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Clonal cell states link gastroesophageal junction tissues, metaplasia, and cancer [MAESTER]

GSE287855 Homo sapiens (human) Single-cell RNA-seq 40 samples Submitted 2025/01/27 Platform GPL21697
At a glance

Single-cell RNA-seq · human · 40 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
40 samples: 6 conditions, mostly in duplicateGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Clonal cell states link Barrett's esophagus and esophageal adenocarcinomabioRxiv : the preprint server for biology · 2023
Summary (written by the submitters)
Barrett's esophagus is a common type of metaplasia and a precursor of esophageal adenocarcinoma. However, the cell states and lineage connections underlying the origin, maintenance, and progression of Barrett’s esophagus have not been resolved in humans. Here, we performed single-cell lineage tracing and transcriptional profiling of patient cells isolated from metaplastic and healthy tissue.
Read the full summary ↓
Our analysis unexpectedly revealed that the squamous esophagus and gastric cardia contained cells belonging to common lineages that also included transitional basal progenitor cells; both esophageal and gastric tissues were also related to Barrett's esophagus. Barrett’s esophagus biopsies consisted of multiple clones, with lineages that contained all progenitor and differentiated cell types. In contrast, precancerous dysplastic lesions were initiated by the expansion of a single molecularly aberrant Barrett’s esophagus clone. Together, these findings provide a comprehensive view of the cell dynamics of Barrett's esophagus, linking cell states along the disease trajectory, from its origin to cancer.
Published in
Clonal cell states link Barrett's esophagus and esophageal adenocarcinoma
Gier RA, Hueros RAR, Rong J et al. · bioRxiv : the preprint server for biology 2023 · PMID 36747708 · doi:10.1101/2023.01.26.525564
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE287855_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1214857 and SRA study SRP559517. Searching any of these in the dataset finder brings you back here.

Study design
6 conditions, mostly in duplicate
a199 s ×7 a198 s ×5 a193 be ×2 a195 scj ×2 a196 scj ×2 a211 be ×2 a186 be S ×1 a187 be S ×1 +18 more

Supports a between-group comparison across 20 samples.

How we read this: 6 replicated groups read from 40 sample titles; they account for 20 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.