← BioTransfer GEO Dataset Finder
GEO series

Driver Gene and Potential Biomarker Investigation of Desmoid-type Fibromatosis Through RNA-seq Analysis

GSE266101 Homo sapiens (human) RNA-seq (gene expression) 43 samples Submitted 2025/09/09 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 43 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
43 samples: 29 × Desmoid type fibromatosis vs 14 × ScaGroups 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
Comprehensive RNA Sequencing Analysis Identifies Network Hub Genes and Biomarkers Differentiating Desmoid-type Fibromatosis From Reactive FibrosisLaboratory investigation; a journal of technical methods and pathology · 2025
Summary (written by the submitters)
Desmoid type fibromatosis(DTF), a locally aggressive fibromatosis, lacks clear pathogenesis. RNA-seq analysis of 29 DTF cases identified hub genes like ZNF536, TWIST2, and SHOX2, indicating involvement in fibroblastic proliferation. These genes were validated in other fibrotic diseases. Immunohistochemistry revealed TWIST2 as a promising diagnostic biomarker, emphasizing its potential clinical utility.
Published in
Comprehensive RNA Sequencing Analysis Identifies Network Hub Genes and Biomarkers Differentiating Desmoid-type Fibromatosis From Reactive Fibrosis
Jeong E, Ku J, Na JM et al. · Laboratory investigation; a journal of technical methods and pathology 2025 · PMID 39617099 · doi:10.1016/j.labinv.2024.102204
This dataset
Open GSE266101 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 GSE266101_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 PRJNA1103343 and SRA study SRP504318. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39617099) ↗
Study design
29 × Desmoid type fibromatosis vs 14 × Sca

Supports a between-group comparison across 43 samples.

How we read this: 2 replicated groups read from 43 sample titles; they account for 43 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

+ 3 more — browse all 43 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.