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BMAL1-HIF2α heterodimers contribute to ccRCC

GSE290669 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 20 samples Submitted 2025/03/17 Platform GPL34295
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 20 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)
Topic
Kidney cancerThis series is part of our curated briefing on it.
Samples
20 samples: 6 conditions, mostly with about 4 replicates eachGroups 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
BMAL1 and ARNT enable circadian HIF2α responses in clear cell renal cell carcinomaNature communications · 2025
Summary (written by the submitters)
Circadian disruption enhances cancer risk, and many tumors exhibit disordered circadian gene expression. We show rhythmic gene expression is unexpectedly robust in clear cell renal cell carcinoma (ccRCC). Furthermore, the clock gene BMAL1 is higher in ccRCC than in healthy kidneys, unlike in other tumor types. BMAL1 is closely related to ARNT and we show that BMAL1-HIF2α regulates a subset of HIF2α target genes in ccRCC cells.
Read the full summary ↓
Depletion of BMAL1 reprograms HIF2α chromatin association and target gene expression and reduces ccRCC growth in culture and in xenografts. Analysis of pre-existing data reveals higher BMAL1 in patient-derived xenografts that are sensitive to growth suppression by HIF2α antagonists. We show that increasing BMAL1 sensitizes ccRCC-derived A498 cells to growth inhibition by PT2399. Together, these findings indicate that an alternate HIF2α heterodimer containing the circadian partner BMAL1 contributes to HIF2α activity, growth, and sensitivity to HIF2α antagonist drugs in ccRCC cells.
Published in
BMAL1 and ARNT enable circadian HIF2α responses in clear cell renal cell carcinoma
Mello RM, Gomez Ceballos D, Sandate CR et al. · Nature communications 2025 · PMID 40595592 · doi:10.1038/s41467-025-60904-0
This dataset
Open GSE290669 in finder → Find more human ChIP / ATAC / CUT&Tag datasets → Kidney 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 GSE290669_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1229506 and SRA study SRP566771. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40595592) ↗
Study design
6 conditions, mostly with about 4 replicates each
A498 shCNT IP BMAL1 ×4 A498 shCNT IP HIF2a ×4 A498 shBMAL1 IP BMAL1 ×4 A498 shBMAL1 IP HIF2a ×4 A498 shCNT IP IgG ×2 A498 shBMAL1 IP IgG ×2

Supports a between-group comparison across 20 samples.

How we read this: 6 replicated groups read from 20 sample titles; they account for 20 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 Kidney cancer datasets

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