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variant Polycomb Repressive complexes 1 (vPRC1s) in synovial sarcoma

GSE291441 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2025/03/17 Platform GPL11154
At a glance

RNA-seq (gene expression) · human · 16 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
16 samples: 8 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.
Paper
DNA demethylating agents suppress preclinical models of synovial sarcomaThe Journal of clinical investigation · 2025
Summary (written by the submitters)
Several variant Polycomb Repressive complexes 1 (vPRC1s) co-exist to robustly deposit mono ubiquitination on histone H2A (H2AK119ub1). Their interconnected roles and specific tasks across normal and disease cellular states remain unclear. In synovial sarcoma (SS), a soft tissue tumor driven by the oncogenic fusion protein, SS18::SSX, the SSX tail exhibits a high affinity to H2AK119ub1 marked genomic regions.
Read the full summary ↓
This mechanism is crucial to sequester the mSWI/SNF complex to PRC1 targets and results in their aberrant expression. We previously showed that PRC1.1 is responsible for H2AK119ub1 deposition in SS and is therefore required for SS18::SSX occupancy. Here, we investigated the role of PRC1 variants in synovial sarcoma.
Published in
DNA demethylating agents suppress preclinical models of synovial sarcoma
Hasegawa N, Benabdallah NS, Smith-Fry K et al. · The Journal of clinical investigation 2025 · PMID 40299558 · doi:10.1172/JCI190855
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 GSE291441_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 PRJNA1233601 and SRA study SRP568902. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly in duplicate
HSSY, Empty Vector, ×2 HSSY, sgPCGF1, ×2 HSSY, sgPCGF3, ×2 HSSY, sgSSX, ×2 SYOI, Empty Vector, ×2 SYOI, sgPCGF1, ×2 SYOI, sgPCGF3, ×2 SYOI, sgSSX, ×2

Supports a between-group comparison across 16 samples.

How we read this: 8 replicated groups read from 16 sample titles; they account for 16 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
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