4.8 Article

Molecular characterization of Barrett's esophagus at single-cell resolution

Publisher

NATL ACAD SCIENCES
DOI: 10.1073/pnas.2113061118

Keywords

Barrett's esophagus; single-cell RNA and DNA analyses; single-base substitution 17 (SBS17a and SBS17b)

Funding

  1. European Research Council [67013]
  2. Netherlands Organization for Scientific Research (NWO-ZonMw) [114021012]

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Barrett's esophagus is categorized into different stages based on morphological appearance, which correlate with the risk of developing esophageal adenocarcinoma. Single-cell sequencing experiments revealed chromosomal instabilities in dysplastic BE cells, with stable cells predominantly found in nondysplastic BE biopsies. The datasets provide insight into the mutational landscape and gene expression patterns at different stages of BE development.
Barrett's esophagus (BE) is categorized, based on morphological appearance, into different stages, which correlate with the risk of developing esophageal adenocarcinoma. More advanced stages are more likely to acquire chromosomal instabilities, but stage specific markers remain elusive. Here, we performed single-cell DNA-sequencing experiments (scDNAseq) with fresh BE biopsies. Dysplastic BE cells frequently contained chromosomal instability (CIN) regions, and these CIN cells carried mutations corresponding to the COSMIC mutational signature SBS17, which were not present in biopsy-matched chromosomally stable (CS) cells or patient-matched nondiseased control cells. CS cells were predominantly found in nondysplastic BE biopsies. The single-base substitution (SBS) signatures of all CS BE cells analyzed were indistinguishable from those of non diseased esophageal or gastric cells. Single-cell RNA-sequencing (scRNAseq) experiments with BE biopsies identified two sets of marker genes which facilitate the distinction between columnar BE epithelium and nondysplastic/dysplastic stages. Moreover, histological validation confirmed a correlation between increased CLDN2 expression and the presence of dysplastic BE stages. Our scDNAseq and scRNAseq datasets, which are a useful resource for the community, provide insight into the mutational landscape and gene expression pattern at different stages of BE development.

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