← BioTransfer GEO Dataset Finder
GEO series

Transcriptomic profiling of co-cultured cancer-host cells identifies hypoxia as a driver of the skeletal muscle cell’s antiproliferative effect on cancer cells

GSE299422 Mus musculus (mouse) RNA-seq (gene expression) 28 samples Submitted 2026/02/06 Platform GPL34290
At a glance

RNA-seq (gene expression) · mouse · 28 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Mus musculus (mouse)
Samples
28 samples: 7 conditions, mostly in duplicateGroups 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
Transcriptomic profiling of co-cultured cancer-host cells identifies hypoxia as a driver of the skeletal muscle cell's anti-proliferative effect on cancer cellsOncogenesis · 2026
Summary (written by the submitters)
Cancer metastasis is the leading cause of cancer-related death. While organs such as the lung are hotspots for metastases, others -like skeletal muscle- remain rarely colonized, a phenomenon that remains poorly understood. In this study, we show that EO771 breast cancer cells proliferated robustly when co-cultured with MLg lung stromal cells, whereas their proliferation was restrained when maintained in direct contact with differentiated C2C12 skeletal muscle myotubes.
Read the full summary ↓
Notably, these effects were not cell-typespecific, as similar results were obtained with 4T1 breast cancer cells and Sol8 myotubes. After two days of co-culture, both cancer and host cells (MLg and C2C12) exhibited distinct niche-specific transcriptional remodeling. Strikingly, the poorly proliferative EO771 cells co-cultured with C2C12 myotubes acquired a hypoxia-associated gene-expression signature despite normoxic conditions (~20% O₂), showing that muscle cells reprogram cancer cells into a hypoxic, anti-proliferative state. Under hypoxic conditions, we confirmed that the depletion of oxygen allows C2C12 cells to nearly abolish EO771 proliferation. Neither exogenous lactate, culture acidosis, their combination, altered glucose levels, nor conditioned medium could reproduce the suppressive environment created by C2C12 myotubes. In contrast, MLg cells induced minimal transcriptional changes in EO771 cells and were themselves broadly reprogrammed by the cancer cells. Moreover, hypoxia enhanced EO771 proliferation in MLg co-cultures, emphasizing the permissive nature of the MLg environment. Collectively, these findings uncover a unique, paradoxical, muscleinduced pseudo-hypoxic program that restricts cancer cell proliferation. They also highlight the need for caution in targeting hypoxia signaling in anti-metastatic therapies, as such interventions could weaken skeletal muscle’s natural defense against tumor colonization.
Published in
Transcriptomic profiling of co-cultured cancer-host cells identifies hypoxia as a driver of the skeletal muscle cell's anti-proliferative effect on cancer cells
Aunan A, Claeyssen C, Abdelhalim M et al. · Oncogenesis 2026 · PMID 41654498 · doi:10.1038/s41389-026-00601-9
This dataset
Open GSE299422 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 GSE299422_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1274402 and SRA study SRP591031. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41654498) ↗
Study design
7 conditions, mostly in duplicate
R3C2C12P ×2 R6MLgP ×2 R3EO771P ×2 R5C2C12E ×2 R5EO771C ×2 R6MLgE ×2 R6EO771M ×2 R2C2C12P ×1 +13 more

Supports a between-group comparison across 14 samples.

How we read this: 7 replicated groups read from 28 sample titles; they account for 14 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
Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.