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Similar activation-driven transcriptional programs in lung CMV- and flu- specific memory CD8+ T cells despite differences in tissue residency profiles

GSE299807 Homo sapiens (human) RNA-seq (gene expression) 25 samples Submitted 2025/12/17 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 25 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
25 samples: 25 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
Human lung CD8(+) tissue-resident memory T cell-derived interferon-γ orchestrates subset-specific antiviral programming in airway epithelial cellsImmunity · 2025
Summary (written by the submitters)
To investigate whether virus-specific human lung memory CD8⁺ T cells exhibit distinct transcriptional responses based on viral tropism, we stimulated total human lung cells ex vivo with peptide pools from either influenza virus (epithelial-restricted) or cytomegalovirus (CMV, broader tropism). Antigen-specific CD8⁺ T cells were identified using activation-induced markers (CD25 and CD137) and sorted for bulk RNA sequencing.
Read the full summary ↓
Despite differences in tissue residency phenotypes, influenza- and CMV-specific CD8⁺ T cells displayed highly similar activation-induced transcriptional programs across nine donors, with shared enrichment of inflammatory and T cell signaling pathways. These findings suggest that lung memory CD8⁺ T cells mount comparable responses to antigen stimulation, regardless of viral specificity or residency profile.
Published in
Human lung CD8(+) tissue-resident memory T cell-derived interferon-γ orchestrates subset-specific antiviral programming in airway epithelial cells
Mattingly CLR, Jimenez AR, Williams ME et al. · Immunity 2025 · PMID 41308652 · doi:10.1016/j.immuni.2025.11.003
This dataset
Open GSE299807 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 GSE299807_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1276561 and SRA study SRP592031. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41308652) ↗
Study design
25 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 25 sample titles: 25 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
Datasets on a similar topic

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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.