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Gene expression analysis of organoid model of human esophageal squamous cell carcinomas (ESCCs)

GSE269447 Homo sapiens (human) RNA-seq (gene expression) 20 samples Submitted 2025/02/25 Platform GPL24676Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 20 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
Esophageal cancerThis series is part of our curated briefing on it.
Samples
20 samples: 20 samples, each with a distinct title — no replicated groupsGroups 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
An organoid library of human esophageal squamous cell carcinomas (ESCCs) uncovers the chemotherapy-resistant ESCC featuresCommunications biology · 2025
Summary (written by the submitters)
Esophageal squamous cell carcinoma (ESCC) is a serious cancer with a poor prognosis and a high recurrence rate after chemotherapy, which is a major clinical challenge. To elucidate the molecular basis of chemotherapy (chemo)-resistance and develop methods to effectively eliminate chemo-resistant tumor clones, we established a cancer organoid model from 24 ESCC patients of various stages, ages, and treatments.
Read the full summary ↓
These ESCCOs recapitulated most oncogenic mutations of primary ESCC tissues and had tumorigenic properties upon xenografting. Each organoid line differs in its responsiveness to 5-fluorouracil (5-FU) and cisplatin (CDDP), chemotherapeutic agents commonly used to treat ESCC patients, with 7 lines exhibiting potent chemo-resistance. Importantly, these chemo-resistant ESCCOs had enhanced expression of genes involved in antioxidant stress response pathways and increased chromatin accessibility of their genomic loci, compared to chemo-sensitive ESCCOs, and these genes became useful biomarkers that can stratify chemo-resistant ESCC in histopathological specimens.
Published in
An organoid library of human esophageal squamous cell carcinomas (ESCCs) uncovers the chemotherapy-resistant ESCC features
Nakagawa S, Sato T, Ohashi E et al. · Communications biology 2025 · PMID 40169778 · doi:10.1038/s42003-025-07869-4
This dataset
Open GSE269447 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 GSE269447_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1121932 and SRA study SRP512791. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40169778) ↗
Study design
20 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 15 samples read as cases, 5 as controls.

How we read this: Read from 20 sample titles: 20 distinct titles with little repetition. 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.