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The combination of IL-7Ra and CCR7 is a highly specific marker to identify and purify homeostatically matured cDC2s (DC2hm).

GSE287912 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2026/02/23 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 14 distinct titles, 4 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
Homeostatic maturation programs drive human cDC2s into a tolerogenic stateImmunity · 2026
Summary (written by the submitters)
To explore whether co-expression of CCR7 and IL7R can better define DC2hm (homeostatically matured cDC2) than either marker alone. We sorted IL7R-CCR7+, IL7R+CCR7-, IL7R+CCR7+ DCs as well as CD141+ cDC1 and CD1c+ cDC2 from Lin-CD11c+HLA-DR+ splenocytes of 4 healthy donors and performed bulk RNA-seq. The results showed that the IL7R+CCR7+ double-positive subset showed the highest expression of DC2hm markers among the five subpopulations, supporting the hypothesis that combining CCR7 and IL7R better defines DC2hm.
Published in
Homeostatic maturation programs drive human cDC2s into a tolerogenic state
Lu M, Han R, Yang H et al. · Immunity 2026 · PMID 41713421 · doi:10.1016/j.immuni.2026.01.028
This dataset
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.

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 GSE287912_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1215268 and SRA study SRP559625. Searching any of these in the dataset finder brings you back here.

Study design
14 distinct titles, 4 of them repeated
Sorted cDCs, Dnr1_cDC ×2 Sorted cDCs, Dnr2_cDC ×2 Sorted cDCs, Dnr6_cDC ×2 Sorted cDCs, Dnr12_cDC ×2

How we read this: Read from 18 sample titles: 14 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
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