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Transcriptional and chromatin accessibility profiling of melanoma cells during BRAF inhibitor–induced drug tolerance

GSE324655 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 31 samples Submitted 2026/03/19 Platform GPL24676Platform GPL21290
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 31 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
31 samples: 9 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.
Paper
Heterogeneous, population-level drug-tolerant persisters exhibit ion-channel remodeling and ferroptosis susceptibilitybioRxiv : the preprint server for biology · 2026
Summary (written by the submitters)
Drug tolerance can emerge rapidly in melanoma following treatment with BRAF inhibitors. This transition has been associated with transcriptional and chromatin state remodeling. To investigate the molecular features of this process, we profiled melanoma cells before and during exposure to a BRAF inhibitor. We generated single-cell RNA sequencing (scRNA-seq), bulk RNA sequencing (bulk RNA-seq), and bulk ATAC-seq datasets from SKMEL5 melanoma cells.
Read the full summary ↓
Cells were analyzed under untreated conditions and following treatment with 8 µM BRAF inhibitor (PLX4720) for defined time periods corresponding to drug-tolerant states. Bulk RNA-seq was performed on multiple SKMEL5 subclones (SC01, SC07, SC10) to characterize transcriptional responses across biological replicates. scRNA-seq and ATAC-seq were used to profile transcriptional heterogeneity and chromatin accessibility changes associated with drug tolerance.
Published in
Heterogeneous, population-level drug-tolerant persisters exhibit ion-channel remodeling and ferroptosis susceptibility
Hayford CE, Baleami B, Stauffer PE et al. · bioRxiv : the preprint server for biology 2026 · PMID 42039444 · doi:10.1101/2022.02.03.479045
This dataset
Open GSE324655 in finder → Find more human RNA-seq 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 GSE324655_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 PRJNA1431156. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42039444) ↗
Study design
9 conditions, mostly in triplicate
SKMEL5 SC01 day 0 bulk RNA-seq, ×3 SKMEL5 SC01 day 3 bulk RNA-seq, ×3 SKMEL5 SC01 day 8 bulk RNA-seq, ×3 SKMEL5 SC07 day 0 bulk RNA-seq, ×3 SKMEL5 SC07 day 3 bulk RNA-seq, ×3 SKMEL5 SC07 day 8 bulk RNA-seq, ×3 SKMEL5 SC10 day 0 bulk RNA-seq, ×3 SKMEL5 SC10 day 3 bulk RNA-seq, ×3 +5 more

Supports a between-group comparison across 27 samples.

How we read this: 9 replicated groups read from 31 sample titles; they account for 27 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
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