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Genome-wide CRISPR screen identifies a cytokine-enhancer circuit driving HIF-2α activation in renal cancer

GSE303721 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 15 samples Submitted 2026/02/06 Platform GPL30173Platform GPL34281
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 15 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
15 samples: 7 conditions, mostly in duplicateGroups 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
Genome-wide CRISPR screen identifies a cytokine-enhancer circuit driving HIF-2α activation in renal cancerThe Journal of clinical investigation · 2026
Summary (written by the submitters)
Resistance to HIF-2α inhibitors such as Belzutifan underscores the need to better understand how HIF-2α is transcriptionally regulated in clear cell renal cell carcinoma (ccRCC). Here, we uncover a cytokine-driven enhancer mechanism that sustains HIF-2α expression through the JAK1-STAT3 signaling pathway. Using a genome-wide CRISPR screen in VHL-deficient ccRCC cells, we identified SOCS3 as a key negative regulator of HIF-2α.
Read the full summary ↓
Mechanistically, loss of SOCS3 activates JAK1-STAT3 signaling, leading to the recruitment of STAT3 to distal enhancers upstream of EPAS1 that physically loop to its promoter to drive HIF-2α transcription. This cytokine-enhancer circuit was recapitulated in ccRCC patient samples and functionally validated using CRISPR interference, which disrupted enhancer-promoter looping and reduced tumor growth in HIF-2α-dependent models. SOCS3 overexpression or pharmacologic inhibition of JAK1/STAT3 markedly suppressed HIF-2α expression and tumor progression both in vitro and in vivo. Unlike prior studies focusing on VHL/HIF occupancy-driven enhancer activation, this work defines a trans-acting cytokine-JAK1-STAT3 pathway that transcriptionally controls EPAS1. Together, these findings reveal a targetable enhancer mechanism that sustains HIF-2α expression and suggest that combined inhibition of JAK1/STAT3 and HIF-2α may overcome therapeutic resistance in kidney cancer
Published in
Genome-wide CRISPR screen identifies a cytokine-enhancer circuit driving HIF-2α activation in renal cancer
Fang J, Simon JM, Wang T et al. · The Journal of clinical investigation 2026 · PMID 41874563 · doi:10.1172/JCI201639
This dataset
Open GSE303721 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 GSE303721_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 PRJNA1297156 and SRA study SRP603769. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41874563) ↗
Study design
7 conditions, mostly in duplicate
HKC8_H3K27ac_ChIP ×2 HKC8_H3K4me1_ChIP ×2 HKC8_H3K4me3_ChIP ×2 HKC8_ChIP_input ×2 HKC8_STAT3_ChIP ×2 786-O_IgG_ChIP ×2 786-O_STAT3_ChIP ×2 786-O_H3K27ac_HiChIP ×1

Supports a between-group comparison across 14 samples.

How we read this: 7 replicated groups read from 15 sample titles; they account for 14 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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