GEO series

A non-canonical function of the tyrosine degradation enzyme FAH drives CDK4/6 inhibitor resistance in breast cancer II

GSE330518 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/07/30 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 12 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: 12 samples: 3 × MCF7 EV DMSO vs 3 × MCF7 EV ABE vs 3 × MCF7 FAH DMSO vs 3 × MCF7 FAH ABEGroups 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)

Resistance to standard-of-care therapies remains a major clinical challenge in the treatment of the most common breast cancer, the hormone receptor–positive (HR+) subtype. Cyclin-dependent kinase 4/6 (CDK4/6) inhibitors improve outcomes in early-stage HR+ disease, yet many patients relapse. Resistance mechanisms of relapsed tumors include genetic alterations, but in many cases no genetic drivers are identified.

Read the full summary ↓

Here, we investigated mechanisms underlying resistance to CDK4/6 inhibitors using breast cancer patient-derived models and tumors. We identified an unexpected, non-catalytic nuclear function of fumarylacetoacetate hydrolase (FAH), an enzyme in the tyrosine catabolism pathway, as a driver of resistance. FAH translocated to the nucleus upon CDK4/6 inhibition, where it interacted with cyclin-dependent kinase 9 (CDK9), and promoted resistance. Nuclear FAH was enriched in tumors from relapsed patients, and inhibition of CDK9 reversed FAH-mediated resistance. These findings establish nuclear FAH as a biomarker of resistance and revealed CDK9 as a therapeutic vulnerability in CDK4/6 inhibitor-resistant HR+ breast cancer.

This dataset

Open GSE330518 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 GSE330518_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 PRJNA1464537 and SRA study SRP699277. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

3 × MCF7 EV DMSO vs 3 × MCF7 EV ABE vs 3 × MCF7 FAH DMSO vs 3 × MCF7 FAH ABE

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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

GSM9728041 MCF7 EV DMSO 1 MCF7 EV DMSO
GSM9728042 MCF7 EV DMSO 2 MCF7 EV DMSO
GSM9728043 MCF7 EV DMSO 3 MCF7 EV DMSO
GSM9728044 MCF7 EV ABE 1 MCF7 EV ABE
GSM9728045 MCF7 EV ABE 2 MCF7 EV ABE
GSM9728046 MCF7 EV ABE 3 MCF7 EV ABE
GSM9728047 MCF7 FAH DMSO 1 MCF7 FAH DMSO
GSM9728048 MCF7 FAH DMSO 2 MCF7 FAH DMSO
GSM9728049 MCF7 FAH DMSO 3 MCF7 FAH DMSO
GSM9728050 MCF7 FAH ABE 1 MCF7 FAH ABE
GSM9728051 MCF7 FAH ABE 2 MCF7 FAH ABE
GSM9728052 MCF7 FAH ABE 3 MCF7 FAH ABE

More Breast cancer datasets

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GSE10885 An integromic analysis reveals that metaplastic carcinomas are distinct from basal-like tumors. 244 samples same disease briefing
GSE10886 A Supervised Risk Predictor of Breast Cancer Based on Biological Subtypes 226 samples same disease briefing
GSE11121 The humoral immune system has a key prognostic impact in node-negative breast cancer 200 samples same disease briefing
GSE330516 A non-canonical function of the tyrosine degradation enzyme FAH drives CDK4/6 inhibitor resistance in breast cancer I 16 samples shares cdk4, fah, non-canonical, degradation, resistance, inhibitor, tyrosine, enzyme
GSE308451 CDK4/6 and SHP2 mediate BRAF/MEK inhibitor resistance in Class 2 and 3 BRAF mutant cancers 90 samples shares cdk4, resistance, inhibitor
GSE296805 An immunological mechanism of resistance to CDK4/6 inhibitors in breast cancer 50 samples shares cdk4, resistance, inhibitor

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.