GEO series

Genome-wide CRISPR screen identifies IRF1 and TFAP4 as transcriptional regulators of Galectin-9 in T cell acute lymphoblastic leukemia [ChIP-seq]

GSE275039 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 20 samples Submitted 2025/03/19 Platform GPL18573

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 20 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: Acute lymphoblastic leukemiaThis series is part of our curated briefing on it.
Samples: 20 samples: 20 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: Genome-wide CRISPR screen identifies IRF1 and TFAP4 as transcriptional regulators of Galectin-9 in T cell acute lymphoblastic leukemiaScience advances · 2025

Summary (written by the submitters)

Galectin-9 is overexpressed in a variety of cancers and associated with worse clinical outcome in some cancers. However, the regulators driving Galectin-9 expression are unknown. Here, we defined the transcriptional regulators and epigenetic circuitry of Galectin-9 in pediatric T cell acute lymphoblastic leukemia (T-ALL), as an example of a disease with strong Galectin-9 expression, in which higher expression was associated with lower overall survival.

Read the full summary ↓

By performing a genome-wide CRISPR screen, we identified the transcription factors IRF1 and TFAP4 as key regulators for Galectin-9 expression by binding its regulatory elements. While IRF1 was observed exclusively on the promoter, TFAP4 binding was detected at an enhancer solely in T-ALL cells associated with higher Galectin-9 levels. Together, our results show that IRF1 is responsible and indispensable for Galectin-9 expression and TFAP4 further fine-tunes its expression. Our approach, a flow-based genome-wide CRISPR screen complemented by transcription factor binding and enhancer mapping, creates innovative opportunities for understanding and manipulating epigenetic transcriptional regulation in cancer.

Published in

Genome-wide CRISPR screen identifies IRF1 and TFAP4 as transcriptional regulators of Galectin-9 in T cell acute lymphoblastic leukemia

Wiggers CRM, Yüzügüldü B, Tadros NG et al. · Science advances 2025 · PMID 40106574 · doi:10.1126/sciadv.ads8351

This dataset

Open GSE275039 in finder → Find more human ChIP / ATAC / CUT&Tag datasets → Acute lymphoblastic leukemia landscape →

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 GSE275039_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1149004 and SRA study SRP526908. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40106574) ↗

Study design

20 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 20 sample titles: 20 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

GSM8464614 CCRF-CEM, IRF1, ChIP
GSM8464615 CCRF-CEM, TFAP4, ChIP
GSM8464616 CCRF-CEM, WCE
GSM8464617 DND-41, IRF1, ChIP
GSM8464618 DND-41, TFAP4, ChIP
GSM8464619 DND-41, WCE
GSM8464620 HPB-ALL, IRF1, ChIP
GSM8464621 HPB-ALL, TFAP4, ChIP
GSM8464622 HPB-ALL, WCE
GSM8464623 Jurkat, IRF1, ChIP
GSM8464624 Jurkat, TFAP4, ChIP
GSM8464625 Jurkat, WCE
GSM8464626 KOPT-K1, IRF1, ChIP
GSM8464627 KOPT-K1, TFAP4, ChIP
GSM8464628 KOPT-K1, WCE
GSM8464629 Loucy, IRF1, ChIP
GSM8464630 Loucy, TFAP4, ChIP
GSM8464631 Loucy, WCE
GSM8464632 HPB-ALL, H3K27ac, ChIP
GSM8464633 HPB-ALL, WCE (for H3K27ac)

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GSE160298 The chromatin accessibility landscape of T-Cell Acute Lymphoblastic Leukemia 80 samples same disease briefing · shares lymphoblastic
GSE115656 Alternative splicing analysis of pediatric B-cell acute lymphoblastic leukemia compared to normal bone marrow derived pro-B cells 38 samples same disease briefing · shares lymphoblastic
GSE13425 Expression data from ALL patients included in the set used to construct a classification signature (COALL cohort) 190 samples same disease briefing
GSE154675 PHF6 Interacts with LMO2 During Normal Haematopoiesis and in Leukaemia and Regulates the Level of Gene Expression and Genome Integrity 41 samples same disease briefing
GSE18198 Expression profile of human T-ALL cell lines treated with DMSO or SAHM1 12 samples same disease briefing
GSE279033 Genome-wide CRISPR screen identifies Menin and SUZ12 as regulators of human developmental timing [CUT&RUN] 32 samples shares crispr, genome-wide, identifies, regulators

Search all human ChIP / ATAC / CUT&Tag 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.