GEO series

Dissection of innate-immune-ligand- and interferon-protein-mediated transcriptional responses in human THP1 cell states

GSE330780 Homo sapiens (human) RNA-seq (gene expression) 117 samples Submitted 2026/05/17 Platform GPL18573

At a glance

RNA-seq (gene expression) · human · 117 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: 117 samples: 87 distinct titles, 22 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)

Interferon regulatory factors (IRFs) are essential for transcription of interferons (IFNs), interferon-stimulated genes (ISGs), and pro-inflammatory cytokines. We profile the transcriptome of human monocyte THP1 cells challenged with cGAMP, LPS, or IFNB1 protein as a function of knockout (KO) or overexpression (OE) of IRFs or KO of IFNAR2.

Read the full summary ↓

We define distinct gene expression groups, reflecting the transcription factors responsible for their induction including subgroups activated by more than one pathway or feed-forward regulation. We compare IRF3- and IRF7-induced gene signatures and note the strong direct induction of a subset of antiviral-acting ISGs by IRF3 or IRF7. LPS treatment induces NF-kB responses in monocyte and macrophage state cells, however, IFNs and ISGs are only co-induced in the macrophage state requiring IRF3. IRF1, IRF2, IRF5, and IRF8 are largely dispensable for IFN-stimulated or innate-immune-mediated gene induction. This study provides a valuable resource for dissecting complex inflammatory gene signatures and their underlying transcription factors thereby anticipating the effects of selectively drugging the underlying pathways.

This dataset

Open GSE330780 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 GSE330780_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 PRJNA1244336 and SRA study SRP581792. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

87 distinct titles, 22 of them repeated

WT ×4 IRF3 KO ×3 IRF9 KO ×3 WT Digitonin ×3 IRF3 KO Digitonin ×3 WT Digitonin + cGAMP ×3 IRF3 KO Digitonin + cGAMP ×3 IRF1 KO ×2 +14 more

How we read this: Read from 117 sample titles: 87 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

GSM9732651 WT Rep1
GSM9732652 WT Rep2
GSM9732653 WT Rep3
GSM9732654 WT Rep4
GSM9732655 IRF1 KO Rep1
GSM9732656 IRF1 KO Rep2
GSM9732657 IRF2 KO Rep1
GSM9732658 IRF2 KO Rep2
GSM9732659 IRF3 KO Rep1
GSM9732660 IRF3 KO Rep2
GSM9732661 IRF3 KO Rep3
GSM9732662 IRF5 KO Rep1
GSM9732663 IRF5 KO Rep2
GSM9732664 IRF7 KO Rep1
GSM9732665 IRF7 KO Rep2
GSM9732666 IRF8 KO Rep1
GSM9732667 IRF8 KO Rep2
GSM9732668 IRF9 KO Rep1
GSM9732669 IRF9 KO Rep2
GSM9732670 IRF9 KO Rep3
GSM9732671 IFNAR2 KO Rep1
GSM9732672 IFNAR2 KO Rep2
GSM9732673 IRF3/7 DKO Rep1
GSM9732674 IRF3/7 DKO Rep2
GSM9732675 WT IFNB1 protein Rep1
GSM9732676 WT IFNB1 protein Rep2
GSM9732677 IRF1 KO IFNB1 protein Rep1
GSM9732678 IRF2 KO IFNB1 protein Rep1
GSM9732679 IRF3 KO IFNB1 protein Rep1
GSM9732680 IRF3 KO IFNB1 protein Rep2
GSM9732681 IRF5 KO IFNB1 protein Rep1
GSM9732682 IRF7 KO IFNB1 protein Rep1
GSM9732683 IRF8 KO IFNB1 protein Rep1
GSM9732684 IRF9 KO IFNB1 protein Rep1
GSM9732685 IRF9 KO IFNB1 protein Rep2
GSM9732686 IFNAR2 KO IFNB1 protein Rep1
GSM9732687 IRF3/7 DKO IFNB1 protein Rep1
GSM9732688 WT Digitonin Rep1
GSM9732689 WT Digitonin Rep2
GSM9732690 WT Digitonin Rep3

+ 77 more — browse all 117 samples with per-sample file links →

Datasets on a similar topic

GSE280005 Transcriptional profiling of sorted THP1 cells infected with wild-type Mtb (H37Rv) or ESX-1-mutant Mtb 32 samples shares thp1
GSE281475 Transcriptomic changes in THP1 human AML cell line on PHF6 knockout, PHF6R274Q mutation, PHIP knockout, and double knockout of PHF6 and PHIP compared to wildtype cells 21 samples shares thp1
GSE281624 Transcriptomic changes in PHF6 knockout THP1 human AML cell line on rescue with PHF6 wildtype (with and without PHIP) or rescue with PHF6R274Q mutant 19 samples shares thp1
GSE323383 Bulk RNAseq in control and LACTB KD human THP1 macrophages 10 samples shares thp1
GSE277149 Transcriptome changes caused by PHF6 knockout in THP1 human AML cell line 9 samples shares thp1
GSE229937 Genes regulated by BRD3 in LPS-primed THP1 monocytes 12 samples shares thp1
GSE254679 RUNX1 interacts with lncRNA SMANTIS to regulate monocytic cell functions [RNA_THP1_SMANTIS_RUNX1_KO] 9 samples shares thp1
GSE254681 RUNX1 interacts with lncRNA SMANTIS to regulate monocytic cell functions [RNA_THP1_diff_OCL] 6 samples shares thp1

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.