GEO series

AS04 drives superior cross-protective antibody response by increased NOTCH signaling of Dendritic Cells and proliferation of memory B cells

GSE299801 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2025/07/29 Platform GPL24676

At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 16 samples

What it is: ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism: Homo sapiens (human)
Samples: 16 samples: 16 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: AS04 drives superior cross-protective antibody response by increased NOTCH signaling of dendritic cells and proliferation of memory B cellsFrontiers in immunology · 2025

Summary (written by the submitters)

The Gardasil-4® vaccine targets HPV types 6, 11, 16 and 18 and is formulated with amorphous alum. Cervarix® targets HPV types 16 and 18 using AS04 (Al(OH)3 + TLR4 agonist MPL) to enhance immune response. Cervarix elicits higher cross-protection against other high-risk HPV types, likely mediated by AS04. To investigate mechanisms of cross-neutralizing potential, six monozygotic twins (12 females aged 9-13 years) were vaccinated with either Cervarix or Gardasil-4 (2 doses, 6 months apart).

Read the full summary ↓

Serum neutralizing antibody titers against HPV 6,16,18,31,33,45,52, and 58 were assessed pre-vaccination and 7 days post-second dose. Multi-omic single cell RNA and ATAC sequencing of PBMCs was performed at the latter timepoint. Cervarix generated higher cross-neutralizing antibody titers than Gardasil-4. Higher frequencies of dendritic cells and memory B cells were observed. Gene Set Enrichment Analysis (GSEA) indicated enhanced pathways related to NOTCH2 signaling in DCs and cell cycling/RNA translation in B cells, correlating positively with cross-neutralizing antibody titers. Increased chromatin accessability in genes related to NOTCH signaling in cDC1 was also observed. Cervarix-vaccinated subjects showed increased DC-to-memory B signaling, through upregulation of NOTCH ligands. Engagement of NOTCH was associated to BCL2 expression in memory B cells, supporting an anti-apoptotic state, and resulted in increased IgG4 expression by B memory cells. Increased DC signaling, including NOTCH, through AS04 in Cervarix supports cell survival and sustained RNA translation in memory B cells, 7 days post-vaccination. This may enhance adaptive immune cell maturation, providing a mechanism that can lead to improved cross-reactivity.

Published in

AS04 drives superior cross-protective antibody response by increased NOTCH signaling of dendritic cells and proliferation of memory B cells

D'Onofrio V, Santana AC, Pauwels M et al. · Frontiers in immunology 2025 · PMID 40808939 · doi:10.3389/fimmu.2025.1623405

This dataset

Open GSE299801 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 GSE299801_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1276556 and SRA study SRP591944. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40808939) ↗

Study design

16 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 16 sample titles: 16 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

GSM9046296 Multiome, Subject 5, PBMC, vaccinated, GEX
GSM9046297 Multiome, Subject 5, PBMC, vaccinated, ATAC
GSM9046298 Multiome, Subject 6, PBMC, vaccinated, GEX
GSM9046299 Multiome, Subject 6, PBMC, vaccinated, ATAC
GSM9046300 Multiome, Subject 7, PBMC, vaccinated, GEX
GSM9046301 Multiome, Subject 7, PBMC, vaccinated, ATAC
GSM9046302 Multiome, Subject 8, PBMC, vaccinated, GEX
GSM9046303 Multiome, Subject 8, PBMC, vaccinated, ATAC
GSM9046304 Multiome, Subject 9, PBMC, vaccinated, GEX
GSM9046305 Multiome, Subject 9, PBMC, vaccinated, ATAC
GSM9046306 Multiome, Subject 10, PBMC, vaccinated, GEX
GSM9046307 Multiome, Subject 10, PBMC, vaccinated, ATAC
GSM9046308 Multiome, Subject 13, PBMC, vaccinated, GEX
GSM9046309 Multiome, Subject 13, PBMC, vaccinated, ATAC
GSM9046310 Multiome, Subject 14, PBMC, vaccinated, GEX
GSM9046311 Multiome, Subject 14, PBMC, vaccinated, ATAC

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