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Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Esophageal Squamous Cell Carcinoma

GSE203067 Homo sapiens (human) Single-cell RNA-seq 21 samples Submitted 2025/05/08 Platform GPL20795
At a glance

Single-cell RNA-seq · human · 21 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Topic
Esophageal cancerThis series is part of our curated briefing on it.
Samples
21 samples: 6 conditions, mostly with about 4 replicates eachGroups 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
Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Esophageal Squamous Cell CarcinomaAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023
Summary (written by the submitters)
We profiled the transcriptome of 85, 263 single cells from ESCC patients with lymph node metastasis (LNM) and clustered 7, 196 myeloid cells into 18 subclusters including nine for macrophage cells, one for neutrophils, two for monocytes, two for mast cells, one for tolerogenic dendritic cells, one for plasmacytoid dendritic cells and two for conventional dendritic cells.
Read the full summary ↓
In this study, we not only provides a high-resolution landscape of the tumor, immune and stromal compartments in metastatic lymph node, but also highlights metastatic-specific patterns comparing with primary tumor. These findings provide insights that may help to shape the tumor microenvironment and inform the development of new strategies against these pro-metastatic non-tumor components for inhibiting tumor growth and overcoming metastasis.
Published in
Single-Cell Transcriptomic Analysis of Primary and Metastatic Tumor Ecosystems in Esophageal Squamous Cell Carcinoma
Jia Y, Zhang B, Zhang C et al. · Advanced science (Weinheim, Baden-Wurttemberg, Germany) 2023 · PMID 36709495 · doi:10.1002/advs.202204565
This dataset
Open GSE203067 in finder → Find more human RNA-seq datasets → Esophageal cancer landscape →
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.

Series matrix ↓
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 GSE203067_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA838394 and SRA study SRP375308. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 36709495) ↗
Study design
6 conditions, mostly with about 4 replicates each
ESCC, L4 ×4 ESCC, N4 ×4 ESCC, T4 ×4 ESCC, L ×3 ESCC, N ×3 ESCC, T ×3

Supports a between-group comparison across 21 samples.

How we read this: 6 replicated groups read from 21 sample titles; they account for 21 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
More Esophageal cancer datasets

Search all human RNA-seq datasets in GEO →

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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.