Identification of Novel Molecular Subgroups in Esophageal Adenocarcinoma to Predict Response to Neo-Adjuvant Therapies.
Cancers (Basel)
; 14(18)2022 Sep 16.
Article
en En
| MEDLINE
| ID: mdl-36139661
Esophageal adenocarcinoma (EAC) is a highly aggressive cancer and its response to chemo- and radiotherapy is unpredictable. EACs are highly heterogeneous at the molecular level. The aim of this study was to perform gene expression analysis of EACs to identify distinct molecular subgroups and to investigate expression signatures in relation to treatment response. In this prospective observational study, RNA sequencing was performed on pre-treatment endoscopic EAC biopsies from a discovery cohort included between 2012 and 2017 in one Dutch Academic Center. Four additional cohorts were analyzed for validation purposes. Unsupervised clustering was performed on 107 patients to identify biological EAC subgroups. Specific cell signaling profiles were identified and evaluated with respect to predicting response to neo-adjuvant chemo(radio)therapy. We identified and validated three distinct biological EAC subgroups, characterized by (1) p38 MAPK/Toll-like receptor signaling; (2) activated immune system; and (3) impaired cell adhesion. Subgroup 1 was associated with poor response to chemo-radiotherapy. Moreover, an immune signature with activated T-cell signaling, and increased number of activated CD4 T memory cells, neutrophils and dendritic cells, and decreased M1 and M2 macrophages and plasma cells, was associated with complete histopathological response. This study provides a novel molecular classification for EACs. EAC subgroup 1 proved to be more therapy-resistant, while immune signaling was increased in patients with complete response to chemo-radiotherapy. Our findings give insight into the biology of EACs and in cellular signaling mechanisms underlying response to neo-adjuvant treatment. Future implementation of this classification will improve patient stratification and enhance the development of targeted therapies.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Tipo de estudio:
Diagnostic_studies
/
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Cancers (Basel)
Año:
2022
Tipo del documento:
Article
País de afiliación:
Países Bajos
Pais de publicación:
Suiza