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Response to Treg therapy is linked to rate of ex vivo Treg expansion

GSE243270 Homo sapiens (human) Single-cell RNA-seq 105 samples Submitted 2024/04/15 Platform GPL16791
At a glance

Single-cell RNA-seq · human · 105 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)
Samples
105 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.
Paper
A phase 2 randomized trial with autologous polyclonal expanded regulatory T cells in children with new-onset type 1 diabetesScience translational medicine · 2024
Summary (written by the submitters)
Background: CD4+CD25hiCD127lo/-FOXP3+ regulatory T cells (Tregs) play a key role in preventing autoimmunity. In type 1 diabetes, adoptive transfer of autologous polyclonal Tregs has been shown to be safe in adults in Phase I clinical trials. Methods: We explore factors contributing to efficacy in autologous polyclonal expanded Tregs (expTregs) Phase 2 clinical trial in 111 children and adolescents with new-onset type 1 diabetes (Sanford/Lisata Therapeutics Trex Phase 2 clinical trial) randomized 1:1:1 high and low treatment to placebo.
Read the full summary ↓
Cytometry, bulk and single cell RNA-seq were perfomed on selected expTregs and PBMC samples from subjects. Results: A single dose of expTreg therapy (1-24x106cells/kg) was safe but did not prevent the decline in residual beta cell function over one year compared to placebo (p=0.39), regardless of age, baseline C-peptide, or dose of expTregs. ExpTregs were highly activated and suppressive, and a transient increase of activated memory Tregs was detectable one week after infusion in the high dose cohort, suggesting effective transfer of expTregs. However, in vitro fold expansion on expTregs varied across subjects even when accounting for age. Lower fold expansion and its’ associated gene signature was linked with better outcome, regardless of Treg dose. Conclusion: These results suggest that expTregs quantity alone does not alter outcome; instead, expTreg quality may be an important factor contributing to the efficacy of adoptive Treg therapy to prevent type 1 diabetes progression.
Published in
A phase 2 randomized trial with autologous polyclonal expanded regulatory T cells in children with new-onset type 1 diabetes
Bender C, Wiedeman AE, Hu A et al. · Science translational medicine 2024 · PMID 38718135 · doi:10.1126/scitranslmed.adn2404
This dataset
Open GSE243270 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 GSE243270_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 PRJNA1017505 and SRA study SRP460597. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38718135) ↗
Study design
A cohort of 105 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run lib77826 … lib77930 and carry no group information.

Samples in this study

+ 65 more — browse all 105 samples with per-sample file links →

Datasets on a similar topic

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