Download Champions' latest AACR 2025 Poster
Predicting clinical checkpoint inhibitor responses with TumorGraft3D PBMC co-culture
Despite the promise of checkpoint inhibitors (CPIs) in cancer therapy, accurately predicting patient responses remains a major challenge due to limitations in current preclinical models. Traditional 2D systems and immortalized cell lines fail to capture the spatial complexity and immune dynamics necessary for evaluating CPI efficacy.
To address these limitations, Champions Oncology developed a translational TumorGraft3D (CTG3D) co-culture platform using low-passage patient-derived xenograft (PDX) organoids with autologous or allogeneic PBMCs or TILs. This system preserves tumor heterogeneity, architecture, and immune contexture for more predictive immunotherapy screening.
To address these limitations, Champions Oncology developed a translational TumorGraft3D (CTG3D) co-culture platform using low-passage patient-derived xenograft (PDX) organoids with autologous or allogeneic PBMCs or TILs. This system preserves tumor heterogeneity, architecture, and immune contexture for more predictive immunotherapy screening.
- The platform integrates flow cytometry, high-content imaging, and luciferase-based viability assays to simultaneously measure immune activation, checkpoint expression, and tumor cell killing, providing multidimensional insights into immune-tumor interactions.
- Models were selected based on multi-omic data and clinical history from a 1,500+ model PDX bank, enabling clinically relevant predictions of CPI response in autologous settings.
- This flexible, high-throughput system supports diverse applications—including ADCC/ADCP assays, immune suppression modeling, and vaccine testing—making it a powerful tool for immune-oncology drug development and personalized therapy design.
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