← BioTransfer GEO Dataset Finder
GEO series

Chromosomal instability shapes the tumor microenvironment of esophageal adenocarcinoma via a cGAS–chemokine–myeloid axis [RNA-seq]

GSE315942 Homo sapiens (human) Single-nucleus RNA-seq 24 samples Submitted 2026/01/16 Platform GPL24676
At a glance

Single-nucleus RNA-seq · human · 24 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)
Samples
24 samples: 8 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 GSE315942 in finder → Find more human RNA-seq datasets →
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 GSE315942_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 PRJNA1399996 and SRA study SRP660689. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41811963) ↗
Study design
8 conditions, mostly in triplicate
OE33 Cas9 control, DMSO, ×3 OE33 Cas9 control, 500nM Reversine, ×3 OE33 cGAS KO, DMSO, ×3 OE33 cGAS KO, 500nM Reversine, ×3 SK-GT-4 Cas9 control, DMSO, ×3 SK-GT-4 Cas9 control, 500nM Reversine, ×3 SK-GT-4 cGAS KO, DMSO, ×3 SK-GT-4 cGAS KO, 500nM Reversine, ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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
Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.