GEO series

Single-Cell RNA Sequencing Reveals Shenbai Granule Retards Colorectal Tumorigenesis by Modulating Cholesterol-Induced Ccl22+ DCs and Tregs Crosstalk

GSE277268 Mus musculus (mouse) Single-cell RNA-seq 15 samples Submitted 2025/07/30 Platform GPL19057Platform GPL18573

At a glance

Single-cell RNA-seq · mouse · 15 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)
Topic: Colorectal cancerThis series is part of our curated briefing on it.
Samples: 15 samples: 15 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: Single-cell RNA sequencing reveals Shen-Bai-Jie-Du decoction retards colorectal tumorigenesis by regulating the TMEM131-TNF signaling pathway-mediated differentiation of immunosuppressive dendritic cellsActa pharmaceutica Sinica. B · 2025

Summary (written by the submitters)

Colorectal tumorigenesis generally follows a progressive sequence from adenoma to adenocarcinoma, accompanied by dynamic changes in the tumor microenvironment (TME). Randomized controlled trials have confirmed that Shenbai Granule (SBG), a traditional Chinese medicine formula, is safe and effective for the prevention of recurrent colorectal adenoma.

Read the full summary ↓

However, the effects and mechanisms of SBG on colorectal tumorigenesis and the TME remain unclear. To investigate this, single-cell RNA sequencing (scRNA-seq) was conducted to reveal the dynamic evolution of the TME. Primary cells were isolated for in vitro validation experiments. The findings demonstrated that SBG reduces both the number and volume of tumors. There was a marked accumulation of Ccl22+ dendritic cells (DCs) and an enhanced interaction between Ccl22+ DCs and CD4+ regulatory T cells (Tregs), which were reversed by the treatment of SBG and its active compound, berberine. Combined treatment with cholesterol and lipopolysaccharide induced characteristic gene expression in Ccl22+ DCs, which may represent a type of “exhausted DCs”. Intraperitoneal injection of the Ccl22+ DCs after SBG treatment eliminated its therapeutic effects. These findings highlight critical crosstalk between Ccl22+ DCs and CD4+ Tregs in colorectal cancer. The multi-component properties of natural products may restore TME homeostasis and offer novel cancer therapy.

Published in

Single-cell RNA sequencing reveals Shen-Bai-Jie-Du decoction retards colorectal tumorigenesis by regulating the TMEM131-TNF signaling pathway-mediated differentiation of immunosuppressive dendritic cells

Tao Y, Ma Y, Gu L et al. · Acta pharmaceutica Sinica. B 2025 · PMID 40698132 · doi:10.1016/j.apsb.2025.05.013

This dataset

Open GSE277268 in finder → Find more RNA-seq datasets → Colorectal 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 GSE277268_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 PRJNA1161624 and SRA study SRP532928. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40698132) ↗

Study design

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

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 15 sample titles: 15 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

GSM8517384 sample1-before, scRNAseq
GSM8517385 sample1-after, scRNAseq
GSM8517386 sample2-before, scRNAseq
GSM8517387 sample2-after, scRNAseq
GSM8517388 sample3-before, scRNAseq
GSM8517389 sample3-after, scRNAseq
GSM8517390 NC1, scRNAseq
GSM8517391 NC2, scRNAseq
GSM8517392 NC3, scRNAseq
GSM8517393 M1, scRNAseq
GSM8517394 M2, scRNAseq
GSM8517395 M3, scRNAseq
GSM8517396 D1, scRNAseq
GSM8517397 D2, scRNAseq
GSM8517398 D3, scRNAseq

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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.