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Differential Activity of MAPK signalling Defines Fibroblast Subtypes in Pancreatic Cancer (RNA-Seq)

GSE246457 Mus musculus (mouse) Single-cell RNA-seq 37 samples Submitted 2024/12/05 Platform GPL19057Platform GPL18573Platform GPL30173
At a glance

Single-cell RNA-seq · mouse · 37 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
Mus musculus (mouse)
Samples
37 samples: 32 distinct titles, 3 of them repeatedGroups 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
Differential activity of MAPK signalling defines fibroblast subtypes in pancreatic cancerNature communications · 2024
Summary (written by the submitters)
Fibroblast heterogeneity is increasingly recognised across cancer conditions. Given their important contribution to disease progression, mapping fibroblasts’ heterogeneity is critical to devise effective anti-cancer therapies. Cancer-associated fibroblasts (CAFs) represent the most abundant cell population in pancreatic ductal adenocarcinoma (PDAC).
Read the full summary ↓
Whether CAF phenotypes are differently specified by PDAC cell lineages remains to be elucidated. Here, we reveal an important role for the MAPK signalling pathway in defining PDAC CAF phenotypes. We show that epithelial MAPK activity promotes the myofibroblastic differentiation of CAFs by sustaining the expression and secretion of TGF-β1. We integrate single-cell profiling of post-perturbation transcriptional responses from mouse models with cellular and spatial profiles of human tissues to define a MAPKhigh CAF (mapCAF) phenotype. We show that this phenotype associates with basal-like tumour cells and reduced frequency of CD8+ T cells. In addition to elevated MAPK activity, this mapCAF phenotype is characterized by TGF-b signalling, hypoxia responsive signatures, and immunoregulatory gene programs. Furthermore, the mapCAF signature is enriched in myofibroblastic CAFs from various cancer conditions and correlates with reduced response to immune checkpoint inhibition in melanoma Altogether, our data expand our knowledge on CAF phenotype heterogeneity and reveal a potential strategy for targeting of myofibroblastic CAFs in vivo.
Published in
Differential activity of MAPK signalling defines fibroblast subtypes in pancreatic cancer
Veghini L, Pasini D, Fang R et al. · Nature communications 2024 · PMID 39627211 · doi:10.1038/s41467-024-54975-8
This dataset
Open GSE246457 in finder → Find more 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 GSE246457_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 PRJNA1032962 and SRA study SRP468892. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39627211) ↗
Study design
32 distinct titles, 3 of them repeated
PSC_TGFB_A ×4 PSC_NT_A ×2 PSC_NT_B ×2

How we read this: Read from 37 sample titles: 32 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
Datasets on a similar topic

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