Dataset Information

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

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.

SUBMITTER: Eritja N

PROVIDER: S-EPMC5752500 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Publications

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

Eritja Núria N Jové Mariona M Fasmer Kristine Eldevik KE Gatius Sònia S Portero-Otin Manuel M Trovik Jone J Krakstad Camilla C Sol Joaquim J Pamplona Reinald R Haldorsen Ingfrid S IS Matias-Guiu Xavier X

Oncotarget 20171120 65

<h4>Purpose</h4>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.<h4>Methods</h4>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 h ...[more]

PMID: 29312587

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Project description:ImportanceEndometrial carcinoma (EC) is the most commonly diagnosed gynecologic cancer. Its early detection is advisable because 20% of women have advanced disease at the time of diagnosis.ObjectiveTo clinically validate a metabolomics-based classification algorithm as a screening test for EC.Design, setting, and participantsThis diagnostic study enrolled 2 cohorts. A multicenter prospective cohort, with 50 cases (postmenopausal women with EC; International Federation of Gynecology and Obstetrics stage I-III and grade G1-G3) and 70 controls (no EC but matched on age, years from menopause, tobacco use, and comorbidities), was used to train multiple classification models. The accuracy of each trained model was then used as a statistical weight to produce an ensemble machine learning algorithm for testing, which was validated with a subsequent prospective cohort of 1430 postmenopausal women. The study was conducted at the San Giovanni di Dio e Ruggi d'Aragona University Hospital of Salerno (Italy) and Lega Italiana per la Lotta contro i Tumori clinic in Avellino (Italy). Data collection was conducted from January 2018 to February 2019, and analysis was conducted from January to March 2019.Main outcomes and measuresThe presence or absence of EC based on evaluation of the blood metabolome. Metabolites were extracted from dried blood samples from all participants and analyzed by gas chromatography-mass spectrometry. A confusion matrix was used to summarize test results. Performance indices included sensitivity, specificity, positive and negative predictive values, positive and negative likelihood ratios, and accuracy. Confirmation or exclusion of EC in women with a positive test result was by means of hysteroscopy. Participants with negative results were followed up 1 year after enrollment to investigate the appearance of EC signs.ResultsThe study population consisted of 1550 postmenopausal women. The mean (SD) age was 68.2 (11.7) years for participants with no EC in the training cohort, 69.4 (13.8) years for women with EC in the training cohort, and 59.7 (7.7) years for women in the validation cohort. Application of the ensemble machine learning to the validation cohort resulted in 16 true-positives, 2 false-positives, and 0 false-negatives, and it correctly classified more than 99% of samples. Disease prevalence was 1.12% (16 of 1430).Conclusions and relevanceIn this study, dried blood metabolomic profile was used to assess the presence or absence of EC in postmenopausal women not receiving hormonal therapy with greater than 99% accuracy.

Project description:The recruitment and subsequent polarization of inflammatory monocytes/macrophages in the perivascular regions of pulmonary arteries is a key feature of pulmonary hypertension (PH). However, the mechanisms driving macrophage polarization within the adventitial microenvironment during PH progression remain unclear. We previously established that reciprocal interactions between fibroblasts and macrophages are essential in driving the activated phenotype of both cell types although the signals involved in these interactions remain undefined. We sought to test the hypothesis that adventitial fibroblasts produce a complex array of metabolites and proteins that coordinately direct metabolomic and transcriptomic re-programming of naïve macrophages to recapitulate the pathophysiologic phenotype observed in PH. Media conditioned by pulmonary artery adventitial fibroblasts isolated from pulmonary hypertensive (PH-CM) or age-matched control (CO-CM) calves were used to activate bone marrow derived macrophages. RNA-Seq and mass spectrometry-based metabolomics analyses were performed. Fibroblast conditioned medium from patients with idiopathic pulmonary arterial hypertension or controls were used to validate transcriptional findings. The microenvironment was targeted in vitro using a fibroblast-macrophage co-culture system and in vivo in a mouse model of hypoxia-induced PH. Both CO-CM and PH-CM actively, yet distinctly regulated macrophage transcriptomic and metabolomic profiles. Network integration revealed coordinated rewiring of pro-inflammatory and pro-remodeling gene regulation in concert with altered mitochondrial and intermediary metabolism in response to PH-CM. Pro-inflammation and metabolism are key regulators of macrophage phenotype in vitro, and are closely related to in vivo flow sorted lung interstitial/perivascular macrophages from hypoxic mice. Metabolic changes are accompanied by increased free NADH levels and increased expression of a metabolic sensor and transcriptional co-repressor, C-terminal binding protein 1 (CtBP1), a mechanism shared with adventitial PH-fibroblasts. Targeting the microenvironment created by both cell types with the CtBP1 inhibitor MTOB, inhibited macrophage pro-inflammatory and metabolic re-programming both in vitro and in vivo. In conclusion, coordinated transcriptional and metabolic reprogramming is a critical mechanism regulating macrophage polarization in response to the complex adventitial microenvironment in PH. Targeting the adventitial microenvironment can return activated macrophages toward quiescence and attenuate pathological remodeling that drives PH progression.

Dataset Information

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

Purpose

Methods

Results

Conclusions

Publications

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

Similar Datasets

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