GEO series

Macrophage-Induced Senescent Cancer-Associated Fibroblasts Promote SASP-Mediated Chemoresistance in Colorectal Cancer

GSE335811 Homo sapiens (human) Single-cell RNA-seq 12 samples Submitted 2026/07/01 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 12 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. 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)
Topic: Colorectal cancerThis series is part of our curated briefing on it.
Samples: 12 samples: 12 × scRNA-seq of primary colon tumor from patient SGroups 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.

Summary (written by the submitters)

Cancer-associated fibroblasts (CAFs) play a crucial role in the tumor microenvironment (TME) by influencing tumor progression and therapy resistance. Accumulating evidence suggests that CAFs undergo senescence, which can impact their effects on the TME. In this study, we integrated single-cell RNA sequencing (scRNA-seq), spatial transcriptomics, and multiple preclinical models to explore the mechanisms underlying CAF senescence and its impact on chemotherapy resistance in colorectal cancer (CRC).

Read the full summary ↓

First, we developed a machine learning-based prediction model, the Cellular Senescence Prediction Model (CSPM), to accurately identify senescent CAFs based on single-cell RNA sequencing data. We used publicly available CRC single-cell cohorts and in-house CRC single-cell data to demonstrate the reliability of the model. By combining in silico analysis and preclinical models, we demonstrated that senescent CAFs induced by IL1B-IL1R1 signaling mediated by macrophages secrete components of the Senescence-Associated Secretory Phenotype (SASP) that impair chemotherapy responsiveness in CRC, suggesting that stromal senescence could be a therapeutic target.

This dataset

Open GSE335811 in finder → Find more human 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 GSE335811_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 PRJNA1479646 and SRA study SRP710604. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

12 × scRNA-seq of primary colon tumor from patient S

Supports a between-group comparison across 12 samples.

How we read this: 1 replicated groups read from 12 sample titles; they account for 12 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

GSM9821494 scRNA-seq of primary colon tumor from patient S1 scRNA-seq of primary co…
GSM9821495 scRNA-seq of primary colon tumor from patient S2 scRNA-seq of primary co…
GSM9821496 scRNA-seq of primary colon tumor from patient S3 scRNA-seq of primary co…
GSM9821497 scRNA-seq of primary colon tumor from patient S4 scRNA-seq of primary co…
GSM9821498 scRNA-seq of primary colon tumor from patient S5 scRNA-seq of primary co…
GSM9821499 scRNA-seq of primary colon tumor from patient S6 scRNA-seq of primary co…
GSM9821500 scRNA-seq of primary colon tumor from patient S7 scRNA-seq of primary co…
GSM9821501 scRNA-seq of primary colon tumor from patient S8 scRNA-seq of primary co…
GSM9821502 scRNA-seq of primary colon tumor from patient S9 scRNA-seq of primary co…
GSM9821503 scRNA-seq of primary colon tumor from patient S10 scRNA-seq of primary co…
GSM9821504 scRNA-seq of primary colon tumor from patient S11 scRNA-seq of primary co…
GSM9821505 scRNA-seq of primary colon tumor from patient S12 scRNA-seq of primary co…

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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.