GEO series

Transcriptomic signatures of immune suppression and cellular dysfunction distinguish latent from transcriptionally active HIV-1 infection in dendritic cells

GSE316074 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2026/01/13 Platform GPL34284

At a glance

RNA-seq (gene expression) · human · 18 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: 18 samples: 18 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: Transcriptomic Signatures of Immune Suppression and Cellular Dysfunction Distinguish Latent from Transcriptionally Active HIV-1 Infection in Dendritic CellsInternational journal of molecular sciences · 2026

Summary (written by the submitters)

Dendritic cells (DCs) are essential for antiviral immunity but are also susceptible to HIV-1 infection. Although sensing and restriction pathways in DCs are well described, the mechanisms underlying latent infection and its functional consequences remain unclear. Here, we performed transcriptomic profiling of monocyte-derived DCs harboring transcriptionally active (Active-HIV) or latent HIV-1 (Latent-HIV) proviruses using a dual-reporter virus.

Read the full summary ↓

Gene set enrichment analysis revealed suppression of metabolic and stress-modulatory programs in Active-HIV compared to unexposed DCs. In contrast, Latent-HIV showed broad downregulation of pathways, including interferon and innate responses and metabolic programs, indicating a hyporesponsive and dampened antiviral state despite the absence of differentially expressed genes (DEGs). DEG analysis of Active-HIV versus Latent-HIV showed that active transcription associates with cellular stress, cytoskeletal remodeling, and RNA-processing. Functional analyses further demonstrated activation of RNA processes, suppression of antigen-presentation pathways, and altered membrane and cytoskeletal signaling in Active-HIV. These pathways suggest that transcriptionally active HIV-1 leverages cellular machinery to support replication, creating a metabolically strained yet immunologically engaged state that disrupts antigen presentation. Conversely, latently infected DCs display a hyporesponsive state consistent with proviral silencing. This dichotomy reveals distinct mechanisms of DC dysfunction that may facilitate HIV-1 persistence and immune evasion.

Published in

Transcriptomic Signatures of Immune Suppression and Cellular Dysfunction Distinguish Latent from Transcriptionally Active HIV-1 Infection in Dendritic Cells

Man S, Jansen J, Kootstra NA et al. · International journal of molecular sciences 2026 · PMID 41596493 · doi:10.3390/ijms27020844

This dataset

Open GSE316074 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 GSE316074_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 PRJNA1400560 and SRA study SRP661050. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41596493) ↗

Study design

18 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 18 sample titles: 18 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

GSM9444149 Donor 1, Active-HIV
GSM9444150 Donor 1, Latent-HIV
GSM9444151 Donor 1, Unexposed
GSM9444152 Donor 2, Active-HIV
GSM9444153 Donor 2, Latent-HIV
GSM9444154 Donor 2, Unexposed
GSM9444155 Donor 3, Active-HIV
GSM9444156 Donor 3, Latent-HIV
GSM9444157 Donor 3, Unexposed
GSM9444158 Donor 4, Active-HIV
GSM9444159 Donor 4, Latent-HIV
GSM9444160 Donor 4, Unexposed
GSM9444161 Donor 5, Active-HIV
GSM9444162 Donor 5, Latent-HIV
GSM9444163 Donor 5, Uninfected
GSM9444164 Donor 6, Active-HIV
GSM9444165 Donor 6, Latent-HIV
GSM9444166 Donor 6, Uninfected

Datasets on a similar topic

GSE274114 Metabolic dysfunction-associated steatohepatitis reduces interferon and macrophage liver gene signatures in chronic HBV patients 39 samples shares dysfunction, signatures
GSE318418 Immunosuppressive monocytes are enriched in hepatocellular carcinoma patients with liver dysfunction in a phase II trial of combination sorafenib and nivolumab [scRNA-Seq] 16 samples shares dysfunction, cellular
GSE217906 Immune-cell signatures of persistent inflammation-immunosuppression and catabolism syndrome 16 samples shares suppression, signatures
GSE318420 Immunosuppressive monocytes are enriched in hepatocellular carcinoma patients with liver dysfunction in a phase II trial of combination sorafenib and nivolumab 210 samples shares dysfunction, cellular
GSE255092 Interaction between HIV-1 Tat and EBV Zta favours immune escape of B cells by downregulating HLA-ABC expression 56 samples shares hiv-1
GSE329693 Microbiome-Derived Metabolites Shape CD4⁺ T-Cell Differentiation and Immune Aging in Chronic HIV-1 Infection [RNA-Seq] 36 samples shares hiv-1
GSE299125 Paracrine Signals from HIV-1 Infected Immune Cells Reprogram Cervical Cancer Pathways 35 samples shares hiv-1
GSE319139 The HIV-1 Vpr R77Q mutant alters host apoptotic gene regulation in CD4+ T cells 33 samples shares hiv-1

Search all human RNA-seq datasets in GEO →

Share this dataset

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.