Familial Adenomatous Polyposis (FAP) Cell Models for Research

Disease Burden and Research Significance

Epidemiology and Clinical Impact

Familial Adenomatous Polyposis (FAP) is a rare inherited cancer predisposition syndrome characterized by the development of hundreds to thousands of colorectal adenomas, with a nearly 100% lifetime risk of colorectal cancer (CRC) if prophylactic colectomy is not performed. The incidence of FAP is estimated at 1 in 7,000 to 1 in 22,000 live births, accounting for less than 1% of all CRC cases (WHO). The average age of adenoma onset is 16 years, and CRC develops by age 40 if untreated. The 5-year survival for localized CRC is about 90%, but drops to 14% for distant metastases (NCI SEER). FAP also presents with extracolonic manifestations, including duodenal adenomas, desmoid tumors, and congenital hypertrophy of the retinal pigment epithelium (CHRPE). Research on FAP is crucial for understanding the early stages of colorectal carcinogenesis and for developing targeted prevention and therapeutic strategies.

Value as a Research Model

FAP serves as an ideal model for studying the adenoma-to-carcinoma sequence, as the progression from benign polyps to malignant tumors is well-defined and driven by a single initiating genetic event: germline mutations in the APC gene. This monogenic cause allows researchers to dissect the molecular mechanisms of tumor initiation and progression in a controlled manner. FAP also provides a platform for testing chemopreventive agents and novel therapeutic interventions. Public datasets, such as those from TCGA and COSMIC, provide extensive genomic and transcriptomic data on FAP-associated tumors, enabling integrative analyses. Open questions include the role of modifier genes, the impact of specific APC mutation sites on phenotype, and the development of targeted therapies for desmoid tumors and duodenal cancer.

Core Molecular Pathogenesis

Major Carcinogenic Pathways

The primary pathway dysregulated in FAP is the Wnt/β-catenin signaling pathway, which is constitutively activated due to loss of APC function. Key steps include:

1. Loss of functional APC protein.

2. Accumulation of β-catenin in the cytoplasm.

3. Translocation of β-catenin to the nucleus.

4. Activation of TCF/LEF transcription factors.

5. Upregulation of target genes such as MYC, CCND1, and MMP7.

Additionally, the PI3K/AKT pathway is often activated through mutations in PIK3CA or loss of PTEN, contributing to cell survival and proliferation. The MAPK pathway (RAS-RAF-MEK-ERK) is also frequently activated via KRAS mutations, promoting cell growth. Defects in DNA mismatch repair (MMR) may occur as secondary events, leading to microsatellite instability in a subset of tumors.

High-Frequency Genetic Alterations
GeneFrequency (%)Mutation TypeFunctional Effect
APC80-90Truncating, frameshift, nonsenseLoss of function, constitutive Wnt activation
KRAS40-50Missense (G12D, G13D)Constitutive activation of MAPK pathway
TP5350-70Missense, loss of heterozygosityLoss of tumor suppressor function
SMAD410-20Missense, deletionDisruption of TGF-β signaling
PIK3CA10-20Missense (E545K, H1047R)Activation of PI3K/AKT pathway
FBXW710-15Missense, frameshiftLoss of ubiquitin ligase activity, stabilization of oncoproteins

Data from TCGA and COSMIC.

Deregulated Signaling Networks

The major signaling networks deregulated in FAP include:

  • • Wnt/β-catenin pathway: Central to FAP pathogenesis. Key nodes: APC, β-catenin (CTNNB1), AXIN, GSK3β, TCF/LEF.
  • • PI3K/AKT/mTOR pathway: Often activated via PIK3CA mutations or PTEN loss. Key nodes: PI3K, AKT, mTOR, PTEN.
  • • MAPK/ERK pathway: Frequently activated via KRAS or BRAF mutations. Key nodes: RAS, RAF, MEK, ERK.
  • • TGF-β/SMAD pathway: Inactivated via SMAD4 mutations, leading to loss of growth inhibition. Key nodes: TGFBR, SMAD2/3, SMAD4.
  • • p53 pathway: Inactivated via TP53 mutations, affecting cell cycle arrest and apoptosis. Key nodes: p53, MDM2, CDKN1A.

Experimental Model Systems

Cell Lines and Organoids
Cell LineOriginKey Mutations
HCT116Colorectal carcinomaKRAS G13D, PIK3CA H1047R, CTNNB1 S45del
SW480Colorectal adenocarcinomaAPC truncating (Q1338), KRAS G12V, TP53 R273H
HT-29Colorectal adenocarcinomaAPC truncating (E853), BRAF V600E, TP53 R273H
DLD-1Colorectal adenocarcinomaAPC truncating (S1411), KRAS G13D, PIK3CA E545K
LoVoColorectal adenocarcinomaAPC truncating (Q1429), KRAS G13D, MSH2 deletion

Organoids derived from FAP patient tissues recapitulate the adenoma-to-carcinoma progression and can be used for drug testing and personalized medicine approaches. They maintain the genetic heterogeneity of the original tumor and can be genetically manipulated using CRISPR.

