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Fibrosarcoma

Disease Characteristics Research Template

2026-05-07
Falcon MONDO:0005164 Model: Edison Scientific Literature 25 citations

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: Fibrosarcoma
  • MONDO ID: (if available)
  • Category: Cancer

Research Objectives

Please provide a comprehensive research report on Fibrosarcoma 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

Fibrosarcoma — Disease Characteristics Research Report (Cancer)

Executive summary

Fibrosarcoma is a malignant mesenchymal (fibroblastic) tumor diagnosis that, in contemporary practice, is best understood as a family of entities and mimics spanning classic “adult-type” fibrosarcoma patterns, congenital/infantile fibrosarcoma (CFS/IFS), and related fusion-defined fibroblastic/spindle-cell neoplasms (including sclerosing epithelioid fibrosarcoma and low-grade fibromyxoid sarcoma). A major recent trend is the use of fusion genes (notably NTRK fusions) to improve classification, diagnostics, and targeted therapy selection—particularly in IFS, where TRK inhibitors have shown high response rates and are now implemented in real-world pediatric oncology. (tang2023progressiveinsightsinto pages 3-6, tang2023progressiveinsightsinto pages 12-13)

1. Disease information

1.1 Definition and overview

1.2 Key identifiers (available from retrieved evidence)

  • MONDO (from Open Targets evidence context):
  • adult fibrosarcoma: MONDO_0002676 (OpenTargets Search: Fibrosarcoma,Infantile fibrosarcoma-NTRK3,NTRK1,NTRK2)
  • pediatric fibrosarcoma: MONDO_0002678 (OpenTargets Search: Fibrosarcoma,Infantile fibrosarcoma-NTRK3,NTRK1,NTRK2)
  • congenital fibrosarcoma: MONDO_0004557 (OpenTargets Search: Fibrosarcoma,Infantile fibrosarcoma-NTRK3,NTRK1,NTRK2)
  • EFO: “fibrosarcoma” EFO_0002087 (OpenTargets Search: Fibrosarcoma,Infantile fibrosarcoma-NTRK3,NTRK1,NTRK2)

Note: Direct retrieval of MeSH, ICD-10/ICD-11, Orphanet, and OMIM identifiers for fibrosarcoma was not available in the current tool context/evidence set; these should be populated from ontology sources (e.g., MeSH Browser, ICD-11, Orphanet, OMIM) during downstream curation.

1.3 Synonyms and alternative names (from retrieved evidence)

1.4 Evidence provenance

The information in this report is derived from aggregated disease-level resources and peer-reviewed literature (reviews, clinical studies/case series, and clinical trial registry entries) rather than individual EHR records, except where case reports are explicitly discussed. (wang2023larotrectinibtreatmentfor pages 1-2, sahni2023limbsalvageof pages 5-7, NCT03834961 chunk 1)

2. Etiology

2.1 Primary causal factors

Molecular (fusion-driven) oncogenesis is central in many fibrosarcoma-related entities: * In IFS, t(12;15)(p13;q25) leading to ETV6::NTRK3 is strongly associated with tumorigenesis and provides a direct drug target. (wang2023larotrectinibtreatmentfor pages 1-2) * Reviews emphasize that fusion genes are prevalent drivers across fibrosarcoma subtypes and are increasingly leveraged for subcategorization and targeted treatment. (tang2023progressiveinsightsinto pages 3-6)

2.2 Risk factors

Robust, population-level risk factor data specific to fibrosarcoma was not captured in the current evidence set. For IFS specifically, disease onset is predominantly in infancy (often congenital presentation), implying developmental/embryonal rather than lifestyle-driven risk in many cases. (wang2023larotrectinibtreatmentfor pages 1-2)

2.3 Protective factors / gene–environment interactions

No high-confidence protective factors or gene–environment interaction evidence specific to fibrosarcoma was retrieved in the current evidence set.

