Neuroblastoma Cell Models for Research
Disease Burden and Research Significance
Neuroblastoma is the most common extracranial solid tumor in children, accounting for approximately 8-10% of all childhood cancers and 15% of pediatric cancer deaths. The global incidence is estimated at 10.2 cases per million children aged 0-14 years, with about 700 new cases diagnosed annually in the United States (NCI). The 5-year survival rate for low-risk and intermediate-risk neuroblastoma exceeds 90%, but for high-risk neuroblastoma, it remains below 50% despite intensive multimodal therapy (WHO). Risk stratification is based on age, stage, histology, and genomic features such as MYCN amplification and ploidy.
Neuroblastoma is an ideal model for studying developmental biology, oncogene addiction, and tumor heterogeneity. Its well-characterized subtypes (e.g., MYCN-amplified vs. non-amplified) and the availability of extensive public datasets (e.g., TCGA, GEO) facilitate mechanistic studies. Open questions include the role of telomere maintenance mechanisms, the tumor microenvironment, and the development of resistance to targeted therapies. Gene-edited cell models enable precise perturbation of genes involved in these processes, accelerating discovery.
Core Molecular Pathogenesis
Neuroblastoma pathogenesis involves several key pathways:
1. MYCN signaling: MYCN amplification occurs in ~20% of tumors and drives proliferation, metabolism, and angiogenesis. MYCN overexpression leads to transcriptional reprogramming.
2. ALK signaling: Activating mutations in ALK (anaplastic lymphoma kinase) are found in ~10% of sporadic cases and ~50% of familial cases. ALK activates PI3K/AKT and MAPK pathways.
3. Telomere maintenance: Activation of telomerase (TERT) or alternative lengthening of telomeres (ALT) is critical for immortalization. TERT promoter mutations and ATRX mutations are common.
4. Apoptosis evasion: Loss of TP53 function (rarely mutated but often inactivated) and overexpression of anti-apoptotic BCL-2 family members contribute to resistance to chemotherapy.
| Gene | Frequency (%) | Mutation Type | Functional Effect |
|---|---|---|---|
| MYCN | 20-25 | Amplification | Oncogene activation, poor prognosis |
| ALK | 10-15 | Point mutations (e.g., F1174L, R1275Q) | Constitutive kinase activity |
| ATRX | 5-10 | Inactivating mutations | ALT activation, genomic instability |
| TERT | 5-10 | Promoter mutations | Telomerase reactivation |
| TP53 | 2-3 | Inactivating mutations | Loss of tumor suppression |
| PHOX2B | 1-2 | Germline mutations | Predisposition, neurodevelopment |
| LIN28B | 5-10 | Overexpression | Let-7 suppression, oncogenesis |
Data from TCGA and COSMIC.
Key signaling networks in neuroblastoma include:
- • PI3K/AKT/mTOR pathway: Activated by ALK mutations and growth factor receptors. Promotes survival and proliferation.
- • MAPK/ERK pathway: Activated by RAS mutations (rare) or upstream receptor tyrosine kinases. Drives cell cycle progression.
- • Wnt/β-catenin pathway: Aberrant activation in a subset of tumors, contributing to stemness and metastasis.
- • p53 pathway: Often inactivated via MDM2 overexpression or TP53 mutation, leading to defective apoptosis.
- • Retinoic acid signaling: Critical for differentiation; often dysregulated in high-risk tumors.
Experimental Model Systems
Common neuroblastoma cell lines include:
| Cell Line | Origin | Key Mutations |
|---|---|---|
| SH-SY5Y | Bone marrow metastasis | MYCN non-amplified, TP53 wild-type |
| IMR-32 | Abdominal mass | MYCN amplified, TP53 wild-type |
| SK-N-BE(2) | Bone marrow metastasis | MYCN amplified, TP53 mutant |
| Kelly | Bone marrow | MYCN amplified, ALK F1174L |
| NB-1 | Tumor | MYCN amplified, ALK R1275Q |
| CHLA-255 | Bone marrow | MYCN amplified, ALK F1174L |
Organoids derived from patient tumors retain 3D architecture and heterogeneity, providing more physiologically relevant models for drug testing.
Animal models include:
- • Patient-derived xenografts (PDX): Immunodeficient mice engrafted with patient tumor cells, preserving genetic heterogeneity.
- • Genetically engineered mouse models (GEMM): Transgenic mice with MYCN overexpression under the TH promoter develop neuroblastoma, mimicking human disease.
- • Induced models: Conditional knock-in of ALK mutations or MYCN amplification using Cre-lox systems.
- • Zebrafish models: Transgenic zebrafish with MYCN overexpression are used for high-throughput drug screens.
CRISPR-Cas9 technology enables the creation of isogenic cell lines with precise genetic modifications. These models are essential for studying gene function and drug response. Examples include:
- • MYCN knockout lines: In MYCN-amplified cell lines (e.g., IMR-32), knocking out MYCN reduces proliferation and induces differentiation.
- • ALK knock-in lines: Introducing ALK mutations (e.g., F1174L) into non-mutated cell lines (e.g., SH-SY5Y) confers constitutive activation and sensitivity to ALK inhibitors.
