| 1. |
- Austdal, Marie, et al.
(författare)
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First Trimester Urine and Serum Metabolomics for Prediction of Preeclampsia and Gestational Hypertension: A Prospective Screening Study.
- 2015
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Ingår i: International Journal of Molecular Sciences. - : MDPI AG. - 1422-0067. ; 16:9, s. 21520-21538
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Tidskriftsartikel (refereegranskat)abstract
- Hypertensive disorders of pregnancy, including preeclampsia, are major contributors to maternal morbidity. The goal of this study was to evaluate the potential of metabolomics to predict preeclampsia and gestational hypertension from urine and serum samples in early pregnancy, and elucidate the metabolic changes related to the diseases. Metabolic profiles were obtained by nuclear magnetic resonance spectroscopy of serum and urine samples from 599 women at medium to high risk of preeclampsia (nulliparous or previous preeclampsia/gestational hypertension). Preeclampsia developed in 26 (4.3%) and gestational hypertension in 21 (3.5%) women. Multivariate analyses of the metabolic profiles were performed to establish prediction models for the hypertensive disorders individually and combined. Urinary metabolomic profiles predicted preeclampsia and gestational hypertension at 51.3% and 40% sensitivity, respectively, at 10% false positive rate, with hippurate as the most important metabolite for the prediction. Serum metabolomic profiles predicted preeclampsia and gestational hypertension at 15% and 33% sensitivity, respectively, with increased lipid levels and an atherogenic lipid profile as most important for the prediction. Combining maternal characteristics with the urinary hippurate/creatinine level improved the prediction rates of preeclampsia in a logistic regression model. The study indicates a potential future role of clinical importance for metabolomic analysis of urine in prediction of preeclampsia.
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| 2. |
- Johansson, Henrik J., et al.
(författare)
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Breast cancer quantitative proteome and proteogenomic landscape
- 2019
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Ingår i: Nature Communications. - : NATURE PUBLISHING GROUP. - 2041-1723. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- In the preceding decades, molecular characterization has revolutionized breast cancer (BC) research and therapeutic approaches. Presented herein, an unbiased analysis of breast tumor proteomes, inclusive of 9995 proteins quantified across all tumors, for the first time recapitulates BC subtypes. Additionally, poor-prognosis basal-like and luminal B tumors are further subdivided by immune component infiltration, suggesting the current classification is incomplete. Proteome-based networks distinguish functional protein modules for breast tumor groups, with co-expression of EGFR and MET marking ductal carcinoma in situ regions of normal-like tumors and lending to a more accurate classification of this poorly defined subtype. Genes included within prognostic mRNA panels have significantly higher than average mRNA-protein correlations, and gene copy number alterations are dampened at the protein-level; underscoring the value of proteome quantification for prognostication and phenotypic classification. Furthermore, protein products mapping to non-coding genomic regions are identified; highlighting a potential new class of tumor-specific immunotherapeutic targets.
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| 3. |
- Tekpli, Xavier, et al.
(författare)
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An independent poor-prognosis subtype of breast cancer defined by a distinct tumor immune microenvironment
- 2019
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Ingår i: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- How mixtures of immune cells associate with cancer cell phenotype and affect pathogenesis is still unclear. In 15 breast cancer gene expression datasets, we invariably identify three clusters of patients with gradual levels of immune infiltration. The intermediate immune infiltration cluster (Cluster B) is associated with a worse prognosis independently of known clinicopathological features. Furthermore, immune clusters are associated with response to neoadjuvant chemotherapy. In silico dissection of the immune contexture of the clusters identified Cluster A as immune cold, Cluster C as immune hot while Cluster B has a pro-tumorigenic immune infiltration. Through phenotypical analysis, we find epithelial mesenchymal transition and proliferation associated with the immune clusters and mutually exclusive in breast cancers. Here, we describe immune clusters which improve the prognostic accuracy of immune contexture in breast cancer. Our discovery of a novel independent prognostic factor in breast cancer highlights a correlation between tumor phenotype and immune contexture.
