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Hypergastrinemia has been associated with high grade dysplasia and adenocarcinoma in patients with Barrett’s esophagus (BE), and experimental studies suggest pro-inflammatory and pro-neoplastic effects of gastrin on BE. This is of potential concern, as BE patients are treated with medications that suppress gastric acid production, resulting in increased physiologic levels of gastrin. We aimed to determine whether treatment with the novel gastrin/CCK(2) receptor antagonist netazepide reduces expression of markers associated with inflammation and neoplasia in BE. This was a randomized, double-blind, placebo-controlled trial of netazepide in patients with BE without dysplasia. Subjects were treated for 12 weeks, with endoscopic assessment at baseline and at end of treatment. The primary outcome was within-individual change in cellular proliferation as assessed by Ki67. Secondary analyses included changes in gene expression, assessed by RNA-sequencing, and safety and tolerability. A total of 20 subjects completed the study and were included in the analyses. There was no difference between arms in mean change in cellular proliferation (netazepide: +35.6 Ki67+ cells/ mm(2), SD 620.7; placebo: +307.8 Ki67+ cells/ mm(2), SD 640.3; p=0.35). Netazepide treatment resulted in increased expression of genes related to gastric phenotype (TFF2, MUC5B) and certain cancer-associated markers (REG3A, PAX9, MUC1), and decreased expression of intestinal markers MUC2, FABP1, FABP2, and CDX1. No serious adverse events related to study drug occurred. The gastrin/CCK(2) receptor antagonist netazepide did not reduce cellular proliferation in patients with non-dysplastic BE. Further research should focus on the biological effects of gastrin in Barrett’s esophagus.

Recent studies show that aneuploidy and driver gene mutations precede cancer diagnosis by many years1–4. We assess whether these genomic signals can be used for early detection and pre-emptive cancer treatment using the neoplastic precursor lesion Barrett’s esophagus as an exemplar5. Shallow whole-genome sequencing of 777 biopsies, sampled from 88 patients in Barrett’s esophagus surveillance over a period of up to 15 years, shows that genomic signals can distinguish progressive from stable disease even 10 years before histopathological transformation. These findings are validated on two independent cohorts of 76 and 248 patients. These methods are low-cost and applicable to standard clinical biopsy samples. Compared with current management guidelines based on histopathology and clinical presentation, genomic classification enables earlier treatment for high-risk patients as well as reduction of unnecessary treatment and monitoring for patients who are unlikely to develop cancer. Longitudinal molecular profiling of copy number alterations in patients with Barrett’s esophagus can identify patients at higher risk of developing esophageal cancer.

BACKGROUND & AIMS: Esophageal adenocarcinomas (EACs) are heterogeneous and often preceded by Barrett's esophagus (BE). Many genomic changes have been associated with development of BE and EAC, but little is known about epigenetic alterations. We performed epigenetic analyses of BE and EAC tissues and combined these data with transcriptome and genomic data to identify mechanisms that control gene expression and genome integrity.METHODS: In a retrospective cohort study, we collected tissue samples and clinical data from 150 BE and 285 EAC cases from the Oesophageal Cancer Classification and Molecular Stratification consortium in the United Kingdom. We analyzed methylation profiles of all BE and EAC tissues and assigned them to subgroups using non-negative matrix factorization with k-means clustering. Data from whole-genome sequencing and transcriptome studies were then incorporated; we performed integrative methylation and RNA-sequencing analyses to identify genes that were suppressed with increased methylation in promoter regions. Levels of different immune cell types were computed using single-sample gene set enrichment methods. We derived 8 organoids from 8 EAC tissues and tested their sensitivity to different drugs.RESULTS: BE and EAC samples shared genome-wide methylation features, compared with normal tissues (esophageal, gastric, and duodenum; controls) from the same patients and grouped into 4 subtypes. Subtype 1 was characterized by DNA hypermethylation with a high mutation burden and multiple mutations in genes in cell cycle and receptor tyrosine signaling pathways. Subtype 2 was characterized by a gene expression pattern associated with metabolic processes (ATP synthesis and fatty acid oxidation) and lack methylation at specific binding sites for transcription factors; 83% of samples of this subtype were BE and 17% were EAC. The third subtype did not have changes in methylation pattern, compared with control tissue, but had a gene expression pattern that indicated immune cell infiltration; this tumor type was associated with the shortest time of patient survival. The fourth subtype was characterized by DNA hypomethylation associated with structure rearrangements, copy number alterations, with preferential amplification of CCNE1 (cells with this gene amplification have been reported to be sensitive to CDK2 inhibitors). Organoids with reduced levels of MGMT and CHFR expression were sensitive to temozolomide and taxane drugs.CONCLUSIONS: In a comprehensive integrated analysis of methylation, transcriptome, and genome profiles of more than 400 BE and EAC tissues, along with clinical data, we identified 4 subtypes that were associated with patient outcomes and potential responses to therapy.

