GEO series

IL-2 and TGF-b1 promote regulatory activity in NK cells following Hematopoietic Stem Cell Transplantation

GSE255298 Homo sapiens (human) Single-cell RNA-seq 13 samples Submitted 2024/11/12 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 13 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: 13 samples: 13 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: Single cell profiling of hematopoietic stem cell transplant recipients reveals TGF-β1 and IL-2 confer immunoregulatory functions to NK cellsiScience · 2024

Summary (written by the submitters)

Natural Killer(NK) cell activity is influenced by cytokines and microenvironment factors, resulting in remarkably diverse functions ranging from contributing to inflammatory responses to instead inhibiting T cell and B cell activity, thereby serving as rheostats of adaptive immunity. Using scRNAseq, we identified a TGFb1highCD56brightNK cell population associated with protection from acute Graft-versus-Host Disease.

Read the full summary ↓

We further define a role for the combination of IL-2 and TGF-b in promoting NK cells to acquire a regulatory phenotype. ‘Induced’ regulatory NK cells produce high amounts of TGF-b1, inhibited T cells, could promote naïve T cells differentiation into regulatory T cells, and exhibited a unique transcriptional program that includes expression of IKZF2(HELIOS) and ZNF683(HOBIT). This phenotype was not stable, and induced regulatory NK cells lost the ability to secrete TGF-b1 upon exposure to different cytokines. These findings define protective CD56brightNK cells in Hematopoietic Stem Cell Transplant, and support IL-2 and TGF-b1 promote regulatory NK cells.

Published in

Single cell profiling of hematopoietic stem cell transplant recipients reveals TGF-β1 and IL-2 confer immunoregulatory functions to NK cells

Mathews JA, Borovsky DT, Reid KT et al. · iScience 2024 · PMID 39720529 · doi:10.1016/j.isci.2024.111416

This dataset

Open GSE255298 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 GSE255298_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 PRJNA1074396. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39720529) ↗

Study design

13 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 13 sample titles: 13 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

GSM8068544 PBMC, GVHD, G002, snRNAseq
GSM8068545 PBMC, NoGVHD, G007, snRNAseq
GSM8068546 PBMC, GVHD, G008, snRNAseq
GSM8068547 PBMC, GVHD, G011, snRNAseq
GSM8068548 PBMC, GVHD, G015, snRNAseq
GSM8068549 PBMC, GVHD, G016, snRNAseq
GSM8068550 PBMC, GVHD, G018, snRNAseq
GSM8068551 PBMC, GVHD, G019, snRNAseq
GSM8068552 PBMC, NoGVHD, B001, snRNAseq
GSM8068553 PBMC, NoGVHD, B002, snRNAseq
GSM8068554 PBMC, NoGVHD, B003, snRNAseq
GSM8068555 PBMC, NoGVHD, B004, snRNAseq
GSM8068556 PBMC, NoGVHD, B005, snRNAseq

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