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Blocking PD-1 engagement rapidly upregulates innate antiviral and immune functions that associate with HIV reservoir decay [scRNA-seq]

GSE298838 Homo sapiens (human) Single-cell RNA-seq 38 samples Submitted 2025/08/31 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 38 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
38 samples
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
Innate antiviral and immune functions associated with the HIV reservoir decay after anti-PD-1 therapyNature medicine · 2026
Summary (written by the submitters)
The HIV reservoir, a small pool of PD-1+CD4+ T cells that carry integrated HIV genomes, remains a formidable obstacle to HIV cure. The clinical use of PD-1 inhibitors has shown promising results in curbing the HIV reservoir in people with HIV (PWH) and cancer, but the underlying mechanisms are unknown. Here, we demonstrate that anti-PD-1 therapy leads to a decay in the frequency of cells harboring HIV DNA at the end of a two-year follow-up in 9 of 14 PWH receiving pembrolizumab within the CITN-12 clinical trial (NCT02595866).
Read the full summary ↓
This reduction correlates with an innate immune response, characterized by increased monocyte frequencies and enhanced myeloid cell-specific transcription of interferon-stimulated genes (ISGs), chemokines, antiviral restriction factors, and TLR signaling. These changes emerge as early as 24 hours post-treatment and persist until the end of therapy. Within 24 hours of treatment, we also observe an increase in proliferating effector HIV-specific CD8+ T cells, increased expression of effector T cell genes, and a decline in plasma TGF-β levels. We validate the generalizability of these ISG expression modules across >1,000 publicly available scRNA-seq samples, revealing a consistent association between high ISG expression in peripheral blood mononuclear cells (PBMCs) and lower expression of WNT pathway and Treg gene sets - pathways known to regulate immune quiescence and persistence of the HIV reservoir - in PBMCs from uninfected controls, as well as in samples from individuals with cancer or infections. Furthermore, we demonstrate that ISGs triggered by TLR ligands protect CD4+ T cells from HIV infection in vitro. These findings support a mechanism by which ISGs restrict the HIV reservoir in vivo and define a set of immune signaling pathways that can be used to identify PWH in whom the HIV reservoir may decay upon anti-PD-1 therapy.
Published in
Innate antiviral and immune functions associated with the HIV reservoir decay after anti-PD-1 therapy
Talla A, Azevedo JLLC, Latif MB et al. · Nature medicine 2026 · PMID 41680482 · doi:10.1038/s41591-025-04139-y
This dataset
Open GSE298838 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 GSE298838_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 PRJNA1271469 and SRA study SRP589583. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41680482) ↗
Study design
A cohort of 38 individual samples

The grouping that defines any comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Sample titles run s001 … s038 and carry no group information.

Samples in this study
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