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Human lungs maintain tissue-resident memory T cells against a broad spectrum of pathogens.

GSE305372 Homo sapiens (human) Single-cell RNA-seq 91 samples Submitted 2026/06/07 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 91 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
91 samples: 49 distinct titles, 2 of them repeatedGroups 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.
Summary (written by the submitters)
Immune responses in the lungs are essential for the prevention and control of a wide range of infections. Tissue-resident memory T (TRM) cells are critical for frontline immunity, yet in murine lungs they undergo rapid attrition, raising questions about their durability in the human lung.
Read the full summary ↓
Here, using a T-cell receptor (TCR)-guided approach integrating single-cell transcriptomics with paired TCR repertoire profiling, we mapped over 87,000 pathogen-specific T cells from human lung tissue across 40 donors, many of whom harbored substantial TRM populations specific to multiple respiratory viruses. These findings suggest, contrary to observations in murine infection models, that the human lung is likely to serve as a reservoir of clonally expanded TRM cells specific to a broad spectrum of pathogens. Although the lung-associated lymph nodes (LLN) contained a small population of TRM cells, most TCRs from highly expanded TRM clones in the lungs were absent in the LLN, suggesting that LLNs are unlikely to serve as a major reservoir for lung TRM cells. While acquisition of the TRM phenotype in the lung was not biased towards specific pathogens, pathogen specificity influenced the transcriptional profiles of CD8+ TRM cells. Notably, influenza A virus (IAV)-specific CD8+ TRM cells expressed significantly higher levels of transcripts linked to tissue residence and effector properties compared to TRM cells specific to other pathogens. Overall, our findings reveal that the human lung retains a stable, yet diverse compartment of pathogen-specific TRM cells, with implications for understanding tissue-resident memory responses that persist after infections and vaccinations.
This dataset
Open GSE305372 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 GSE305372_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 PRJNA1280066 and SRA study SRP593372. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
49 distinct titles, 2 of them repeated
10x single-cell library of lung sample from d… ×40 10x single-cell library of lung-draining lymp… ×4

How we read this: Read from 91 sample titles: 49 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

+ 51 more — browse all 91 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.