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Intestinal Epithelial C/EBPβ Deficiency Impairs Colitis-Associated Tumorigenesis by Disrupting CXCL1 /CXCL2/CXCL5-CXCR2-Mediated Neutrophil Infiltration [RNA-seq ]

GSE264497 Mus musculus (mouse) RNA-seq (gene expression) 15 samples Submitted 2025/06/25 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 15 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
Mus musculus (mouse)
Samples
15 samples: 5 × colon, WT Control IEC vs 5 × colon, WT AOM/DSS IEC vs 5 × colon, CebpbΔ IEC AOM/DSSGroups 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
Intestinal epithelial C/EBPβ deficiency impairs colitis-associated tumorigenesis by disrupting CXCL1/CXCL2/CXCL5-CXCR2-mediated neutrophil infiltrationActa biochimica et biophysica Sinica · 2025
Summary (written by the submitters)
To investigate the function of intestinal-specific cebpb loss in the infiltration of neutrophils, we performed transcriptomic sequencing to compare global gene expression in the colon tissues from AOM/DSS mice models.
Published in
Intestinal epithelial C/EBPβ deficiency impairs colitis-associated tumorigenesis by disrupting CXCL1/CXCL2/CXCL5-CXCR2-mediated neutrophil infiltration
Li M, Wang X, Hu W et al. · Acta biochimica et biophysica Sinica 2025 · PMID 40922684 · doi:10.3724/abbs.2025119
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 GSE264497_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: 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 PRJNA1102849 and SRA study SRP503130. Searching any of these in the dataset finder brings you back here.

Study design
5 × colon, WT Control IEC vs 5 × colon, WT AOM/DSS IEC vs 5 × colon, CebpbΔ IEC AOM/DSS

Supports a between-group comparison across 15 samples.

How we read this: 3 replicated groups read from 15 sample titles; they account for 15 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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