title: Generation of 2,000 breast cancer metabolic landscapes reveals a poor prognosis group with active serotonin production.
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.
authors.affiliation: School of Bioscience and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
authors.forename: Vytautas
authors.initials: V
authors.lastname: Leoncikas
authors.affiliation: School of Bioscience and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
authors.forename: Huihai
authors.initials: H
authors.lastname: Wu
authors.affiliation: Oncology DMPK, AstraZeneca, Alderley Park, Cheshire, SK10 4TG, United Kingdom.
authors.forename: Lara T
authors.initials: LT
authors.lastname: Ward
authors.affiliation: School of Bioscience and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
authors.forename: Andrzej M
authors.initials: AM
authors.lastname: Kierzek
authors.affiliation: School of Bioscience and Medicine, Faculty of Health and Medical Sciences, University of Surrey, Guildford, Surrey, GU2 7XH, United Kingdom.
authors.forename: Nick J
authors.initials: NJ
authors.lastname: Plant
mesh_terms: D014408:Biomarkers, Tumor; D001943:Breast Neoplasms / Q000235:genetics / Q000378:metabolism* / Q000401:mortality*; D045744:Cell Line, Tumor; D016000:Cluster Analysis; D019295:Computational Biology / Q000379:methods; D005109:Extracellular Matrix; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D006801:Humans; D053208:Kaplan-Meier Estimate; D055442:Metabolome; D055432:Metabolomics / Q000379:methods; D008954:Models, Biological; D011379:Prognosis; D012701:Serotonin / Q000096:biosynthesis*; D059467:Transcriptome
chemical_list: D014408:Biomarkers, Tumor; D012701:Serotonin
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