Optimized large-scale longitudinal biorepository of gastroesophageal adenocarcinoma patient-derived organoids: High-fidelity models for personalized treatment to overcome resistance.
A major limitation in studying gastroesophageal adenocarcinoma (GEA) has been the lack of reliable models that represent the diseases complexity. We present lessons learned from a comprehensive large-scale biobanking effort combining traditional sample collection with several in vitro models including 3-dimensional patient-derived organoids (PDOs), 2-dimensional cancer-associated fibroblasts (CAFs), tumor-infiltrating lymphocytes (TILs) and/or in vivo xenografts. This initiative started in 2018, integrating multiple advanced ex-vivo models such as PDOs, patient-derived xenografts (PDXs) and organoids (PDXOs). This unique resource now includes tumor avatars from over 380 consented patients, making it the largest living GEA biobank in the world. We achieved > 90% success rate in creating per-patient models, including 227 tumor-derived and 203 neighboring normal PDOs. These organoids accurately mirror key features of the original tumors, such as their histology (e.g. microsatellite instability), mutations, and drug response, across treatment points. Notably, PDOs can predict individual patient responses to chemotherapy within five weeks, underscoring their clinical relevance. Furthermore, high-throughput drug screening on PDO subsets generates personalized chemosensitivity profiles for 22 drugs. Through a process of continued refinement of culture techniques and tumor sampling approach, our large-scale comprehensive collection of GEA avatars represents a unique and valuable preclinical experimental resource for precision oncology. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=76 SRC="FIGDIR/small/663874v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@f8a032org.highwire.dtl.DTLVardef@dd6fa3org.highwire.dtl.DTLVardef@1cc558corg.highwire.dtl.DTLVardef@492a5_HPS_FORMAT_FIGEXP M_FIG Schematic depiction of GEA live-banking workflow C_FIG