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The landscape of gain and loss of function mutations in melanoma [RNA-seq]

GSE297199 Homo sapiens (human) RNA-seq (gene expression) 242 samples Submitted 2026/05/17 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 242 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
242 samples: 16 conditions, mostly in duplicateGroups 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 is a common and aggressive cancer, with a rising incidence in most developed countries. Major discoveries in melanoma biology have been rapidly translated, allowing cures for some late-stage patients. Despite these advances, incomplete knowledge of genes and pathways that are gained or lost during melanogenesis prohibits cures for many patients.
Read the full summary ↓
To identify gain of function and loss of function drivers of melanoma, we established a multi-omics cohort of melanoma patient-derived xenografts (melPDomiX). By linking mutations with gene and protein expression, we characterize gain or loss of function of specific melanoma drivers in treatment refractory tumor models. We use multi-omics integration and structural-context representation to distinguish gain from loss of function variants, revealing new candidate melanoma genes and targets. This study provides a comprehensive resource of tumor models with the genetic, molecular and structural features of gain and loss of function melanoma drivers, allowing future development of better therapeutics for this devastating and heterogenous malignancy.
This dataset
Open GSE297199 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 GSE297199_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 PRJNA1262988. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
16 conditions, mostly in duplicate
WM ×164 WM4237 ×4 WM4299 ×4 WM4420 ×4 WM4011 ×2 WM4039 ×2 WM4070 ×2 WM4071 ×2 +50 more

Supports a between-group comparison across 200 samples.

How we read this: 16 replicated groups read from 242 sample titles; they account for 200 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

+ 202 more — browse all 242 samples with per-sample file links →

More Melanoma datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

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.