Alveolar Soft Part Sarcoma (ASPS) Cell Models for Research

Disease Burden and Research Significance

Epidemiology and Clinical Impact

Alveolar Soft Part Sarcoma (ASPS) is an ultra-rare soft tissue sarcoma, accounting for less than 1% of all soft tissue sarcomas. The global incidence is estimated at 0.1–0.2 cases per million person-years (WHO Classification of Tumours, 5th edition, 2020). ASPS predominantly affects adolescents and young adults (median age 20–30 years), with a slight female predominance. The 5-year survival rate for localized disease is approximately 60–70%, but for metastatic disease, it drops to less than 20% (NCI SEER data, 2023). The most common metastatic sites are the lungs, brain, and bones. Despite its rarity, ASPS is of high research interest due to its unique molecular pathogenesis and resistance to conventional chemotherapy.

Value as a Research Model

ASPS is an ideal model for studying gene fusion-driven oncogenesis. The hallmark ASPSCR1-TFE3 fusion is present in over 90% of cases, providing a clear genetic driver. This fusion is amenable to CRISPR-based modeling, allowing researchers to introduce the translocation into isogenic cell lines to study its functional consequences. Public datasets, such as those from TCGA (though limited due to rarity) and the COSMIC database, provide mutation and expression data. Open questions include the role of the fusion in transcriptional reprogramming, the tumor microenvironment, and resistance to anti-angiogenic therapies. Gene-edited models are essential to dissect these mechanisms.

Core Molecular Pathogenesis

Major Carcinogenic Pathways

The primary oncogenic driver in ASPS is the ASPSCR1-TFE3 fusion protein, which acts as an aberrant transcription factor. Key pathways include:

  • • TFE3-mediated transcriptional activation: The fusion protein retains the DNA-binding domain of TFE3, leading to overexpression of downstream targets.
  • • MET signaling: TFE3 directly upregulates MET, activating the HGF/MET axis, promoting proliferation and invasion.
  • • HIF1A pathway: The fusion stabilizes HIF1A, leading to a pseudo-hypoxic state and upregulation of VEGF, contributing to angiogenesis.
  • • PI3K/AKT/mTOR: Constitutive activation of this pathway supports cell survival and growth.
High-Frequency Genetic Alterations
GeneFrequency (%)Mutation TypeFunctional Effect
ASPSCR1-TFE3 fusion>90%Chromosomal translocation t(X;17)(p11;q25)Aberrant transcription factor, drives oncogenesis
TFE3>90%Gene fusion (partner ASPSCR1)Overexpression of TFE3 targets
MET~30% (overexpression)Upregulation (not mutation)Activation of HGF/MET signaling
TP53<5%Mutation (rare)Loss of tumor suppressor function
PTEN<5%Mutation (rare)Activation of PI3K/AKT pathway

Data from COSMIC (v100) and TCGA (SARC cohort, limited ASPS cases).

Deregulated Signaling Networks

The ASPSCR1-TFE3 fusion deregulates multiple signaling networks:

  • • MET/HGF axis: Upregulation of MET leads to activation of downstream MAPK and PI3K pathways.
  • • HIF1A/VEGF axis: Pseudo-hypoxic conditions promote angiogenesis.
  • • PI3K/AKT/mTOR: Constitutive activation supports cell growth and survival.
  • • Wnt/β-catenin: Crosstalk with TFE3 may enhance proliferation.

Key nodes for targeted intervention include MET, VEGFR, and mTOR.

Experimental Model Systems

Cell Lines and Organoids
Cell LineOriginKey Mutations
ASPS-1Primary tumor (pleural effusion)ASPSCR1-TFE3 fusion
ASPS-2Metastatic lesion (lung)ASPSCR1-TFE3 fusion
ASPS-KYPrimary tumorASPSCR1-TFE3 fusion

Organoid models of ASPS are emerging, offering 3D culture systems that better recapitulate the tumor microenvironment. However, they are not yet widely available. Gene-edited cell lines, such as those with the ASPSCR1-TFE3 fusion introduced via CRISPR, are valuable for mechanistic studies.

