Oncotarget

Research Papers:

Tumour-microenvironmental blood flow determines a metabolomic signature identifying lysophospholipids and resolvin D as biomarkers in endometrial cancer patients

Núria Eritja, Mariona Jové, Kristine Eldevik Fasmer, Sònia Gatius, Manuel Portero-Otin, Jone Trovik, Camilla Krakstad, Joaquim Sol, Reinald Pamplona, Ingfrid S. Haldorsen _ and Xavier Matias-Guiu

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Oncotarget. 2017; 8:109018-109026. https://doi.org/10.18632/oncotarget.22558

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Abstract

Núria Eritja1,2,*, Mariona Jové3,*, Kristine Eldevik Fasmer4,5,*, Sònia Gatius1,2, Manuel Portero-Otin3, Jone Trovik6,7, Camilla Krakstad6,7, Joaquim Sol3, Reinald Pamplona3,**, Ingfrid S. Haldorsen4,5,** and Xavier Matias-Guiu1,2,8,**

1Department of Pathology and Molecular Genetics/Oncologic Pathology Group, Arnau de Vilanova University Hospital, University of Lleida, IRBLleida, Lleida, Spain

2Centro de Investigación Biomédica en Red de Oncología (CIBERONC), Madrid, Spain

3Department of Experimental Medicine, University of Lleida, IRBLleida, Lleida, Spain

4Department of Radiology, Haukeland University Hospital, Bergen, Norway

5Department of Clinical Medicine, University of Bergen, Bergen, Norway

6Department of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway

7Department of Clinical Science, Center for Cancer Biomarkers, University of Bergen, Bergen, Norway

8Department of Pathology, University Hospital of Bellvitge, Bellvitge Biomedical Research Institute (IDIBELL), L’Hospitalet de Llobregat, Catalonia, Spain

*These authors have contributed equally to this work

**Senior co-authors

Correspondence to:

Ingfrid S. Haldorsen, email: [email protected]

Xavier Matias-Guiu, email: [email protected]

Keywords: endometrial cancer; DCE-MRI; blood flow; metabolomic analysis

Received: July 07, 2017    Accepted: October 30, 2017    Published: November 20, 2017

ABSTRACT

Purpose: We aimed to study the potential influence of tumour blood flow –obtained from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI)- in the metabolomic profiles of endometrial tumours.

Methods: Liquid chromatography coupled to mass spectrometry established the metabolomic profile of endometrial cancer lesions exhibiting high (n=12) or low (n=14) tumour blood flow at DCE-MRI. Univariate and multivariate statistics (ortho-PLS-DA, a random forest (RF) classifier and hierarchical clustering) and receiver operating characteristic (ROC) curves were used to establish a panel for potentially discriminating tumours with high versus low blood flow.

Results: Tumour blood flow is associated with specific metabolomic signatures. Ortho-PLS-DA and RF classifier resulted in well-defined clusters with an out-of-bag error lower than 8%. We found 28 statistically significant molecules (False Discovery Rate corrected p<0.05). Based on exact mass, retention time and isotopic distribution we identified 9 molecules including resolvin D and specific lysophospholipids associated with blood flow, and hence with a potentially regulatory role relevant in endometrial cancer.

Conclusions: Tumour flow parameters at DCE-MRI quantifying vascular tumour characteristics are reflected in corresponding metabolomics signatures and highlight disease mechanisms that may be targetable by novel therapies.


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