Evidence map›Paper›PMID 39892389›Full record

ArticleCell genomics2025

Defining hypoxia in cancer: A landmark evaluation of hypoxia gene expression signatures.

Matteo Di Giovannantonio, Fiona Hartley, Badran Elshenawy, Alessandro Barberis, Dan Hudson, Hana S Shafique, Vincent E S Allott, David A Harris, Simon R Lord, Syed Haider and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cell genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

22 citing papers in PubMed.

  1. Review
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  19. Lanthanide Nanotheranostics in Radiotherapy.International journal of molecular sciences · 2025
    Review
  20. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Matteo Di GiovannantonioComputational Biology and Integrative Genomics Lab, Department of Oncology, University of Oxford, Oxford, UK.
Fiona HartleyComputational Biology and Integrative Genomics Lab, Department of Oncology, University of Oxford, Oxford, UK.
Badran ElshenawyComputational Biology and Integrative Genomics Lab, Department of Oncology, University of Oxford, Oxford, UK.
Alessandro BarberisComputational Biology and Integrative Genomics Lab, Department of Oncology, University of Oxford, Oxford, UK.
Dan HudsonChinese Academy of Medical Sciences Oxford Institute, University of Oxford, Oxford, UK; The Rosalind Franklin Institute, Didcot, UK.
Hana S ShafiqueDuke University School of Medicine, Durham, NC, USA.
Vincent E S AllottSt. Catherine's College, University of Oxford, Oxford, UK.
David A HarrisMerton College, University of Oxford, Oxford, UK.
Simon R LordComputational Biology and Integrative Genomics Lab, Department of Oncology, University of Oxford, Oxford, UK.
Syed HaiderBreast Cancer Now Toby Robins Breast Cancer Research Centre, The Institute of Cancer Research, London, UK.
Adrian L HarrisComputational Biology and Integrative Genomics Lab, Department of Oncology, University of Oxford, Oxford, UK.
Francesca M BuffaComputational Biology and Integrative Genomics Lab, Department of Oncology, University of Oxford, Oxford, UK; CompBio Lab, Department of Computing Sciences, Bocconi University, Milan, Italy; AI and Systems Biology Lab, IFOM - Istituto Fondazione di Oncologia Molecolare ETS, Milan, Italy. Electronic address: francesca.buffa@unibocconi.it.
Benjamin H L HarrisComputational Biology and Integrative Genomics Lab, Department of Oncology, University of Oxford, Oxford, UK; St. Catherine's College, University of Oxford, Oxford, UK; Cutrale Perioperative and Ageing Group, Imperial College London, London, UK. Electronic address: benjamin.harris@oncology.ox.ac.uk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumor hypoxia drives metabolic shifts, cancer progression, and therapeutic resistance. Challenges in quantifying hypoxia have hindered the exploitation of this potential "Achilles' heel." While gene expression signatures have shown promise as surrogate measures of hypoxia, signature usage is heterogeneous and debated. Here, we present a systematic pan-cancer evaluation of 70 hypoxia signatures and 14 summary scores in 104 cell lines and 5,407 tumor samples using 472 million length-matched random gene signatures. Signature and score choice strongly influenced the prediction of hypoxia in vitro and in vivo. In cell lines, the Tardon signature was highly accurate in both bulk and single-cell data (94% accuracy, interquartile mean). In tumors, the Buffa and Ragnum signatures demonstrated superior performance, with Buffa/mean and Ragnum/interquartile mean emerging as the most promising for prospective clinical trials. This work delivers recommendations for experimental hypoxia detection and patient stratification for hypoxia-targeting therapies, alongside a generalizable framework for signature evaluation.

Indexed as

HypoxiaNeoplasmsTranscriptomeTumor HypoxiaAnimalsCell HypoxiaCell Line, TumorGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMicebiomarkersgene signaturehypoxiahypoxia-targeting therapiespatient stratificationradiotherapysignature scoressingle celltranscriptomicstumorigenesis

Identifiers

PMID39892389
PMCPMC11872601

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.