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Splicing targeting approaches highlight actionable vulnerabilities in advanced prostate cancer [22Rv1]

GSE234734 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2024/03/06 Platform GPL24676
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
Prostate cancerThis series is part of our curated briefing on it.
Samples
12 samples: 3 × 22Rv1 DMSO treated replica vs 3 × 22Rv1 Indisulam treated replica vs 3 × 22Rv1 THZ531 treated replica vs 3 × 22Rv1 Pladienolide B treated replicaGroups 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
Splicing targeting drugs highlight intron retention as an actionable vulnerability in advanced prostate cancerJournal of experimental & clinical cancer research : CR · 2024
Summary (written by the submitters)
To investigate if pharmacological inhibition of splicing could uncover novel actionable vulnerabilities in CRPC, we profiled the genome-wide transcriptional changes elicited in 22Rv1 cells by treatment with three drugs that inhibit the splicing through different molecular targets: i. Pladienolide B, that impairs the activity of SF3B1; ii. Indisulam that promote degradation of the splicing factor RBM39; iii. THZ531 inhibits the cyclin dependent kinases (CDK) 12 and 13.
Published in
Splicing targeting drugs highlight intron retention as an actionable vulnerability in advanced prostate cancer
Naro C, Antonioni A, Medici V et al. · Journal of experimental & clinical cancer research : CR 2024 · PMID 38413979 · doi:10.1186/s13046-024-02986-0
This dataset
Open GSE234734 in finder → Find more human RNA-seq datasets → Prostate cancer landscape →
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 GSE234734_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 PRJNA982834 and SRA study SRP442919. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38413979) ↗
Study design
3 × 22Rv1 DMSO treated replica vs 3 × 22Rv1 Indisulam treated replica vs 3 × 22Rv1 THZ531 treated replica vs 3 × 22Rv1 Pladienolide B treated replica

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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
More Prostate cancer datasets

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.