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Transcriptomic profiling of tumor-infiltrating and lymph node-derived Treg and B cells in Foxp3-Cre-YFP and Foxp3-Cre-YFP Appl2f/f melanoma-bearing Mice

GSE294977 Mus musculus (mouse) RNA-seq (gene expression) 24 samples Submitted 2026/01/28 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 24 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
24 samples: 8 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)
Tregs are a critical target for developing anti-tumor immunotherapy, however, they are also critical for maintaining systemic immune tolerance and homeostasis. It remains a formidable challenge to specifically disable Tregs in the tumor microenvironment without compromising systemic immune tolerance. An ideal target is that barely expressed or dispensable in peripheral Tregs but significantly increased and critical for the immunosuppressive activity of tumor infiltrated Tregs (TIL-Tregs).
Read the full summary ↓
In an attempt to search for specific targets that mediate TIL-Tregs fitness in the tumor microenvironment, we performed RNA-seq of TIL-Tregs and Tregs from the draining lymph nodes (dLN-Tregs) of mice bearing B16-F0 melanoma.
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 GSE294977_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 PRJNA1252126 and SRA study SRP579474. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly in triplicate
LN_KO_B ×3 LN_KO_Treg ×3 Tu_KO_B ×3 Tu_KO_Treg ×3 LN_WT_B ×3 LN_WT_Treg ×3 Tu_WT_B ×3 Tu_WT_Treg ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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
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