GEO series

Epigenetic regulation of melanoma phenotypic plasticity and therapeutic resistance

GSE315960 Homo sapiens (human) RNA-seq (gene expression) 27 samples Submitted 2026/04/29 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 27 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: 27 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.

Summary (written by the submitters)

Melanoma progression and treatment failure are driven in part by the ability of tumor cells to undergo dynamic phenotypic state transitions. Here, we identify the SAGA chromatin-modifying complex as a critical epigenetic regulator that constrains melanoma phenotypic plasticity and preserves therapeutic vulnerability. Loss of SAGA-dependent epigenetic regulation disrupts lineage-associated chromatin states, leading to widespread transcriptional reprogramming and enhanced cellular adaptability.

Read the full summary ↓

As a consequence, SAGA-deficient melanoma cells exhibit increased phenotypic heterogeneity and acquire resistance to targeted therapy. Mechanistically, SAGA loss impairs histone acetylation–dependent control of gene expression programs linked to differentiation and stress responses, enabling the emergence of drug-tolerant cell states. Together, these findings establish SAGA as an epigenetic safeguard against melanoma cell-state plasticity and reveal how disruption of chromatin regulatory complexes promotes therapeutic resistance.

This dataset

Open GSE315960 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 GSE315960_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 PRJNA1400009 and SRA study SRP660704. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

9 conditions, mostly in triplicate

A375_GFPsg_DMSO ×3 A375_GFPsg_Tram ×3 A375_GFPsg_Vemu ×3 A375_TADA2Bsg1_DMSO ×3 A375_TADA2Bsg1_Tram ×3 A375_TADA2Bsg1_Vemu ×3 A375_TADA2Bsg2_DMSO ×3 A375_TADA2Bsg2_Tram ×3 +1 more

Supports a between-group comparison across 27 samples.

How we read this: 9 replicated groups read from 27 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

GSM9441737 A375_GFPsg_DMSO_rep1 A375_GFPsg_DMSO
GSM9441738 A375_GFPsg_DMSO_rep2 A375_GFPsg_DMSO
GSM9441739 A375_GFPsg_DMSO_rep3 A375_GFPsg_DMSO
GSM9441740 A375_GFPsg_Tram_rep1 A375_GFPsg_Tram
GSM9441741 A375_GFPsg_Tram_rep2 A375_GFPsg_Tram
GSM9441742 A375_GFPsg_Tram_rep3 A375_GFPsg_Tram
GSM9441743 A375_GFPsg_Vemu_rep1 A375_GFPsg_Vemu
GSM9441744 A375_GFPsg_Vemu_rep2 A375_GFPsg_Vemu
GSM9441745 A375_GFPsg_Vemu_rep3 A375_GFPsg_Vemu
GSM9441746 A375_TADA2Bsg1_DMSO_rep1 A375_TADA2Bsg1_DMSO
GSM9441747 A375_TADA2Bsg1_DMSO_rep2 A375_TADA2Bsg1_DMSO
GSM9441748 A375_TADA2Bsg1_DMSO_rep3 A375_TADA2Bsg1_DMSO
GSM9441749 A375_TADA2Bsg1_Tram_rep1 A375_TADA2Bsg1_Tram
GSM9441750 A375_TADA2Bsg1_Tram_rep2 A375_TADA2Bsg1_Tram
GSM9441751 A375_TADA2Bsg1_Tram_rep3 A375_TADA2Bsg1_Tram
GSM9441752 A375_TADA2Bsg1_Vemu_rep1 A375_TADA2Bsg1_Vemu
GSM9441753 A375_TADA2Bsg1_Vemu_rep2 A375_TADA2Bsg1_Vemu
GSM9441754 A375_TADA2Bsg1_Vemu_rep3 A375_TADA2Bsg1_Vemu
GSM9441755 A375_TADA2Bsg2_DMSO_rep1 A375_TADA2Bsg2_DMSO
GSM9441756 A375_TADA2Bsg2_DMSO_rep2 A375_TADA2Bsg2_DMSO
GSM9441757 A375_TADA2Bsg2_DMSO_rep3 A375_TADA2Bsg2_DMSO
GSM9441758 A375_TADA2Bsg2_Tram_rep1 A375_TADA2Bsg2_Tram
GSM9441759 A375_TADA2Bsg2_Tram_rep2 A375_TADA2Bsg2_Tram
GSM9441760 A375_TADA2Bsg2_Tram_rep3 A375_TADA2Bsg2_Tram
GSM9441761 A375_TADA2Bsg2_Vemu_rep1 A375_TADA2Bsg2_Vemu
GSM9441762 A375_TADA2Bsg2_Vemu_rep2 A375_TADA2Bsg2_Vemu
GSM9441763 A375_TADA2Bsg2_Vemu_rep3 A375_TADA2Bsg2_Vemu

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