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Loss of the USP22 deubiquitylase confers resistance to chemotherapy in small cell lung cancer [CUT&Tag]

GSE296258 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 23 samples Submitted 2025/05/08 Platform GPL30173
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 23 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)
Topic
Small cell lung cancerThis series is part of our curated briefing on it.
Samples
23 samples: 21 distinct titles, 1 of them repeatedGroups 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)
Small cell lung cancer (SCLC) responds exceptionally well to cytotoxic chemotherapy. However, relapse with the emergence of chemoresistant disease is rapid and accompanied by poor treatment outcomes. To understand the genetic basis of chemoresistance in SCLC, we applied in vivo CRISPR deletion screening to patient-derived xenograft (PDX) models.
Read the full summary ↓
Top screen hits included genes encoding components of the transcriptional co-activator SAGA (Spt-Ada-Gcn5 acetyltransferase) complex. We demonstrate that deletion of the SAGA deubiquitylase USP22 conferred cisplatin/etoposide resistance in two chemosensitive PDX models, and that restoring expression in a PDX model harboring homozygous truncating mutation of USP22 re-sensitized tumors to chemotherapy. USP22 loss increased gene body histone H2A-K119 monoubiquitylation in genes encoding key regulators of neuronal differentiation, and suppressed neural and neuroendocrine gene expression including targets of ASCL1. Chemoresistance following USP22 loss reflected attenuated DNA damage-driven phosphorylation events and apoptosis, in conjunction with increased expression of glycolysis and hypoxia-related genes. Glycolysis program upregulation may reflect a targetable vulnerability, as inhibition of GLUT1 re-sensitized USP22-null tumors to chemotherapy.
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 GSE296258_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 PRJNA1258284. Searching any of these in the dataset finder brings you back here.

Study design
21 distinct titles, 1 of them repeated
FHSC14_IgG ×3

How we read this: Read from 23 sample titles: 21 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
More Small cell lung cancer datasets

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