The Salivary Microbiome and Predicted Metabolite Production are Associated with Progression from Barrett's Esophagus to Esophageal Adenocarcinoma.

Esophageal adenocarcinoma (EAC) is rising in incidence and associated with poor survival, and established risk factors do not explain this trend. Microbiome alterations have been associated with progression from the precursor Barrett's esophagus (BE) to EAC, yet the oral microbiome, tightly linked to the esophageal microbiome and easier to sample, has not been extensively studied in this context. We aimed to assess the relationship between the salivary microbiome and neoplastic progression in BE to identify microbiome-related factors that may drive EAC development. We collected clinical data and oral health and hygiene history and characterized the salivary microbiome from 250 patients with and without BE, including 78 with advanced neoplasia (high grade dysplasia or early adenocarcinoma). We assessed differential relative abundance of taxa by 16S rRNA gene sequencing and associations between microbiome composition and clinical features and used microbiome metabolic modeling to predict metabolite production. We found significant shifts and increased dysbiosis associated with progression to advanced neoplasia, with these associations occurring independent of tooth loss, and the largest shifts were with the genus Streptococcus. Microbiome metabolic models predicted significant shifts in the metabolic capacities of the salivary microbiome in patients with advanced neoplasia, including increases in L-lactic acid and decreases in butyric acid and L-tryptophan production. Our results suggest both a mechanistic and predictive role for the oral microbiome in esophageal adenocarcinoma. Further work is warranted to identify the biological significance of these alterations, to validate metabolic shifts, and to determine whether they represent viable therapeutic targets for prevention of progression in BE.

The gut microbiome, short chain fatty acids, and related metabolites in cystic fibrosis patients with and without colonic adenomas.

BACKGROUND: Adults with cystic fibrosis (CF) are at increased risk for colon cancer. CF patients have reductions in intestinal bacteria that produce short chain fatty acids (SCFAs), although it is unclear whether this corresponds with intestinal SCFA levels and the presence of colonic neoplasia. The aim of this study was to compare gut microbiome and SCFA composition in patients with and without CF, and to assess associations with colonic adenomas. METHODS: Colonic aspirates were obtained from adults with and without CF undergoing colon cancer screening or surveillance colonoscopy. Microbiome characterization was performed by 16S rRNA V3-V4 sequencing. Targeted profiling of SCFAs and related metabolites was performed by LC-MS. RESULTS: 42 patients (21 CF, 21 control) were enrolled. CF patients had significantly reduced alpha diversity and decreased relative abundance of many SCFA-producing taxa. There were no significant differences in SCFA levels in CF patients, although there were reduced levels of branched chain fatty acids (BCFAs) and related metabolites. CF patients with adenomas, but not controls with adenomas, had significantly increased relative abundance of Bacteroides fragilis. CF microbiome composition was significantly associated with isovalerate concentration and the presence of adenomas. CONCLUSIONS: CF patients have marked disturbances in the gut microbiome, and CF patients with adenomas had notably increased relative abundance of B. fragilis, a pathogen known to promote colon cancer. Reductions in BCFAs but not SCFAs were found in CF. Further studies are warranted to evaluate the role of B. fragilis as well the biological significance of reductions in BCFAs in CF.

Use of the Electronic Health Record to Target Patients for Non-endoscopic Barrett's Esophagus Screening.

BACKGROUND: Clinical prediction models targeting patients for Barrett's esophagus (BE) screening include data obtained by interview, questionnaire, and body measurements. A tool based on electronic health records (EHR) data could reduce cost and enhance usability, particularly if combined with non-endoscopic BE screening methods. AIMS: To determine whether EHR-based data can identify BE patients. METHODS: We performed a retrospective review of patients ages 50-75 who underwent a first-time esophagogastroduodenoscopy. Data extracted from the EHR included demographics and BE risk factors. Endoscopy and pathology reports were reviewed for histologically confirmed BE. Screening criteria modified from clinical guidelines were assessed for association with BE. Subsequently, a score based on multivariate logistic regression was developed and assessed for its ability to identify BE subjects. RESULTS: A total of 2931 patients were assessed, and BE was found in 1.9%. Subjects who met screening criteria were more likely to have BE (3.3% vs. 1.1%, p = 0.001), and the criteria predicted BE with an AUROC of 0.65 (95% CI 0.59-0.71). A score based on logistic regression modeling included gastroesophageal reflux disease, sex, body mass index, and ever-smoker status and identified BE subjects with an AUROC of 0.71 (95% CI 0.64-0.77). Both prediction tools produced higher AUROCs in women than in men. CONCLUSIONS: EHR-based BE risk prediction tools identify BE patients with fair accuracy. While these tools may improve the efficiency of patient targeting for BE screening in the primary care setting, challenges remain to identify high-risk patients for non-invasive BE screening in clinical practice.