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Identification of a novel PDC-E2 epitope in Primary Biliary Cholangitis and application for engineered Treg therapy

GSE281263 Homo sapiens (human) Single-cell RNA-seq 632 samples Submitted 2025/08/01 Platform GPL30173
At a glance

Single-cell RNA-seq · human · 632 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
632 samples: 632 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
Identification of a novel PDC-E2 epitope in primary biliary cholangitis: Application for engineered Treg therapyJournal of autoimmunity · 2024
Summary (written by the submitters)
Background and Aims: Primary biliary cholangitis (PBC) is a chronic autoimmune liver disease, characterized by progressive destruction of small intrahepatic bile ducts and portal inflammation. Treatment options are limited with reliance on liver transplantation in advanced cases. The adaptive immune response is implicated in disease pathogenesis by both the presence of anti-mitochondrial antibodies targeting the E2 subunit of the pyruvate dehydrogenase complex (PDC-E2), in 90-95% of patients, and T cells infiltrating the portal tracts in affected individuals.
Read the full summary ↓
Here, we examined T cell responses to peptides derived from PDC-E2, with a focus on CD4 T cell responses restricted to HLA Class II DRB4*0101, an allele found in 62% of PBC patients, to uncover PDC-E2 epitopes that could be used for Engineered Treg therapy. Approach and Results: Using an Activation Induced Marker assay and single cell RNA-sequencing, we found clonal expansion of CD4 T cells reactive to PDC-E2 epitopes in both conventional (Tconv) and regulatory T (Treg) cells. The TCR repertoires were non-overlapping and private and included TCRs specific for a novel PDC-E2 epitope restricted to DRB4*0101. CD4 Tconv cells from healthy and PBC subjects that responded to the PDC-E2 novel epitope showed phenotypic heterogeneity skewed towards T follicular helper cell subset. Using a TCR specific for this novel PDC-E2 epitope, we created an engineered Treg that suppressed PDC-E2 specific polyclonal CD4 Tconv cells from PBC patients. Conclusions: This study advances the knowledge of PDC-E2 specific T cell responses and introduces a novel PDC-E2 epitope recognized by reactive Tconv and Treg cells. Generation of engineered Treg specific for this epitope with effective suppressive activity provides therapeutic potential as Treg therapy targeting PDC-E2 in PBC.
Published in
Identification of a novel PDC-E2 epitope in primary biliary cholangitis: Application for engineered Treg therapy
Tewari R, Yang SJ, McClain ED et al. · Journal of autoimmunity 2024 · PMID 39476446 · doi:10.1016/j.jaut.2024.103327
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 GSE281263_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: 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 PRJNA1182824 and SRA study SRP543654. Searching any of these in the dataset finder brings you back here.

Study design
632 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 the first 400 of 632 sample titles: 400 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

+ 592 more — browse all 632 samples with per-sample file links →

Datasets on a similar topic

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