Abstract LB487: Patient-specific esophageal adenocarcinoma-on-a-chip: Modeling tumor-stromal-immune interactions and therapeutic response

Abstract Introduction: Esophageal adenocarcinoma drives most esophageal cancer mortality in North America, with poor 5-year survival (15-25%) despite taxane-based triplet chemotherapy. Extensive inter- and intra-patient genomic heterogeneity often limits the effectiveness of genetically guided targeted therapies and contributes to resistance to chemotherapy and immunotherapy. Currently, no definitive guidelines exist to predict patient-specific treatment response. Conventional animal models and 2D cell lines inadequately recapitulate the tumor microenvironment (TME), underscoring the need for personalized platforms that capture interactions among immune cells, cancer-associated fibroblasts (CAFs), and the vasculature. In this study, we developed an immune-competent esophageal adenocarcinoma-on-a-chip model that incorporates both stromal components and immune cells and enables personalized therapy testing by simulating patient-specific tumor-immune interactions within the TME. Methods: Treatment-naive patient-derived organoids (PDOs), matched CAFs, autologous tumor-infiltrating lymphocytes (TILs), and primary esophageal endothelial cells were integrated into a two-channel chip (Emulate). Tumor organoids were seeded in the epithelial channel, while CAF and endothelial cells occupied the stromal channel, separated by a porous PDMS membrane. Flow at 60 µl/h and stretch (10%, 0.15 Hz) were applied to mimic perfusion and peristalsis. After stromal monolayer formation, labeled TILs were perfused for 2 hours at 1000 µl/h. 3D microtissue organization and TIL dynamics were monitored for 10 days. Parallel static transwell cultures (-flow/-stretch) using the same patient-derived cells were established to assess the impact of dynamic biomechanical cues. Results: Real-time imaging demonstrated tumor growth and dynamic TME remodeling for up to 10 days under physiologically relevant flow and shear stress. Progressive formation of complex 3D microtissues was observed in both epithelial and stromal channels. Autologous TILs adhered within the stromal channel, proliferated, and formed clusters, with some migrating toward the tumor-containing epithelial channel, indicating active tumor-immune crosstalk. Matched static transwell cultures failed to generate comparable 3D stromal structures or directional TIL migration, confirming the critical role of flow and cyclic stretch in stromal architecture and immune recruitment. Conclusion: This patient-specific, TME-inclusive esophagus-on-a-chip platform offers a robust alternative to animal models by capturing physiological flow and stretch-driven tumor-immune dynamics. Our model enables rapid ex vivo assessment of personalized chemotherapy and immunotherapy responses, offering clinically relevant results to guide precision treatment in esophageal adenocarcinoma. Citation Format: Manal Al Dow, Sanjima Pal, Cedric Julien, Anna Staravoitava, Betty Giannias, Nick Bertos, Kim Ma, Lorenzo Ferri, Jonathan Cools Lartigue. Patient-specific esophageal adenocarcinoma-on-a-chip: Modeling tumor-stromal-immune interactions and therapeutic response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(8_Suppl):Abstract nr LB487.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2026-04-17
DOI
https://doi.org/10.1158/1538-7445.am2026-lb487
Primary Topic
3D Printing in Biomedical Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract LB487: Patient-specific esophageal adenocarcinoma-on-a-chip: Modeling tumor-stromal-immune interactions and therapeutic response

Lorenzo Ferri, Manal Al Dow, Sanjima Pal, Betty Giannias et al.
Cancer Research
3D Printing in Biomedical Research
article

Abstract LB487: Patient-specific esophageal adenocarcinoma-on-a-chip: Modeling tumor-stromal-immune interactions and therapeutic response

Lorenzo Ferri, Manal Al Dow, Sanjima Pal, Betty Giannias, Nick Bertos, Jonathan Cools Lartigue, Cedric Julien, Anna Staravoitava, Kim Ma
article en

Abstract

Abstract Introduction: Esophageal adenocarcinoma drives most esophageal cancer mortality in North America, with poor 5-year survival (15-25%) despite taxane-based triplet chemotherapy. Extensive inter- and intra-patient genomic heterogeneity often limits the effectiveness of genetically guided targeted therapies and contributes to resistance to chemotherapy and immunotherapy. Currently, no definitive guidelines exist to predict patient-specific treatment response. Conventional animal models and 2D cell lines inadequately recapitulate the tumor microenvironment (TME), underscoring the need for personalized platforms that capture interactions among immune cells, cancer-associated fibroblasts (CAFs), and the vasculature. In this study, we developed an immune-competent esophageal adenocarcinoma-on-a-chip model that incorporates both stromal components and immune cells and enables personalized therapy testing by simulating patient-specific tumor-immune interactions within the TME. Methods: Treatment-naive patient-derived organoids (PDOs), matched CAFs, autologous tumor-infiltrating lymphocytes (TILs), and primary esophageal endothelial cells were integrated into a two-channel chip (Emulate). Tumor organoids were seeded in the epithelial channel, while CAF and endothelial cells occupied the stromal channel, separated by a porous PDMS membrane. Flow at 60 µl/h and stretch (10%, 0.15 Hz) were applied to mimic perfusion and peristalsis. After stromal monolayer formation, labeled TILs were perfused for 2 hours at 1000 µl/h. 3D microtissue organization and TIL dynamics were monitored for 10 days. Parallel static transwell cultures (-flow/-stretch) using the same patient-derived cells were established to assess the impact of dynamic biomechanical cues. Results: Real-time imaging demonstrated tumor growth and dynamic TME remodeling for up to 10 days under physiologically relevant flow and shear stress. Progressive formation of complex 3D microtissues was observed in both epithelial and stromal channels. Autologous TILs adhered within the stromal channel, proliferated, and formed clusters, with some migrating toward the tumor-containing epithelial channel, indicating active tumor-immune crosstalk. Matched static transwell cultures failed to generate comparable 3D stromal structures or directional TIL migration, confirming the critical role of flow and cyclic stretch in stromal architecture and immune recruitment. Conclusion: This patient-specific, TME-inclusive esophagus-on-a-chip platform offers a robust alternative to animal models by capturing physiological flow and stretch-driven tumor-immune dynamics. Our model enables rapid ex vivo assessment of personalized chemotherapy and immunotherapy responses, offering clinically relevant results to guide precision treatment in esophageal adenocarcinoma. Citation Format: Manal Al Dow, Sanjima Pal, Cedric Julien, Anna Staravoitava, Betty Giannias, Nick Bertos, Kim Ma, Lorenzo Ferri, Jonathan Cools Lartigue. Patient-specific esophageal adenocarcinoma-on-a-chip: Modeling tumor-stromal-immune interactions and therapeutic response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(8_Suppl):Abstract nr LB487.

Cancer ResearchVol. 86(8_Supplement)
McGill University Health Centre (CA), McGill University (CA)
Good health and well-being
Openalex Percentile: Top 8%
3D Printing in Biomedical Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.