Identification of Novel Molecular Subgroups in Esophageal Adenocarcinoma to Predict Response to Neo-Adjuvant Therapies.
Sanne J M HoefnagelWillem J KoemansHina N KhanJan KosterSybren L MeijerJolanda M van DierenLiudmila L KodachJohanna W van SandickSilvia CalpeCarmen M Del Sancho-SerraAna C P CorreiaMark Ivo van Berge HenegouwenSuzanne Sarah GisbertzMaarten C C M HulshofSandro MattioliManon C W SpaanderKausilia K KrishnadathPublished in: Cancers (2022)
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.
Keyphrases
- locally advanced
- early stage
- toll like receptor
- photodynamic therapy
- gene expression
- dendritic cells
- machine learning
- combination therapy
- induced apoptosis
- squamous cell carcinoma
- single cell
- rectal cancer
- radiation therapy
- immune response
- cancer therapy
- cell adhesion
- healthcare
- deep learning
- cell cycle arrest
- radiation induced
- cell therapy
- inflammatory response
- stem cells
- small molecule
- dna methylation
- nuclear factor
- single molecule
- ejection fraction
- newly diagnosed
- working memory
- endoplasmic reticulum stress
- current status
- young adults
- oxidative stress
- cell death
- drug delivery
- regulatory t cells
- double blind
- papillary thyroid