The genome of esophageal adenocarcinoma (EAC) is highly unstable and might evolve over time. Here, we track karyotype evolution in EACs in response to treatment and upon recurrence through multi-region and longitudinal analysis. To this end, we introduce L-PAC (low-purity inference of absolute copy-number alterations [CNAs]), a bio-informatics technique that allows inference of absolute CNAs of low-purity samples by leveraging the information of high-purity samples from the same cancer.
View Article and Find Full Text PDFEsophageal 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.
View Article and Find Full Text PDFObjective: This study investigated the patterns, predictors, and survival of recurrent disease following esophageal cancer surgery.
Background: Survival of recurrent esophageal cancer is usually poor, with limited prospects of remission.
Methods: This nationwide cohort study included patients with distal esophageal and gastroesophageal junction adenocarcinoma and squamous cell carcinoma after curatively intended esophagectomy in 2007 to 2016 (follow-up until January 2020).