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| 4. |
- Tessem, May-Britt, et al.
(författare)
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Biological response in various compartments of the rat lens after in vivo exposure to UVR-B analyzed by HR-MAS 1H NMR spectroscopy
- 2006
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Ingår i: Investigative Ophthalmology and Visual Science. - : Association for Research in Vision and Ophthalmology (ARVO). - 0146-0404 .- 1552-5783. ; 47:12, s. 5404-5411
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Tidskriftsartikel (refereegranskat)abstract
- PURPOSE: The purpose of the present study was to investigate metabolic changes in different compartments of the rat lens (anterior, nuclear, posterior, and equatorial) after exposure to an acute double threshold dose of ultraviolet-B radiation (UVR-B) by using high-resolution magic angle spinning (HR-MAS) (1)H nuclear magnetic resonance (NMR) spectroscopy and pattern recognition (PR) METHODS: methods. One eye in each of 28 6-week-old female albino Sprague-Dawley rats was exposed to in vivo 7.5 kJ/m2 UVR-B for 15 minutes. The contralateral eye was left unexposed. One week after irradiation, all rats were killed, and both lenses were isolated. Each lens was cored by a trephine, and the cylinder was sliced into three portions (anterior, nuclear, and posterior). The lens material that remained after the coring process was analyzed as the equatorial region. Analysis of lens metabolism was performed by HR-MAS 1H NMR spectroscopy (14.1 T; Avance DRX600; Bruker BioSpin GmbH, Rheinstetten, Germany), and the metabolic profiles were statistically analyzed by the PR method of principal component analysis (PCA). RESULTS: Metabolic differences were detected among the compartments in the lens, both in samples from the contralateral nonexposed lenses and in samples from lenses exposed to in vivo UVR-B. In the rat lens, exposure to UVR-B caused changes in GSH, phosphocholine, myo-inositol, succinate, formate, and adenosine triphosphate (ATP)/adenosine diphosphate (ADP) and in levels of the amino acids phenylalanine, taurine, hypo-taurine, tyrosine, alanine, valine, isoleucine, and glutamate, that varied among lens compartments. CONCLUSIONS: HR-MAS 1H NMR spectroscopy, combined with PR methods (PCA), is effective for analysis of separate parts of the intact rat lens. To understand the biochemistry of the lens, it is important to divide the lens into sections, representing functionally and anatomically distinct compartments.
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| 5. |
- Öman, Tommy, 1974-, et al.
(författare)
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Identification of metabolites from 2D 1H-13C HSQC NMR using peak correlation plots
- 2014
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Ingår i: BMC Bioinformatics. - : Springer Science and Business Media LLC. - 1471-2105. ; 15
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Tidskriftsartikel (refereegranskat)abstract
- Background: Identification of individual components in complex mixtures is an important and sometimes daunting task in several research areas like metabolomics and natural product studies. NMR spectroscopy is an excellent technique for analysis of mixtures of organic compounds and gives a detailed chemical fingerprint of most individual components above the detection limit. For the identification of individual metabolites in metabolomics, correlation or covariance between peaks in 1H NMR spectra has previously been successfully employed. Similar correlation of 2D 1H-13C Heteronuclear Single Quantum Correlation spectra was recently applied to investigate the structure of heparine. In this paper, we demonstrate how a similar approach can be used to identify metabolites in human biofluids (post-prostatic palpation urine).Results: From 50 1H-13C Heteronuclear Single Quantum Correlation spectra, 23 correlation plots resembling pure metabolites were constructed. The identities of these metabolites were confirmed by comparing the correlation plots with reported NMR data, mostly from the Human Metabolome Database.Conclusions: Correlation plots prepared by statistically correlating 1H-13C Heteronuclear Single Quantum Correlation spectra from human biofluids provide unambiguous identification of metabolites. The correlation plots highlight cross-peaks belonging to each individual compound, not limited by long-range magnetization transfer as conventional NMR experiments.
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