Dual inhibition of CDK4/6 and XPO1 induced senescence with acquired vulnerability to CRBN-based PROTAC drugs
RNA-seq (gene expression) · human · 10 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
- 10 samples: 10 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.
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.
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.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE233531_RAW.tar (it can run to tens of gigabytes).
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 PRJNA976619 and SRA study SRP439751. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 10 sample titles: 10 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.
- GSM7429899 Huh7_Control
- GSM7429900 Huh7_CDK46
- GSM7429901 PLC_Control
- GSM7429902 PLC_CDK46
- GSM7429903 PLC_KPT330
- GSM7429904 PLC_Combination
- GSM7429905 97H_Control
- GSM7429906 97H_CDK46
- GSM7429907 97H_KPT330
- GSM7429908 97H_Combination
- GSE295260 CDK4/6 inhibition induces a senescence-associated secretory phenotype via delayed NF-κB activation 40 samples shares cdk4, inhibition, senescence
- GSE295258 CDK4/6 inhibition induces a senescence-associated secretory phenotype via delayed NF-κB activation 54 samples shares cdk4, inhibition, senescence
- GSE295261 CDK4/6 inhibition induces a senescence-associated secretory phenotype via delayed NF-κB activation [CUT&Tag] 24 samples shares cdk4, inhibition, senescence
- GSE274142 Single-Cell RNA Sequencing Identifies Molecular Biomarkers Predicting Late Progression to CDK4/6 Inhibition in Patients with HR+/HER2- Metastatic Breast Cancer 89 samples shares cdk4, inhibition
- GSE274141 Single-Cell RNA Sequencing Identifies Molecular Biomarkers Predicting Late Progression to CDK4/6 Inhibition in Patients with HR+/HER2- Metastatic Breast Cancer [FFPE] 54 samples shares cdk4, inhibition
- GSE303026 CDK8/19 inhibition suppresses adaptive resistance to CDK4/6 inhibitors in vitro and in vivo 44 samples shares cdk4, inhibition
- GSE323965 Transcriptional signatures indicating RB function may predict response to CDK4/6 inhibition in endometrial cancer [RNA-Seq] 39 samples shares cdk4, inhibition
- GSE289411 JNK pathway suppression drives resistance to combination endocrine therapy and CDK4/6 inhibition in ER+ breast cancer 36 samples shares cdk4, inhibition
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.