Animal Models (PDX, GEMM, Induced)
  • • Patient-derived xenografts (PDX): Implantation of FAP tumor tissue into immunodeficient mice, preserving tumor heterogeneity and allowing drug efficacy testing.
  • • Genetically engineered mouse models (GEMM): The ApcMin/+ mouse is the most common model, carrying a truncating mutation in Apc, developing multiple intestinal adenomas. Other models include ApcΔ716 and Apc1638N.
  • • Induced models: Use of Cre-lox systems to conditionally knock out Apc in the intestinal epithelium, allowing temporal and spatial control of tumor initiation.
  • • Carcinogen-induced models: Treatment of mice with azoxymethane (AOM) combined with dextran sulfate sodium (DSS) induces colonic tumors, but these are not specific to FAP.
Gene-Edited Cell Models

CRISPR-Cas9 technology enables the generation of isogenic cell lines with precise genetic modifications, such as knockout of APC or knock-in of specific mutations. These models are invaluable for studying the functional consequences of individual mutations in a controlled genetic background. For example, an APC knockout in a wild-type colorectal cell line can recapitulate the loss of APC function and activate Wnt signaling. Conversely, a knock-in of a common APC mutation (e.g., Q1338*) can be introduced into a cell line to study its specific effects. Commercially available, sequence-verified gene-edited cell models accelerate research by providing validated tools that save time and ensure reproducibility. These models are widely used for drug screening, target validation, and mechanistic studies.

Related Disease

Disease name Disease type

Related Products

Product name Cat.No. Species Gene ID
TP53 Knockout HCT 116 Cell Line EDC07854 Human 7157 Details Get a Quote
CTNNB1 Knockout HCT 116 Cell Line EDJ-KQ22 Human 1499 Details Get a Quote
CTNNB1 Knockout HEK293 Cell Line EDC07547 Human 1499 Details Get a Quote
CCND1 Knockout HEK293 Cell Line EDC07534 Human 595 Details Get a Quote
APC2 Knockout HEK293 Cell Line EDJ-KQ277 Human 10297 Details Get a Quote
AXIN1 Knockout HEK293 Cell Line EDJ-KQ278 Human 8312 Details Get a Quote
AXIN2 Knockout HEK293 Cell Line EDJ-KQ280 Human 8313 Details Get a Quote
LEF1 Knockout HEK293 Cell Line EDJ-KQ312 Human 51176 Details Get a Quote
TCF7L2 Knockout HEK293 Cell Line EDJ-KQ340 Human 6934 Details Get a Quote
SMAD4 Knockout HEK293 Cell Line EDJ-KQ401 Human 4089 Details Get a Quote
HRAS Knockout HEK293 Cell Line EDJ-KQ467 Human 3265 Details Get a Quote
PTGS2 Knockout HEK293 Cell Line EDJ-KQ586 Human 5743 Details Get a Quote
CASP3 Knockout HEK293 Cell Line EDJ-KQ632 Human 836 Details Get a Quote
STK11 Knockout HEK293 Cell Line EDJ-KQ869 Human 6794 Details Get a Quote
GSK3B Knockout HEK293 Cell Line EDJ-KQ902 Human 2932 Details Get a Quote

Applications of Gene-Edited Cells

Functional Genomics

Gene-edited cell lines are used to validate the role of specific genes in FAP pathogenesis. For instance, knocking out APC in a colorectal cell line leads to constitutive Wnt activation, confirming its tumor suppressor function. Similarly, introducing a KRAS G12V mutation into a cell line can demonstrate its oncogenic potential. CRISPR screens using pooled libraries can identify genes that are synthetic lethal with APC loss, providing potential therapeutic targets.

Drug Screening and Resistance

Isogenic cell line pairs, differing only in a specific genetic alteration, are ideal for drug screening. For example, an APC knockout cell line and its wild-type counterpart can be used to identify compounds that selectively kill APC-deficient cells. Gene-edited models can also be used to study drug resistance mechanisms by exposing cells to increasing concentrations of a drug and identifying acquired mutations.

Biomarker Discovery

CRISPR-based synthetic lethality screens can identify biomarkers that predict response to targeted therapies. For instance, loss of APC may confer sensitivity to inhibitors of β-catenin or its downstream effectors. Gene-edited cell lines can be used to validate candidate biomarkers and to develop companion diagnostics.

Public Data Resources

DatabaseURLDescription
TCGAhttps://portal.gdc.cancer.govThe Cancer Genome Atlas provides genomic, transcriptomic, and clinical data for colorectal cancer, including FAP-associated tumors.
cBioPortalhttps://www.cbioportal.orgVisualization and analysis of cancer genomics data, including mutation frequencies and co-occurrence.
DepMaphttps://depmap.orgThe Cancer Dependency Map provides CRISPR screen data and gene dependency profiles for hundreds of cancer cell lines.
GEOhttps://www.ncbi.nlm.nih.gov/geoGene Expression Omnibus stores microarray and RNA-seq data from FAP-related studies.
COSMIChttps://cancer.sanger.ac.uk/cosmicCatalogue of Somatic Mutations in Cancer provides mutation data for APC and other genes.

Frequently Asked Research Questions

The most common mutations are truncating mutations in the APC gene, leading to loss of function.
CRISPR-Cas9 can be used to introduce a frameshift or premature stop codon in the APC gene. Commercially available kits and services are available.
Loss of APC leads to constitutive activation of Wnt/β-catenin signaling, driving cell proliferation and tumor formation.
Yes, patient-derived organoids can be generated from FAP adenomas and used for drug testing and mechanistic studies.
Isogenic cell lines allow for the study of specific mutations in a controlled background, enabling target validation, drug screening, and functional genomics.

Key References and Database URLs

WHO https://www.who.int
NCI https://www.cancer.gov
NCBI Gene https://www.ncbi.nlm.nih.gov/gene
TCGA https://portal.gdc.cancer.gov
COSMIC https://cancer.sanger.ac.uk/cosmic
ClinVar https://www.ncbi.nlm.nih.gov/clinvar
UniProt https://www.uniprot.org
DepMap https://depmap.org
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