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Epigenetic regulation of melanoma phenotypic plasticity and therapeutic resistance [ChIP-seq]

GSE316110 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 39 samples Submitted 2026/04/29 Platform GPL24676
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 39 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
MelanomaThis series is part of our curated briefing on it.
Samples
39 samples: 12 conditions, mostly in triplicateGroups 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)
Melanoma progression and treatment failure are driven in part by the ability of tumor cells to undergo dynamic phenotypic state transitions. Here, we identify the SAGA chromatin-modifying complex as a critical epigenetic regulator that constrains melanoma phenotypic plasticity and preserves therapeutic vulnerability. Loss of SAGA-dependent epigenetic regulation disrupts lineage-associated chromatin states, leading to widespread transcriptional reprogramming and enhanced cellular adaptability.
Read the full summary ↓
As a consequence, SAGA-deficient melanoma cells exhibit increased phenotypic heterogeneity and acquire resistance to targeted therapy. Mechanistically, SAGA loss impairs histone acetylation–dependent control of gene expression programs linked to differentiation and stress responses, enabling the emergence of drug-tolerant cell states. Together, these findings establish SAGA as an epigenetic safeguard against melanoma cell-state plasticity and reveal how disruption of chromatin regulatory complexes promotes therapeutic resistance.
This dataset
Open GSE316110 in finder → Find more human ChIP / ATAC / CUT&Tag datasets → Melanoma 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 GSE316110_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 PRJNA1400616 and SRA study SRP661097. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly in triplicate
A375_Ctrl_DMSO_H3K9ac ×3 A375_Ctrl_Vemu_H3K9ac ×3 A375_TADA2Bsg1_DMSO_H3K9ac ×3 A375_TADA2Bsg1_Vemu_H3K9ac ×3 A375_TADA2Bsg2_DMSO_H3K9ac ×3 A375_TADA2Bsg2_Vemu_H3K9ac ×3 A375_GCN5PCAFsg_DMSO_H3K9ac ×3 A375_GCN5PCAFsg_Vemu_H3K9ac ×3 +7 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 39 sample titles; they account for 36 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
More Melanoma datasets

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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.