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IL-36γ Armored CAR T Cells Reprogram Neutrophils to Induce Endogenous Antitumor Immunity

GSE307110 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2026/03/01 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 15 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
15 samples: 12 distinct titles, 3 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.
Summary (written by the submitters)
Chimeric antigen receptor (CAR) T cells are ineffective against solid tumors due to obstacles of antigen heterogeneity and the immunosuppressive tumor microenvironment (TME). Previous efforts focused on enhancing cytotoxicity and persistence of CAR T cells, while the feasibility of improving their therapeutic efficacy by leveraging the modulatory effects of CAR T cells on host anti-tumor immunity remains unclear.
Read the full summary ↓
Here, we report that IL-36γ armored CAR T cells eradicated primary solid tumors and enabled rejection of rechallenged antigen-negative tumors. IL-36γ armored CAR T cells favorably modulated the TME and reprogrammed unique neutrophil subsets with tumoricidal ability and antigen-(cross)presenting functions, resulting in the induction of endogenous T cells recognizing tumor antigens beyond CAR-targeted antigens. Our study demonstrates that neutrophil engagement by CAR T cells is a critical step in the establishment of the cancer-immunity cycle and introduces a broadly applicable method to overcome key barriers to adoptive cell therapies for solid tumors.
This dataset
Open GSE307110 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 GSE307110_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 PRJNA1314506 and SRA study SRP616809. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 distinct titles, 3 of them repeated
1H6 ×2 2H6 ×2 3H6 ×2

How we read this: Read from 15 sample titles: 12 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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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.