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CDK4-selective inhibitor AU2-94 for the treatment of advanced and therapy-resistant prostate cancer

GSE330358 Homo sapiens (human) RNA-seq (gene expression) 36 samples Submitted 2026/05/28 Platform GPL28038
At a glance

RNA-seq (gene expression) · human · 36 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
Prostate cancerThis series is part of our curated briefing on it.
Samples
36 samples: 12 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.
Summary (written by the submitters)
INTRODUCTION: CDK4-selective inhibitors are emerging as promising anti-cancer agents. Relative to dual CDK4/6 inhibitors, CDK4-selective inhibitors have potential to retain efficacy while improving tolerability. However, the therapeutic value and mechanistic consequences of selectively targeting CDK4 in prostate cancer remain undefined.
Read the full summary ↓
Here, we investigated the therapeutic potential of CDK4 inhibitors AU2-94 and atirmociclib across diverse prostate cancer models. METHODS: Anti-proliferative activity was assessed in a panel of prostate cancer cell lines spanning AR-driven hormone-sensitive and AR-independent castration-resistant states, including therapy-resistant models. Efficacy was further evaluated in organoids from patient-derived xenografts and xenograft mouse models. Biochemical and molecular analyses were performed to define CDK4 selectivity, RB pathway engagement, transcriptional consequences, and downstream effects on cell cycle and resistance-associated programs. AU2-94 was also tested in combination with standard-of-care therapies (enzalutamide, docetaxel) and the PI3K inhibitor alpelisib. RESULTS: AU2-94 exhibited greater selectivity for CDK4 compared to atirmociclib. AU2-94 supressed proliferation across prostate cancer models irrespective of AR status and retained activity in aggressive and therapy-resistant settings. In RB-proficient models, AU2-94 reduced RB phosphorylation, attenuated E2F1-dependent transcriptional outputs, activated AR signalling, and decreased expression of proliferation-associated factors such as c-Myc and FOXM1. In vivo, AU2-94 significantly inhibited tumour growth in both AR-driven (LNCaP) and AR-independent (PC3) xenografts and suppressed RB pathway signalling in tumour tissue. Moreover, AU2-94 enhanced anti-tumour responses in combination with enzalutamide, docetaxel, or alpelisib, demonstrating additive or synergistic effects associated with reinforced cell-cycle blockade and suppression of resistance-associated signalling. CONCLUSION: These findings establish selective CDK4 inhibition as a therapeutically active and mechanistically rational strategy in prostate cancer, and support AU2-94 as a candidate for further preclinical and clinical development, including in combination regimens for advanced and therapy-resistant disease.
This dataset
Open GSE330358 in finder → Find more human RNA-seq datasets → Prostate 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 GSE330358_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 PRJNA1463704 and SRA study SRP698673. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 conditions, mostly in triplicate
AU2-94, 1uM, 24 hours ×3 AU2-94, 2uM, 24 hours ×3 Atirmociclib, 1uM, 24 hours ×3 Atirmociclib, 2uM, 24 hours ×3 Ribociclib, 2uM, 24 hours ×3 Vehicle, 2uM, 24 hours ×3 AU2-94, 1uM, 72 hours ×3 AU2-94, 2uM, 72 hours ×3 +4 more

Supports a between-group comparison across 36 samples.

How we read this: 12 replicated groups read from 36 sample titles; they account for 36 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 Prostate cancer datasets

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