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Single-cell sequencing reveals dynamic immune features of paraneoplastic pemphigus in a patient with follicular lymphoma

GSE318717 Homo sapiens (human) Single-cell RNA-seq 10 samples Submitted 2026/03/18 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 10 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Topic
Follicular lymphomaThis series is part of our curated briefing on it.
Samples
10 samples: 10 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
Single-cell sequencing reveals dynamic immune features of paraneoplastic pemphigus in a patient with follicular lymphomaFrontiers in immunology · 2026
Summary (written by the submitters)
Background: Paraneoplastic pemphigus (PNP) is a highly fatal autoimmune blistering disease that commonly occurs in patients with underlying benign or malignant neoplasms. It poses significant challenges for diagnosis and treatment. To date, the cellular and molecular mechanisms underlying the pathogenesis of PNP remain largely unclear.
Read the full summary ↓
Objective: This study aims to elucidate the cellular and molecular mechanisms of PNP, particularly when it occurs secondary to lymphoma, by analyzing the dynamic immune landscape throughout the course of treatment. Method: We performed single-cell transcriptome sequencing and single-cell T cell receptor (TCR) analysis on peripheral blood mononuclear cells (PBMCs) and bone marrow cells (BMCs) obtained from a patient with follicular lymphoma (FL) accompanied by PNP. Samples were collected at three critical time points: before treatment, during treatment, and after successful treatment. Result: Before treatment, we observed a specific enrichment of ITGAL+ T cells, abnormal γδT cell subtypes, and BCL2+ B cells in PBMCs. Notably, naïve T cells and an abnormal B cell subtype were also enriched in BMCs. The single-cell transcriptome results mapped the lymphoma-associated tumor microenvironment and revealed post-treatment immune reconstitution. This reconstitution involved activated DNA damage and T cell immune responses, which was further supported by the observation of a gradually expanded TCR clone as the treatment progressed. Conclusion: Our study delineates the dynamic immune landscape in a patient with FL-associated PNP throughout treatment, demonstrating that successful treatment correlates with immune reconstitution involving specific T cell responses and TCR clone expansion. These findings provide novel insights into the cellular and molecular mechanisms of PNP, especially in cases secondary to lymphoma.
Published in
Single-cell sequencing reveals dynamic immune features of paraneoplastic pemphigus in a patient with follicular lymphoma
Wei R, Liu B, Liu Y et al. · Frontiers in immunology 2026 · PMID 41929499 · doi:10.3389/fimmu.2026.1733718
This dataset
Open GSE318717 in finder → Find more human RNA-seq datasets → Follicular lymphoma landscape →
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 GSE318717_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: 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 PRJNA1419827. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41929499) ↗
Study design
10 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 10 sample titles: 10 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
More Follicular lymphoma datasets

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