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CD47 Expression in Solid Tumors Correlates with Phagocytic Tumor-Associated Macrophage Gene Signature

GSE296861 Homo sapiens (human) RNA-seq (gene expression) 109 samples Submitted 2025/09/04 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 109 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
109 samples
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
CD47 expression in solid tumors correlates with phagocytic tumor-associated macrophage gene signatureFrontiers in immunology · 2025
Summary (written by the submitters)
CD47 is a “don’t eat me” signal that is frequently overexpressed in tumors to evade phagocytosis by tumor associated macrophages (TAM). Investigational agents targeting CD47, such as magrolimab, aim to induce phagocytosis of tumor cells by TAMs. Previously, two functionally defined key TAM subsets have been identified: complement C1q C chain positive (C1QC) TAMs, which display pro-phagocytic activity, and secreted phosphoprotein 1 positive (SPP1) TAMs that express pro-angiogenic markers. Here we characterize CD47 expression and its relationship with tumor macrophages in solid tumor samples.
Published in
CD47 expression in solid tumors correlates with phagocytic tumor-associated macrophage gene signature
van Buuren N, Xu M, Zhang Y et al. · Frontiers in immunology 2025 · PMID 41415295 · doi:10.3389/fimmu.2025.1699237
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 GSE296861_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 PRJNA1261839 and SRA study SRP584672. Searching any of these in the dataset finder brings you back here.

Study design
A cohort of 109 individual samples

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

How we read this: Sample titles run Hu-P-3655 … Hu-P-5088 and carry no group information.

Samples in this study

+ 69 more — browse all 109 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.