← BioTransfer GEO Dataset Finder
GEO series

Destabilization of the noncanonical PRC1.1 complex via USP7 inhibition induces neuronal differentiation in neuroblastoma [CHIP-Seq, CUT&RUN, PCGF1KO]

GSE315997 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 10 samples Submitted 2026/02/26 Platform GPL34284
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 10 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
10 samples: 10 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
Inhibition of USP7 Destabilizes the Noncanonical PRC1.1 Complex and Induces Neuroblastoma DifferentiationMolecular cancer research : MCR · 2026
Summary (written by the submitters)
Pediatric cancers are frequently driven by genomic alterations that result in impaired differentiation during tissue development. To identify protein complex-level dependencies required for differentiation in neuroblastoma, a pediatric cancer of the developing peripheral nervous system, we curated a list of protein complexes using the CORUM database and mined the Dependency Map (DepMap) using single sample gene set enrichment analysis.
Read the full summary ↓
This analysis identified the non-canonical PRC1.1 complex, which represses transcriptional activity through ubiquitination of histone 2A, lysine 119 (H2AK119Ub), as a selectively enriched dependency in neuroblastoma. Knockout of several PRC1.1 subunits reduced neuroblastoma growth, arrested the cell cycle, and induced a neuronal differentiation program. While no known direct inhibitors of PRC1.1 exist, co-dependency analysis of PRC1.1 subunits against all other genes in DepMap identified that the deubiquitinase USP7 strongly correlated with PRC1.1 dependency. Treatment with XL177A, a small molecule inhibitor of USP7, significantly reduced neuroblastoma growth in both cellular and animal models. Integrated RNA- and ChIP-sequencing showed that both PRC1.1 knockout and USP7 inhibition resulted in highly correlated transcriptional alterations and reduced H2AK119Ub deposition on chromatin, suggesting that USP7 inhibition reduced neuroblastoma growth through a PRC1.1-dependent mechanism. Mechanistically, global proteomics and ubiquitinomics revealed that USP7 inhibition disrupted non-canonical PRC1 complex assembly, resulting in destabilization of PRC1.1 and subsequent proteolysis. Our findings expand our understanding of the chromatin complexes required to maintain a de-differentiated state in neuroblastoma and suggest the therapeutic potential for USP7 inhibitors in the treatment of this disease.
Published in
Inhibition of USP7 Destabilizes the Noncanonical PRC1.1 Complex and Induces Neuroblastoma Differentiation
Cmarik EA, Wahi A, Chandekar SS et al. · Molecular cancer research : MCR 2026 · PMID 41855552 · doi:10.1158/1541-7786.MCR-25-1153
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 GSE315997_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1400085 and SRA study SRP660766. Searching any of these in the dataset finder brings you back here.

Study design
10 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 10 sample titles: 10 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
Datasets on a similar topic

Search all human ChIP / ATAC / CUT&Tag 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.