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Epigenetic heterogeneity and state-specific transcriptional programs determine differential drug response in osteosarcoma [Cut&Run]

GSE270503 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 56 samples Submitted 2025/09/29 Platform GPL18573
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 56 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
56 samples: 22 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.
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 GSE270503 in finder → Find more human datasets → Osteosarcoma landscape →
Download · which file do I need?

Direct links to NCBI, 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.

All supplementary files ↗
3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE270503_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

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 PRJNA1126764. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
22 conditions, mostly in duplicate
OS742_IgG ×5 OS742_H3K27Ac ×5 OS152_IgG ×3 OS152_H3K27Ac ×3 OS526_IgG ×3 OS526_H3K27Ac ×3 OS774_IgG ×3 OS833_H3K27Ac ×3 +14 more

Supports a between-group comparison across 56 samples.

How we read this: 22 replicated groups read from 56 sample titles; they account for 56 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

+ 16 more — browse all 56 samples with per-sample file links →

More Osteosarcoma datasets

Search all human 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.