- • TP53 knockout lines: In TP53 wild-type lines, knockout of TP53 recapitulates loss-of-function and increases resistance to genotoxic agents.
- • Reporter lines: GFP or luciferase reporters under the control of MYCN or ALK promoters enable real-time monitoring of pathway activity.
Commercially available, sequence-verified gene-edited cell models accelerate research by providing consistent, validated tools. These models are generated using CRISPR/Cas9 and are available from commercial sources, ensuring high quality and reproducibility.
Related Disease
| Disease name | Disease type |
|---|
Related Services
Related Products
| Product name | Cat.No. | Species | Gene ID | |
|---|---|---|---|---|
| BTBD9 Knockout SH-SY5Y Cell Line | EDJ-KZ121 | Human | 114781 | Details Get a Quote |
| CAPNS1 Knockout SK-N-SH Cell Line | EDJ-KZ128 | Human | 826 | Details Get a Quote |
| LIPA Knockout SH-SY5Y Cell Line | EDJ-KZ335 | Human | 3988 | Details Get a Quote |
| GPBAR1 Knockout SK-N-AS Cell Line | EDC07743 | Human | 151306 | Details Get a Quote |
| F2R Knockout SK-N-SH Cell Line | EDC07923 | Human | 2149 | Details Get a Quote |
| Snap25 Knockout N1E-115 Cell Line | EDC08238 | Mouse | 20614 | Details Get a Quote |
Applications of Gene-Edited Cells
Gene-edited cell lines allow functional validation of candidate genes identified in genomic studies. For example:
- • Knockout of tumor suppressors: Loss of TP53 or ATRX in cell lines confirms their role in genomic stability and apoptosis.
- • Knock-in of oncogenes: Introducing MYCN or ALK mutations into non-tumorigenic lines transforms them, enabling mechanistic studies.
- • Reporter lines: CRISPR-mediated insertion of fluorescent tags (e.g., mCherry) into endogenous loci allows tracking of protein expression and localization.
Isogenic pairs (wild-type vs. gene-edited) are powerful tools for drug screening:
- • Target validation: Knockout of a putative drug target (e.g., ALK) confirms its role in drug sensitivity.
- • Resistance modeling: Chronic exposure of gene-edited cells to drugs can select for resistant clones, revealing resistance mechanisms.
- • Combination screening: Using isogenic lines with different mutations (e.g., MYCN amplified vs. non-amplified) helps identify genotype-specific drug responses.
CRISPR-based synthetic lethality screens identify genes that are essential only in specific genetic backgrounds. For example:
- • MYCN-amplified cells: Screening for genes that are selectively lethal in MYCN-amplified cells can reveal novel therapeutic targets.
- • ALK-mutant cells: Identifying dependencies on ALK signaling pathways can lead to biomarkers for patient stratification.
- • Reporter lines: Using CRISPR to knock out genes in reporter lines can identify regulators of pathway activity, serving as potential biomarkers.
Public Data Resources
| Database | URL | Description |
|---|---|---|
| TCGA | https://portal.gdc.cancer.gov/ | The Cancer Genome Atlas provides genomic, transcriptomic, and clinical data for neuroblastoma. |
| cBioPortal | https://www.cbioportal.org/ | Visualization and analysis of cancer genomics data, including neuroblastoma studies. |
| DepMap | https://depmap.org/portal/ | Dependency Map provides CRISPR screens and gene expression data for cancer cell lines, including neuroblastoma. |
| GEO | https://www.ncbi.nlm.nih.gov/geo/ | Gene Expression Omnibus hosts microarray and RNA-seq datasets from neuroblastoma studies. |
| COSMIC | https://cancer.sanger.ac.uk/cosmic | Catalogue of Somatic Mutations in Cancer includes mutation data for neuroblastoma. |
| ClinVar | https://www.ncbi.nlm.nih.gov/clinvar/ | Database of clinically relevant variants, including germline mutations in neuroblastoma predisposition genes. |
Frequently Asked Research Questions
What is the most common genetic alteration in neuroblastoma?
How can I generate a MYCN knockout cell line?
What is the role of ALK mutations in neuroblastoma?
Can gene-edited cell models be used for drug resistance studies?
Where can I find public data on neuroblastoma cell lines?
Key References and Database URLs
| WHO Classification of Tumours of the Central Nervous System (5th edition) | https://www.who.int/publications/i/item/9789240085794 |
|---|---|
| NCI Neuroblastoma Treatment (PDQ) | https://www.cancer.gov/types/neuroblastoma |
| NCBI Gene | https://www.ncbi.nlm.nih.gov/gene/4613 |
| NCBI Gene | https://www.ncbi.nlm.nih.gov/gene/238 |
| NCBI Gene | https://www.ncbi.nlm.nih.gov/gene/7157 |
| TCGA TARGET Program | https://ocg.cancer.gov/programs/target |
| COSMIC Neuroblastoma | https://cancer.sanger.ac.uk/cosmic |
| ClinVar | https://www.ncbi.nlm.nih.gov/clinvar |
| UniProt | https://www.uniprot.org |
| DepMap | https://depmap.org/portal |
| 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/portal/ |