GEO series

Concurrent CDK7 and CDK9 Blockade Sustains Transcriptional Shutdown and Suppresses Oncogenic Dependencies in Cancer

GSE325770 Homo sapiens (human) RNA-seq (gene expression) 33 samples Submitted 2026/05/08 Platform GPL16791

At a glance

RNA-seq (gene expression) · human · 33 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: 33 samples: 32 distinct titles, 1 of them repeatedGroups 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)

Transcriptional cyclin-dependent kinases (CDKs) are attractive cancer targets owned to their critical role in the regulation of RNA polymerase II (RNAPII) to maintain oncogenic gene-expression programs. CDK7 supports transcriptional initiation and promoter escape, whereas CDK9 promotes productive elongation. Because inhibition of a single node can be partially buffered by transcriptional plasticity, we tested whether co-targeting CDK7 and CDK9 enforces a deeper and more durable transcriptional shutdown with improved antitumor activity.

Read the full summary ↓

By combining genetic and pharmacological perturbations across breast and ovarian cancer models, we found that dual CDK7–CDK9 knockout caused the strongest suppression of proliferation and nascent RNA synthesis, accompanied by greater loss of RNAPII phosphorylation and pronounced depletion of MYC and MCL1, compared with single knockouts. Pharmacological co-inhibition phenocopied these effects, producing rapid EU suppression that preceded decreases in EdU incorporation and cell number, preventing adaptation to single treatments and yielding deeper pathway inhibition than either monotherapy. In ovarian cancer models, combined inhibition similarly enhanced suppression of transcriptional output and growth relative to single agents, supporting generalizability across tumor contexts. RNA sequencing after short inhibitor exposures showed that combined CDK7/CDK9 inhibition induced a transcriptomic state distinct from either single agent, with broad downregulation of pathways linked to transcription and RNA processing, ribosome biogenesis, and growth-associated programs. Together, these data support CDK7/CDK9 co-targeting as a mechanistically grounded strategy to intensify and stabilize transcriptional inhibition in cancer, coupling proximal RNAPII control to depletion of short-lived oncogenic drivers and collapse of growth-promoting networks and providing a clear rationale for combinatorial therapeutic development.

This dataset

Open GSE325770 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 GSE325770_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 PRJNA1441579 and SRA study SRP686015. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

32 distinct titles, 1 of them repeated

MDA-MD-231, Parental ×2

How we read this: Read from 33 sample titles: 32 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

GSM9613079 MDA-MD-231, DMSO
GSM9613080 MDA-MD-231, Parental
GSM9613081 MDA-MD-231, SY200, 3h
GSM9613082 MDA-MD-231, SY200, 6h
GSM9613083 MDA-MD-231, SY200, 12h
GSM9613084 MDA-MD-231, V50, 3h
GSM9613085 MDA-MD-231, V50, 6h
GSM9613086 MDA-MD-231, V50, 12h
GSM9613087 MDA-MD-231, SY200/V50, 3h
GSM9613088 MDA-MD-231, SY200/V50, 6h
GSM9613089 MDA-MD-231, SY200/V50, 12h
GSM9613090 MDA-MD-468, DMSO
GSM9613091 MDA-MD-468, Parental
GSM9613092 MDA-MD-468, SY200, 3h
GSM9613093 MDA-MD-468, SY200, 6h
GSM9613094 MDA-MD-468, SY200, 12h
GSM9613095 MDA-MD-468, V50, 3h
GSM9613096 MDA-MD-468, V50, 6h
GSM9613097 MDA-MD-468, V50, 12h
GSM9613098 MDA-MD-468, SY200/V50, 3h
GSM9613099 MDA-MD-468, SY200/V50, 6h
GSM9613100 MDA-MD-468, SY200/V50, 12h
GSM9613101 MDA-MD-231, Parental 2
GSM9613102 MDA-MD-231, Empty vector, 72h
GSM9613103 MDA-MD-231, Empty vector, 96h
GSM9613104 MDA-MD-231, CDK1 KO, 72h
GSM9613105 MDA-MD-231, CDK1 KO, 96h
GSM9613106 MDA-MD-231, CDK7 KO, 72h
GSM9613107 MDA-MD-231, CDK7 KO, 96h
GSM9613108 MDA-MD-231, CDK9 KO, 72h
GSM9613109 MDA-MD-231, CDK9 KO, 96h
GSM9613110 MDA-MD-231, CDK7/9 KO, 72h
GSM9613111 MDA-MD-231, CDK7/9 KO, 96h

Datasets on a similar topic

GSE262443 Co-targeting CDK7/CDK9 and CKIα exerts efficacious anticancer effects against TERT gene-rearranged neuroblastoma 12 samples shares cdk7, cdk9
GSE283178 Disruption of transcriptional programming by CDK9 inhibition suppresses triple-negative breast cancer and is enhanced by EGFR inhibition 21 samples shares cdk9, suppresses
GSE335516 CDK7 inhibition suppresses Hippo-YAP signaling to reverse CDK4/6 inhibitor resistance in hormone receptor-positive breast cancer 18 samples shares cdk7, suppresses
GSE291596 Co-targeting CDK2 and CDK9 inhibits MYC oncogenic programs and has anti-tumor effects in CIC-rearranged sarcoma 12 samples shares cdk9, oncogenic
GSE50625 Targeting transcriptional dependencies in cancer using a covalent CDK7 inhibitor 92 samples shares cdk7, dependencies
GSE50624 Targeting transcriptional dependencies in cancer using a covalent CDK7 inhibitor (expression) 79 samples shares cdk7, dependencies
GSE62726 Targeting of Super-Enhancer-Associated Oncogenic Transcription in MYCN-driven tumor cells by CDK7 inhibition 46 samples shares cdk7, oncogenic
GSE50622 Targeting transcriptional dependencies in cancer using a covalent CDK7 inhibitor (ChIP-Seq) 13 samples shares cdk7, dependencies

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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.