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Comprehensive transcriptomic characterization of two melanoma cell lines with acquired dual resistance to BRAF and MEK inhibitors: toward understanding and reversing therapy resistance

GSE302561 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/08/16 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × WM9_control biol vs 3 × WM9_resistant biol vs 3 × HS294T_control biol vs 3 × HS294T_resistant biolGroups 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
Comprehensive transcriptomic characterization of two melanoma cell lines with acquired dual resistance to BRAF and MEK inhibitorsScientific reports · 2026
Summary (written by the submitters)
To elucidate the molecular mechanisms underlying acquired resistance to dual BRAF and MEK inhibition, we performed transcriptomic profiling of two melanoma cell lines, Hs294T and WM9, rendered resistant to the combination of vemurafenib and cobimetinib.RNA-seq analysis revealed distinct resistance-associated gene expression signatures in each model, with only partial overlap, suggesting divergent adaptive responses to the same therapeutic pressure.
Read the full summary ↓
Both resistant cell lines exhibited strong upregulation of extracellular matrix compo-nents, epithelial-mesenchymal transition (EMT) markers, and chemokine signaling genes, along with repression of melanocytic lineage markers. Inference of transcription factor and kinase activity uncovered line-specific regulatory rewiring, including activa-tion of MYOCD, SMAD3, and TP53, and suppression of immune regulators such as RFX5 and RFXANK. Network-based analysis identified key resistance hubs - IL6, FN1, COL1A1, and EGFR. WM9 cells showed broader transcriptional reprogramming and prominent engagement of inflammatory and immune-related pathways. At the same time, Hs294T resistance was marked by a more restricted program focused on stromal remodeling and impaired antigen presentation.
Published in
Comprehensive transcriptomic characterization of two melanoma cell lines with acquired dual resistance to BRAF and MEK inhibitors
Kujawa T, Simiczyjew A, Kot M et al. · Scientific reports 2026 · PMID 41872271 · doi:10.1038/s41598-026-45586-y
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 GSE302561_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 PRJNA1291195 and SRA study SRP601348. Searching any of these in the dataset finder brings you back here.

Study design
3 × WM9_control biol vs 3 × WM9_resistant biol vs 3 × HS294T_control biol vs 3 × HS294T_resistant biol

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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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.