Ruoyu Ma
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Ruoyu Ma has a total of 22 co-authors. Here are the top co-authors by number of shared publications:
- Betty Giannias
Department of Surgery, McGill University, Montreal, QC H3A 0G4, Canada
1 shared publication - France Bourdeau
Department of Surgery, McGill University, Montreal, QC H3A 0G4, Canada
1 shared publication - Gertruda Evaristo
Department of Pathology, McGill University, Montreal, QC H3A 0G4, Canada
1 shared publication - Hellen Kuasne
Goodman Cancer Institute, McGill University, Montreal, QC H3A 0G4, Canada
1 shared publication - Hong Zhao
Goodman Cancer Institute, McGill University, Montreal, QC H3A 0G4, Canada
1 shared publication - James Tankel
Division of Thoracic and Upper Gastrointestinal Surgery, McGill University Health Centre, Montreal, QC H4A 3J1, Canada
1 shared publication
Latest Publications
- Open Access
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 disease’s 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 world’s largest living GEA biobank. We achieved a >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 with known genetic landscapes 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.
Open AccessOptimized 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 disease’s 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 world’s largest living GEA biobank. We achieved a >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 with known genetic landscapes 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.