← BioTransfer GEO Dataset Finder
GEO series

Molecular Subtypes of Human Skeletal Muscle in Cancer Cachexia

GSE254877 Homo sapiens (human) RNA-seq (gene expression) 84 samples Submitted 2025/07/17 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 84 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
Homo sapiens (human)
Samples
84 samples: 84 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
Molecular subtypes of human skeletal muscle in cancer cachexiaNature · 2025
Summary (written by the submitters)
Cancer-associated muscle wasting associates with poor clinical outcomes1, but its underlying biology is largely uncharted in humans2. Unbiased RNAome analysis (coding and non-coding RNAs) with unsupervised clustering using Integrative Non-negative Matrix Factorization (intNMF)3 provides an avenue to identify distinct molecular subtypes, here applied to muscle of patients with colorectal or pancreatic cancer.
Read the full summary ↓
Rectus abdominis biopsies from 84 patients was profiled using high-throughput next generation sequencing. Here we show that intNMF with stringent quality metrics of clustering identifies 2 highly coherent molecular subtypes within muscle of patients with cancer. Patients in Subtype 1 (vs Subtype 2) showed clinical manifestations of cachexia: high-grade weight loss, low muscle mass, atrophy of Type IIA and Type IIX muscle fibres and reduced survival. Based on differential expression between the subtypes, our results indicate biological processes that may contribute to cancer-associated loss of muscle mass and function, including altered post-transcriptional regulation, and perturbation of neuronal systems, cytokine storm/cellular immune response, extracellular matrix, and metabolic abnormalities spanning xenobiotic metabolism, hemostasis, signal transduction, embryonic/pluripotent stem cells, and amino acid metabolism. Differential expression between subtypes indicates involvement of multiple, intertwined higher-order gene regulatory networks, suggesting potential for interacting (hub)lncRNA-miRNA-mRNA interaction networks as targets for future research.
Published in
Molecular subtypes of human skeletal muscle in cancer cachexia
Bhatt BJ, Ghosh S, Mazurak V et al. · Nature 2025 · PMID 40931079 · doi:10.1038/s41586-025-09502-0
This dataset
Open GSE254877 in finder → Find more human 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 GSE254877_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 PRJNA1072128 and SRA study SRP487525. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40931079) ↗
Study design
84 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 84 sample titles: 84 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

+ 44 more — browse all 84 samples with per-sample file links →

Datasets on a similar topic

Search all human 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.