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Chromosomal instability shapes the tumor microenvironment of esophageal adenocarcinoma via a cGAS–chemokine–myeloid axis

GSE316127 Homo sapiens (human) Single-nucleus RNA-seq 30 samples Submitted 2026/01/16 Platform GPL24676
At a glance

Single-nucleus RNA-seq · human · 30 samples

What it is
Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue). 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)
Topic
Esophageal cancerThis series is part of our curated briefing on it.
Samples
30 samples: 10 conditions, mostly in triplicateGroups 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
Chromosomal instability shapes the tumor microenvironment of esophageal adenocarcinoma via a cGAS-chemokine-myeloid axisScience advances · 2026
Summary (written by the submitters)
Chromosomal instability (CIN), a pervasive feature of esophageal adenocarcinoma (EAC), drives tumor aggressiveness and metastasis. CIN stimulates the cGAS–STING pathway, typically linked to anti-tumor immunity. However, despite the high CIN burden in EAC, the cGAS–STING pathway remains largely intact. To address this paradox, we interrogated multiple esophageal cancer models, discovering myeloid-attracting chemokines – with CXCL8 as a prominent hit – as conserved CIN-driven targets in EAC.
Read the full summary ↓
Using multiplexed immunofluorescence microscopy, we quantified ongoing CIN in human EAC tumors by measuring cGAS-positive micronuclei, validated by whole-genome sequencing. Coupling in situ CIN detection with single-nucleus RNA sequencing and multiplex immunophenotyping of human EAC, we link CIN to tumor-intrinsic innate immune activation, CXCL8 expression, and myeloid cell-mediated immunosuppression. In EAC patients, CIN-high, myeloid-dominated tumors correlate with poor outcomes and aberrant cGAS–STING signaling. These insights explain the counterintuitive maintenance of cGAS–STING and highlight disruption of the CIN–cGAS–inflammation axis as a potential therapeutic strategy in EAC.
Published in
Chromosomal instability shapes the tumor microenvironment of esophageal adenocarcinoma via a cGAS-chemokine-myeloid axis
Beernaert B, Jady-Clark RL, Shah P et al. · Science advances 2026 · PMID 41811963 · doi:10.1126/sciadv.aeb1611
This dataset
Open GSE316127 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 GSE316127_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 PRJNA1401584 and SRA study SRP661396. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41811963) ↗
Study design
10 conditions, mostly in triplicate
CP-A, Cas9 control, ×3 CP-A, p53 KO (Clone 1), ×3 CP-A, p53 KO (Clone 1) + p16 KO, ×3 CP-A, p53 KO (Clone 1) + dnMCAK, ×3 CP-A, p53 KO (Clone 2), ×3 CP-A, p53 KO (Clone 2) + p16 KO, ×3 CP-A, p53 KO (Clone 2) + dnMCAK, ×3 CP-A, p53 KO (Clone 3), ×3 +2 more

Supports a between-group comparison across 30 samples.

How we read this: 10 replicated groups read from 30 sample titles; they account for 30 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

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