Animal Models (PDX, GEMM, Induced)
  • • Patient-derived xenografts (PDX): Established by implanting ASPS tumor fragments into immunodeficient mice. These models retain the original tumor's genetic and histological features.
  • • Genetically engineered mouse models (GEMM): Conditional expression of ASPSCR1-TFE3 in mesenchymal stem cells has been attempted, but no fully penetrant GEMM exists yet.
  • • Cell line-derived xenografts: Using ASPS cell lines injected subcutaneously or orthotopically.
  • • Induced models: CRISPR-engineered human cell lines with the fusion can be used in xenograft studies.
Gene-Edited Cell Models

CRISPR-based gene editing enables the creation of isogenic cell lines with precise genetic modifications. For ASPS, researchers can:

  • • Knock-in the ASPSCR1-TFE3 fusion into a non-transformed cell line (e.g., HEK293 or mesenchymal stem cells) to study its oncogenic effects.
  • • Knockout TFE3 in ASPS cell lines to validate its dependency.
  • • Introduce point mutations in genes like MET or PTEN to study resistance mechanisms.

Commercially available, sequence-verified gene-edited models accelerate research by providing consistent and validated tools. These models are essential for drug screening and functional genomics.

Related Disease

Disease name Disease type

Related Products

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MYOD1 Knockout HEK293 Cell Line EDJ-KQ1334 Human 4654 Details Get a Quote
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Applications of Gene-Edited Cells

Functional Genomics

Gene-edited cell lines are used to validate the role of specific genes in ASPS. For example:

  • • TFE3 knockout in ASPS cell lines reduces proliferation and invasion, confirming its oncogenic role.
  • • ASPSCR1-TFE3 knock-in in non-transformed cells induces transformation, providing a model to study early events.
  • • MET knockout or knockdown can assess the dependency on MET signaling.
Drug Screening and Resistance

Isogenic pairs (e.g., wild-type vs. TFE3 knockout) are used in high-throughput screens to identify compounds that selectively target ASPS cells. Resistance models can be generated by chronic exposure to drugs like crizotinib (MET inhibitor) or sunitinib (VEGFR inhibitor), followed by CRISPR editing to identify resistance mutations.

Biomarker Discovery

CRISPR-based synthetic lethality screens can identify genes that, when knocked out, are lethal only in ASPS cells. This approach can uncover novel therapeutic targets and biomarkers. For example, screening for vulnerabilities in the MET pathway or DNA repair pathways.

Public Data Resources

DatabaseURLDescription
TCGAhttps://portal.gdc.cancer.govThe Cancer Genome Atlas provides genomic, transcriptomic, and clinical data for sarcomas, including ASPS (limited cases).
cBioPortalhttps://www.cbioportal.orgVisualization and analysis of cancer genomics data, including ASPS studies.
DepMaphttps://depmap.orgDependency map of cancer cell lines, including ASPS cell lines, for CRISPR screens and drug sensitivity.
GEOhttps://www.ncbi.nlm.nih.gov/geoGene Expression Omnibus for microarray and RNA-seq datasets of ASPS.
COSMIChttps://cancer.sanger.ac.uk/cosmicCatalogue of Somatic Mutations in Cancer, including ASPS fusion data.

Frequently Asked Research Questions

The ASPSCR1-TFE3 fusion, present in over 90% of cases, resulting from the t(X;17)(p11;q25) translocation.
Yes, ASPS-1 and ASPS-KY are available from commercial repositories, but they are not gene-edited. Custom CRISPR-edited models can be generated on request.
CRISPR can create isogenic cell lines with or without the ASPSCR1-TFE3 fusion, enabling functional studies, drug screening, and identification of resistance mechanisms.
The rarity of the disease and the lack of a fully penetrant GEMM. PDX models are the most reliable, but they are limited in availability.
TCGA, cBioPortal, DepMap, and COSMIC provide genomic, expression, and dependency data. GEO offers transcriptomic datasets.

Key References and Database URLs

WHO Classification of Tumours of Soft Tissue and Bone, 5th edition (2020) https://publications.iarc.fr/Book-And-Report-Series/Who-Classification-Of-Tumours/WHO-Classification-Of-Tumours-Of-Soft-Tissue-And-Bone-2020
NCI SEER Cancer Statistics https://seer.cancer.gov/statfacts/html/soft.html
NCBI Gene https://www.ncbi.nlm.nih.gov/gene/25980
NCBI Gene https://www.ncbi.nlm.nih.gov/gene/7030
COSMIC https://cancer.sanger.ac.uk/cosmic
TCGA https://portal.gdc.cancer.gov
cBioPortal https://www.cbioportal.org
DepMap https://depmap.org
GEO https://www.ncbi.nlm.nih.gov/geo
UniProt https://www.uniprot.org/uniprot/P19532
UniProt https://www.uniprot.org/uniprot/Q9BZE9
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