Evidence map›Paper›PMID 27350877›Full record

ArticleCancer & metabolism2016

Metabolic clusters of breast cancer in relation to gene- and protein expression subtypes.

Tonje H Haukaas, Leslie R Euceda, Guro F Giskeødegård, Santosh Lamichhane, Marit Krohn, Sandra Jernström, Miriam R Aure, Ole C Lingjærde, Ellen Schlichting, Øystein Garred and 6 more

Abstract read
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In one paragraph

Article in Cancer & metabolism, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers.

0numbers the graph read from it
0cells of the map it votes in
50citing 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

50 citing papers in PubMed.

  1. Beyond DNA damage: 3D tumor models and the integrin mechanobiology of radioresistance.Journal of experimental & clinical cancer research : CR · 2026
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  15. Omics-Based Investigations of Breast Cancer.Molecules (Basel, Switzerland) · 2023
    Review
  16. Article
  17. Article
  18. Review
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  20. Review
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

16 authors.

Tonje H HaukaasDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway ; K.G. Jebsen Center for Breast Cancer Research, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway.
Leslie R EucedaDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway.
Guro F GiskeødegårdDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway ; St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway.
Santosh LamichhaneDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway ; Department of Food Science, Faculty of Science and Technology, Aarhus University, Årslev, Denmark.
Marit KrohnK.G. Jebsen Center for Breast Cancer Research, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway ; Department of Cancer Genetics, Institute for Cancer Research Oslo University Hospital, The Norwegian Radium Hospital, Oslo, Norway.
Sandra JernströmK.G. Jebsen Center for Breast Cancer Research, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway ; Department of Cancer Genetics, Institute for Cancer Research Oslo University Hospital, The Norwegian Radium Hospital, Oslo, Norway.
Miriam R AureK.G. Jebsen Center for Breast Cancer Research, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway ; Department of Cancer Genetics, Institute for Cancer Research Oslo University Hospital, The Norwegian Radium Hospital, Oslo, Norway.
Ole C LingjærdeK.G. Jebsen Center for Breast Cancer Research, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway ; Department of Computer Science, University of Oslo, Oslo, Norway ; Centre for Cancer Biomedicine, University of Oslo, Oslo, Norway.
Ellen SchlichtingSection for Breast and Endocrine Surgery, Oslo University Hospital, Ullevål, Oslo Norway.
Øystein GarredDepartment of Pathology, Oslo University Hospital, Oslo, Norway.
Eldri U DueK.G. Jebsen Center for Breast Cancer Research, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway ; Department of Cancer Genetics, Institute for Cancer Research Oslo University Hospital, The Norwegian Radium Hospital, Oslo, Norway.
Gordon B MillsDepartment of Systems Biology, The University of Texas M.D. Anderson Cancer Center, Houston, TX USA.
Kristine K SahlbergK.G. Jebsen Center for Breast Cancer Research, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway ; Department of Research, Vestre Viken, Drammen, Norway.
Anne-Lise Børresen-DaleK.G. Jebsen Center for Breast Cancer Research, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway ; Department of Cancer Genetics, Institute for Cancer Research Oslo University Hospital, The Norwegian Radium Hospital, Oslo, Norway.
Tone F BathenDepartment of Circulation and Medical Imaging, Norwegian University of Science and Technology (NTNU), Trondheim, Norway ; K.G. Jebsen Center for Breast Cancer Research, Institute of Clinical Medicine, Faculty of Medicine, University of Oslo, Oslo, Norway.
Oslo Breast Cancer Consortium (OSBREAC)

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Kathrin Milbury · 1985 to 2026
$290.8M
Tyrosine Kinase-Dependant and - Independent Pathways of EGFR in Breast Cancer ProP01CA099031 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI HUNG, MIEN-CHIE · 2003 to 2014
$11.6M
NCI NIH HHS P01 CA099031NCI NIH HHS P30 CA016672
6 · The paper itself

Abstract

backgroundThe heterogeneous biology of breast cancer leads to high diversity in prognosis and response to treatment, even for patients with similar clinical diagnosis, histology, and stage of disease. Identifying mechanisms contributing to this heterogeneity may reveal new cancer targets or clinically relevant subgroups for treatment stratification. In this study, we have merged metabolite, protein, and gene expression data from breast cancer patients to examine the heterogeneity at a molecular level.

methodsThe study included primary tumor samples from 228 non-treated breast cancer patients. High-resolution magic-angle spinning magnetic resonance spectroscopy (HR MAS MRS) was performed to extract the tumors metabolic profiles further used for hierarchical cluster analysis resulting in three significantly different metabolic clusters (Mc1, Mc2, and Mc3). The clusters were further combined with gene and protein expression data.

resultsOur result revealed distinct differences in the metabolic profile of the three metabolic clusters. Among the most interesting differences, Mc1 had the highest levels of glycerophosphocholine (GPC) and phosphocholine (PCho), Mc2 had the highest levels of glucose, and Mc3 had the highest levels of lactate and alanine. Integrated pathway analysis of metabolite and gene expression data uncovered differences in glycolysis/gluconeogenesis and glycerophospholipid metabolism between the clusters. All three clusters had significant differences in the distribution of protein subtypes classified by the expression of breast cancer-related proteins. Genes related to collagens and extracellular matrix were downregulated in Mc1 and consequently upregulated in Mc2 and Mc3, underpinning the differences in protein subtypes within the metabolic clusters. Genetic subtypes were evenly distributed among the three metabolic clusters and could therefore contribute to additional explanation of breast cancer heterogeneity.

conclusionsThree naturally occurring metabolic clusters of breast cancer were detected among primary tumors from non-treated breast cancer patients. The clusters expressed differences in breast cancer-related protein as well as genes related to extracellular matrix and metabolic pathways known to be aberrant in cancer. Analyses of metabolic activity combined with gene and protein expression provide new information about the heterogeneity of breast tumors and, importantly, the metabolic differences infer that the clusters may be susceptible to different metabolically targeted drugs.

Indexed as

Breast cancer subgroupsExtracellular matrixHR MAS MRSMetabolic clusterMetabolomics

Identifiers

PMID27350877
PMCPMC4922058

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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.