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Innate immune activation profiles are associated with polarization of the T cell response to recombinant arenaviral vectors

GSE338107 Homo sapiens (human) Single-cell RNA-seq 27 samples Submitted 2026/07/14 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 27 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
27 samples: 9 conditions, mostly in duplicateGroups 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)
Arenavirus-based vectors are uniquely positioned to generate durable T cell responses against tumors, which remains a central challenge in cancer immunotherapy. Two members of the arenavirus family, Lymphocytic choriomeningitis virus and Pichinde virus, were genetically engineered to encode a non-oncogenic fusion protein, originating from human papillomavirus 16 E6 and E7.
Read the full summary ↓
Hereafter, these vectors are referred to as HB-201 and HB-202, respectively. HB-201 alone or in combination with HB-202 elicited strong and durable E6/E7-specific CD8+ T cell responses in HPV 16+ cancer patients . Despite their classification within the same virus family, Lymphocytic choriomeningitis virus and Pichinde virus are phylogenetically distant, which may influence virus-host interactions and the pathways leading to antiviral immune responses. Previous studies showed that both vectors infect and activate professional antigen presenting cells. To elaborate on these findings, this study aimed to characterize in depth the innate immune response to HB-201 and HB-202 by single cell sequencing in an in vitro human PBMCs infection model. We confirmed the preferential infection of antigen presenting cells for both vectors, with HB-201 infecting the cross-priming conventional dendritic cell subset cDC1 more efficiently than HB-202. Furthermore, HB-201 induced stronger type I interferon responses than HB-202, as well as quantitative and qualitative differences in inflammatory response linked to a distinct reshaping of monocyte subsets towards intermediate and non-classical monocytes. Antigen presentation and T cell priming cytokines in dendritic cells appeared to favor antiviral CD8+ T cell responses upon HB-201 infection, whereas a more balanced CD4+ and CD8+ priming profile was observed upon HB-202 infection. Immunogenicity data from patients treated with HB-201 and HB-202 confirmed the in vitro findings with functional differences in early T cell response. Thus, despite their shared origins within the arenavirus family, HB-201 and HB-202 demonstrate distinct differences in early host-virus interaction, potentially resulting in shaping unique T cell responses.
This dataset
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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 GSE338107_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 PRJNA1492518 and SRA study SRP716629. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
9 conditions, mostly in duplicate
101-0006_SCR_HB ×2 109-0003_C1D1_HB ×2 115-0017_SCR_HB ×2 106-0005_SCR_HB ×2 109-0015_SCR_HB ×2 111-0001_C1D1_HB ×2 HOOK26_HB ×2 HOOK60_HB ×2 +10 more

Supports a between-group comparison across 18 samples.

How we read this: 9 replicated groups read from 27 sample titles; they account for 18 of them. 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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