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Cytokines drive the formation of memory-like NK cell subsets via epigenetic rewiring and transcriptional mechanisms [CITE-seq]

GSE264696 Homo sapiens (human) Single-cell RNA-seq 16 samples Submitted 2024/06/28 Platform GPL25526
At a glance

Single-cell RNA-seq · human · 16 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
16 samples: 16 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
Cytokines drive the formation of memory-like NK cell subsets via epigenetic rewiring and transcriptional regulationScience immunology · 2024
Summary (written by the submitters)
NK cells are innate lymphoid cells that protect the host against malignant and infected cells. Activation with the cytokines IL-12, IL-15, and IL-18 induces NK cells to differentiate into memory-like NK cells that have enhanced function compared to conventional NK (cNK) cells. However, mechanisms governing their biology and whether all cNK cells become memory-like are unclear.
Read the full summary ↓
We identified that IL-12/15/18 activation results in two main fates: reprogramming into enriched memory-like (eML) or priming into effector (eff)cNK cells. eML NK cells have distinct epigenetics, phenotype, and enhanced function (IFNγ, cytotoxicity) compared to cNK and effcNK cells. In contrast, effcNK cells transcriptionally and epigenetically resemble cNK cells. Furthermore, we identify that within cNK cells CD56bright and CD56dim NK cells are the origin of distinct subsets of eML NK cells. Moreover, these two subsets of eML NK cells persist within patients receiving ML NK cell therapy for several months. Thus, IL-12/15/18 activation of NK cells results in multiple cell fates, with epigenetic and transcriptional mechanisms orchestrating eML NK cell differentiation and function. These mechanistic insights provide new strategies to enhance NK cellular therapy.
Published in
Cytokines drive the formation of memory-like NK cell subsets via epigenetic rewiring and transcriptional regulation
Foltz JA, Tran J, Wong P et al. · Science immunology 2024 · PMID 38941480 · doi:10.1126/sciimmunol.adk4893
This dataset
Open GSE264696 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 GSE264696_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 PRJNA1103814 and SRA study SRP503664. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38941480) ↗
Study design
16 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 16 sample titles: 16 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
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