Cell Line-Derived Xenograft (CDX) Models
Fast and Scalable Cell Line-Derived Xenograft (CDX) Models
LIDE’s Cell Line-Derived Xenograft (CDX) models offer a high-throughput, cost-effective in vivo platform for evaluating oncology drug candidates. Derived from well-characterized cancer cell lines, these models are ideal for rapid efficacy testing, biomarker investigation, and early pharmacology studies.
Why choose CDX models?
CDX models are established by transplanting human cancer cell lines into immunodeficient mice, offering several key advantages:
- Speed & Efficiency: Faster engraftment and tumor development compared to PDX — perfect for agile screening.
- Highly Reproducible: Standardized tumor growth from immortalized lines ensures consistency across studies.
- Cost-Effective: Lower resource requirements make CDX models ideal for initial dose and regimen studies.
- Predictive Biology: They mirror many molecular and pharmacological traits of the source tumors, including treatment responses
LIDE’s Expansive CDX Portfolio
We curate one of the most diverse and rapidly growing CDX collections-ideal for early-stage R&D. 120+ established models spanning major tumor types:
| Cancer Type | Cell Lines | # of Available CDX Models |
| Bladder Cancer | 5637, RT112, SW780, T24 | 4 |
| Breast Cancer | BT474, HCC1806, HCC-1954, JIMT-1, MCF-7, MDA-MB-231, MDA-MB-453, MDA-MB-468, MFM-223, SUM149PT, ZR-75-1 | 11 |
| Cervical Cancer | C-33A, HeLa, SK-UT-1 | 3 |
| Colon Cancer | COLO 205, DLD-1, GP2D, HCT-116, HT-29, LS513, LOVO, RKO, SW1463, SW48, SW480, SW620, SW837 | 13 |
| Esophageal Cancer | KYSE-30 | 1 |
| Fibrosarcoma | HT1080 | 1 |
| Gastric Cancer | AGS, KATO III, MKN1, MKN45, NCI-N87, NCI-N87-Claudin 18.2, NUGC-3, SNU-16, SNU-5 | 9 |
| Liver Cancer | Hep G2, Hep3B, Huh7, MHCC97H, SNU-398 | 5 |
| Lung Cancer | A549, Clau-1, Clau-3, DMS114, EBC-1, HCC827, MSTO-211H, NCI-H1299, NCI-H1373, NCI-H1975, NCI-H2009, NCI-H209, NCI-H2122, NCI-H226, NCI-H292, NCI-H358, NCI-H441, NCI-H460, NCI-H524, NCI-H596, NCI-H838, PC-9, SHP-77 | 23 |
| Lymphoma & Leukemia | Daudi, Jurkat clone E6-1, Karpars-299, K-562, KG-1, MOLT-4, MOLM-13, MOLM-16, MV-4-11, NALM-6, OCI-AML2, OCI-LY3, Ramos(RA 1), Raji, RPMI 8226, RS4;11, Toledo | 17 |
| Melanoma | A-375, A-431 | 2 |
| Pancreas Cancer | ASPC-1, BXPC-3, Capan-2, HPAC, MIA PaCa-2, PANC-1, PK-59 | 7 |
| Prostate Cancer | 22Rv1, DU145, LNCaP Clone FGC, PC-3 | 4 |
| Renal Carcinoma | 786-O, A-498, SK-NEP-1 | 3 |
| Ovarian Cancer | SK-OV-3, PA-1, A2780, ES-2, OVCAR-3 | 5 |
| Glioblastoma | U87-MG, U251, LN-229 | 3 |
| Multiple Myeloma | MOLP-8 | 1 |
| Osteosarcoma | SAOS-2 | 1 |
| Retinoblastoma | WERI-Rb-1, Y-79 | 2 |
| Head and Neck Cancer | SCC090, CAL 27, CAL-33, KYES450, FaDu | 5 |
| Rhabdomyosarcoma | RD-ES | 1 |
LIDE’s CDX models are compatible with humanized mouse systems, enabling immunotherapy evaluation within human-like immune contexts.
Additionally, LIDE has 220+ human cancer cell lines available in house for CDX development, enriched with drug-resistant variants and clinically relevant phenotypes.
| Application | Why CDX Makes a Difference |
|---|---|
| High-Throughput Screening | Efficiently compare multiple drug candidates across fast-growing models |
| Dose & Schedule Optimization | Explore dose-response dynamics before committing to resource-intensive PDX |
| Standard-of-Care Benchmarking | Test new compounds directly against established therapies |
| Biomarker Discovery | Link molecular features to in vivo drug response across uniform models |
| Proof of Concept & MoA Validation | Fast, reliable efficacy readouts to inform next-phase decisions |
| Immune-Oncology Testing (Humanized) | Model checkpoint inhibitors, CAR-Ts, and ADCs with functional immune systems |
Differentiating CDX vs PDX: Why Both Matter
While PDX models preserve tumor heterogeneity and deliver high translational fidelity, they require months to establish and scale. CDX models, on the other hand, offer:
- Rapid experimentation cycles
- Lower compound and animal usage
- Immediate, reproducible results
- Ideal for early phase selection before deploying PDX or orthotopic validation