← BioTransfer GEO Dataset Finder
GEO series

Transcriptome Response to Autoantibodies in Human Primary Epidermis Keratinocyte Model for Pemphgus Vulgaris

GSE288492 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2025/02/10 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 24 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
24 samples: 8 conditions, mostly in triplicateGroups 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)
Pemphigus vulgaris (PV) is an autoimmune disease caused by autoantibodies (AAbs) targeting Desmoglein 1 (DSG1) or Desmoglein 3 (DSG3) on keratinocytes, leading to disrupted cell-cell adhesion and epidermal blistering. To investigate the early signaling events triggered by AAb binding, we examined transcriptomic responses in a human primary epidermis keratinocyte (HPEK) model for PV.
Read the full summary ↓
After incubating the single-chain variable fragment (scFv) PX43, which targets DSG1 and DSG3, and human IgG as control for 5h, 10h and 24h, differentially expressed genes (DEGs) and regulated pathways was analyzed using DESeq2 and pathway enrichment analysis. Few significantly differentially expressed DEGs (under 10) were identified of PX43 compared to hIgG at all three time points (5h, 10h and 24h) with adjusted pvalue below 0.05 and |log2FC| >1. Upregulated inflammatory related pathways including TNFα signaling were identified only at 24h. Correlation analysis of the log2 transformed transcripts per million (TPM) shows the very high positive correlation of PX43 and hIgG at all time points (spearman correlation above 0.9) These findings indicate that AAbs targeting DSG1 and DSG3 do not drive broad transcriptomic or proteomic changes at the HPEK model.
This dataset
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.

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 GSE288492_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1217866 and SRA study SRP560908. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly in triplicate
2D_hIgG_5h ×3 2D_PX43_5h ×3 2D_hIgG_10h ×3 2D_PX43_10h ×3 2D_hIgG_24h ×3 2D_PX43_24h ×3 2D_hIgG_48h ×3 2D_PX43_48h ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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
Datasets on a similar topic

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.