← BioTransfer GEO Dataset Finder
GEO series

The Polycomb Protein EED Constrains the SCLC Neuroendocrine Phenotype and Drives Lung Cancer Histological Transformation [Bulk RNA-seq]

GSE293599 Mus musculus (mouse) RNA-seq (gene expression) 50 samples Submitted 2026/08/05 Platform GPL34290Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 50 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
Mus musculus (mouse)
Samples
50 samples: 19 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)
Lung cancer is comprised of distinct histological subtypes including lung adenocarcinoma (LUAD) and small cell lung cancer (SCLC). Although histological subtypes of lung cancer are often mutually exclusive, patients can present with combined LUAD and SCLC histology tumors. Moreover, LUADs can histologically transform to SCLC through lineage plasticity as a mechanism of resistance to targeted therapies, which most often occurs in EGFR-Mutant LUAD with concurrent RB1 and TP53 inactivation after treatment with EGFR inhibitors.
Read the full summary ↓
The mechanisms that promote LUAD to SCLC histological transformation are poorly understood. Expression of genes associated with PRC2 activity increase during LUAD to SCLC histological transformation, but it is unknown whether PRC2 is a causative driver of histological transformation in lung cancer. To study the role of the PRC2 complex in SCLC tumorigenesis, we used CRISPR-based somatic gene editing to make SCLC genetically-engineered mouse models (GEMMs) deficient for PRC2 through inactivation of EED; PRC2’s core scaffolding subunit. Strikingly, EED inactivation caused complete histological transformation from ASCL1-positive SCLC to LUAD through an intermediate NEUROD1-positive/NCAM-positive cell state. Mechanistically, SCLC to LUAD histological transformation is initiated when PRC2 inactivation de-represses bivalent genes marked by both H3K27me3 and K3K4me3 including RAS, PI3K, and MAPK pathway genes as well as NEUROD1. Lastly, we developed an EGFR-Mutant LUAD GEMM with concurrent RB1 and TP53 inactivation where EGFR inhibition can promote SCLC transformation and a metastatic phenotype; both of which are completely abrogated by EED inactivation. Together, these findings show that the PRC2 complex is required to drive ASCL1-positive neuroendocrine SCLC with its loss promoting the LUAD phenotype nominating PRC2 inhibition as a therapeutic strategy to block SCLC transformation.
This dataset
Open GSE293599 in finder → Find more mouse RNA-seq datasets →
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 GSE293599_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 PRJNA1245338 and SRA study SRP576105. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
19 conditions, mostly in duplicate
EED Mutant tumor # ×4 EED Mutant tumor #1260 ×3 EED-WT EGFR OFF tumor 1547 ×3 EED WT tumor # ×2 EED WT tumor #1267 ×2 1014 sgControl ×2 1014 Eed sg1 ×2 1014 Eed sg2 ×2 +19 more

Supports a case/control comparison: 26 samples read as cases, 6 as controls.

How we read this: 19 replicated groups read from 50 sample titles; they account for 42 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

+ 10 more — browse all 50 samples with per-sample file links →

Datasets on a similar topic

Search all mouse 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.