Towards Personalized Treatment Strategies for Esophageal Adenocarcinoma; A Review on the Molecular Characterization of Esophageal Adenocarcinoma and Current Research Efforts on Individualized Curative Treatment Regimens

Abstract

Esophageal cancers confer a major health challenge and are highly aggressive malignancies with poor prognosis. Esophageal adenocarcinoma (EAC) is one of the two major histopathological subtypes of esophageal cancer. Despite advances in treatment modalities, the prognosis of patients with EAC remains poor, with a 5-year survival rate that rarely exceeds 30% in patients treated with curative intent. Chemoradiotherapy followed by resection is the treatment of choice for EAC patients, which are deemed to be curable. Current patient stratification and treatments are based on outcomes from clinical trials. Unfortunately, the molecular heterogeneity of EAC which determines the chemo- and radiosensitivity of these cancers are not taken into account. A more personalized approach in the treatment of EAC could improve patient outcomes. This review aims at summarizing literature on translational and clinical research in the field of EAC which could be of importance to develop personalized approaches. As suggested by the TCGA, expression data features molecular classifications by different platforms, including miRNA, genomic mutations and reverse-phase protein arrays. Here, we summarize literature on transcriptomic, data-driven approaches to identify distinct subtypes of EAC associated with molecular features. These novel classifications may determine the responsiveness to chemo(radio)therapy and help to identify novel molecular targets within cell signaling pathways. Moreover, we discuss the current clinical research efforts on tailored treatment regimens for patients with EAC taking into account the heterogeneous response to chemoradiotherapy. We summarize the evidence regarding active surveillance instead of immediate surgical resection after application of neoadjuvant chemo(radio)therapy in EAC. We consider that in future patients with complete response to chemo(radio)therapy, predicted by (transcriptomic) biomarkers, might benefit most from this approach. Finally, challenges to overcome for current findings to be implemented in clinical practice and move the field forward are being discussed.