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XCR1+ and CD11b+ migratory dendritic cells cooperate for the crosspriming of intratumoral CD8+ T cells with a tissue-resident memory phenotype [RNA-Seq]

GSE337601 Mus musculus (mouse) RNA-seq (gene expression) 36 samples Submitted 2026/07/07 Platform GPL34328
At a glance

RNA-seq (gene expression) · mouse · 36 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
Mus musculus (mouse)
Samples
36 samples: 11 conditions, mostly in triplicateGroups 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 composition and diversity of tumor-infiltrating CD8+ T cell populations have important consequences on the development of anti-tumor immunity. In a murine model of lung cancer, we have addressed the role of dendritic cell subsets on the generation of various types of tumor-infiltrating CD8+ T cells. We show that CD44+PD1- effector and PD1+TIM3+ exhausted, tumor-infiltrating CD8+ T cells require XCR1+ DC1s but not IRF4-dependent CD11b+ DC2s.
Read the full summary ↓
By contrast, CD103+CD69+ TRM-like, tumor-infiltrating CD8+ T cells require both DC1s and DC2s. The same requirement is found in tumor-draining lymph nodes where we identify CD103+ TRM-like precursors that are dependent on both XCR1+ DC1s and CD11b+, migratory DC2s. Mechanistically, we evidence that both types of migratory DCs cooperate. Mild TCR triggering by low MHCI-peptide density at the surface of cross-presenting migratory DC2s and low IL-12 support TGFb-dependent TRM specification in lymph nodes. High TCR triggering and high MHCI-peptide density at the surface of cross-presenting migratory DC1s and high IL-12 support proliferative expansion and CXCR6 acquisition. Altogether, these findings highlight the induction of intratumoral TRM-like cells under the collective aegis of multiple DCs subsets within tumor-draining lymph nodes reconciliating TRM phenotype instruction with proliferative expansion.
This dataset
Open GSE337601 in finder → Find more mouse 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 GSE337601_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 PRJNA1490476 and SRA study SRP715499. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
11 conditions, mostly in triplicate
Divided_OT1_CD103neg, DC1act, ×4 Divided_OT1_CD103pos, DC1act, ×4 Divided_OT1_CD103neg, DC2act, ×4 Divided_OT1_CD103pos, DC2act, ×4 Not_Trm_PD1neg, ×3 Not_Trm_PD1_pos_Tim3_neg, ×3 Not_Trm_PD1_pos_Tim3_pos, ×3 Trm_Tim3_neg, ×3 +3 more

Supports a between-group comparison across 36 samples.

How we read this: 11 replicated groups read from 36 sample titles; they account for 36 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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