GEO series

Lactylation of LSD1 is an acquired epigenetic vulnerability of BRAFi/MEKi-resistant melanoma [RNA-seq]

GSE256122 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/02/13 Platform GPL20795

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: 9 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)

BRAFV600E mutant melanomas treated with BRAF inhibitor (Dabrafenib) and MEK inhibitor (Trametinib) almost invariably develop drug resistance (DTR). Restored glycolysis, frequently found in clinical targeted therapy-resistant melanoma biopsies, has been shown to elicit drug resistance. How resumed glycolysis controls the emergence of acquired resistance, especially via intrinsic mechanisms that circumvent the BRAF/MEK module, remains unknown.

Read the full summary ↓

Here, we identify lactylation of LSD1, induced by re-accumulated lactate in DTR melanoma cells, selectively drives survival via epigenetic reprogramming. Mechanistically, lactylation of LSD1 promotes its interaction with FosL1, thereby preventing its ubiquitination and degradation by E3 ligase tripartite-motif-containing protein 21 (TRIM21). In DTR melanoma cells, chromatin binding capacity of FosL1 was significantly strengthened due to reduced acetylation, which in turn increases selective chromatin enrichment of LSD1. We further demonstrate that lactylated LSD1 co-orchestrates gene transcription with FosL1 to repress ferroptosis in DTR cells via interfering with transferrin receptor protein 1 (TFRC)-mediated iron uptake. LSD1 inhibitor (LSD1i) activates ferroptosis, resulting in drastic DTR melanoma regression in mice. Importantly, LSD1i-induced immunogenic ferroptosis synergizes with immune checkpoint blockade (ICB) in vivo. Together, our results highlight a crucial role of metabolic rewiring-induced epigenetic reprogramming as a bypass resistance mechanism in DTR melanoma, which provides a therapeutically actionable strategy to overcome acquired resistance to targeted therapy.

This dataset

Open GSE256122 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 GSE256122_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 PRJNA1078297 and SRA study SRP490663. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

9 conditions, mostly in duplicate

P_DMSO ×2 P_DT ×2 R_DT ×2 P-CTL ×2 P-L ×2 R_CTL ×2 R_KDL ×2 R_KDF ×2 +1 more

Supports a between-group comparison across 18 samples.

How we read this: 9 replicated groups read from 18 sample titles; they account for 18 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

GSM8086090 P_DMSO1 P_DMSO
GSM8086091 P_DMSO2 P_DMSO
GSM8086092 P_DT1 P_DT
GSM8086093 P_DT2 P_DT
GSM8086096 R_DT1 R_DT
GSM8086097 R_DT2 R_DT
GSM8086098 P-CTL P-CTL
GSM8086099 P-CTL2 P-CTL
GSM8086100 P-L1 P-L
GSM8086101 P-L12 P-L
GSM8086102 R_CTL1 R_CTL
GSM8086103 R_CTL2 R_CTL
GSM8086104 R_KDL1 R_KDL
GSM8086105 R_KDL12 R_KDL
GSM8086106 R_KDF1 R_KDF
GSM8086107 R_KDF12 R_KDF
GSM8262786 R_DMSO1 R_DMSO
GSM8262787 R_DMSO2 R_DMSO

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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.