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RNA-sequence data of clinically never-metastatic primary small cell lung cancer cases and small cell lung cancer metastasis cases, FOXA2 knock-down and overexpression in cell lines

GSE281525 Homo sapiens (human) RNA-seq (gene expression) 61 samples Submitted 2025/04/13 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 61 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
Small cell lung cancerThis series is part of our curated briefing on it.
Samples
61 samples: 11 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.
Paper
FOXA2 promotes metastatic competence in small cell lung cancerNature communications · 2025
Summary (written by the submitters)
Small cell lung cancer (SCLC) is known for its high metastatic potential, with most patients demonstrating clinically evident metastases in multiple organs at diagnosis. The factors contributing to this exceptional metastatic capacity have not been defined. To bridge this gap, we compared gene expression in SCLC patient samples who never experienced metastasis or relapse throughout their clinical course, versus primary SCLC patient samples from more typical patients who had metastatic disease at diagnosis.
Read the full summary ↓
This analysis identified FOXA2 as a transcription factor strongly associated with SCLC metastasis.
Published in
FOXA2 promotes metastatic competence in small cell lung cancer
Kawasaki K, Salehi S, Zhan YA et al. · Nature communications 2025 · PMID 40419484 · doi:10.1038/s41467-025-60141-5
This dataset
Open GSE281525 in finder → Find more human RNA-seq datasets → Small cell lung cancer 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 GSE281525_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 PRJNA1184332 and SRA study SRP544319. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40419484) ↗
Study design
11 conditions, mostly in triplicate
Metastatsis, sample ×25 Never-met primary tumor, sample ×7 Met-associated primary tumor , sample ×5 H1836, control sample ×3 H1836, shFOXA2-1 sample ×3 H1836, shFOXA2-2 sample ×3 SHP77 control sample ×3 SHP77, shFOXA2-1 sample ×3 +3 more

Supports a case/control comparison: 37 samples read as cases, 9 as controls.

How we read this: 11 replicated groups read from 61 sample titles; they account for 61 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

+ 21 more — browse all 61 samples with per-sample file links →

More Small cell lung cancer datasets

Search all human RNA-seq datasets in GEO →

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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.