3. Phenotypes

3.1 Core clinical phenotypes (IFS emphasized due to strong evidence base)

Suggested HPO terms (mapping for KB curation; not all were explicitly coded in the evidence text): * Localized mass: HP:0002664 (Tumor) / HP:0100242 (Soft tissue mass) * Pain absent: HP:0030199 (Painless) (conceptual) * Rapid growth: HP:0003676 (Rapidly progressive) (conceptual)

3.2 Laboratory/immunophenotype-related phenotypes

IFS lacks a unique IHC marker; reported IHC patterns include: * Frequent vimentin positivity and often desmin/S100 negativity, with lack of a specific immunohistochemical tumor marker overall. (li2024characterizationofthe pages 1-2)

4. Genetic / molecular information

4.1 Causal genes and recurrent alterations

Key genes strongly implicated via recurrent fusions: * NTRK3 (ETV6::NTRK3) in IFS/CFS; a central oncogenic driver and therapeutic target. (wang2023larotrectinibtreatmentfor pages 1-2, OpenTargets Search: Fibrosarcoma,Infantile fibrosarcoma-NTRK3,NTRK1,NTRK2) * Broader kinase-fusion spectra include NTRK1, NTRK3, RET, BRAF, RAF1 across spindle-cell tumors with fibrosarcoma-like morphologies (including IFS-like and adult FS-like). (suurmeijer2024kinasefusionpositive pages 1-3)

Hallmark fusion summary (including DFSP, LGFMS/SEF context from a 2023 review): | Entity/subtype | Key fusion/alteration | Evidence/frequency | Typical age group | Clinical utility (diagnostic/therapeutic) | Key source (DOI URL) and year | |---|---|---|---|---|---| | Congenital/infantile fibrosarcoma (CFS/IFS) | ETV6::NTRK3 from t(12;15)(p13;q25) | Reported in ~85% of IFS cases; canonical defining lesion (wang2023larotrectinibtreatmentfor pages 1-2, li2024characterizationofthe pages 1-2) | Predominantly infants; most common soft-tissue sarcoma in children <1 year (wang2023larotrectinibtreatmentfor pages 1-2, li2024characterizationofthe pages 1-2) | Strong diagnostic marker; supports TRK inhibitor use such as larotrectinib in fusion-positive disease (wang2023larotrectinibtreatmentfor pages 1-2, sahni2023limbsalvageof pages 5-7) | Wang et al., Front Oncol, 2023, https://doi.org/10.3389/fonc.2023.1206833 | | Congenital/infantile fibrosarcoma (variant fusions) | EML4::NTRK3, LMNA::NTRK1, PHIP::BRAF | Reported as additional/non-canonical fusions in CFS/IFS; Tang 2023 cites case-level responses including near-complete response to crizotinib in LMNA::NTRK1 and proposed trametinib relevance for PHIP::BRAF (tang2023progressiveinsightsinto pages 3-6, tang2023progressiveinsightsinto pages 12-13) | Infants/young children (tang2023progressiveinsightsinto pages 3-6) | Helps refine diagnosis in ETV6-negative cases; suggests targeted therapy options matched to kinase alteration (tang2023progressiveinsightsinto pages 3-6, tang2023progressiveinsightsinto pages 12-13) | Tang et al., Front Cell Dev Biol, 2023, https://doi.org/10.3389/fcell.2023.1284428 | | Dermatofibrosarcoma protuberans (DFSP) | COL1A1::PDGFB | Identified in 172 cases (91.4%); described as recurrent/classic DFSP fusion (tang2023progressiveinsightsinto pages 3-6) | Not specified in provided snippet | High-value diagnostic marker; PDGFB-axis relevance for molecular classification and targeted approaches (tang2023progressiveinsightsinto pages 3-6) | Tang et al., Front Cell Dev Biol, 2023, https://doi.org/10.3389/fcell.2023.1284428 | | DFSP (alternative fusions) | COL1A2::PDGFB, COL6A3::PDGFD, EMILIN2::PDGFD, SLC2A5::BTBD7 | RNA-seq has uncovered alternative fusions beyond COL1A1::PDGFB (tang2023progressiveinsightsinto pages 3-6) | Not specified in provided snippet | Expands molecular diagnosis, especially for atypical/classic-fusion-negative DFSP (tang2023progressiveinsightsinto pages 3-6) | Tang et al., Front Cell Dev Biol, 2023, https://doi.org/10.3389/fcell.2023.1284428 | | Kinase fusion–positive spindle cell tumors (bone/soft tissue spectrum; IFS-like, adult FS-like, MPNST-like, LPFNT-like, myxoma-like) | NTRK3, NTRK1, RET, BRAF, RAF1 fusions | Combined literature series: NTRK3 n=6, NTRK1 n=4, RET n=2, BRAF n=2, RAF1 n=1; 73% occurred in patients <30 years; NTRK3 associated with high-grade morphology in 5/6 and NTRK1 with lower grade in 3/4 (suurmeijer2024kinasefusionpositive pages 1-3) | Mostly children and young adults; some older adults reported (suurmeijer2024kinasefusionpositive pages 1-3) | Fusion status aids classification, supports pan-TRK IHC/RNA sequencing workup, and identifies actionable kinase targets (suurmeijer2024kinasefusionpositive pages 1-3) | Suurmeijer et al., Genes Chromosomes Cancer, 2024, https://doi.org/10.1002/gcc.23205 | | Low-grade fibromyxoid sarcoma (LGFMS) | FUS::BBF2H7 (as reported in Tang 2023) | Listed by Tang 2023 as a key recurrent fusion in LGFMS (tang2023progressiveinsightsinto pages 12-13, tang2023progressiveinsightsinto media b1dcbf19) | Not specified in provided snippet | Important diagnostic fusion for subtype assignment (tang2023progressiveinsightsinto pages 12-13) | Tang et al., Front Cell Dev Biol, 2023, https://doi.org/10.3389/fcell.2023.1284428 | | Sclerosing epithelioid fibrosarcoma (SEF) | FUS rearrangements rare in pure SEF | Tang 2023 notes FUS rearrangements are rare in pure SEF; SEF also described as aggressive (tang2023progressiveinsightsinto pages 12-13) | Not specified in provided snippet | Molecular findings may help with differential diagnosis, but rarity limits routine fusion-based definition from provided evidence (tang2023progressiveinsightsinto pages 12-13) | Tang et al., Front Cell Dev Biol, 2023, https://doi.org/10.3389/fcell.2023.1284428 | | Fibrosarcoma-related entities overview table | Multiple subtype-defining fusions summarized in a single review table | Tang 2023 Table 1 summarizes DFSP, CFS/IFS, LGFMS and associated hallmark fusions (tang2023progressiveinsightsinto media b1dcbf19) | Mixed by subtype | Useful as a compact classification/knowledge-base curation reference (tang2023progressiveinsightsinto media b1dcbf19) | Tang et al., Front Cell Dev Biol, 2023, https://doi.org/10.3389/fcell.2023.1284428 |

