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A chemical screen identifies PRMT5 as a therapeutic vulnerability for paclitaxel-resistant triple-negative breast cancer

GSE264630 Homo sapiens (human) RNA-seq (gene expression) 32 samples Submitted 2024/06/21 Platform GPL24676Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 32 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
Breast cancerThis series is part of our curated briefing on it.
Samples
32 samples: 14 conditions, mostly in duplicateGroups 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)
Paclitaxel -resistant triple negative breast cancer (TNBC) remains one of the most challenging breast cancers to treat. Using an epigenetic chemical probe screen, we uncover an acquired vulnerability of paclitaxel-resistant TNBC cells to protein arginine methyltransferases (PRMTs) inhibition. Analysis of cell lines and in-house clinical samples demonstrates that resistant cells evade paclitaxel killing through stabilizing mitotic chromatin assembly.
Read the full summary ↓
Genetic or pharmacologic inhibition of PRMT5 alters RNA splicing, particularly intron retention of Aurora kinases B (AURKB), leading to a decrease in protein expression, and finally results in selective mitosis catastrophe in paclitaxel-resistant cells. These findings are fully recapitulated in a patient derived xenograft (PDX) model generated from a paclitaxel-resistant TNBC patient, providing the rationale for targeting PRMTs in paclitaxel-resistant TNBC.
This dataset
Open GSE264630 in finder → Find more human RNA-seq datasets → Breast 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 GSE264630_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 PRJNA1103684 and SRA study SRP503532. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
14 conditions, mostly in duplicate
PDX model, LLY283 ×3 PDX model, control ×3 MDA-MB-436 cells, DMSO ×2 MDA-MB-436-20RC cells, DMSO ×2 MDA-MB-436-20RC cells,GSK591 ×2 MDA-MB-436-20RC cells, LLY283 ×2 MDA-MB-436 cells, GSK591 ×2 MDA-MB-436 cells, LLY283 ×2 +8 more

Supports a between-group comparison across 30 samples.

How we read this: 14 replicated groups read from 32 sample titles; they account for 30 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 Breast 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.