Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives

Frontiers in Molecular Biosciences, Journal Year: 2021, Volume and Issue: 8

Published: Sept. 20, 2021

Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize therapies and patient care based on individual characteristics. Its success highly depends way characterization of disease its evolution, patient’s classification, follow-up treatment could be optimized. Thus, personalized must combine innovative tools measure, integrate model data. Towards this goal, clinical metabolomics appears as ideally suited obtain relevant information. Indeed, signature brings crucial insight stratify patients according their responses a pathology and/or treatment, provide prognostic diagnostic biomarkers, improve therapeutic outcomes. However, translation from laboratory studies practice remains subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) mass spectrometry (MS) are two key platforms for measurement metabolome. NMR has several advantages features that essential metabolomics. inherently very robust, reproducible, unbiased, quantitative, informative at structural molecular level, requires little sample preparation reduced data processing. also well adapted large cohorts, multi-sites longitudinal studies. review focus potential context Starting with current status NMR-based level highlighting strengths, weaknesses challenges, article explores how, far initial “opposition” or “competition”, MS have been integrated demonstrated great complementarity, terms classification biomarker identification. Finally, perspective discussion provides into methodological developments significantly raise more resolutive, sensitive accessible tool applications point-of-care diagnosis. Thanks these advances, strong join other analytical currently used settings.

Language: Английский

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Soft Tissue Sarcoma: An Insight on Biomarkers at Molecular, Metabolic and Cellular Level

Cancers, Journal Year: 2021, Volume and Issue: 13(12), P. 3044 - 3044

Published: June 18, 2021

Soft tissue sarcomas (STSs) are a heterogeneous group of rare tumors. Although constituting only 1% all human malignancies, STSs represent the second most common type solid tumors in children and adolescents comprise an important secondary malignancies. Over 100 histologic subtypes have been characterized to date (occurring predominantly trunk, extremity, retroperitoneum), many more being discovered due molecular profiling. STS mortality remains high, despite adjuvant chemotherapy. New prognostic stratification markers needed help identify patients at risk recurrence possibly apply intensive or novel treatments. Recent scientific advancements enabled precise characterization sarcoma revealed therapeutic targets prognostic/predictive biomarkers. This review aims providing comprehensive overview relevant cellular, metabolic biomarkers for STS, highlight advances STS-related biomarker research.

Language: Английский

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Fluxomics - New Metabolomics Approaches to Monitor Metabolic Pathways

Frontiers in Pharmacology, Journal Year: 2022, Volume and Issue: 13

Published: March 21, 2022

Fluxomics is an innovative -omics research field that measures the rates of all intracellular fluxes in central metabolism biological systems. gathers data from multiple different fields, portraying whole picture molecular interactions. Recently, fluxomics has become one most relevant approaches to investigate metabolic phenotypes. Metabolic flux using

Language: Английский

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Multiplatform Untargeted Metabolomics

Magnetic Resonance in Chemistry, Journal Year: 2023, Volume and Issue: 61(12), P. 628 - 653

Published: April 3, 2023

Metabolomics samples like human urine or serum contain upwards of a few thousand metabolites, but individual analytical techniques can only characterize hundred metabolites at best. The uncertainty in metabolite identification commonly encountered untargeted metabolomics adds to this low coverage problem. A multiplatform (multiple techniques) approach improve upon the number reliably detected and correctly assigned. This be further improved by applying synergistic sample preparation along with use combinatorial sequential non-destructive destructive techniques. Similarly, peak detection strategies that employ multiple probabilistic approaches have led better annotation decisions. Applying these also addresses issues reproducibility found single platform methods. Nevertheless, analysis large data sets from disparate presents unique challenges. While general processing workflow is similar across platforms, many software packages are fully capable types instrument. Traditional statistical methods such as principal component were not designed handle multiple, distinct sets. Instead, multivariate requires multiblock other model for understanding contribution instruments. review summarizes advantages, limitations, recent achievements metabolomics.

Language: Английский

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Saliva biomarkers in oral disease

Clinica Chimica Acta, Journal Year: 2023, Volume and Issue: 548, P. 117503 - 117503

Published: Aug. 1, 2023

Language: Английский

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