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Preclinical efficacy of combination therapy with allogeneic induced pluripotent stem cell-derived invariant natural killer T and α-galactosylceramide-pulsed antigen-presenting cells

GSE292489 Homo sapiens (human) Single-cell RNA-seq 20 samples Submitted 2026/03/31 Platform GPL28038
At a glance

Single-cell RNA-seq · human · 20 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism
Homo sapiens (human)
Samples
20 samples: 10 conditions, mostly in duplicateGroups 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
Preclinical efficacy of combination therapy with allogeneic induced pluripotent stem cell-derived invariant natural killer T and α-galactosylceramide-pulsed antigen-presenting cellsStem cell research & therapy · 2026
Summary (written by the submitters)
Invariant natural killer T (iNKT) cells, upon activation, exhibit antitumor roles by bridging innate and acquired immunity. To overcome the challenges in producing iNKT cells from patients with cancer, we previously developed allogeneic human induced pluripotent stem cell-derived iNKT (iPSC-iNKT) cells. However, the activation of iPSC-iNKT cells by glycolipid ligands remains a critical step for iNKT cell-mediated cancer therapy.
Read the full summary ↓
To show the effect of iPSC-iNKT cell-mediated antitumor immunity, in this preclinical study, by taking advantage of a human immune cell-transplanted patient-derived xenograft model using human IL-7/15 knock-in NSG mice, we demonstrate that a combination of iPSC-iNKT cells and α-galactosylceramide-pulsed antigen-presenting cells (αGalCer/APC) induces robust antitumor effects. Single-cell analysis of tumor-infiltrating lymphocytes revealed that this combination therapy uniquely expanded tumor-reactive memory-phenotype CD4 and CD8 T cells. Taken together, upon activation by αGalCer/APC, iPSC-iNKT cells are capable of effectively inducing antitumor T cell immunity, making them a promising tool for generating personalized antitumor T cell immunity.
Published in
Preclinical efficacy of combination therapy with allogeneic induced pluripotent stem cell-derived invariant natural killer T and α-galactosylceramide-pulsed antigen-presenting cells
Aoki T, Kobayashi M, Okoshi M et al. · Stem cell research & therapy 2026 · PMID 41904478 · doi:10.1186/s13287-026-04994-7
This dataset
Open GSE292489 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 GSE292489_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 PRJNA1238856 and SRA study SRP571945. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41904478) ↗
Study design
10 conditions, mostly in duplicate
GEX_TIL in no treatment group ×2 GEX_TIL in DC/Gal treatment group ×2 GEX_TIL in iPSC-iNKT treatment group ×2 GEX_TIL in iPSC-iNKT+DC/Gal treatment group ×2 GEX_Donor T cells ×2 VDJ_TIL in no treatment group ×2 VDJ_TIL in DC/Gal treatment group ×2 VDJ_TIL in iPSC-iNKT treatment group ×2 +2 more

Supports a between-group comparison across 20 samples.

How we read this: 10 replicated groups read from 20 sample titles; they account for 20 of them. 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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