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Eosinophils restrict CRC metastasis by inhibiting pro-tumorigenic Spp1+ macrophage differentiation.

GSE282765 Homo sapiens (human) RNA-seq (gene expression) 42 samples Submitted 2024/12/17 Platform GPL34281Platform GPL24247Platform GPL24676Platform GPL34328
At a glance

RNA-seq (gene expression) · human · 42 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
42 samples: 42 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)
Eosinophils, traditionally associated with allergic responses, have emerged as critical immune modulators in colorectal cancer (CRC). Here, we reveal that eosinophils actively shape the tumor microenvironment and influence metastatic progression. Using comprehensive transcriptomics analysis of human CRC and a murine orthotopic tumor model, we identify a conserved tumor-specific eosinophil signature and activation profile.
Read the full summary ↓
Despite their declining presence in advanced CRC, eosinophils suppress metastatic dissemination by counteracting the pro-tumorigenic functions of SPP1+ macrophages – a subset linked to immune exclusion and tumor metastasis. Mechanistically, eosinophils respond to tumor-derived signals and inhibit macrophage differentiation into SPP1+ cells. Eosinophil depletion exacerbates peritoneal tumor spread. These findings highlight the pivotal role of eosinophils in restraining late-stage CRC progression and unveil a novel eosinophil–macrophage axis as potential therapeutic targets.
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 GSE282765_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 PRJNA1190381 and SRA study SRP627970. Searching any of these in the dataset finder brings you back here.

Study design
42 samples, each with a distinct title — no replicated groups

Supports a case/control comparison: 8 samples read as cases, 11 as controls.

How we read this: Read from 42 sample titles: 42 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

+ 2 more — browse all 42 samples with per-sample file links →

More Colorectal cancer datasets

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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.