Evidence map›Paper›PMID 27358048›Full record

ArticleGenome biology2016

Genomic alterations underlie a pan-cancer metabolic shift associated with tumour hypoxia.

Syed Haider, Alan McIntyre, Ruud G P M van Stiphout, Laura M Winchester, Simon Wigfield, Adrian L Harris, Francesca M Buffa

Abstract read
In one paragraph

Article in Genome biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 61 papers.

0numbers the graph read from it
0cells of the map it votes in
61citing 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

61 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Proteogenomic discovery ofScience advances · 2025
    Article
  9. Article
  10. Article
  11. Article
  12. Identification of Hypoxia-ALCAMAdvanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Repurposing antifungal drugs for cancer therapy.Journal of advanced research · 2023
    Review
  19. Article
  20. Expression and kinetic characterization of PYCR3.Archives of biochemistry and biophysics · 2023
    Article

1 more citing papers are in PubMed but not listed here.

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

7 authors.

Syed HaiderComputational Biology and Integrative Genomics, Department of Oncology, University of Oxford, Oxford, UK.
Alan McIntyreMolecular Oncology Laboratories, Department of Oncology, The Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK.
Ruud G P M van StiphoutComputational Biology and Integrative Genomics, Department of Oncology, University of Oxford, Oxford, UK.
Laura M WinchesterComputational Biology and Integrative Genomics, Department of Oncology, University of Oxford, Oxford, UK.
Simon WigfieldMolecular Oncology Laboratories, Department of Oncology, The Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK.
Adrian L HarrisMolecular Oncology Laboratories, Department of Oncology, The Weatherall Institute of Molecular Medicine, University of Oxford, Oxford, UK.
Francesca M BuffaComputational Biology and Integrative Genomics, Department of Oncology, University of Oxford, Oxford, UK. Francesca.Buffa@oncology.ox.ac.uk.

Funding

Cancer Research UK 11359Cancer Research UK 16466Cancer Research UK 18974Medical Research Council G0300648
6 · The paper itself

Abstract

backgroundAltered metabolism is a hallmark of cancer. However, the role of genomic changes in metabolic genes driving the tumour metabolic shift remains to be elucidated. Here, we have investigated the genomic and transcriptomic changes underlying this shift across ten different cancer types.

resultsA systematic pan-cancer analysis of 6538 tumour/normal samples covering ten major cancer types identified a core metabolic signature of 44 genes that exhibit high frequency somatic copy number gains/amplifications (>20 % cases) associated with increased mRNA expression (ρ > 0.3, q < 10(-3)). Prognostic classifiers using these genes were confirmed in independent datasets for breast and kidney cancers. Interestingly, this signature is strongly associated with hypoxia, with nine out of ten cancer types showing increased expression and five out of ten cancer types showing increased gain/amplification of these genes in hypoxic tumours (P ≤ 0.01). Further validation in breast and colorectal cancer cell lines highlighted squalene epoxidase, an oxygen-requiring enzyme in cholesterol biosynthesis, as a driver of dysregulated metabolism and a key player in maintaining cell survival under hypoxia.

conclusionsThis study reveals somatic genomic alterations underlying a pan-cancer metabolic shift and suggests genomic adaptation of these genes as a survival mechanism in hypoxic tumours.

Indexed as

Genetic VariationAnimalsBiomarkers, TumorCell Line, TumorCell Transformation, NeoplasticCluster AnalysisDisease Models, AnimalDNA Copy Number VariationsEnergy MetabolismFemaleGene Expression ProfilingGene Expression Regulation, EnzymologicGene Expression Regulation, NeoplasticGenetic Association StudiesGenomic InstabilityGenomicsBiomarkers, TumorCancerIntegrative biologyMetabolismTumour microenvironment

Identifiers

PMID27358048
PMCPMC4926297

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.