← BioTransfer GEO Dataset Finder
GEO series

The effects of ATP and CD39 inhibition in monocyte-derived dendritic cells.

GSE287531 Homo sapiens (human) RNA-seq (gene expression) 54 samples Submitted 2026/02/02 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 54 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
54 samples: 54 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)
Extracellular ATP (eATP) is a damage associated molecular pattern (DAMP) that may be released by cancer cells as a result of chemotherapy-induced immunogenic cell death (ICD). We have demonstrated that preserving extracellular ATP (eATP) by inhibiting the extracellular ATPase CD39 boosts anti-tumor immunity in various models. We recently reported the development of AB598, a very specific and potent therapeutic antibody that inhibits CD39 enzymatic activity.
Read the full summary ↓
We demonstrated using a cancer cell-moDC co-culture system that chemotherapy-induced ATP release with AB598 inhibition is sufficient to activate moDCs to a greater antigen presenting cell (APC) phenotype. Using this co-culture system, we generated and tested an ATP signature that shows promising utility in tumor biopsies.
This dataset
Open GSE287531 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 GSE287531_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 PRJNA1213681 and SRA study SRP558661. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
54 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 54 sample titles: 54 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

+ 14 more — browse all 54 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.