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Rewiring the fusion oncoprotein EWSR1::FLI1 in Ewing scarcoma with bivalent small molecules [RNA-Seq]

GSE290895 Homo sapiens (human) RNA-seq (gene expression) 54 samples Submitted 2025/03/17 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 54 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)
Samples
54 samples: 18 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.
Summary (written by the submitters)
Dysregulated transcription is a defining hallmark of cancer. Recently, novel chemically induced proximity approaches have enabled the rewiring of transcriptional machinery to drive expression of pro-apoptotic genes using bivalent small molecules. In this work, we demonstrate that this strategy is amenable to relocalizing DNA bound transcriptional machinery, such as fusion transcription factors that commonly drive pediatric malignancies.
Read the full summary ↓
Targeting fusion transcription factors, such as EWSR1::FLI1 in Ewing sarcoma, with these bivalent compounds may open new therapeutic avenues. Here, we develop a small molecule, EB-TCIP, that recruits FKBP12F36V-tagged EWSR1::FLI1 to DNA sites bound by the transcriptional regulator BCL6, leading to rapid chromatin remodeling and expression of BCL6 target genes. This proof-of-concept study demonstrates that DNA binding proteins with pioneering transcription factor activity, such as EWSR1::FLI1, can be relocalized on chromatin to induce expression of repressed genes. Insights herein will guide the development of future bivalent molecules that rewire DNA binding transcriptional machinery.
This dataset
Open GSE290895 in finder → Find more human 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 GSE290895_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 PRJNA1230725 and SRA study SRP567438. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
18 conditions, mostly in triplicate
EWS502 cells with Chr2-2 KO control - Day 4 ×3 EWS502 cells with LacZ KO control - Day 4 ×3 EWS502 cells with BCL6 KO guide 1 - Day 4 ×3 EWS502 cells with BCL6 KO guide 2 - Day 4 ×3 EWS502 FKBP(F36V)-EWS/FLI1 cells treated with… ×3 EWS502 FKBP(F36V)-EWS/FLI1 cells treated with… ×3 EWS502 FKBP(F36V)-EWS/FLI1 cells treated with… ×3 EWS502 FKBP(F36V)-EWS/FLI1 cells treated with… ×3 +10 more

Supports a case/control comparison: 18 samples read as cases, 12 as controls.

How we read this: 18 replicated groups read from 54 sample titles; they account for 54 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

+ 14 more — browse all 54 samples with per-sample file links →

Datasets on a similar topic

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.