Evidence map›Paper›PMID 29312587›Full record

ArticleOncotarget2017

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 1 more

Open access · diamondAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.9field-weighted citation impact, top 14% of its field
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

10 citing papers in PubMed, 19 citations in OpenAlex.

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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

11 authors at 5 institutions in 2 countries.

Núria EritjaDepartment of Pathology and Molecular Genetics/Oncologic Pathology Group, Arnau de Vilanova University Hospital, University of Lleida, IRBLleida, Lleida, Spain.
Mariona JovéDepartment of Experimental Medicine, University of Lleida, IRBLleida, Lleida, Spain.
Kristine Eldevik FasmerDepartment of Radiology, Haukeland University Hospital, Bergen, Norway.
Sònia GatiusDepartment of Pathology and Molecular Genetics/Oncologic Pathology Group, Arnau de Vilanova University Hospital, University of Lleida, IRBLleida, Lleida, Spain.
Manuel Portero-OtinDepartment of Experimental Medicine, University of Lleida, IRBLleida, Lleida, Spain.
Jone TrovikDepartment of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway.
Camilla KrakstadDepartment of Obstetrics and Gynecology, Haukeland University Hospital, Bergen, Norway.
Joaquim SolDepartment of Experimental Medicine, University of Lleida, IRBLleida, Lleida, Spain.
Reinald PamplonaDepartment of Experimental Medicine, University of Lleida, IRBLleida, Lleida, Spain.
Ingfrid S HaldorsenDepartment of Radiology, Haukeland University Hospital, Bergen, Norway.
Xavier Matias-GuiuDepartment of Pathology and Molecular Genetics/Oncologic Pathology Group, Arnau de Vilanova University Hospital, University of Lleida, IRBLleida, Lleida, Spain.
Biomedical Research Institute of Lleida · ESCentro de Investigación Biomédica en Red de Cáncer · ESHaukeland University Hospital · NOUniversitat de Lleida · ESUniversity of Bergen · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeWe 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.

methodsLiquid 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.

resultsTumour 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.

conclusionsTumour 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.

Indexed as

blood flowDCE-MRIendometrial cancermetabolomic analysis

Identifiers

PMID29312587
PMCPMC5752500
OpenAlexW2773374996

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 Socratic graph.