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CDK8/19 inhibition suppresses adaptive resistance to CDK4/6 inhibitors in vitro and in vivo

GSE303026 Homo sapiens (human) RNA-seq (gene expression) 44 samples Submitted 2026/07/24 Platform GPL34281Platform GPL18573Platform GPL20795
At a glance

RNA-seq (gene expression) · human · 44 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)
Samples
44 samples: 10 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)
CDK4/6 inhibitors have become a standard of care for estrogen receptor-positive breast cancer and are being developed for other malignancies. However, resistance to these drugs readily develops, limiting their impact on patient survival. Mechanisms of resistance to CDK4/6 inhibition involve multiple changes in gene expression, which may be followed by genetic alterations.
Read the full summary ↓
We have investigated the process of tumor cell adaptation to CDK4/6 inhibitors and the impact of selective inhibitors of CDK8/19 Mediator kinases, broad-spectrum regulators of transcriptional reprogramming, on such adaptation. The addition of CDK8/19 inhibitors (SNX631/SNX631-6) prevented the development of CDK4/6 inhibitor resistance in different cell lines and in vivo tumor models with varying levels of CDK4/6 inhibitor sensitivity. RNA-seq analysis revealed specific transcriptomic changes associated with adaptation to palbociclib in vitro and in vitro. Combining palbociclib with CDK8/19 inhibitors suppressed many of the adaptation-associated changes in gene expression. The findings indicate a potential therapeutic benefit of combining CDK4/6 and CDK8/19 inhibitors.
This dataset
Open GSE303026 in finder → Find more human RNA-seq datasets →
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 GSE303026_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 PRJNA1293376 and SRA study SRP601823. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
10 conditions, mostly in triplicate
500nM Palbo ×10 DMSO Vehicle ×5 MCF7 50 mg/kg Palbo and 30 mg/kg SNX631-6 ×5 MCF7 Vehicle Control ×4 MCF7 50 mg/kg Palbo ×4 MCF7 30 mg/kg SNX631-6 ×4 MCF7 Vehicle DMSO 0.1% ×3 MCF7 500nM SNX631 ×3 +2 more

Supports a between-group comparison across 44 samples.

How we read this: 10 replicated groups read from 44 sample titles; they account for 44 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

+ 4 more — browse all 44 samples with per-sample file links →

Datasets on a similar topic

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.