Evidence map›Paper›PMID 26813959›Full record

ArticleScientific reports2016

Generation of 2,000 breast cancer metabolic landscapes reveals a poor prognosis group with active serotonin production.

Vytautas Leoncikas, Huihai Wu, Lara T Ward, Andrzej M Kierzek, Nick J Plant

Abstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. International journal of molecular sciences · 2026
    Article
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  3. Article
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  5. Article
  6. Article
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  8. Article
  9. The Role of Serotonin in Breast Cancer Stem Cells.Molecules (Basel, Switzerland) · 2021
    Review
  10. Cytoguardin: A Tryptophan Metabolite against Cancer Growth and Metastasis.International journal of molecular sciences · 2021
    Review
  11. Article
  12. Article
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  15. Review
  16. Article
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  18. Framework and resource for more than 11,000 gene-transcript-protein-reaction associations in human metabolism.Proceedings of the National Academy of Sciences of the United States of America · 2017
    Article
  19. Article
  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

5 authors.

Vytautas LeoncikasSchool of Bioscience and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
Huihai WuSchool of Bioscience and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
Lara T WardOncology DMPK, AstraZeneca, Alderley Park, Cheshire, SK10 4TG, United Kingdom.
Andrzej M KierzekSchool of Bioscience and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
Nick J PlantSchool of Bioscience and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A major roadblock in the effective treatment of cancers is their heterogeneity, whereby multiple molecular landscapes are classified as a single disease. To explore the contribution of cellular metabolism to cancer heterogeneity, we analyse the Metabric dataset, a landmark genomic and transcriptomic study of 2,000 individual breast tumours, in the context of the human genome-scale metabolic network. We create personalized metabolic landscapes for each tumour by exploring sets of active reactions that satisfy constraints derived from human biochemistry and maximize congruency with the Metabric transcriptome data. Classification of the personalized landscapes derived from 997 tumour samples within the Metabric discovery dataset reveals a novel poor prognosis cluster, reproducible in the 995-sample validation dataset. We experimentally follow mechanistic hypotheses resulting from the computational study and establish that active serotonin production is a major metabolic feature of the poor prognosis group. These data support the reconsideration of concomitant serotonin-specific uptake inhibitors treatment during breast cancer chemotherapy.

Indexed as

MetabolomeMetabolomicsBiomarkers, TumorBreast NeoplasmsCell Line, TumorCluster AnalysisComputational BiologyExtracellular MatrixFemaleGene Expression ProfilingGene Expression Regulation, NeoplasticHumansKaplan-Meier EstimateModels, BiologicalPrognosisSerotoninBiomarkers, TumorSerotonin

Identifiers

PMID26813959
PMCPMC4728432

What OpenQuestion holds

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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.