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MLK4 regulates macrophage-induced gene expression changes associated with extracellular matrix remodeling, cell adhesion, and invasion

GSE304746 Homo sapiens (human) RNA-seq (gene expression) 16 samples Submitted 2025/09/03 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 16 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
Breast cancerThis series is part of our curated briefing on it.
Samples
16 samples: 4 × siNT vs 4 × siNT+M2 vs 4 × siMLK4 vs 4 × siMLK4+M2Groups 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)
Tumor-associated macrophages (TAMs) are key mediators of triple-negative breast cancer (TNBC) progression, yet the molecular mechanisms by which they promote malignancy remain incompletely defined. To gain insights into the molecular mechanisms involved in macrophage-driven induction of breast cancer proliferation and the role of MLK4 signaling, we performed expression profiling using mRNA-seq. Our result highlights MLK4’s role in promoting EMT and ECM reorganization during the cross-talk between cancer cells and macrophages.
This dataset
Open GSE304746 in finder → Find more human RNA-seq datasets → Breast 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 GSE304746_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 PRJNA1302441 and SRA study SRP607014. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
4 × siNT vs 4 × siNT+M2 vs 4 × siMLK4 vs 4 × siMLK4+M2

Supports a between-group comparison across 16 samples.

How we read this: 4 replicated groups read from 16 sample titles; they account for 16 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
More Breast cancer datasets

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.