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Comparison of axicabtagene ciloleucel and tisagenlecleucel patient CAR-T cell products by single cell RNA sequencing

GSE297676 Homo sapiens (human) Single-cell RNA-seq 57 samples Submitted 2025/07/30 Platform GPL30173
At a glance

Single-cell RNA-seq · human · 57 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
57 samples: 57 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
Comparison of axicabtagene ciloleucel and tisagenlecleucel patient CAR-T cell products by single-cell RNA sequencingJournal for immunotherapy of cancer · 2025
Summary (written by the submitters)
Background: Autologous CD19 CAR T cell therapy leads to durable responses and improved survival in patients with relapsed or refractory large B cell lymphoma (R/R LBCL). Among approved CAR T cell products, axicabtagene ciloleucel (axi-cel; CD19/CD28) has greater real-world efficacy and cytokine-associated toxicity than tisagenlecleucel (tisa-cel; CD19/4-1BB), for reasons that are poorly understood.
Read the full summary ↓
Methods: Here we report single cell RNA sequencing (scRNA-seq) of 57 pre-infusion CAR T cell products from axi-cel (n=39) and tisa-cel (n=18) patients treated as standard-of-care for R/R LBCL, and their biological associations with clinical outcomes. In vitro CAR manufacturing conditions mimicking those known for axi-cel and tisa-cel were performed using CD19/CD28z or CD19/4-1BBz constructs. Results: ScRNA-seq revealed that axi-cel and tisa-cel are markedly different products. Axi-cel is comprised of more CD4 central memory, CD8 central memory, and CD8 effectors, whereas tisa-cel is comprised of more proliferative CD4 and CD8 cells. Across multiple T cell subsets, axi-cel had greater expression of immune response pathways and protein synthesis and trafficking pathways vs. tisa-cel. On comparison of infusion product CAR transgene-positive (CAR+) cells to CAR transgene-negative (CAR-) T cells, axi-cel CAR+ cells had vastly different gene expression than axi-cel CAR- cells. Unexpectedly, tisa-cel CAR+ cells were highly similar to tisa-cel CAR- cells. Under recapitulated CAR-T manufacturing conditions known to be utilized for axi-cel and tisa-cel, we found that CAR+ cells differed from CAR- cells early after manufacturing yet became more similar to CAR- cells after prolonged expansion. Prolonged time in expansion culture, as utilized during tisa-cel manufacturing, greatly decreased naïve and central memory T cell subsets. Conclusions: Following manufacture, axi-cel is less differentiated and has greater immune activation compared to tisa-cel, potentially accounting for its greater efficacy and toxicity in patients. Our data support the conclusion that tisa-cel is adversely affected by its manufacturing rather than by the CAR construct.
Published in
Comparison of axicabtagene ciloleucel and tisagenlecleucel patient CAR-T cell products by single-cell RNA sequencing
Yu X, Jain MD, Menges MA et al. · Journal for immunotherapy of cancer 2025 · PMID 40730421 · doi:10.1136/jitc-2025-011807
This dataset
Open GSE297676 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 GSE297676_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 PRJNA1265670 and SRA study SRP586653. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40730421) ↗
Study design
57 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 57 sample titles: 57 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

+ 17 more — browse all 57 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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