GEO series

Dual STAT3/STAT5 inhibition as a novel treatment strategy in T-prolymphocytic leukemia

GSE286270 Homo sapiens (human) RNA-seq (gene expression) 118 samples Submitted 2025/06/16 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 118 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: 118 samples: 118 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: Dual STAT3/STAT5 inhibition as a novel treatment strategy in T-prolymphocytic leukemiaLeukemia · 2025

Summary (written by the submitters)

T-prolymphocytic leukemia (T-PLL) is a rare, aggressive T-cell malignancy with poor outcomes and an urgent need for new therapeutic approaches. Integrating genomic data and new transcriptomic profiling, we identified recurrent JAK/STAT mutations as a hallmark in T-PLL in an unprecedented cohort of 335 T-PLL cases, predominantly involving JAK3 and STAT5B.

Read the full summary ↓

In line, transcriptomic and immunoblot analyses revealed constitutive JAK/STAT activation in virtually all samples. Building on these findings, we explored the therapeutic potential of dual STAT3/STAT5 non-PROTAC degraders in T-PLL treatment, with JPX-1244 as our lead substance. JPX-1244 efficiently and selectively induced cell death in primary T-PLL samples, including those resistant to conventional therapies, by blocking STAT3/STAT5 phosphorylation and inducing their degradation. The extent of STAT3/STAT5 degradation directly correlated with cytotoxicity. RNA-sequencing confirmed the downregulation of STAT5 target genes. While JAK/STAT mutations did not predict treatment responses, elevated TOX, PAK6, and SPINT1 expression was associated with drug sensitivity. In a subsequent combination screening, cladribine, venetoclax, and azacytidine emerged as most effective combination partners even in low-responding T-PLL samples, synergistically reducing STAT5 phosphorylation. These findings highlight dual STAT3/STAT5 inhibition, particularly in combination with hypomethylating agents, as a promising therapeutic approach in T-PLL, warranting further preclinical and clinical investigation.

Published in

Dual STAT3/STAT5 inhibition as a novel treatment strategy in T-prolymphocytic leukemia

Dechow A, Timonen S, Ianevski A et al. · Leukemia 2025 · PMID 40234614 · doi:10.1038/s41375-025-02577-8

This dataset

Open GSE286270 in finder → Find more human 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 GSE286270_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 PRJNA1208510 and SRA study SRP556303. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40234614) ↗

Study design

118 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 118 sample titles: 118 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

GSM8722353 T-PLL patient sample P01, untouched
GSM8722354 T-PLL patient sample P02, untouched
GSM8722355 T-PLL patient sample P03, untouched
GSM8722356 T-PLL patient sample P04, untouched
GSM8722357 T-PLL patient sample P05, untouched
GSM8722358 T-PLL patient sample P06, untouched
GSM8722359 T-PLL patient sample P07, untouched
GSM8722360 T-PLL patient sample P08, untouched
GSM8722361 T-PLL patient sample P09, untouched
GSM8722362 T-PLL patient sample P10, untouched
GSM8722363 T-PLL patient sample P11, untouched
GSM8722364 T-PLL patient sample P12, untouched
GSM8722365 T-PLL patient sample P13, untouched
GSM8722366 T-PLL patient sample P14, untouched
GSM8722367 T-PLL patient sample P15, untouched
GSM8722368 T-PLL patient sample P16, untouched
GSM8722369 T-PLL patient sample P17, untouched
GSM8722370 T-PLL patient sample P18, untouched
GSM8722371 T-PLL patient sample P19, untouched
GSM8722372 T-PLL patient sample P20, untouched
GSM8722373 T-PLL patient sample P21, untouched
GSM8722374 T-PLL patient sample P22, untouched
GSM8722375 T-PLL patient sample P23, untouched
GSM8722376 T-PLL patient sample P24, untouched
GSM8722377 T-PLL patient sample P25, untouched
GSM8722378 T-PLL patient sample P26, untouched
GSM8722379 T-PLL patient sample P27, untouched
GSM8722380 T-PLL patient sample P28, untouched
GSM8722381 T-PLL patient sample P29, untouched
GSM8722382 T-PLL patient sample P30, untouched
GSM8722383 T-PLL patient sample P31, untouched
GSM8722384 T-PLL patient sample P32, untouched
GSM8722385 T-PLL patient sample P01, 8h, control
GSM8722386 T-PLL patient sample P01, 8h, JPX
GSM8722387 T-PLL patient sample P01, 8h, control + IL6
GSM8722388 T-PLL patient sample P01, 8h, JPX + IL6
GSM8722389 T-PLL patient sample P01, 24h, control
GSM8722390 T-PLL patient sample P01, 24h, control + IL6
GSM8722391 T-PLL patient sample P15, 8h, control
GSM8722392 T-PLL patient sample P15, 8h, JPX

+ 78 more — browse all 118 samples with per-sample file links →

Datasets on a similar topic

GSE288275 Inhibition of the STAT3/Fanconi anemia axis is synthetic lethal with PARP inhibitor in breast cancer 24 samples shares stat3, inhibition
GSE274024 NOX4/NOX1 dual inhibition in cholangiocarcinoma as an effective approach to target TGF-beta protumorigenic actions in cancer associated fibroblasts 45 samples shares inhibition, dual
GSE281506 Combining Menin and MEK inhibition to target poor prognosis KMT2A-rearranged RAS pathway-mutant acute myeloid leukemia 42 samples shares inhibition, leukemia
GSE78220 mRNA expressions in pre-treatment melanomas undergoing anti-PD-1 checkpoint inhibition therapy 28 samples shares inhibition, treatment
GSE305560 TP53-Agnostic Lethality through Combined Pan-HDAC and CDK Inhibition in Acute Myeloid Leukemia 18 samples shares inhibition, leukemia
GSE292732 A pilot trial of perioperative IDH Inhibition in treatment-naïve IDH-mutant glioma 11 samples shares inhibition, treatment
GSE327029 KPNA3 drives temozolomide resistance in glioblastoma by upregulating MGMT and activating STAT3 to sustain glioma stem cells 12 samples shares stat3
GSE302359 Interferons promote autophagy via the STAT1/STAT5B-SOCS1 axis 12 samples shares stat5

Search all human RNA-seq datasets in GEO →

Share this dataset

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.