Predictive biomarkers for response to TGF- β inhibition in resensitizing chemo(radiated) esophageal adenocarcinoma
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Updated: Jun 19, 2025

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Published on: October 27, 2020
Dajia Liu1, Amber P van der Zalm2, Jan Koster3
1Amsterdam UMC Location University of Amsterdam, Center for Experimental and Molecular Medicine, Laboratory of Experimental Oncology and Radiobiology, Meibergdreef 9, Amsterdam 1105 AZ, the Netherlands; Amsterdam UMC location University of Amsterdam, Department of Medical Oncology, Meibergdreef 9, Amsterdam 1105 AZ, the Netherlands; Cancer Center Amsterdam, Cancer Biology, Amsterdam, the Netherlands.
Abstract:
Epithelial-mesenchymal transition (EMT) has been identified as a driver of therapy resistance, particularly in esophageal adenocarcinoma (EAC), where transforming growth factor beta (TGF-β) can induce this process. Inhibitors of TGF-β may counteract the occurrence of mesenchymal, resistant tumor cell populations following chemo(radio)therapy and improve treatment outcomes in EAC. Here, we aimed to identify predictive biomarkers for the response to TGF-β targeting. In vitro approximations of neoadjuvant treatment were applied to publicly available primary EAC cell lines. TGF-β inhibitors fresolimumab and A83-01 were employed to inhibit EMT, and mesenchymal markers were quantified via flow cytometry to assess efficacy. Our results demonstrated a robust induction of mesenchymal cell states following chemoradiation, with TGF-β inhibition leading to variable reductions in mesenchymal markers. The cell lines were clustered into responders and non-responders. Genomic expression profiles were obtained through RNA-seq analysis. Differentially expressed gene (DEG) analysis identified 10 positively- and 23 negatively-associated hub genes, which were bioinformatically identified. Furthermore, the correlation of DEGs with response to TGF-β inhibition was examined using public pharmacogenomic databases, revealing 9 positively associated and 11 negatively associated DEGs. Among these, ERBB2, EFNB1, and TNS4 were the most promising candidates. Our findings reveal a distinct gene expression pattern associated with the response to TGF-β inhibition in chemo(radiated) EAC. The identified DEGs and predictive markers may assist patient selection in clinical studies investigating TGF-β targeting.
Insights
Transforming growth factor beta (TGF-β) inhibition can reduce therapy resistance in esophageal adenocarcinoma (EAC). Researchers identified key genes, like ERBB2, EFNB1, and TNS4, to predict patient response to TGF-β targeting, improving EAC treatment selection.
Area of Science:
- Oncology
- Molecular Biology
- Cancer Therapeutics
Background:
- Epithelial-mesenchymal transition (EMT) drives therapy resistance in esophageal adenocarcinoma (EAC).
- Transforming growth factor beta (TGF-β) signaling promotes EMT and chemoresistance in EAC.
- Targeting TGF-β may overcome resistance and improve EAC treatment outcomes.
Purpose of the Study:
- To identify predictive biomarkers for response to TGF-β inhibition in EAC.
- To assess the efficacy of TGF-β inhibitors in counteracting EMT-induced resistance.
- To correlate gene expression profiles with treatment response.
Main Methods:
- In vitro modeling of neoadjuvant treatment on EAC cell lines.
- Application of TGF-β inhibitors (fresolimumab, A83-01) to block EMT.
- Quantification of mesenchymal markers via flow cytometry.
- RNA sequencing (RNA-seq) for genomic expression profiling.
- Bioinformatic analysis of differentially expressed genes (DEGs).
Main Results:
- Chemoradiation robustly induced mesenchymal states in EAC cells.
- TGF-β inhibition showed variable efficacy in reducing mesenchymal markers.
- EAC cell lines were classified into responders and non-responders to TGF-β inhibition.
- Bioinformatic analysis identified 10 positively and 23 negatively associated hub genes.
- ERBB2, EFNB1, and TNS4 emerged as promising predictive markers.
Conclusions:
- Distinct gene expression patterns correlate with TGF-β inhibition response in EAC.
- Identified DEGs and biomarkers can aid patient selection for TGF-β targeted therapies.
- This research supports personalized treatment strategies for esophageal adenocarcinoma.

