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DRUG-seq of high-density neutrophils (HDNs), mature low-density neutrophils (M-LDN), and immature low-density neutrophils (IM-LDN) in patients with colorectal cancer

GSE302902 Homo sapiens (human) RNA-seq (gene expression) 51 samples Submitted 2025/11/02 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 51 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)
Topic
Colorectal cancerThis series is part of our curated briefing on it.
Samples
51 samples: 17 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.
Paper
Agonist signaling drives neutrophil subpopulations to promote/inhibit colorectal cancer liver metastasisNature communications · 2025
Summary (written by the submitters)
High-density neutrophils (HDNs), mature low-density neutrophils (M-LDN), and immature low-density neutrophils (IM-LDN) were isolated from peripheral blood of nine treatment-naïve colorectal cancer (CRC) patients with histologically confirmed diagnoses, followed by gene expression profiling of these neutrophil subsets using Digital RNA with pertUrbation of Genes (DRUG) sequencing.
Published in
Agonist signaling drives neutrophil subpopulations to promote/inhibit colorectal cancer liver metastasis
Xu Z, Feng H, Feng W et al. · Nature communications 2025 · PMID 41408063 · doi:10.1038/s41467-025-67579-7
This dataset
Open GSE302902 in finder → Find more human RNA-seq datasets → Colorectal cancer landscape →
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 GSE302902_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 PRJNA1292799 and SRA study SRP601535. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41408063) ↗
Study design
17 conditions, mostly in triplicate
1_HDN ×3 3_IMLDN ×3 5_IMLDN ×3 7_IMLDN ×3 7_MLDN ×3 8_HDN ×3 8_MLDN ×3 8_IMLDN ×3 +9 more

Supports a between-group comparison across 51 samples.

How we read this: 17 replicated groups read from 51 sample titles; they account for 51 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

+ 11 more — browse all 51 samples with per-sample file links →

More Colorectal cancer datasets

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.