GEO series

DUSP6 mediates resistance to JAK2 inhibition and drives leukemic progression (RNA-Seq)

GSE190517 Homo sapiens (human) Single-cell RNA-seq 20 samples Submitted 2022/10/25 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 20 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Topic: Myeloproliferative neoplasmsThis series is part of our curated briefing on it.
Samples: 20 samples
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)

Chronic myeloproliferative neoplasms (MPNs) exhibit a propensity for transformation to secondary acute myeloid leukemia (sAML), for which the underlying mechanisms remain poorly understood, resulting in limited treatment options and dismal clinical outcomes. Here, we performed bulk transcriptome profiling accompanied by single cell RNA-sequencing on CD34+ stem/progenitor cells from serial patient samples obtained at the chronic MPN and sAML phases, identifying aberrantly increased expression of dual-specificity phosphatase 6 (DUSP6) underlying disease transformation.

Read the full summary ↓

Genetic and pharmacologic targeting of DUSP6 led to inhibition of S6 and JAK/STAT signaling, resulting in potent suppression of cell proliferation, while also reducing inflammatory cytokine production in primary samples. Furthermore, ectopic DUSP6 expression augmented proliferation and mediated JAK2 inhibitor resistance, while DUSP6 inhibition reduced colony-forming potential of JAK2 inhibitor-persistent patient cells. Mechanistically, DUSP6 perturbation dampened S6 signaling via inhibition of RSK1, which we identified as a second indispensable candidate associated with poor clinical outcome. Ectopic expression of DUSP6 in patient-derived xenograft (PDX) models exacerbated disease severity and led to early lethality, whereas DUSP6 knockdown suppressed leukemic engraftment. Finally, pharmacological inhibition of DUSP6 potently and specifically suppressed disease development across Jak2 V617F and MPL W515L MPN mouse models, as well as sAML PDXs, without inducing toxicity in healthy controls. These findings underscore DUSP6 in driving disease transformation and therapeutic resistance, and highlight the DUSP6-RSK1 axis as a novel, druggable pathway in myeloid malignancies.

This dataset

Open GSE190517 in finder → Find more human RNA-seq datasets → Myeloproliferative neoplasms 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 GSE190517_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA787454 and SRA study SRP349960. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 36581736) ↗

Samples in this study

The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.

+ 20 more — browse all 20 samples with per-sample file links →

More Myeloproliferative neoplasms datasets

GSE214914 DUSP6 mediates resistance to JAK2 inhibition and drives leukemic progression (single-cell RNA-seq) 4 samples same disease briefing · shares dusp6, jak2, progression, resistance, inhibition, mediates, leukemic, rna-seq
GSE225396 ZRSR2-loss causes aberrant splicing in a JAK2V617F-driven myeloproliferative neoplasm but is not sufficient to drive disease progression 17 samples same disease briefing · shares jak2, progression
GSE183374 HMGA1 Chromatin Regulators Drive MPN Progression [RNA-Seq] 12 samples same disease briefing · shares progression, rna-seq
GSE288706 Mesenchymal stromal cells from JAK2V617F myeloproliferative neoplasms support healthy and malignant haematopoiesis in a humanised scaffold model in vivo 12 samples same disease briefing · shares jak2
GSE243648 The deacetylases HDAC1/HDAC2 control JAK2V617F-STAT signaling through the ubiquitin ligase SIAH2 9 samples same disease briefing · shares jak2
GSE266434 Decoding Endothelial MPL and JAK2V617F Mutation: Insight into Cardiovascular Dysfunction in Myeloproliferative Neoplasms 4 samples same disease briefing · shares jak2
GSE300470 A Stem and Progenitor Cell-Derived Gene Expression Signature is Prognostic for Survival in Myelofibrosis [RNA-Seq] 358 samples same disease briefing · shares rna-seq
GSE288557 ULK1 as a novel therapeutic target in Myeloproliferative Neoplasms [RNA-Seq] 12 samples same disease briefing · shares rna-seq

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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.