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NKG2D blockade impairs cytotoxic CD8+ tissue resident memory T cell accumulation and attenuates severity of chronic lung allograft dysfunction after transplantation

GSE285515 Homo sapiens (human) Single-cell RNA-seq 15 samples Submitted 2024/12/29 Platform GPL16791
At a glance

Single-cell RNA-seq · human · 15 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
15 samples: 15 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
NKG2D blockade impairs tissue-resident memory T cell accumulation and reduces chronic lung allograft dysfunctionJCI insight · 2025
Summary (written by the submitters)
Chronic lung allograft dysfunction (CLAD) significantly limits long-term survival following lung transplantation. To identify potential targets for CLAD prevention, T cells from explanted CLAD lungs and lung-draining lymph nodes, as well as diseased and non-diseased controls were isolated and single-cell RNA sequencing and TCR sequencing were performed.
Read the full summary ↓
TCR sequencing revealed a clonally expanded population of tissue resident memory (TRM) CD8+ T cells with high cytotoxic potential including upregulation KLRK1, encoding the co-receptor NKG2D. These cytotoxic CD8+ TRM accumulated around the CLAD airways and had 100-fold increase in clonal overlap with lung draining lymph nodes when compared to non-CLAD lungs. Using a murine model of orthotopic lung transplant, we confirmed that cytotoxic CD8+ TRM accumulation was due to chronic rejection and not transplant alone. Furthermore, blocking NKG2D in-vivo attenuated the airway remodeling following transplantation and diminished airway accumulation of CD8+ T cells. Our findings support NKG2D as a potential therapeutic target for CLAD, affecting cytotoxic CD8+ TRM accumulation.
Published in
NKG2D blockade impairs tissue-resident memory T cell accumulation and reduces chronic lung allograft dysfunction
Moghbeli K, Lipp MA, Bueno M et al. · JCI insight 2025 · PMID 39989456 · doi:10.1172/jci.insight.184048
This dataset
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.

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 GSE285515_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1204132 and SRA study SRP554320. Searching any of these in the dataset finder brings you back here.

Study design
15 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 15 sample titles: 15 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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