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Rb and p53 cooperate to suppress prostate cancer lineage plasticity, metastasis, and antiandrogen resistance

GSE90891 Mus musculus (mouse) RNA-seq (gene expression) 27 samples Submitted 2017/02/24 Platform GPL13112
At a glance

RNA-seq (gene expression) · mouse · 27 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
Mus musculus (mouse)
Samples
27 samples: 24 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)
Prostate cancer relapsing from antiandrogen therapies can exhibit variant histology with altered lineage marker expression, suggesting lineage plasticity facilitates therapeutic resistance. Mechanisms underlying prostate cancer lineage plasticity are unknown, and relevant experimental models are needed. We demonstrate Rb1 loss facilitates lineage plasticity and metastasis of prostate adenocarcinoma initiated by Pten mutation in the mouse.
Read the full summary ↓
Additional loss of Trp53 causes resistance to antiandrogen therapy. Gene expression profiling indicates mouse tumors are comparable to human prostate cancer neuroendocrine variants; both mouse and human tumors exhibit increased expression of epigenetic reprogramming factors like Ezh2 and Sox2. Clinically relevant Ezh2 inhibitors restore androgen receptor expression and sensitivity to antiandrogen therapy. These findings uncover genetic mutations enabling prostate cancer progression, identify mouse models for studying prostate cancer lineage plasticity, and suggest an epigenetic approach for extending clinical responses to antiandrogen therapy.
This dataset
Open GSE90891 in finder → Find more mouse 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 GSE90891_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 PRJNA356285 and SRA study SRP094570. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 28059767) ↗
Study design
24 distinct titles, 1 of them repeated
WT_PRO ×4

How we read this: Read from 27 sample titles: 24 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
Datasets on a similar topic

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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.