Recent studies show that aneuploidy and driver gene mutations precede cancer diagnosis by many years

SummaryCancer arises through a process of somatic evolution and recent studies have shown that aneuploidies and driver gene mutations precede cancer diagnosis by several years to decades1–4 Here, we address the question whether such genomic signals can be used for early detection and pre-emptive cancer treatment. To this end we study Barrett’s oesophagus, a genomic copy number driven neoplastic precursor lesion to oesophageal adenocarcinoma5. We use shallow whole genome sequencing of 777 biopsies sampled from 88 patients in surveillance for Barrett’s oesophagus over a period of up to 15 years. These data show that genomic signals exist that distinguish progressive from stable disease with an AUC of 0.87 and a sensitivity of 50% even ten years prior to histopathological disease transformation. These finding are validated on two independent cohorts of 75 and 248 patients. Compared against current patient management guidelines genomic risk classification enables earlier treatment for high risk patients as well as reduction of unnecessary treatment and monitoring for patients who are unlikely to develop cancer.

Background Early cancer recurrence after oesophagectomy is a common problem, with an incidence of 20–30 per cent despite the widespread use of neoadjuvant treatment. Quantification of this risk is difficult and existing models perform poorly. This study aimed to develop a predictive model for early recurrence after surgery for oesophageal adenocarcinoma using a large multinational cohort and machine learning approaches. Methods Consecutive patients who underwent oesophagectomy for adenocarcinoma and had neoadjuvant treatment in one Dutch and six UK oesophagogastric units were analysed. Using clinical characteristics and postoperative histopathology, models were generated using elastic net regression (ELR) and the machine learning methods random forest (RF) and extreme gradient boosting (XGB). Finally, a combined (ensemble) model of these was generated. The relative importance of factors to outcome was calculated as a percentage contribution to the model. Results A total of 812 patients were included. The recurrence rate at less than 1 year was 29·1 per cent. All of the models demonstrated good discrimination. Internally validated areas under the receiver operating characteristic (ROC) curve (AUCs) were similar, with the ensemble model performing best (AUC 0·791 for ELR, 0·801 for RF, 0·804 for XGB, 0·805 for ensemble). Performance was similar when internal–external validation was used (validation across sites, AUC 0·804 for ensemble). In the final model, the most important variables were number of positive lymph nodes (25·7 per cent) and lymphovascular invasion (16·9 per cent). Conclusion The model derived using machine learning approaches and an international data set provided excellent performance in quantifying the risk of early recurrence after surgery, and will be useful in prognostication for clinicians and patients., Early recurrence after surgery for adenocarcinoma of the oesophagus is common. A risk prediction model was derived using modern machine learning methods that accurately predicts risk of early recurrence using postoperative pathology. Machine learning may help

Background & Aims: Most patients with esophageal adenocarcinoma (EAC) present with de novo tumors. Although this could be due to inadequate screening strategies, the precise reason for this observation is not clear. We compared survival of patients with prevalent EAC with and without synchronous Barrett esophagus (BE) with intestinal metaplasia (IM) at the time of EAC diagnosis. Methods: Clinical data were studied using Cox proportional hazards regression to evaluate the effect of synchronous BE-IM on EAC survival independent of age, sex, TNM stage, and tumor location. We analyzed data from a cohort of patients with EAC from the Mayo Clinic (n=411; 203 with BE and IM) and a multicenter cohort from the United Kingdom (n=1417; 638 with BE and IM). Results: In the Mayo cohort, BE with IM had a reduced risk of death compared to patients without BE and IM (hazard ratio [HR] 0.44; 95% CI, 0.34–0.57; PConclusion: Two types of EAC can be characterized based on the presence or absence of BE. These findings could increase our understanding the etiology of EAC, and be used in management and prognosis of patients.