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PI3K and MAPK signaling nodes as divergent drivers of phenotypic plasticity in cancer-associated fibroblasts in colorectal cancer

GSE309233 Homo sapiens (human) Single-cell RNA-seq 12 samples Submitted 2026/02/12 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: 3 × CT5.3hTERT,DMSO,24h vs 3 × CT5.3hTERT,Everolimus,24h vs 3 × CT5.3hTERT,Omipalisib,24h vs 3 × CT5.3hTERT,Uprosertib,24hGroups 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
PI3K and MAPK Signaling Nodes Serve as Divergent Drivers of Phenotypic Plasticity in Cancer-Associated Fibroblasts in Colorectal CancerCancer research · 2026
Summary (written by the submitters)
Cancer-associated fibroblasts (CAFs) exhibit phenotypic heterogeneity with each functional state playing critical roles in tumor progression. Notably, subtypes like inflammatory CAF (iCAF), characterized by increased chemokine/cytokine secretion, and myofibroblast-like CAF (myCAF), characterized by enhanced extracellular matrix (ECM) deposition and increased actomyosin contractility, can undergo phenotypic switching in response to cues from the tumor microenvironment (TME) and/or therapeutic interventions.
Read the full summary ↓
However, the signaling pathways associated with their diverse phenotypes remain poorly understood. Through the analysis of single-cell RNA sequencing analysis of human colorectal cancer (CRC) we identified that the PI3K/mTOR and MAPK/ERK signaling pathways, among other pathways, are linked to the formation of myCAF and iCAF subtypes, respectively.In addition,we identified that PI3K/mTOR inhibition promotes the formation of iCAF through compensatory FGF-2 secretion and stimulation of the FGFR1-JAK2-STAT3 pathway; iCAF-derived chemokines/cytokines consequently enhance tumor spheroid growth and neutrophil infiltration.
Published in
PI3K and MAPK Signaling Nodes Serve as Divergent Drivers of Phenotypic Plasticity in Cancer-Associated Fibroblasts in Colorectal Cancer
Xia Z, De Vuyst F, Ernst S et al. · Cancer research 2026 · PMID 41817574 · doi:10.1158/0008-5472.CAN-25-0766
This dataset
Open GSE309233 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 GSE309233_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 PRJNA1334379 and SRA study SRP627278. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41817574) ↗
Study design
3 × CT5.3hTERT,DMSO,24h vs 3 × CT5.3hTERT,Everolimus,24h vs 3 × CT5.3hTERT,Omipalisib,24h vs 3 × CT5.3hTERT,Uprosertib,24h

Supports a between-group comparison across 12 samples.

How we read this: 4 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
More Colorectal cancer datasets

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