% with pathogenic germline variants (see Etiology). (mcdonald2023prevalenceofpathogenic pages 1-2)

10. Diagnostics

WHO CNS5-era diagnostic practice is integrated and multi-assay. Molecular markers may be detected via IHC surrogate assays, FISH for copy-number changes (including 1p/19q codeletion), and DNA/RNA next-generation sequencing; methylome profiling can classify tumors and infer copy-number alterations. (osborn2022the2021world pages 1-3)

Methylation profiling and NGS are described as core parts of the evolving molecular neuropathology toolbox, with methylation profiling “critical” for complex cases and for subgrouping heterogeneous entities; targeted sequencing is practical for routine diagnostics and may reveal targets for emerging therapies. (bertero2024molecularneuropathologyan pages 1-3, bertero2024molecularneuropathologyan pages 3-4)

Liquid biopsy remains investigational. A 2024 GBM liquid biopsy review notes analytes such as ctDNA, miRNA, CTCs, EVs/exosomes, proteins, but emphasizes major challenges including blood–brain barrier limitations, variable detection rates (ctDNA ~10–55%), small cohorts, and lack of standardized pre-analytical/analytical methods; no circulating biomarker is clinically validated for routine GBM management. (seyhan2024circulatingliquidbiopsy pages 48-49, seyhan2024circulatingliquidbiopsy pages 1-2)

For CSF cfDNA in glioma, a 2024 review reports NGS detection of tumor-specific mutations in 70% of glioma cases, 82.5% in brainstem glioma with targeted panels, and 97.3% concordance when primary tumor alterations were present—highlighting potential as an adjunct in hard-to-biopsy contexts. (otsuji2024liquidbiopsyfor pages 12-14)

Table: This table summarizes the main current diagnostic modalities used in glioma care, what each modality detects, where it is most useful, and key limitations. It emphasizes the shift toward integrated molecular diagnosis in WHO CNS5, including methylation profiling, RNA-seq, and CSF liquid biopsy.

11. Outcome / prognosis

11.1 High-grade glioma / glioblastoma prognosis

A 2023 high-grade glioma guideline states glioblastoma has a grim prognosis with median overall survival ~15 months and 5-year survival 5–10%. (segura2023seomgeinoclinicalguidelines pages 1-2)

In real-world Austrian population data (2014–2018; published Aug 2024), median OS for 1,420 glioblastoma patients was 11.6 months overall and 16.1 months among patients ≤65 years receiving postoperative standard-of-care therapy; ≥5-year survival occurred in 4.9% of those with ≥5-year follow-up. (hainfellner2024glioblastomainthe pages 1-3)

11.2 Prognostic stratification by molecular subtype (real-world molecular era)

A Belgian registry study (2017–2019) showed marked survival differences by molecular subtype: median OS 9.3 months for IDH‑wildtype glioblastoma vs 25.9 months for grade 4 IDH‑mutant astrocytoma; 3‑year survival for IDH‑mutant astrocytoma was 86.0% (grade 2) and 75.7% (grade 3). (pinson2024epidemiologyandsurvival pages 1-2)

12. Treatment

12.1 Standard of care (adult high-grade glioma / glioblastoma)

Guidelines emphasize multimodal treatment with maximal safe resection, radiotherapy, and temozolomide-based chemotherapy (Stupp regimen). (segura2023seomgeinoclinicalguidelines pages 4-5, segura2023seomgeinoclinicalguidelines pages 2-4)

12.2 Device-based therapy: Tumor Treating Fields (TTFields)

A 2023 systematic review/meta-analysis of real-world TTFields studies found improved OS when TTFields was added to standard chemoradiotherapy (pooled HR 0.63, 95% CI 0.53–0.75), with pooled median OS 22.6 months (TTFields) vs 17.4 months (no TTFields). (ballo2023associationoftumor pages 1-2)

A 2024 global post-marketing safety surveillance analysis (>25,000 treated CNS malignancy patients) reported most common TTFields-related adverse events were localized scalp reactions: beneath-array skin reaction 43%, tingling 14%, warmth 12%, with no TTFields-related systemic adverse events reported. (mrugala2024globalpost‑marketingsafety pages 1-2)

12.3 Precision therapy for IDH-mutant grade 2 glioma: vorasidenib (INDIGO)

The phase 3 INDIGO trial (NEJM, Aug 2023; DOI: https://doi.org/10.1056/NEJMoa2304194) enrolled 331 patients with residual/recurrent grade 2 IDH1/2-mutant glioma after surgery only. Vorasidenib significantly improved median imaging-based PFS (27.7 vs 11.1 months, HR 0.39) and delayed time to next intervention (HR 0.26). (mellinghoff2023vorasidenibinidh1 pages 1-3)

Safety: grade ≥3 alanine aminotransferase elevation occurred in ~9.6–10% of vorasidenib patients vs 0% placebo in trial reporting. (mellinghoff2023vorasidenibinidh1 pages 1-3, ruda2024idhinhibitionin pages 6-7)

ClinicalTrials.gov identifier: NCT04164901. (mellinghoff2023vorasidenibinidh1 pages 1-3)

12.4 Supportive care

Guidelines highlight dexamethasone for edema (preferred dose range 4–16 mg/day) and seizure management with levetiracetam as first-line monotherapy for patients with seizures. (segura2023seomgeinoclinicalguidelines pages 7-8)

Table: This table summarizes current glioma treatments and real-world implementation evidence, including standard chemoradiotherapy, TTFields, vorasidenib, and supportive care. It highlights efficacy, safety, and ontology-ready MAXO action terms for knowledge base use.

13. Prevention

No population screening or primary prevention strategies were retrieved with tool evidence in this run. Prevention is therefore largely limited to: * Tertiary prevention/supportive care to reduce complications (edema, seizures, thrombosis, neurocognitive decline) in diagnosed patients. (segura2023seomgeinoclinicalguidelines pages 7-8) * Genetic counseling/surveillance for individuals with cancer predisposition syndromes, with pediatric surveillance guidance emphasizing early tumor surveillance and cascade testing. (hansford2024updateoncancer pages 1-2)

14. Other species / natural disease

Naturally occurring canine gliomas are used in comparative oncology. An in vitro comparative study tested human and canine glioma cell lines and noted similarities supporting canine glioma as a surrogate model; cannabidiol showed cytotoxicity in the ~4.9–8.2 μg/ml range, with mitochondrial dysfunction (reduced oxygen consumption, swollen mitochondria) contributing to apoptosis. (gross2021cannabidiolinducesapoptosis pages 1-2)

15. Model organisms

This run retrieved limited explicit model-organism methodology evidence beyond the comparative canine in vitro model above; thus, additional statements about specific GEMMs/PDX/organoid resources are not asserted.

Expert opinions / authoritative analyses (selected)

• WHO CNS5 expert summaries emphasize that molecular diagnostics are central to classification while histology and immunohistochemistry remain essential, and that integrated diagnoses and layered reporting improve reproducibility and clinical relevance. (reuss2023updatesonthe pages 1-2, osborn2022the2021world pages 1-3)
• Molecular neuropathology reviews in 2024 frame DNA methylation profiling and DNA/RNA NGS as an “essential and evolving toolbox” for diagnosis and management, enabling tumor subgrouping and supporting targeted therapy selection. (bertero2024molecularneuropathologyan pages 1-3)

Visual evidence note

Attempts were made to retrieve a WHO CNS5 classification figure/table and a CBTRUS survival table using the image retrieval tool, but the tool failed to fetch images from available text chunks in this run; therefore, no figure/table image citations are provided.

References

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