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The Ashkenazi-centric G334R variant of TP53 is severely impaired for transactivation but retains tumor suppressor function in a mouse model [ChIP-Seq]

GSE277586 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 44 samples Submitted 2025/09/19 Platform GPL30173
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 44 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Homo sapiens (human)
Samples
44 samples
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)
Mutations in the TP53 tumor suppressor gene are the most abundant genetic occurrences in cancer. Some of these mutations lead to loss of function of p53 protein, some are gain of function, and some variants are hypomorphic (partially-functional). Currently, there is no clinical distinction between different p53 mutations and cancer therapy or prognosis.
Read the full summary ↓
Mutations in the oligomerization domain of p53 appear to be quite distinct in function, compared to mutations in the DNA binding domain. Here we show that, like other p53 oligomerization domain mutants, the Ashkenazi-specific G334R mutant accumulates to very high levels in cells and is significantly impaired for the transactivation of canonical p53 target genes. Surprisingly, we find that this mutant retains the ability to bind to consensus p53 target sites. A mouse model reveals that mice containing the G334R variant show increased predisposition to cancer, but only a fraction of these mice develop cancer at late onset. We show that the G334R variant retains the ability to interact with the SP1 transcription factor and contributes to the transactivation of joint SP1-p53 target genes. The combined evidence indicates that G334R is a unique oligomerization domain mutant that retains some tumor suppressor function.
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 GSE277586_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1162871 and SRA study SRP533636. Searching any of these in the dataset finder brings you back here.

Samples in this study

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