Endoscopic eradication therapy for Barrett's esophagus-related neoplasia: a final 10-year report from the UK National HALO Radiofrequency Ablation Registry.

BACKGROUND AND AIMS: Long-term durability data for effectiveness of radiofrequency ablation (RFA) to prevent esophageal adenocarcinoma in patients with dysplastic Barrett's esophagus (BE) are lacking. METHODS: We prospectively collected data from 2535 patients with BE (mean length, 5.2 cm; range, 1-20) and neoplasia (20% low-grade dysplasia, 54% high-grade dysplasia, 26% intramucosal carcinoma) who underwent RFA therapy across 28 UK hospitals. We assessed rates of invasive cancer and performed detailed analyses of 1175 patients to assess clearance rates of dysplasia (CR-D) and intestinal metaplasia (CR-IM) within 2 years of starting RFA therapy. We assessed relapses and rates of return to CR-D (CR-D2) and CR-IM (CR-IM2) after further therapy. CR-D and CR-IM were confirmed by an absence of dysplasia and intestinal metaplasia on biopsy samples taken at 2 consecutive endoscopies. RESULTS: Ten years after starting treatment, the Kaplan-Meier (KM) cancer rate was 4.1% with a crude incidence rate of .52 per 100 patient-years. CR-D and CR-IM after 2 years of therapy were 88% and 62.6%, respectively. KM relapse rates were 5.9% from CR-D and 18.7% from CR-IM at 8 years, with most occurring in the first 2 years. Both were successfully retreated with rates of CR-D2 of 63.4% and CR-IM2 of 70.0% 2 years after retreatment. EMR before RFA increased the likelihood of rescue EMR from 17.2% to 41.7% but did not affect the rate of CR-D, whereas rescue EMR after RFA commenced reduced CR-D from 91.4% to 79.7% (χ2P < .001). CONCLUSIONS: RFA treatment is effective and durable to prevent esophageal adenocarcinoma. Most treatment relapses occur early and can be successfully retreated.

Accuracy of clinical staging for T2N0 oesophageal cancer: systematic review and meta-analysis.

Oesophageal cancer is the sixth commonest cause of overall cancer mortality. Clinical staging utilizes multiple imaging modalities to guide treatment and prognostication. T2N0 oesophageal cancer is a treatment threshold for neoadjuvant therapy. Data on accuracy of current clinical staging tests for this disease subgroup are conflicting. We performed a meta-analysis of all primary studies comparing clinical staging accuracy using multiple imaging modalities (index test) to histopathological staging following oesophagectomy (reference standard) in T2N0 oesophageal cancer. Patients that underwent neoadjuvant therapy were excluded. Electronic databases (MEDLINE, Embase, Cochrane Library) were searched up to September 2019. The primary outcome was diagnostic accuracy of combined T&N clinical staging. Publication date, first recruitment date, number of centers, sample size and geographical location main histological subtype were evaluated as potential sources of heterogeneity. The search strategy identified 1,199 studies. Twenty studies containing 5,213 patients met the inclusion criteria. Combined T&N staging accuracy was 19% (95% CI, 15-24); T staging accuracy was 29% (95% CI, 24-35); percentage of patients with T downstaging was 41% (95% CI, 33-50); percentage of patients with T upstaging was 28% (95% CI, 24-32) and percentage of patients with N upstaging was 34% (95% CI, 30-39). Significant sources of heterogeneity included the number of centers, sample size and study region. T2N0 oesophageal cancer staging remains inaccurate. A significant proportion of patients were downstaged (could have received endotherapy) or upstaged (should have received neoadjuvant chemotherapy). These findings were largely unchanged over the past two decades highlighting an urgent need for more accurate staging tests for this subgroup of patients.

Using saliva epigenetic data to develop and validate a multivariable predictor of esophageal cancer status.

Background: Salivary epigenetic biomarkers may detect esophageal cancer. Methods: A total of 256 saliva samples from esophageal adenocarcinoma patients and matched volunteers were analyzed with Illumina EPIC methylation arrays. Three datasets were created, using 64% for discovery, 16% for testing and 20% for validation. Modules of gene-based methylation probes were created using weighted gene coexpression network analysis. Module significance to disease and gene importance to module were determined and a random forest classifier generated using best-scoring gene-related epigenetic probes. A cost-sensitive wrapper algorithm maximized cancer diagnosis. Results: Using age, sex and seven probes, esophageal adenocarcinoma was detected with area under the curve of 0.72 in discovery, 0.73 in testing and 0.75 in validation datasets. Cancer sensitivity was 88% with specificity of 31%. Conclusion: We have demonstrated a potentially clinically viable classifier of esophageal cancer based on saliva methylation.

Development and validation of a multivariable risk factor questionnaire to detect oesophageal cancer in 2-week wait patients.

