← BioTransfer GEO Dataset Finder
GEO series

SCD1-dependant activation of GSK3β-NRF2-SLC7A11 pathway regulates lipid metabolism and suppresses ferroptosis in KRAS/STK11/KEAP1 co-mutant lung adenocarcinoma

GSE262660 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2025/02/07 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 36 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
Lung cancerThis series is part of our curated briefing on it.
Samples
36 samples: 36 samples, each with a distinct title — no replicated groupsGroups 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
SCD1 Inhibition Blocks the AKT-NRF2-SLC7A11 Pathway to Induce Lipid Metabolism Remodeling and Ferroptosis Priming in Lung AdenocarcinomaCancer research · 2025
Summary (written by the submitters)
InactivatingSTK11/KEAP1 co-mutations are genomic drivers of primary resistance totherapies and worse outcome in KRAS-mutatedlung adenocarcinoma(LUAD), however the underlying mechanisms is still not understood.Here we provide a transcriptomic analysis of over 3800 “real-world” LUAD cases that concomitant loss of STK11 and KEAP1 in a KRAS-mutant tumorleads to significant upregulation of fatty acid metabolism, and redox signaling pathways with significantly high expression of ferroptosis evasion genes, SCD1 and SLC7A11.
Read the full summary ↓
Global transcriptomics and kinase arrays demonstrate the role SCD1 in regulating AKT/GSK3β/NRF2 signaling mediated modulation of SLC7A11 and GSH metabolism. Furthermore, in a lipidomic assay, SCD1 knockout led to regulation of SFA-MUFA levels that promoted ferroptosis. SCD1 inhibition reverses the resistance to ferroptosis induction promoted by STK11/KEAP1 loss inmouse models. These data provide evidence that SCD1 protects ferroptosis induction and therapeutic targeting of this pathway is a promising translational strategy in KRAS mutant LUADs with concomitant loss ofSTK11 and KEAP1.
Published in
SCD1 Inhibition Blocks the AKT-NRF2-SLC7A11 Pathway to Induce Lipid Metabolism Remodeling and Ferroptosis Priming in Lung Adenocarcinoma
Sen U, Coleman C, Gandhi N et al. · Cancer research 2025 · PMID 40198901 · doi:10.1158/0008-5472.CAN-24-2745
This dataset
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.

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 GSE262660_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1092743 and SRA study SRP498316. Searching any of these in the dataset finder brings you back here.

Study design
36 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 36 sample titles: 36 distinct titles with little repetition. 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
More Lung cancer 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.