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Transcriptomic analysis of the in vivo effects of CDK8/19 inactivation in 22Rv1 xenografts growing in intact and castrated NSG mice

GSE240370 Homo sapiens (human) RNA-seq (gene expression) 66 samples Submitted 2024/03/31 Platform GPL20301Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 66 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
66 samples
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
Mediator kinase inhibition reverses castration resistance of advanced prostate cancerThe Journal of clinical investigation · 2024
Summary (written by the submitters)
RNA-Seq analysis was carried out to investigate the effects of CDK8/19 inactivation in the tumors formed in intact and castrated NSG mice by different 22Rv1 derivatives, with or without SNX631 treatment. The 22Rv1 derivatives were generated as following: Parental 22Rv1 (Rv1-WT) were transduced with a lentivirus expressing luciferase, yielding the derivative Rv1-Luc.
Read the full summary ↓
22Rv1 cells with a double knockout of CDK8 and CDK19 (Rv1-dKO) were made via CRISPR/Cas9. Rv1-dKO cells were further transduced with lentiviruses to generate Rv1-dKO re-expression derivatives that express wild-type CDK19 (Rv1-dKO-CDK19) and the kinase-inactive D173A mutant (Rv1-dKO-CDK19M). SNX631 is a selective and orally bioavalable CDK8/19 inhibtor.
Published in
Mediator kinase inhibition reverses castration resistance of advanced prostate cancer
Li J, Hilimire TA, Liu Y et al. · The Journal of clinical investigation 2024 · PMID 38546787 · doi:10.1172/JCI176709
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 GSE240370_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 PRJNA1003454 and SRA study SRP454054. Searching any of these in the dataset finder brings you back here.

Samples in this study

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