GEO series

Transcriptomical characterization of T-Large Granular Lymphocyte Leukemia (T-LGLL) patients having different STAT3/STAT5B genetic status and clinical manifastations

GSE228868 Homo sapiens (human) RNA-seq (gene expression) 25 samples Submitted 2025/09/22 Platform GPL21290

At a glance

RNA-seq (gene expression) · human · 25 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: 25 samples: 5 conditions, mostly with about 5 replicates eachGroups 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: Transcriptomic landscape of CD8+ and CD4 + T-LGL leukemia revealed the distinct impact of STAT3 and STAT5B activating mutationsLeukemia · 2025

Summary (written by the submitters)

T-Large Granular Lymphocyte Leukemia is a rare lymphoproliferative disorder characterized by the abnormal clonal expansion of cytotoxic T-LGL. The immunophenotype, clinical presentation, and prognosis are associated with activating mutations in STAT3 and STAT5B genes, which define four distinct subsets of the disease: CD8+ with STAT3 mutation, CD8+ wild-type, CD4+ with STAT5B mutation, and CD4+ wild-type.

Read the full summary ↓

RNA-seq data analysis of these patients reveals aberrant genes and non-coding RNA expression, pathways dysregulation, and the peculiarities of STAT3 mutated cases, which are associated with severe symptoms. This study offers new insights into the pathogenesis and clinical characteristics of T-LGLL patients, highlighting potential new targetable oncogenic axes for this disease.

Published in

Transcriptomic landscape of CD8+ and CD4 + T-LGL leukemia revealed the distinct impact of STAT3 and STAT5B activating mutations

Calabretto G, Binatti A, Teramo A et al. · Leukemia 2025 · PMID 40721648 · doi:10.1038/s41375-025-02708-1

This dataset

Open GSE228868 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 GSE228868_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 PRJNA951761 and SRA study SRP430672. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40721648) ↗

Study design

5 conditions, mostly with about 5 replicates each

CD8+, STAT3 mutated, LGL ×5 CD8+, WT, LGL ×5 CD4+, WT, LGL ×5 CD4+, STAT5B mutated, LGL ×5 CD8+, WT, Ct ×5

Supports a between-group comparison across 25 samples.

How we read this: 5 replicated groups read from 25 sample titles; they account for 25 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

GSM7140859 CD8+, STAT3 mutated, LGL3 CD8+, STAT3 mutated, LGL
GSM7140860 CD8+, STAT3 mutated, LGL16 CD8+, STAT3 mutated, LGL
GSM7140861 CD8+, STAT3 mutated, LGL80 CD8+, STAT3 mutated, LGL
GSM7140862 CD8+, STAT3 mutated, LGL254 CD8+, STAT3 mutated, LGL
GSM7140863 CD8+, STAT3 mutated, LGL272 CD8+, STAT3 mutated, LGL
GSM7140864 CD8+, WT, LGL179 CD8+, WT, LGL
GSM7140865 CD8+, WT, LGL56 CD8+, WT, LGL
GSM7140866 CD8+, WT, LGL48 CD8+, WT, LGL
GSM7140867 CD8+, WT, LGL5 CD8+, WT, LGL
GSM7140868 CD8+, WT, LGL299 CD8+, WT, LGL
GSM7140869 CD4+, WT, LGL149 CD4+, WT, LGL
GSM7140870 CD4+, WT, LGL21 CD4+, WT, LGL
GSM7140871 CD4+, WT, LGL258 CD4+, WT, LGL
GSM7140872 CD4+, WT, LGL305 CD4+, WT, LGL
GSM7140873 CD4+, WT, LGL20 CD4+, WT, LGL
GSM7140874 CD4+, STAT5B mutated, LGL49 CD4+, STAT5B mutated, L…
GSM7140875 CD4+, STAT5B mutated, LGL196 CD4+, STAT5B mutated, L…
GSM7140876 CD4+, STAT5B mutated, LGL2 CD4+, STAT5B mutated, L…
GSM7140877 CD4+, STAT5B mutated, LGL379 CD4+, STAT5B mutated, L…
GSM7140878 CD4+, STAT5B mutated, LGL132 CD4+, STAT5B mutated, L…
GSM7140879 CD8+, WT, Ctr168 CD8+, WT, Ct
GSM7140880 CD8+, WT, Ctr176 CD8+, WT, Ct
GSM7140881 CD8+, WT, Ctr164 CD8+, WT, Ct
GSM7140882 CD8+, WT, Ctr178 CD8+, WT, Ct
GSM7140883 CD8+, WT, Ctr179 CD8+, WT, Ct

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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.