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

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2017
Author
Eritja Sánchez, Núria
Jové Font, Mariona
Eldevik Fasmer, Kristine
Gatius Calderó, Sònia
Portero Otín, Manuel
Trovik, Jone
Krakstad, Camilla
Sol, Joaquim
Pamplona Gras, Reinald
Haldorsen, Ingfrid S.
Matias-Guiu, Xavier
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Eritja Sánchez, Núria; Jové Font, Mariona; Eldevik Fasmer, Kristine; Gatius Calderó, Sònia; Portero Otín, Manuel; Trovik, Jone; ... Matias-Guiu, Xavier. (2017) . Tumour-microenvironmental blood flow determines a metabolomic signature identifying lysophospholipids and resolvin D as biomarkers in endometrial cancer patients. Oncotarget, 2017, vol. 8, núm. 65, p, 109018-109026. https://doi.org/10.18632/oncotarget.22558.
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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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http://hdl.handle.net/10459.1/62325
DOI
https://doi.org/10.18632/oncotarget.22558
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Oncotarget, 2017, vol. 8, núm. 65, p, 109018-109026
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Except where otherwise noted, this item's license is described as cc-by (c) Eritja et al., 2017