Dataset Information

Esophageal microbiome signature in patients with Barrett's esophagus and esophageal adenocarcinoma.

ABSTRACT: Preliminary studies suggested a possible correlation of microbiota with Barrett's esophagus (BE) and esophageal adenocarcinoma (EAC), where the need for tools to ameliorate its poor prognosis is mandatory. We explored the potential signature of esophageal microbiota and its predicted functional profile along the continuous spectrum from BE to EAC. We analyzed through 16S-based amplicon sequencing the mucosal microbiota and the microbiota-related functional predictions in 10 BE and 6 EAC patients compared with 10 controls, exploring also potential differences between the metaplastic mucosa (BEM) and the adjacent normal areas of BE patients (BEU). BEM and EAC showed a higher level of ? and ?-diversity. BEM evidenced a decrease of Streptococcus and an increase of Prevotella, Actinobacillus, Veillonella, and Leptotrichia. EAC displayed a striking reduction of Streptococcus, with an increase of Prevotella, Veillonella and Leptotrichia. LefSe analysis identified Leptotrichia as the main taxa distinguishing EAC. BEM showed a decreased ?-diversity compared with BEU and a reduction of Bacteroidetes, Prevotella and Fusobacterium. Functional predictions identified peculiar profiles for each group with a high potential for replication and repair in BEM; an upregulated energy, replication and signaling metabolisms, with the fatty-acids biosynthesis and nitrogen and D-alanine pathways down-regulated in EAC. Our pilot study identifies a unique microbial structure and function profile for BE and EAC, as well as for metaplastic and near-normal areas. It proposes a new concept for BE, which could be intended not only as the histological, but, also, as the microbial closest precursor of EAC. This requires further larger follow-up studies, but opens intriguing horizons towards innovative diagnostic and therapeutic options for EAC.

SUBMITTER: Lopetuso LR

PROVIDER: S-EPMC7199943 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Esophageal microbiome signature in patients with Barrett's esophagus and esophageal adenocarcinoma.

Lopetuso Loris Riccardo LR Severgnini Marco M Pecere Silvia S Ponziani Francesca Romana FR Boskoski Ivo I Larghi Alberto A Quaranta Gianluca G Masucci Luca L Ianiro Gianluca G Camboni Tania T Gasbarrini Antonio A Gasbarrini Antonio A Costamagna Guido G Consolandi Clarissa C Cammarota Giovanni G

PloS one 20200505 5

Preliminary studies suggested a possible correlation of microbiota with Barrett's esophagus (BE) and esophageal adenocarcinoma (EAC), where the need for tools to ameliorate its poor prognosis is mandatory. We explored the potential signature of esophageal microbiota and its predicted functional profile along the continuous spectrum from BE to EAC. We analyzed through 16S-based amplicon sequencing the mucosal microbiota and the microbiota-related functional predictions in 10 BE and 6 EAC patients ...[more]

PMID: 32369505

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Project description:BackgroundEsophageal adenocarcinoma (EAC) often presents at a late, incurable stage, and mortality has increased substantially, due to an increase in incidence of EAC arising out of Barrett's esophagus. When diagnosed early, however, the combination of surgery and adjuvant therapies is associated with high cure rates. Metabolomics provides a means for non- invasive screening of early tumor-associated perturbations in cellular metabolism.MethodsUrine samples from patients with esophageal carcinoma (n = 44), Barrett's esophagus (n = 31), and healthy controls (n = 75) were examined using (1)H-NMR spectroscopy. Targeted profiling of spectra using Chenomx software permitted quantification of 66 distinct metabolites. Unsupervised (principal component analysis) and supervised (orthogonal partial least-squares discriminant analysis OPLS-DA) multivariate pattern recognition techniques were applied to discriminate between samples using SIMCA-P(+) software. Model specificity was also confirmed through comparison with a pancreatic cancer cohort (n = 32).ResultsClear distinctions between esophageal cancer, Barrett's esophagus and healthy controls were noted when OPLS-DA was applied. Model validity was confirmed using two established methods of internal validation, cross-validation and response permutation. Sensitivity and specificity of the multivariate OPLS-DA models were summarized using a receiver operating characteristic curve analysis and revealed excellent predictive power (area under the curve = 0.9810 and 0.9627 for esophageal cancer and Barrett's esophagus, respectively). The metabolite expression profiles of esophageal cancer and pancreatic cancer were also clearly distinguishable with an area under the receiver operating characteristics curve (AUROC) = 0.8954.ConclusionsUrinary metabolomics identified discrete metabolic signatures that clearly distinguished both Barrett's esophagus and esophageal cancer from controls. The metabolite expression profile of esophageal cancer was also discrete from its precursor lesion, Barrett's esophagus. The cancer-specific nature of this profile was confirmed through comparison with pancreatic cancer. These preliminary results suggest that urinary metabolomics may have a future potential role in non-invasive screening in these conditions.

Dataset Information

Esophageal microbiome signature in patients with Barrett's esophagus and esophageal adenocarcinoma.

Publications

Esophageal microbiome signature in patients with Barrett's esophagus and esophageal adenocarcinoma.

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