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Comparative gene expression profiling of parental A375 melanoma cells and a panel of spontaneously vemurafenib-resistant derivative cell lines

GSE285131 Homo sapiens (human) RNA-seq (gene expression) 33 samples Submitted 2024/12/26 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 33 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
33 samples: 11 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
A critical role of FAK signaling in Rac1-driven melanoma cell resistance to MAPK pathway inhibitionOncogene · 2025
Summary (written by the submitters)
The use of selective BRAF inhibitors (BRAFi) has produced remarkable outcomes for patients with advanced cutaneous melanoma harboring a BRAFV600E mutation. Unfortunately, the majority of patients eventually develop drug-resistant disease through a variety of mechanisms. We previously described the creation of a panel of spontaneously BRAFi/MEKi-resistant A375 melanoma cells that displayed multiple different resistance mechanisms arising within the same parental cell population.
Read the full summary ↓
These resistance mechanisms include (i) rearrangements in the BRAF gene resulting in truncation of the N-terminal regulatory domain or tandem duplication of the BRAF kinase domain, (ii) loss of Ras-GAP NF1, and (iii) a slower arising form of drug resistance associated with a more spread cell morphology and increased phospho-MEK S298, a characteristic of cells with increased Rac1 signaling. We provide here comprehensive gene expression profiling for this panel of cell lines. Rac1 mutation, particularly the P29S variant, is common in melanoma patients, where it is associated with BRAFi/MEKi resistance and worse clinical outcomes. Here we delineate mechanisms of Rac1-driven MAPKi-resistance and identify strategies to inhibit the growth of this class of cutaneous melanomas. We find that Rac1-driven melanomas manifest pleiotropic resistance mechanisms including (i) reduced dependence on BRAF/MEK, (ii) activation of alternative MAPK pathways utilizing Jun kinase and p38 MAP kinase, and (iii) a partial reliance on YAP/TAZ signaling. Importantly, although Rac1-driven melanoma cells display reduced dependence on BRAF/MEK, they are not completely ERK-independent. Moreover, the presence of activated Rac1 appears to create a dependency on focal adhesion kinase (FAK) signaling in undifferentiated melanoma cells. As a result, we find that, despite the pleiotropic mechanisms of Rac1-driven MAPKi resistance, combined inhibition of MEK and FAK with avutometinib plus defactinib is a promising approach for suppressing the growth of Rac1-driven cells. Thus, the avutometinib plus defactinib combination, which is currently being investigated for brain metastatic cutaneous melanoma may also have utility against Rac1-driven MAPKi-resistance in heavily pre-treated, advanced disease.
Published in
A critical role of FAK signaling in Rac1-driven melanoma cell resistance to MAPK pathway inhibition
Riordan JD, Nathanson TA, Varzavand A et al. · Oncogene 2025 · PMID 41109929 · doi:10.1038/s41388-025-03603-w
This dataset
Open GSE285131 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 GSE285131_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: 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 PRJNA1201221 and SRA study SRP553053. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41109929) ↗
Study design
11 conditions, mostly in triplicate
A375 parental cells, vehicle-treated, ×3 A375 parental cells, 3µM vem-treated 24h, ×3 A375 parental cells, 3µM vem-treated 96h, ×3 A375 spontaneously vem-resistant line EC1.1, … ×3 A375 spontaneously vem-resistant line EC2.1, … ×3 A375 spontaneously vem-resistant line EC7.1, … ×3 A375 spontaneously vem-resistant line ECS2.2.… ×3 A375 spontaneously vem-resistant line ECS2.2.… ×3 +3 more

Supports a between-group comparison across 33 samples.

How we read this: 11 replicated groups read from 33 sample titles; they account for 33 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.