GEO series

Non-canonical function of transferrin receptor-1 promotes breast cancer metastasis by activating HCK-STAT3-MMP9 signaling

GSE318333 Homo sapiens (human) RNA-seq (gene expression) 8 samples Submitted 2026/07/22 Platform GPL16791

At a glance

RNA-seq (gene expression) · human · 8 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: 8 samples: 8 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.
Paper: Non-canonical function of transferrin receptor-1 promotes breast cancer metastasis by activating HCK‒STAT3‒MMP9 signallingClinical and translational medicine · 2026

Summary (written by the submitters)

Transferrin receptor 1 (TfR-1), a key mediator of cellular iron uptake, is significantly upregulated across a broad spectrum of malignancies, and its overexpression highly correlated with poor clinical outcomes, such as in breast cancer. However, its precise role in breast cancer progression remains unclear. In this study, analysis of clinical samples from breast cancer patients and public databases demonstrated that high level of TfR-1 in breast cancer samples is strongly associated with metastasis.

Read the full summary ↓

We further verified that elevated TfR-1 enhances the proliferative and metastatic potential of breast cancer cells both in vitro and in vivo. Mechanistically, we uncovered an unexpected protein kinase activity of TfR-1, which directly phosphorylates hematopoietic cell kinase (HCK). Concurrently, TfR-1 activates ubiquitin-specific protease 32 (USP32), thereby stabilizing HCK protein. Subsequently, phosphorylated HCK facilitates the activation of the transcription factor STAT3, resulting in increased expression and secretion of matrix metalloproteinase 9 (MMP9). Moreover, HCK exerts reciprocal phosphorylation on TfR-1, forming a positive feedback loop. Collectively, our findings unravel a novel molecular mechanism underlying TfR-1-mediated metastasis in breast cancer, highlighting the importance of TfR-1’s non-canonical phosphorylation activity beyond its established role in iron transport, and identifying potential therapeutic targets for cancer intervention.

Published in

Non-canonical function of transferrin receptor-1 promotes breast cancer metastasis by activating HCK‒STAT3‒MMP9 signalling

Zhao Q, Wang Y, Wang P et al. · Clinical and translational medicine 2026 · PMID 42437977 · doi:10.1002/ctm2.70731

This dataset

Open GSE318333 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 GSE318333_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 PRJNA1418596 and SRA study SRP674532. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42437977) ↗

Study design

8 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 8 sample titles: 8 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

GSM9492537 MDA-MB-231/4175 Mock(#1)
GSM9492538 MDA-MB-231/4175 Mock(#2)
GSM9492539 MDA-MB-231/4175 Mock(#3)
GSM9492540 MDA-MB-231/4175 Mock(#4)
GSM9492541 MDA-MB-231/4175 TfR-1(#1)
GSM9492542 MDA-MB-231/4175 TfR-1(#2)
GSM9492543 MDA-MB-231/4175 TfR-1(#3)
GSM9492544 MDA-MB-231/4175 TfR-1(#4)

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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.