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Epigenetic heterogeneity and state-specific transcriptional programs determine differential drug response in osteosarcoma [ATAC-seq]

GSE270502 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 87 samples Submitted 2025/09/29 Platform GPL20301
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 87 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Topic
OsteosarcomaThis series is part of our curated briefing on it.
Samples
87 samples: 43 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.
Summary (written by the submitters)
Osteosarcoma is a genomically complex tumor with structural rearrangements, aneuploidy, and chromosomal alterations, resulting in significant intertumoral heterogeneity. This complexity hampers the identification of key oncogenic pathways and subtypes. We hypothesized that chromatin accessibility could uncover molecular features to clarify their transcriptional programs, suggesting new therapies.
Read the full summary ↓
Using ATAC-seq, H3K27ac profiling, and single-cell multiome analysis, we identified two distinct cellular states in osteosarcoma driven by unique transcription factor networks linked to normal bone development. These subtypes can be detected in patient samples via a specific gene expression signature with prognostic value.
This dataset
Open GSE270502 in finder → Find more human ChIP / ATAC / CUT&Tag datasets → Osteosarcoma 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 GSE270502_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1126816 and SRA study SRP515377. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
43 conditions, mostly in duplicate
Patient derived Xenograph_PDX ×3 OsteosarcomaPDX-CL_OS052 ×2 OsteosarcomaPDX-CL_OS525 ×2 OsteosarcomaPDX-CL_OS152 ×2 OsteosarcomaPDX-CL_OS186 ×2 OsteosarcomaPDX-CL_OS526 ×2 OsteosarcomaPDX-CL_OS384 ×2 OsteosarcomaPDX-CL_OS457 ×2 +35 more

Supports a between-group comparison across 87 samples.

How we read this: 43 replicated groups read from 87 sample titles; they account for 87 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

+ 47 more — browse all 87 samples with per-sample file links →

More Osteosarcoma datasets

Search all human ChIP / ATAC / CUT&Tag 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.