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肿瘤微环境血流决定了一种代谢组学特征,该特征可识别溶血磷脂和消退素D作为子宫内膜癌患者的生物标志物。

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

作者信息

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

机构信息

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

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

出版信息

Oncotarget. 2017 Nov 20;8(65):109018-109026. doi: 10.18632/oncotarget.22558. eCollection 2017 Dec 12.

DOI:10.18632/oncotarget.22558
PMID:29312587
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5752500/
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.

摘要

目的

我们旨在研究通过动态对比增强磁共振成像(DCE-MRI)获得的肿瘤血流对子宫内膜肿瘤代谢组学特征的潜在影响。

方法

液相色谱-质谱联用技术确定了在DCE-MRI中显示高肿瘤血流(n=12)或低肿瘤血流(n=14)的子宫内膜癌病变的代谢组学特征。使用单变量和多变量统计方法(正交偏最小二乘判别分析(ortho-PLS-DA)、随机森林(RF)分类器和层次聚类)以及受试者工作特征(ROC)曲线来建立一个区分高血流与低血流肿瘤的潜在判别指标。

结果

肿瘤血流与特定的代谢组学特征相关。正交偏最小二乘判别分析和随机森林分类器产生了明确的聚类,袋外误差低于8%。我们发现了28个具有统计学意义的分子(错误发现率校正p<0.05)。基于精确质量、保留时间和同位素分布,我们鉴定出9种分子,包括与血流相关的消退素D和特定溶血磷脂,因此它们在子宫内膜癌中可能具有潜在的调节作用。

结论

DCE-MRI中量化肿瘤血管特征的肿瘤血流参数反映在相应的代谢组学特征中,并突出了可能成为新疗法靶点的疾病机制。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd96/5752500/2f12464e1519/oncotarget-08-109018-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd96/5752500/369e62a0336c/oncotarget-08-109018-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd96/5752500/c94d8b58b078/oncotarget-08-109018-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd96/5752500/8eb153b66088/oncotarget-08-109018-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd96/5752500/2f12464e1519/oncotarget-08-109018-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd96/5752500/369e62a0336c/oncotarget-08-109018-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd96/5752500/c94d8b58b078/oncotarget-08-109018-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd96/5752500/8eb153b66088/oncotarget-08-109018-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fd96/5752500/2f12464e1519/oncotarget-08-109018-g004.jpg

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