← BioTransfer GEO Dataset Finder
GEO series

Targeting CD206+ macrophages disrupts the establishment of a key anti-tumor immune axis [Bulk RNA-seq]

GSE281471 Homo sapiens (human) RNA-seq (gene expression) 243 samples Submitted 2024/11/08 Platform GPL20301Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 243 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
243 samples: 243 samples, each with a distinct title — no replicated groupsGroups 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
Targeting CD206+ macrophages disrupts the establishment of a key antitumor immune axisThe Journal of experimental medicine · 2025
Summary (written by the submitters)
The direct and indirect effects of targeting specific tumor-associated macrophage (TAM) subsets in cancer are not well-defined. TAM targeting strategies are frequently based on the ‘M1’ or ‘M2’ polarization categories, even as substantial data challenges this binary modeling of macrophage cell state. One molecule consistently referenced as a delineator of a putative immunosuppressive ‘M2’ state is the surface protein CD206.
Read the full summary ↓
We thus made a novel conditional CD206 (Mrc1) knock-in mouse to specifically visualize and/or deplete CD206+ TAMs and assess their correspondence with pro-tumoral immunity. Early, but not late depletion of CD206+ macrophages and monocytes (here, ‘Mono/Macs’) led to an indirect loss of a key anti-tumor network of NK cells, conventional type I dendritic cells (cDC1) and CD8 T cells. Among myeloid cells, we found that the CD206+ TAMs are the primary producers of CXCL9, and able to differentially attract activated CD8 T cells. In contrast, a population of stress-responsive TAMs (“Hypoxic” or Spp1+) and immature monocytes, which lack CD206 expression and become prominent following early depletion, expressed markedly diminished levels of CXCL9. Those NK and CD8 T cells which enter CD206-depleted tumors express vastly reduced levels of the corresponding receptor Cxcr3, the cDC1-attracting chemokine Xcl1 and cDC1 growth factor Flt3l transcripts. Consistent with the loss of this critical network, early CD206+ TAM depletion decreased tumor control by antigen specific CD8 T cells in mice. Likewise, in humans, the CD206Replete, but not the CD206Depleted Mono/Mac gene signature correlated robustly with CD8 T cell, NK cell and stimulatory cDC1 gene signatures and transcriptomic signatures skewed towards CD206Replete Mono/Macs associated with better survival. Together, these findings negate the unqualified classification of CD206+ ‘M2-like’ macrophages as immunosuppressive and provide further evidence of the context-dependence of macrophage function in tumors.
Published in
Targeting CD206+ macrophages disrupts the establishment of a key antitumor immune axis
Ray A, Hu KH, Kersten K et al. · The Journal of experimental medicine 2025 · PMID 39601781 · doi:10.1084/jem.20240957
This dataset
Open GSE281471 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 GSE281471_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 PRJNA1183904 and SRA study SRP544117. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39601781) ↗
Study design
243 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 243 sample titles: 243 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

+ 203 more — browse all 243 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

Share this dataset

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.