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Resistance to BRAF inhibitors drives melanoma sensitivity to Chk1 inhibition

GSE286402 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2026/01/30 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 18 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)
Topic
MelanomaThis series is part of our curated briefing on it.
Samples
18 samples
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)
BRAF inhibitor-resistant melanomas (BRAFiR) acquire (epi)genetic and functional alterations that enable them to evade alternative treatments. Identifying these alterations is critical to advancing treatment strategies. Here, we explored the effect of Chk1 inhibition (Chk1i) on BRAFiR cells, revealing higher sensitivity compared to treatment-naïve cells both in vitro and in vivo.
Read the full summary ↓
Using FUCCI-labeling and time-lapse microscopy, we show that S phase progression is required for Chk1i-induced cytotoxicity in BRAFiR cells, but not in treatment-naïve cells. Replication stress markers, including reduced BrdU incorporation and increased phospho-RPA and γH2AX, were exclusive to BRAFiR cells exposed to Chk1i. Untreated BRAFiR cells exhibited upregulated DNA replication genes, reduced ongoing replication fibers and increased origin firing, suggesting intrinsic replication changes. MAPK pathway reactivation in treatment-naïve cells mimicked BRAFiR traits, increasing sensitivity to Chk1i. These findings indicate that Chk1i exploits elevated replication stress in BRAFiR, highlighting its therapeutic potential in overcoming MAPK inhibitor resistance in melanoma.
This dataset
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.

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 GSE286402_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1209068 and SRA study SRP556532. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 18 more — browse all 18 samples with per-sample file links →

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