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BET inhibitor Pelabresib and AR inhibitor enzalutamide perturbed pathways in prostate cancer CRPC PDX LuCaP 35CR

GSE254665 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/01/18 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 × Vehicle vs 3 × Enzalutamide vs 3 × Pelabresib vs 3 × Pelabresib+EnzaGroups 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
BET inhibitors reduce tumor growth in preclinical models of gastrointestinal gene signature-positive castration-resistant prostate cancerThe Journal of clinical investigation · 2025
Summary (written by the submitters)
To study the effect of inhibiting AR and HNF1A/HNF4G activity either alone or in combination on the growth of CRPC PDX LuCaP 35CR
Published in
BET inhibitors reduce tumor growth in preclinical models of gastrointestinal gene signature-positive castration-resistant prostate cancer
Shukla S, Li D, Cho WH et al. · The Journal of clinical investigation 2025 · PMID 40553565 · doi:10.1172/JCI180378
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 GSE254665_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 PRJNA1071482 and SRA study SRP487056. Searching any of these in the dataset finder brings you back here.

Study design
3 × Vehicle vs 3 × Enzalutamide vs 3 × Pelabresib vs 3 × Pelabresib+Enza

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

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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.