Predictive biomarkers for response to TGF- β inhibition in resensitizing chemo(radiated) esophageal adenocarcinoma

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.

PubMed

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.