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siNRAS and siDGKH knockdown in NRAS mutant melanoma cells

GSE312301 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2026/05/26 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 48 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
48 samples: 12 conditions, mostly with about 4 replicates eachGroups 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)
NRAS mutations occur in 10-30% of cutaneous melanomas and are associated with high tumor mutational burden. Mutant NRAS signaling drives aberrant cell growth and proliferation, in part, through the activation of the RAF-MEK-ERK1/2 kinase pathway; however, targeted therapies to this pathway have shown limited effectiveness in melanoma patients.
Read the full summary ↓
The role of other signaling pathways is poorly characterized. We show that one isoform of diacylglycerol kinase (DGKη), a lipid signaling regulator, is highly expressed in NRAS mutant patient samples. Knockdown of DGKη in NRAS mutant cell lines resulted in significant growth inhibition in vitro, due to decreased cell cycle progression. DGKη was regulated by RAS inhibitors and MEK inhibitors. Transcriptomic data showed downregulation of the estrogen response late signature including decreased CCND1 expression. These data suggest that DGKη mediates cell cycle progression in NRAS mutant melanoma cells and represents a potential therapeutic strategy for these patients.
This dataset
Open GSE312301 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 GSE312301_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 PRJNA1372813 and SRA study SRP650860. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly with about 4 replicates each
SKMEL173_siCntrl ×4 SKMEL173_siDGKH_05 ×4 SKMEL173_siDGKH_06 ×4 SKMEL173_siNRAS_05 ×4 SKMEL173_siNRAS_06 ×4 SKMEL173_Untreated ×4 SKMEL30_siCntrl ×4 SKMEL30_siDGKH_05 ×4 +4 more

Supports a between-group comparison across 48 samples.

How we read this: 12 replicated groups read from 48 sample titles; they account for 48 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

+ 8 more — browse all 48 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.