ATCC’s Human-Relevant Cancer Models for Mechanism-Based Toxicity and Drug Response Profiling

Background and Purpose

The Human Cancer Models Initiative (HCMI) is a global collaboration led by the National Cancer Institute (NCI) that aims to advance translational oncology by developing patient-derived cancer models. Traditional cell lines often fail to capture the complexity of human tumors, which limits their utility in drug discovery and precision medicine. HCMI addresses this gap by generating biologically relevant 2-D and 3-D models derived directly from patient samples, ensuring high genomic fidelity and clinical relevance. ATCC contributes to the initiative by developing, manufacturing, and distributing these models worldwide. The HCMI portfolio includes over 300 models spanning 28 tissue types, including colorectal, pancreatic, brain, and esophageal cancers, as well as rare malignancies such as Wilms tumor and Ewing’s sarcoma. These models reflect diverse clinical diagnoses, stages, age ranges, and racial backgrounds, providing researchers with tools to study tumor heterogeneity and health disparities. Comparative analyses show strong concordance with The Cancer Genome Atlas (TCGA), retaining over 80% of oncogenic drivers and preserving transcriptional and epigenetic landscapes. The purpose of this work is to provide researchers with clinically relevant models that improve preclinical testing, support biomarker discovery, and enable precision oncology strategies.

Methods

Organoids were cultured in 3-D extracellular matrix conditions using ATCC Organoid Growth Kits and passaged to form uniform structures prior to drug screening. Models were seeded into 96-well plates and treated with a panel of chemotherapeutic and targeted compounds using 12-point or 8-point dilution curves. Drug response was assessed via ATP-based luminescent viability assays and live-cell fluorescence imaging. Genomic characterization was performed using whole-exome or targeted sequencing, and data were compared to matched patient tumors and TCGA datasets to confirm model fidelity. Z’ factor scores were calculated to validate assay robustness, enabling correlation of genomic alterations with drug sensitivity.

Results and discussion

ATCC has expanded the HCMI portfolio to include 91 colorectal and over 54 pancreatic cancer organoids, each annotated with clinical, genomic, and drug-response data. Colorectal models, primarily adenocarcinomas, mirror TCGA mutation profiles and exhibit genotype-dependent drug sensitivity across 24 compounds. Pancreatic models similarly reflect key driver mutations (KRAS, TP53, SMAD4) and exhibit differential responses to targeted agents, including KRAS inhibitors. High-throughput assays demonstrated strong reproducibility (Z’ >0.7), and models preserved patient tumor morphology and molecular features. Sequencing and clinical metadata are publicly available via the HCMI portal. 

Conclusion

The HCMI portfolio, distributed by ATCC, represents a next-generation resource for oncology research and toxicology. These patient-derived models enable mechanism-based toxicity screening in human-relevant systems, improving prediction of drug-induced cytotoxicity, off-target effects, and population-level variability. Their genomic fidelity and 3-D architecture provide a robust platform for safety pharmacology and risk assessment. Ongoing expansion to include breast, glioblastoma, and ovarian cancer models will further strengthen translational toxicology and precision medicine efforts.