GEO series

CTLA-4 Blockade Shifts the B Cell Repertoire Towards Autoimmunity

GSE307261 Homo sapiens (human) RNA-seq (gene expression) 58 samples Submitted 2025/09/10 Platform GPL18573

At a glance

RNA-seq (gene expression) · human · 58 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: 58 samples: 58 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: CTLA-4 blockade shifts the B cell repertoire toward autoimmunityThe Journal of clinical investigation · 2025

Summary (written by the submitters)

Checkpoint inhibitors targeting CTLA-4 and PD-1 revolutionized the treatment of cancer patients but their use is limited by the emergence of immune-related adverse events (irAE). We assessed autoreactive B cell frequencies in the blood of cancer patients before and after treatment with checkpoint inhibitors by testing the reactivity of recombinant antibodies cloned from single B cells.

Read the full summary ↓

We found that anti-PD-1 and anti-CTLA-4 combination therapy induced the emergence of autoreactive mature naïve B cells, whereas central B-cell tolerance remained functional. In contrast, anti-PD-1 alone did not alter autoreactive B cell counterselection. Anti-CTLA-4 injections in humanized mice also resulted in the production of autoreactive B cells, whereas anti-PD-1 did not. We conclude that CTLA-4 but not PD-1 is required for the removal of developing autoreactive mature naïve B cells and that CTLA-4 blockade broadens the peripheral B cell repertoire which likely contains clones that promote not only irAEs but also anti-tumor responses.

Published in

CTLA-4 blockade shifts the B cell repertoire toward autoimmunity

Çakan E, Wang M, Dai Y et al. · The Journal of clinical investigation 2025 · PMID 41026527 · doi:10.1172/JCI189074

This dataset

Open GSE307261 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 GSE307261_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 PRJNA1315040 and SRA study SRP617525. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41026527) ↗

Study design

58 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 58 sample titles: 58 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

GSM9220069 p134 B cells (week 6) scRNA-seq
GSM9220070 p134 B cells (week 6) scBCR-seq
GSM9220071 p134 B cells (7 months) scRNA-seq
GSM9220072 p134 B cells (7 months) scBCR-seq
GSM9220073 p134 B cells (day 0) scRNA-seq
GSM9220074 p134 B cells (day 0) scBCR-seq
GSM9220075 p134 T cells (week 6) scRNA-seq
GSM9220076 p134 T cells (week 6) scTCR-seq
GSM9220077 p134 T cells (7 months) scRNA-seq
GSM9220078 p134 T cells (7 months) scTCR-seq
GSM9220079 p134 T cells (day 0) scRNA-seq
GSM9220080 p134 T cells (day 0) scTCR-seq
GSM9220081 p145 B cells (week 6) scRNA-seq
GSM9220082 p145 B cells (week 6) scBCR-seq
GSM9220083 p145 B cells (7 months) scRNA-seq
GSM9220084 p145 B cells (7 months) scBCR-seq
GSM9220085 p145 B cells (day 0) scRNA-seq
GSM9220086 p145 B cells (day 0) scBCR-seq
GSM9220087 p145 T cells (week 6) scRNA-seq
GSM9220088 p145 T cells (week 6) scTCR-seq
GSM9220089 p145 T cells (7 months) scRNA-seq
GSM9220090 p145 T cells (7 months) scTCR-seq
GSM9220091 p145 T cells (day 0) scRNA-seq
GSM9220092 p145 T cells (day 0) scTCR-seq
GSM9220093 p196 B cells (week 6) scRNA-seq
GSM9220094 p196 B cells (week 6) scBCR-seq
GSM9220095 p196 B cells (7 months) scRNA-seq
GSM9220096 p196 B cells (7 months) scBCR-seq
GSM9220097 p196 T cells (week 6) scRNA-seq
GSM9220098 p196 T cells (week 6) scTCR-seq
GSM9220099 p196 T cells (7 months) scRNA-seq
GSM9220100 p196 T cells (7 months) scTCR-seq
GSM9220101 p196 T cells (day 0) scRNA-seq
GSM9220102 p196 T cells (day 0) scTCR-seq
GSM9220103 p326 B cells (week 6) scRNA-seq
GSM9220104 p326 B cells (week 6) scBCR-seq
GSM9220105 p326 B cells (7 months) scRNA-seq
GSM9220106 p326 B cells (7 months) scBCR-seq
GSM9220107 p326 B cells (day 0) scRNA-seq
GSM9220108 p326 B cells (day 0) scBCR-seq

+ 18 more — browse all 58 samples with per-sample file links →

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GSE272734 Combination anti-PD-1 and anti-CTLA-4 therapy generates waves of clonal responses that include progenitor-exhausted CD8 T cells [dataset 2] 40 samples shares ctla-4
GSE310581 Spatially controlled enhanced anti-tumor efficacy via CAR T cells engineered with a CTLA-4-based autoregulated circuit 12 samples shares ctla-4
GSE272993 Combination anti-PD-1 and anti-CTLA-4 therapy generates waves of clonal responses that include progenitor-exhausted CD8 T cells [dataset 1] 360 samples shares ctla-4
GSE176021 Distinct transcriptional programs characterize neoantigen-specific T cells in lung cancers treated with neoadjuvant PD-1 blockade [single-cell RNA-seq] 110 samples shares blockade
GSE278330 Systemic IL-23 blockade downregulates IL-23 receptor-expressing Type 17 T-cell subsets and upregulates regulatory gene expression in myeloid cells in human psoriasis skin 63 samples shares blockade
GSE307213 CDK10 suppression sensitizes cells to CDK12/13 blockade 48 samples shares blockade
GSE225620 Blood-based Genomic and Cellular Determinants of Response to Neoadjuvant PD-1 Blockade in Patients with Non-Small-Cell Lung Cancer 43 samples shares blockade

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