Table: This table summarizes fibrosarcoma-related entities and their hallmark molecular alterations using only the supported evidence snippets. It highlights which fusions are most diagnostically informative and which currently have therapeutic implications, especially for NTRK-driven infantile fibrosarcoma.

4.2 Pathogenic variants / classification / somatic vs germline

4.3 Molecular testing modalities (practical)

  • FISH for ETV6 rearrangement was used in IFS diagnosis and can confirm gene breakage consistent with ETV6::NTRK3; high-throughput sequencing can confirm the fusion. (wang2023larotrectinibtreatmentfor pages 1-2)
  • NGS (DNA- or RNA-based) panels are commonly used in real-world pediatric practice to confirm NTRK fusions before TRK inhibitor therapy. (vince2024beyondclinicaltrials pages 1-2)
  • Pan-TRK immunohistochemistry can support screening in NTRK-fusion tumors and was positive in NTRK-fusion positive tumors in a kinase fusion–positive spindle-cell tumor series. (suurmeijer2024kinasefusionpositive pages 1-3, NCT03834961 chunk 1)

4.4 Recent (2024) single-cell transcriptomics in IFS

A 2024 scRNA-seq study profiled four IFS tumors and reported: * A cellular atlas comprising 14 cell populations. * Potential novel diagnostic markers: POSTN, IGFBP2, CTHRC1. * Tumor microenvironment interactions dominated by endothelial cells and macrophages, supporting a mechanistic role for tumor–stroma/immune crosstalk. (li2024characterizationofthe pages 1-2)

5. Environmental information

No specific environmental toxin/lifestyle/infectious causal agents were retrieved in the current evidence set for fibrosarcoma.

