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ESR1 and p53 Interactome Defines Mechanisms of Therapeutic Response to Tamoxifen Therapy in Luminal Breast Cancer Patients

GSE263089 Homo sapiens (human) RNA-seq (gene expression) 35 samples Submitted 2024/06/28 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 35 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
35 samples: 35 samples, each with a distinct title — no replicated groupsGroups 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
ESR1 and p53 interactome alteration defines mechanisms of tamoxifen response in luminal breast canceriScience · 2024
Summary (written by the submitters)
The canonical mechanism behind tamoxifen (Tam)’s therapeutic effect on estrogen receptor  /ESR1+ breast cancers is inhibition of ESR1-dependent estrogen signaling. Although ESR1+ tumors expressing wild-type p53 were reported to be more responsive to Tam therapy, p53 has not been factored into choice of this therapy and the mechanism underlying the role of p53 in Tam response remain unclear.
Read the full summary ↓
In a window of opportunity trial on patients with newly diagnosed stage I-III ESR1+/HER2/ wild-type p53 –breast cancer who were randomized to arms with or without Tam prior to surgery, we reveal that the ESR1-p53 interaction in tumors was inhibited by Tam. This resulted in functional reactivation of p53 leading to transcriptional reprogramming that favors tumor suppressive signaling, as well as downregulation of oncogenic pathways. These findings illustrating the convergence of ESR1 and p53 signaling during Tam therapy contribute to mechanistic understanding of the impact of p53 on the response to Tam therapy.
Published in
ESR1 and p53 interactome alteration defines mechanisms of tamoxifen response in luminal breast cancer
Oturkar CC, Rosario SR, Hutson AD et al. · iScience 2024 · PMID 38868185 · doi:10.1016/j.isci.2024.109995
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 GSE263089_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 PRJNA1095632 and SRA study SRP499418. Searching any of these in the dataset finder brings you back here.

Study design
35 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 35 sample titles: 35 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
More Breast 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.