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Molecular targets of colorectal cancer transformation revealed by single-cell sequencing

GSE264607 Mus musculus (mouse) Single-cell RNA-seq 14 samples Submitted 2025/12/04 Platform GPL19057

At a glance

Single-cell RNA-seq · mouse · 14 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Mus musculus (mouse)
Samples: 14 samples: 14 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: KLK1 as an Epithelial-Specific Brake Inhibits Colorectal Tumorigenesis by Suppressing B1R-Mediated Fibroblast Phenotypic TransitionAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025

Summary (written by the submitters)

Ulcerative colitis (UC) is associated with a significant risk of colorectal cancer transformation, which is considered one of its major complications. Prolonged chronic inflammation in the colon mucosa can lead to carcinogenesis due to various factors including dysregulation of cell proliferation and apoptosis, abnormal activation of the immune system, as well as DNA damage and repair abnormalities.

Read the full summary ↓

Furthermore, the release of inflammatory mediators may directly or indirectly promote the formation and growth of cancer cells. The AOM/DSS mouse model is widely utilized to mimic the process of human colorectal cancer development, including chronic inflammation, carcinogenesis, and tumor progression. The model involves the administration of azoxymethane (AOM), a carcinogenic substance that induces DNA mutations and damage in colonic epithelial cells, leading to the initiation of colorectal cancer. Subsequently, dextran sulfate sodium (DSS), a chemical compound that induces intestinal inflammation, is administered through drinking water. The mice are subjected to cycles of DSS treatment interspersed with recovery periods, during which colitis-associated colorectal tumorigenesis occurs. The assessment typically involves monitoring of colon length, tumor formation, and histopathological examination. The mechanisms underlying colorectal cancer transformation in UC remain incompletely understood. However, research suggests that controlling inflammation, implementing standardized treatment protocols, and regular surveillance through colonoscopy and follow-up are crucial for both prevention and early detection of carcinogenesis. Therefore, further investigations into the mechanisms of colorectal cancer transformation in UC and the development of novel prevention and treatment strategies are essential for improving the prognosis and quality of life of UC patients.

Published in

KLK1 as an Epithelial-Specific Brake Inhibits Colorectal Tumorigenesis by Suppressing B1R-Mediated Fibroblast Phenotypic Transition

Zhou L, Wang M, Liu S et al. · Advanced science (Weinheim, Baden-Wurttemberg, Germany) 2025 · PMID 40859429 · doi:10.1002/advs.202507063

This dataset

Open GSE264607 in finder → Find more mouse 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 GSE264607_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 PRJNA1103232 and SRA study SRP504794. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40859429) ↗

Study design

14 samples, each with a distinct title — no replicated groups

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

How we read this: Read from 14 sample titles: 14 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

GSM8223831 Normal 1,scRNAseq
GSM8223832 Normal 2,scRNAseq
GSM8223833 Normal 3,scRNAseq
GSM8223834 Normal 4,scRNAseq
GSM8223835 Normal 5,scRNAseq
GSM8223836 colitis 1,scRNA-seq
GSM8223837 colitis 2,scRNA-seq
GSM8223838 colitis 3,scRNA-seq
GSM8223839 colitis 4,scRNA-seq
GSM8223840 colitis associate cancer(CAC1),scRNA-seq
GSM8223841 colitis associate cancer(CAC2),scRNA-seq
GSM8223842 colitis associate cancer(CAC3),scRNA-seq
GSM8223843 colitis associate cancer(CAC4),scRNA-seq
GSM8223844 colitis associate cancer(CAC5),scRNA-seq

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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.