6. Mechanism / pathophysiology

6.1 Causal chain (IFS, NTRK fusion-driven model)

  1. Chromosomal translocation (e.g., t(12;15)) produces ETV6::NTRK3 fusion. (wang2023larotrectinibtreatmentfor pages 1-2)
  2. The fusion encodes an oncogenic TRK fusion protein (kinase-driven), acting as a tumor-initiating/maintaining driver and creating a drug target. (wang2023larotrectinibtreatmentfor pages 1-2, orbach2020spotlightonthe pages 5-6)
  3. This driver state underlies clinical responsiveness to TRK inhibitors (larotrectinib/entrectinib), enabling tumor shrinkage, organ/limb sparing, and integration into neoadjuvant strategies. (sahni2023limbsalvageof pages 5-7, NCT03834961 chunk 1)

6.2 Immune microenvironment and cellular processes (2024 scRNA-seq)

  • The IFS microenvironment shows strong cell–cell communication signatures involving endothelial cells and macrophages that may promote tumorigenesis through ligand–receptor interactions. (li2024characterizationofthe pages 1-2)

Suggested ontology terms: * GO biological processes (suggested): GO:0001525 (angiogenesis); GO:0006954 (inflammatory response); GO:0008283 (cell population proliferation). * CL cell types (suggested): CL:0000115 (endothelial cell); CL:0000235 (macrophage).

7. Anatomical structures affected

7.1 Organ/tissue localization

Fibrosarcoma/IFS are soft tissue tumors; IFS often occurs in extremities and other soft tissue sites in infancy (case reports include lower extremity masses). (wang2023larotrectinibtreatmentfor pages 1-2)

Suggested UBERON terms (for KB curation): * Soft tissue: UBERON:0000479 * Lower limb: UBERON:0002101 (when extremity presentation)

8. Temporal development

8.1 Onset

8.2 Course/progression

9. Inheritance and population

9.1 Inheritance

No evidence in the retrieved set supports a germline inheritance pattern for fibrosarcoma/IFS; the key drivers described are tumor (somatic) fusions. (wang2023larotrectinibtreatmentfor pages 1-2)

9.2 Epidemiology

Disease-specific population incidence/prevalence for fibrosarcoma was not directly retrieved.

However, for the broader biomarker epidemiology of NTRK fusion–positive tumors (relevant because many IFS are NTRK-fusion driven), one large series summarized in a 2025 review reported 0.30% NTRK-positive tumors overall (889/295,676), with higher frequency in children (1.34%) than adults (0.28%). (kubota2025currentmanagementof pages 1-2)

10. Diagnostics

10.1 Clinical/imaging and pathology workflow (IFS example)

A contemporary IFS diagnostic workup described in a 2023 newborn case report included: * Imaging (MRI/CT) to define mass extent and vascular involvement. * Biopsy (e.g., ultrasound-guided fine-needle biopsy) with histopathology showing spindle-cell tumor. * Immunohistochemistry (e.g., vimentin positivity; variable results for other markers; lack of a specific marker). * Molecular confirmation with FISH demonstrating ETV6 breakage and sequencing confirming ETV6::NTRK3. (wang2023larotrectinibtreatmentfor pages 1-2)

10.2 NTRK fusion testing and implementation

Real-world pediatric oncology practice shows NTRK fusion testing is commonly performed via DNA/RNA NGS panels, often triggered by tumor behavior (poor response/progression/aggressiveness) or tumor type suggestive of NTRK fusions, and is required to justify TRK inhibitor use. (vince2024beyondclinicaltrials pages 1-2)

11. Outcome / prognosis

11.1 TRK inhibitor outcomes (IFS and pediatric NTRK-fused tumors)

  • An international consensus review summarized larotrectinib activity in IFS: among 29 treated IFS patients (28 evaluable), overall tumor response rate 96% (CI reported in the review). (orbach2020spotlightonthe pages 5-6)
  • A 2023 case report also cited pooled trial outcomes including IFS: 27/28 responses (96%), median PFS 28.3 months, 67% progression-free at 12 months, and estimated 12‑month survival 88% (with median OS 44.4 months cited). (sahni2023limbsalvageof pages 5-7)
  • A 2024 real-world Brazilian cohort (17 pediatric NTRK-fused tumors; 11 soft-tissue sarcomas) treated with larotrectinib reported centrally reviewed imaging responses in 14 patients: 11/14 objective responses (2 complete, 9 partial) and 3 stable disease; most adverse events were grade 1–2. At median 25 months observation, 15/17 were alive (4 no evidence of disease; 11 alive with disease, mostly without progression). (vince2024beyondclinicaltrials pages 1-2)

