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Macrophages transfer functional target-cell proteins to their surface during live cell uptake

GSE329293 Homo sapiens (human) RNA-seq (gene expression) 20 samples Submitted 2026/06/10 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 20 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
20 samples: 20 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.
Summary (written by the submitters)
A cell’s proteome is assumed to reflect its transcriptional and translational activity. Macrophages regularly acquire xenobiotic material from neighboring cells, which is thought to result in degradation of the material. However, increasing lines of evidence suggest that not all uptaken material is degraded and that other transfer-like processes also occur.
Read the full summary ↓
Field standard technologies are unable to rigorously report on precisely how and by whom the macrophage protein repertoire is altered during these interactions, leaving unresolved the extent to which non-degradative processes contribute to altered phenotypes. Here, we leveraged chemical tools and proteomics to show that intact target cancer cell surface proteins are transferred to the macrophage cell surface at functionally impactful levels in a manner associated with live cell uptake. Widespread acquisition of proteins during cell uptake reengineers the macrophage cell surface proteome and is a transcriptionally silent, cell non-autonomous process with the potential to alter metabolic uptake.
This dataset
Open GSE329293 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 GSE329293_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 PRJNA1458308 and SRA study SRP695417. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
20 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 20 sample titles: 20 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
Datasets on a similar topic

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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.