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A STAT5B-driven mouse model of hepatosplenic γδ T cell lymphoma reveals therapeutic efficacy of JAK inhibitors

GSE271616 Mus musculus (mouse) RNA-seq (gene expression) 23 samples Submitted 2026/03/12 Platform GPL24676Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 23 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
Mus musculus (mouse)
Samples
23 samples: 7 conditions, mostly in triplicateGroups 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
Preclinical models of hepatosplenic γδ T-cell lymphoma with an activating STAT5B mutation display sensitivity to JAK inhibitor upadacitinibHemaSphere · 2026
Summary (written by the submitters)
Hepatosplenic T cell lymphoma (HSTL) is a rare, aggressive disease primarily affecting young adults. The disease progresses rapidly, with patients displaying low survival rates and poor responses to standard chemotherapy-based treatments. Currently no targeted therapies are available for HSTL, and pre-clinical models to test new treatment options have not been established.
Read the full summary ↓
Hence, new models recapitulating HSTL are needed. The JAK-STAT signalling pathway is a key pathway dysregulated in HSTL and STAT5B N642H is the most frequent oncogenic mutation. Using a transgenic mouse model, we have previously validated STAT5B N642H as a strong driver of γδ T cell lymphoma. Here, we have established clonal, murine γδ T cell lymphoma cell lines driven by oncogenic STAT5B, which resemble key features of human HSTL. The IL-2 dependent cell line, C15, displays immunophenotypic features as well as commonly dysregulated gene expression profiles shared with patient-derived HSTL cell lines. C15 cells can be engrafted intravenously into immunocompetent mice to generate an aggressive HSTL-like disease. Recipient mice display an expansion of malignant γδ T cells causing hepatosplenomegaly and elevated alanine transaminase (ALT) and aspartate transaminase (AST) levels. Using these models, we tested the potential of JAK inhibition as a targeted treatment strategy for HSTL, with the clinically-approved JAK inhibitor upadacitinib displaying significant anti-tumor efficacy against HSTL cells in vitro and in vivo. Overall, we have developed a robust, accessible and faithful preclinical model of HSTL with the advantage of immune-competence, which can facilitate the study of physiological disease mechanisms and new (immuno)therapy strategies.
Published in
Preclinical models of hepatosplenic γδ T-cell lymphoma with an activating STAT5B mutation display sensitivity to JAK inhibitor upadacitinib
Aung MMK, Schönefeldt S, Pfalz-Kraupp S et al. · HemaSphere 2026 · PMID 42007450 · doi:10.1002/hem3.70345
This dataset
Open GSE271616 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 GSE271616_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 PRJNA1132296 and SRA study SRP518232. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42007450) ↗
Study design
7 conditions, mostly in triplicate
BC ×5 C15 ×3 C2 ×3 C6 ×3 WT_Ly5.2_gd ×3 DERL2 ×3 DERL7 ×3

Supports a between-group comparison across 23 samples.

How we read this: 7 replicated groups read from 23 sample titles; they account for 23 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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