INTRODUCTION: Oesophageal cancer is associated with poor health outcomes. Upper GI (UGI) endoscopy is the gold standard for diagnosis but is associated with patient discomfort and low yield for cancer. We used a machine learning approach to create a model which predicted oesophageal cancer based on questionnaire responses. METHODS: We used data from 2 separate prospective cross-sectional studies: the Saliva to Predict rIsk of disease using Transcriptomics and epigenetics (SPIT) study and predicting RIsk of diSease using detailed Questionnaires (RISQ) study. We recruited patients from National Health Service (NHS) suspected cancer pathways as well as patients with known cancer. We identified patient characteristics and questionnaire responses which were most associated with the development of oesophageal cancer. Using the SPIT dataset, we trained seven different machine learning models, selecting the best area under the receiver operator curve (AUC) to create our final model. We further applied a cost function to maximise cancer detection. We then independently validated the model using the RISQ dataset. RESULTS: 807 patients were included in model training and testing, split in a 70:30 ratio. 294 patients were included in model validation. The best model during training was regularised logistic regression using 17 features (median AUC: 0.81, interquartile range (IQR): 0.69-0.85). For testing and validation datasets, the model achieved an AUC of 0.71 (95% CI: 0.61-0.81) and 0.92 (95% CI: 0.88-0.96) respectively. At a set cut off, our model achieved a sensitivity of 97.6% and specificity of 59.1%. We additionally piloted the model in 12 patients with gastric cancer; 9/12 (75%) of patients were correctly classified. CONCLUSIONS: We have developed and validated a risk stratification tool using a questionnaire approach. This could aid prioritising patients at high risk of having oesophageal cancer for endoscopy. Our tool could help address endoscopic backlogs caused by the COVID-19 pandemic.

Novel epigenetic network biomarkers for early detection of esophageal cancer.

BACKGROUND: Early detection of esophageal cancer is critical to improve survival. Whilst studies have identified biomarkers, their interpretation and validity is often confounded by cell-type heterogeneity. RESULTS: Here we applied systems-epigenomic and cell-type deconvolution algorithms to a discovery set encompassing RNA-Seq and DNA methylation data from esophageal adenocarcinoma (EAC) patients and matched normal-adjacent tissue, in order to identify robust biomarkers, free from the confounding effect posed by cell-type heterogeneity. We identify 12 gene-modules that are epigenetically deregulated in EAC, and are able to validate all 12 modules in 4 independent EAC cohorts. We demonstrate that the epigenetic deregulation is present in the epithelial compartment of EAC-tissue. Using single-cell RNA-Seq data we show that one of these modules, a proto-cadherin module centered around CTNND2, is inactivated in Barrett's Esophagus, a precursor lesion to EAC. By measuring DNA methylation in saliva from EAC cases and controls, we identify a chemokine module centered around CCL20, whose methylation patterns in saliva correlate with EAC status. CONCLUSIONS: Given our observations that a CCL20 chemokine network is overactivated in EAC tissue and saliva from EAC patients, and that in independent studies CCL20 has been found to be overactivated in EAC tissue infected with the bacterium F. nucleatum, a bacterium that normally inhabits the oral cavity, our results highlight the possibility of using DNAm measurements in saliva as a proxy for changes occurring in the esophageal epithelium. Both the CTNND2/CCL20 modules represent novel promising network biomarkers for EAC that merit further investigation.

Challenges in screening for latent tuberculosis in inflammatory bowel disease prior to biologic treatment: a UK cohort study.

OBJECTIVE: The aim of this study was to determine the occurrence of latent tuberculosis infections (LTBI) and active TB in a cohort of patients with inflammatory bowel disease (IBD) treated with biologics. We also examined the effects of immunosuppressive drugs on indeterminate interferon-gamma release assays (IGRA) in LTBI screening. DESIGN: Retrospective study of patients treated with biologics between March 2007 and November 2015. SETTING: St Mark's Hospital, North West London, UK. PATIENTS: 732 patients with IBD who were screened for LTBI using either tuberculin skin test or IGRA before starting a biologic treatment. METHODS: Retrospective case note review of all patients with IBD who were screened for LTBI prior to initiating biologics. Patients who developed active TB were identified from the London TB register. RESULTS: Of 732 patients with IBD, 31 (4.2%) were diagnosed with and treated for LTBI with no significant side effects. Six of 596 patients (1.0%) who received biologic treatment developed active TB. There was a higher proportion of indeterminate IGRA in the immunosuppressive medication group compared with the non-immunosuppressive group (33% (59/181) compared with 9% (6/66), p<0.001). The combination of steroids and thiopurines had the highest proportion of indeterminate IGRA (64%, 16/25). High and low doses of steroids were equally likely to result in an indeterminate IGRA result (67% (8/12) and 57% (4/7), respectively). CONCLUSIONS: This study highlights the challenges of LTBI screening prior to commencing biologic therapy and demonstrates the risk of TB in patients who have been screened and who are receiving prolonged and continuing doses of antitumour necrosis factor.