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Feeder-free generation of functional dendritic cells from human pluripotent stem cells

GSE309916 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2026/05/13 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 10 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
10 samples: 2 × Donor_1_cDC vs 2 × Donor_2_cDC vs 2 × Donor_3_cDCGroups 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)
The scarcity of primary conventional dendritic cells (cDCs) and the limited effectiveness of monocyte-derived dendritic cells (moDCs) have long hindered progress in human dendritic cell research and immunotherapy. We developed a feeder-free differentiation platform that generates CD1c⁺CD141⁺ hPSC-cDCs phenotypically aligned with CD141⁺ tissue-resident cDC2 subsets found in human tissues.
Read the full summary ↓
We further optimized the differentiation process using a Design-of-Experiments framework to refine cytokine and serum conditions, enhancing differentiation efficiency while reducing cytokine demand. These hPSC-cDCs exhibit efficient antigen uptake, defined cytokine responses, and robust priming of antigen-specific CD8⁺ T cell proliferation and effector differentiation, outperforming moDCs in direct comparison. Together, this work establishes a robust, and generalizable platform for mechanistic studies and translational development of dendritic cell-based vaccines and standardized ex vivo T cell expansion.
This dataset
Open GSE309916 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 GSE309916_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 PRJNA1363987 and SRA study SRP644521. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
2 × Donor_1_cDC vs 2 × Donor_2_cDC vs 2 × Donor_3_cDC

Supports a between-group comparison across 6 samples.

How we read this: 3 replicated groups read from 10 sample titles; they account for 6 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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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.