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Dual targeting CDK4/6 and CDK7 augments tumor response and anti-tumor immunity in breast cancer

GSE281158 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/11/07 Platform GPL34295Platform GPL24247
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: 12 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
Dual targeting of CDK4/6 and CDK7 augments tumor response and antitumor immunity in breast cancer modelsThe Journal of clinical investigation · 2025
Summary (written by the submitters)
CDK4/6 inhibitors (CDK4/6i) have significantly improved the prognosis for hormone-positive (HR+) breast cancer patients. However, the emergence of drug resistance severely limits their long-term efficacy, and CDK4/6i monotherapy remains largely ineffective against triple-negative breast cancer (TNBC). Here, we demonstrate that combining CDK4/6i with CDK7 inhibitors (CDK7i) offers a promising therapeutic strategy to overcome resistance in both HR+ breast cancer and TNBC.
Read the full summary ↓
Kinetic analyses reveal that CDK7i primarily targets RNA polymerase II-mediated transcription, a key driver of CDK4/6i resistance by amplifying E2F activity following the degradation of the retinoblastoma protein. Consequently, the combination of CDK4/6i and CDK7i synergistically suppresses E2F activity and inhibits the growth of drug-resistant tumors. Furthermore, this combination stimulates immune response pathways and cytokine production in cancer cells, enhancing anti-tumor immunity. These findings provide critical insights into evolving CDK inhibition strategies and highlight the therapeutic application of CDK7i in breast cancer management.
Published in
Dual targeting of CDK4/6 and CDK7 augments tumor response and antitumor immunity in breast cancer models
Kim S, Son E, Park HR et al. · The Journal of clinical investigation 2025 · PMID 40794455 · doi:10.1172/JCI188839
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 GSE281158_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 PRJNA1182401 and SRA study SRP543360. Searching any of these in the dataset finder brings you back here.

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

Supports a case/control comparison: 2 samples read as cases, 2 as controls.

How we read this: Read from 12 sample titles: 12 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
More Breast 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.