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Single-cell dynamics of breakthrough toxicities following anakinra prophylaxis for axicabtagene ciloleucel treatment in lymphoma

GSE246490 Homo sapiens (human) Single-cell RNA-seq 23 samples Submitted 2025/05/14 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 23 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)
Samples
23 samples: 15 distinct titles, 2 of them repeatedGroups 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 dynamics of breakthrough toxicities after anakinra prophylaxis for axicabtagene ciloleucel in lymphomaBlood advances · 2025
Summary (written by the submitters)
Chimeric antigen receptor T cells have transformed the treatment of multiple hematologic malignancies, but are limited in application due to treatment-related toxicities. Cytokine release syndrome (CRS) and neurotoxicity (NT) are the primary toxicities associated with these therapies and are thought to be mediated by broad immune activation due to robust T-cell expansion.
Read the full summary ↓
Current treatment of these toxicities utilize anti-IL-6 directed therapy and/or systemic glucocorticoids to mitigate the consequences of this complex inflammatory cascade. We sought to use anakinra, an IL-1R antagonist, as a prophylactic strategy to prevent clinically meaningful CRS/NT, defined as grade 2 or higher toxicity necessitating clinical intervention. Although our study, in line with others, demonstrated that IL-1R antagonism is insufficient to prevent such toxicities entirely, we were able to gain insight into the molecular immune signaling associated with breakthrough CRS & NT in the presence of anakinra prophylaxis using our scRNA dataset of patients treated with and without IL-1R antagonism. We demonstrate that IL-4 and IL-10 anti-inflammatory pathways in infused CAR-T products of both anakinra and non-anakinra cohorts were negatively associated with grade 2+ toxicities. We also found that expression of IFNg pathways and ligand-receptor activities, as well as cytokine levels of IFNg and CXCL10 in CD14+ monocytes, were significantly enriched in patients with breakthrough toxicity in the anakinra cohort. This correlated with an increase in IFNg in the peripheral blood of patients with breakthrough toxicities, among other cytokines. These data identify IFNg as a potential key mechanism in the development of CAR-T cell-associated toxcities and suggest that this pathway is also targetable and not inhibited by anakinra alone.
Published in
Single-cell dynamics of breakthrough toxicities after anakinra prophylaxis for axicabtagene ciloleucel in lymphoma
Frigault MJ, Yao N, Berger TR et al. · Blood advances 2025 · PMID 39928957 · doi:10.1182/bloodadvances.2024015161
This dataset
Open GSE246490 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 GSE246490_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 PRJNA1033334. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39928957) ↗
Study design
15 distinct titles, 2 of them repeated
Pool_CARneg ×6 Pool_IP ×4

How we read this: Read from 23 sample titles: 15 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
Datasets on a similar topic

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