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Characterization of a gene expression biomarker predictive of hypoxia-inducible factor-1 modulation

GSE291564 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2025/03/14 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 24 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)
Samples
24 samples: 8 conditions, mostly in triplicateGroups 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
Characterization of a gene expression biomarker predictive of hypoxia-inducible factor-1 modulationChemico-biological interactions · 2025
Summary (written by the submitters)
We describe here a gene expression biomarker that can accurately identify chemicals and genetic conditions that perturb hypoxia-inducible factor-1 (HIF-1), a transcription factor critical for the cellular response to hypoxia involved in the pathophysiology of cancer, inflammation, and ischemia. The HIF-1 biomarker genes were identified from transcript profiles in a variety of human cell lines after hypoxia as well as genetic knockdown of the HIF1A gene.
Read the full summary ↓
The HIF-1 biomarker of 122 genes was found to be enriched for: genes bound by HIF-1 using ChIP-Seq, metabolic pathways regulated by HIF-1 (e.g., gluconeogenesis). Using Ingenuity Pathway Analysis, HIF-1 was the top predicted regulator of the genes. The biomarker could identify activation of HIF-1 by overexpression of the HIF1A gene or suppression of the negative regulator, von-Hipple Lindau (VHL) gene; suppression of HIF-1 occurred by inhibition of the expression of HIF1A or the heterodimer partner aryl hydrocarbon receptor nuclear translocator (ARNT). The biomarker was specific for HIF-1 activation, as activation or suppression of the HIF-2 gene was not detected by the biomarker. Using a reference chemical set with 180 positives and 45 negatives, the balanced accuracy of the HIF-1 biomarker to identify activation was 94.1%. An in-silico screen of a gene expression compendium identified hundreds of potential activators. Eleven of these were selected for verification and all were found to activate HIF-1 biomarker genes in wild-type but not HIF1A-null cells. The HIF-1 biomarker will be a useful tool to identify environmentally relevant chemicals that affect HIF-1 in high-throughput transcriptomics screening studies.
Published in
Characterization of a gene expression biomarker predictive of hypoxia-inducible factor-1 modulation
Corton JC, Chorley B, Liu J · Chemico-biological interactions 2025 · PMID 40499705 · doi:10.1016/j.cbi.2025.111595
This dataset
Open GSE291564 in finder → Find more human RNA-seq datasets →
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 GSE291564_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 PRJNA1234154 and SRA study SRP569257. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40499705) ↗
Study design
8 conditions, mostly in triplicate
HIF1A-null_DMSO ×3 WT_DMSO ×3 HIF1A-null_Ciclopirox_15uM ×3 WT_Ciclopirox_15uM ×3 HIF1A-null_Wortmannin_1uM ×3 WT_Wortmannin_1uM ×3 HIF1A-null_CoCl2_200uM ×3 WT_CoCl2_200uM ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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
Datasets on a similar topic

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