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Genome-wide occupancy of PPARG and RXRA after treatment with PPARG inverse agonist

GSE298628 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 10 samples Submitted 2026/05/28 Platform GPL20795
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 10 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
10 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)
We report our mechanistic investigation into the conformationally-driven activation bias of PPARG in muscle-invasive urothelial cancer (MIUC) and our efforts to pharmacologically reverse this activation bias through covalent PPARG inverse agonism. Studies into tumor-associated mutations in both PPARG and RXRA were integrated with structure-based drug design as well as insights from biochemical mechanistic studies to discover FX-909, a first-in-class clinical PPARG inverse agonist that robustly enforces a conformationally repressive state of PPARG, even in highly activated biological contexts.
Read the full summary ↓
FX-909 is a potent, highly selective, and powerful suppressor of PPARG transcriptional activity through enhancement of PPARG-NCOR (Nuclear Co-Repressor) binding affinity. Treatment with FX-909 resulted in selective growth inhibition in PPARG-activated MIUC cell lines. Further, FX-909 achieved durable regressions in xenograft models of MIUC. FX-909 is the first chemical tool that is capable of recapitulating PPARG genetic knockout in vivo and is currently in clinical development for the treatment of intractable MIUC.
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 GSE298628_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 PRJNA1270055 and SRA study SRP588916. Searching any of these in the dataset finder brings you back here.

Samples in this study

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