12. Treatment

12.1 Standard modalities

For IFS, standard care historically emphasizes surgical resection (with or without chemotherapy), with attention to avoiding mutilating surgery when possible. (orbach2020spotlightonthe pages 5-6, kubota2025currentmanagementof pages 8-9)

Suggested MAXO terms: * Surgical tumor resection: MAXO:0000468 (surgical excision) (suggested) * Chemotherapy: MAXO:0000647 (suggested)

12.2 Targeted therapy: TRK inhibitors (tumor-agnostic precision oncology)

Larotrectinib * Mechanism: TRK inhibitor targeting NTRK fusion proteins; used orally including liquid formulations for infants. (orbach2020spotlightonthe pages 5-6) * Implementation examples: * Newborn IFS treated at 20 days with oral larotrectinib showed significant tumor shrinkage without adverse effects in a case report. (wang2023larotrectinibtreatmentfor pages 1-2) * Limb-salvage case achieved complete response at 8 months. (sahni2023limbsalvageof pages 5-7)

Entrectinib * Discussed as an orally available selective inhibitor targeting NTRK/ROS1/ALK; clinical trial analyses show activity in NTRK fusion–positive tumors. (orbach2020spotlightonthe pages 9-9)

Suggested MAXO terms: * Targeted therapy: MAXO:0000749 (targeted molecular therapy) (suggested)

12.3 Clinical trials and real-world studies (examples)

  • NCT03834961 (Children’s Oncology Group; Phase II): neoadjuvant larotrectinib for previously untreated TRK fusion solid tumors; primary objective includes ORR in infantile fibrosarcoma, with incorporation of pan-TRK IHC screening and ctDNA monitoring, and long-term neurocognitive follow-up. (NCT03834961 chunk 1)
  • NCT05236257 (EPI VITRAKVI; observational): compares larotrectinib-treated IFS patients with historical controls; requires molecular confirmation of an NTRK fusion. (NCT05236257 chunk 1)

13. Prevention

No primary prevention or population screening strategies specific to fibrosarcoma/IFS were retrieved. Given the rarity and early-life onset of IFS, prevention is largely not established; secondary prevention is focused on timely diagnosis, molecular testing, and referral for appropriate multimodal therapy. (vince2024beyondclinicaltrials pages 1-2, NCT03834961 chunk 1)

14. Other species / natural disease

Comparative oncology evidence in the retrieved set includes canine fibrosarcoma proteomic work indicating that fibrosarcoma/soft tissue sarcoma biology can be studied in companion animals, but detailed cross-species natural history for “fibrosarcoma” per se was not extracted in the current evidence snippets. (tang2023progressiveinsightsinto pages 3-6)

15. Model organisms

No dedicated in vivo genetic model organism data for fibrosarcoma was retrieved in the current evidence set.

Evidence highlights (direct abstract quotes)

Retrieved visual evidence

A review table summarizing fibrosarcoma-related entities and hallmark fusion genes is available (Table 1 from Tang et al., 2023). (tang2023progressiveinsightsinto media b1dcbf19)

Limitations of this report

  • The current evidence set is strongest for infantile fibrosarcoma and NTRK fusion–driven disease; it contains limited direct, contemporary (2023–2024) population-level epidemiology for classic adult fibrosarcoma.
  • Direct identifiers for MeSH/ICD/Orphanet/OMIM were not retrieved through the current tools and should be added from dedicated ontology resources.

References

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  8. (NCT03834961 chunk 1): Larotrectinib in Treating Patients With Previously Untreated TRK Fusion Solid Tumors and TRK Fusion Relapsed Acute Leukemia. Children's Oncology Group. 2019. ClinicalTrials.gov Identifier: NCT03834961

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  16. (NCT05236257 chunk 1): A Study Called EPI VITRAKVI to Compare Treatment Results in Patients With Infantile Fibrosarcoma (IFS), a Type of Connective Soft Tissue Cancer, Who Received a Treatment Called Larotrectinib From a Study Called SCOUT With Patient Data From an External Database. Bayer. 2022. ClinicalTrials.gov Identifier: NCT05236257