← BioTransfer GEO Dataset Finder
GEO series

HDAC6 Inhibition Disrupts HDAC6-P300 Interaction Reshaping the Cancer Chromatin Landscape (ChIP-Seq)

GSE273645 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 13 samples Submitted 2024/08/19 Platform GPL19057Platform GPL18573
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 13 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
Mus musculus (mouse)
Samples
13 samples: 13 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
HDAC6 inhibition disrupts HDAC6-P300 interaction reshaping the cancer chromatin landscapeClinical epigenetics · 2024
Summary (written by the submitters)
Histone deacetylases (HDACs) are crucial regulators of gene expression, DNA synthesis, and cellular processes, making them essential targets in cancer research. HDAC6, specifically, influences protein stability and chromatin dynamics. Despite HDAC6's potential therapeutic value, its exact role in gene regulation and chromatin remodeling needs further clarification.
Read the full summary ↓
This study examines how HDAC6 inactivation influences lysine acetyltransferase P300 stabilization and subsequent effects on chromatin structure and function in cancer cells. We employed the HDAC6 inhibitor ITF3756, siRNA, or CRISPR/Cas9 gene editing to inactivate HDAC6 in different epigenomic backgrounds. Constantly, this inactivation led to significant changes in chromatin accessibility, particularly increased acetylation of histone H3 lysines 9, 14, and 27 (ATAC-seq and H3K27Ac ChIP-seq analysis). Transcriptomics, proteomics, and gene ontology analysis revealed gene changes in cell proliferation, adhesion, migration, and apoptosis. Significantly, HDAC6 inactivation altered P300 ubiquitination, stabilizing P300 and leading to downregulating genes critical for cancer cell survival. Our study highlights the substantial impact of HDAC6 inactivation on the chromatin landscape of cancer cells and suggests a role for P300 in contributing to the anticancer effects. The stabilization of P300 with HDAC6 inhibition proposes a potential shift in therapeutic focus from HDAC6 itself to its interaction with P300. This finding opens new avenues for developing targeted cancer therapies, improving our understanding of epigenetic mechanisms in cancer cells.
Published in
HDAC6 inhibition disrupts HDAC6-P300 interaction reshaping the cancer chromatin landscape
Zamperla MG, Illi B, Barbi V et al. · Clinical epigenetics 2024 · PMID 39155390 · doi:10.1186/s13148-024-01725-8
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 GSE273645_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 PRJNA1142561 and SRA study SRP523409. Searching any of these in the dataset finder brings you back here.

Study design
13 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 13 sample titles: 13 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

Search all ChIP / ATAC / CUT&Tag datasets in GEO →

Share this dataset

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.