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HIF2ɑ Requires Engagement with YAP/TAZ and AP-1 Transcription Factors to Maintain Oncogenic Transcription in Clear Cell Renal Cell Carcinoma [RNA-Seq]

GSE295181 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2026/03/31 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 12 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Topic
Kidney cancerThis series is part of our curated briefing on it.
Samples
12 samples: 3 × 786O_Ctrl vs 3 × 786O_shHIF2 vs 3 × 786O_shJUN vs 3 × 786O_shYTGroups 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.
Summary (written by the submitters)
Clear Cell Renal Cell Carcinoma (ccRCC) is characterized by loss of tumor suppressor von Hippel-Lindau (VHL), leading to activation of Hypoxia-inducible Factor 2ɑ (HIF2ɑ) oncogenic transcription factor and pseudo-hypoxia. Integrated analysis of public ccRCC multi-omic datasets revealed frequent inactivation of the Hippo tumor suppressor pathway and corresponding increase in YAP/TAZ transcription activity in ccRCC tumors, which is associated with worse overall survival in treatment naïve patients.
Read the full summary ↓
By combining Cut&Tag and BRB-seq analysis, we assessed the chromatin binding and gene regulation of YAP and HIF2ɑ, and unveiled that these two proteins are co-recruited to AP-1 sites through interactions with the AP-1 transcription factors. YAP/TAZ, HIF2ɑ and JUN are dependent on each other to maintain their expression, and function cooperatively to promote the expression of highly expressed transcription factors and other important oncogenes. Our findings not only revealed the therapeutic potentials of adjunct YAP/TAZ-based therapies in the treatment of advanced ccRCC, but also revealed novel mechanistic insights into the dynamic interactions among YAP, HIF2ɑ and AP-1 proteins that could be further exploited to improve treatment for ccRCC.
This dataset
Open GSE295181 in finder → Find more human RNA-seq 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 GSE295181_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA1253674 and SRA study SRP580216. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × 786O_Ctrl vs 3 × 786O_shHIF2 vs 3 × 786O_shJUN vs 3 × 786O_shYT

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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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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.