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A dual role for PSIP1/LEDGF in T-cell acute lymphoblastic leukemia [CUT&RUN]

GSE253137 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 12 samples Submitted 2024/10/20 Platform GPL21273Platform GPL20795
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 12 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
12 samples: 2 × CD2-iCre PSIP1 WT, H3K27me3, CUT&RUN, WT vs 2 × CD2-iCre PSIP1 WT, IgG, CUT&RUN, WT vs 2 × CD2-iCre PSIP1 KO, H3K27me3, CUT&RUN, KO vs 2 × CD2-iCre PSIP1 KO, IgG, CUT&RUN, KOGroups 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
A dual role for PSIP1/LEDGF in T cell acute lymphoblastic leukemiaScience advances · 2024
Summary (written by the submitters)
T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive hematological malignancy. Although intensified therapeutic protocols have improved the outcome of T-ALL patients, they coincide with severe short- and long-term side effects. In addition, no salvage therapeutic strategies are available for primary therapy-resistant or relapsed T-ALL, resulting in a dismal outcome for these patients.
Read the full summary ↓
It highlights the need to identify new targets in T-ALL biology that allow the development of less toxic targeted therapies. PSIP1, a histone mark reader, is a dependency factor in KMT2A-rearranged myeloid leukemia, but is dispensable for normal hematopoiesis, making it an attractive therapeutic target. Nonetheless, rare recurrent inactivating mutations and deletions of PSIP1, suggest that PSIP1 could act as a tumor suppressor in T-ALL. Here, we demonstrate that the loss of Psip1 accelerates T-ALL initiation in mice and we identified a correlation with reduced H3K27me3 binding. Contrastingly, loss of PSIP1 impaired cell proliferation in several human and murine T-ALL cell lines. In these cell lines, PSIP1 loss leads to a significant downregulation of COX20, an assembly factor of the cytochrome c oxidase in the mitochondria, and is associated with a reduction in mitochondrial respiration. Similarly to what was observed for PSIP1, loss of COX20 expression also leads to an impairment of proliferation in these T-ALL cell lines. These data corroborate that PSIP1 can exert a dual role in the context of T-ALL, either as a tumor suppressor gene during tumor initiation or as a dependency factor in tumor maintenance.
Published in
A dual role for PSIP1/LEDGF in T cell acute lymphoblastic leukemia
Demoen L, Matthijssens F, Reunes L et al. · Science advances 2024 · PMID 39485844 · doi:10.1126/sciadv.ado6765
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 GSE253137_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 PRJNA1064101 and SRA study SRP483396. Searching any of these in the dataset finder brings you back here.

Study design
2 × CD2-iCre PSIP1 WT, H3K27me3, CUT&RUN, WT vs 2 × CD2-iCre PSIP1 WT, IgG, CUT&RUN, WT vs 2 × CD2-iCre PSIP1 KO, H3K27me3, CUT&RUN, KO vs 2 × CD2-iCre PSIP1 KO, IgG, CUT&RUN, KO

Supports a between-group comparison across 8 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 8 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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