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A dual role for PSIP1/LEDGF in T-cell acute lymphoblastic leukemia [RNA-seq]

GSE253138 Homo sapiens (human) RNA-seq (gene expression) 42 samples Submitted 2024/10/20 Platform GPL18573Platform GPL19057
At a glance

RNA-seq (gene expression) · human · 42 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
42 samples: 9 × Lck-Cre Pten Psip1 KO, thymoma, L vs 6 × Lck-Cre Pten Psip1 WT, thymoma, L vs 6 × CD2-iCre CD2-Lmo2 Psip1 WT, thymoma, CDNA vs 6 × CD2-iCre CD2-Lmo2 Psip1 KO, thymoma, CDNAGroups 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
Open GSE253138 in finder → Find more RNA-seq datasets →
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 GSE253138_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: 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 PRJNA1064102 and SRA study SRP483400. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39485844) ↗
Study design
9 × Lck-Cre Pten Psip1 KO, thymoma, L vs 6 × Lck-Cre Pten Psip1 WT, thymoma, L vs 6 × CD2-iCre CD2-Lmo2 Psip1 WT, thymoma, CDNA vs 6 × CD2-iCre CD2-Lmo2 Psip1 KO, thymoma, CDNA

Supports a between-group comparison across 27 samples.

How we read this: 4 replicated groups read from 42 sample titles; they account for 27 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

+ 2 more — browse all 42 samples with per-sample file links →

Datasets on a similar topic

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