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      Metabolomic Biomarkers for Detection, Prognosis and Identifying Recurrence in Endometrial Cancer

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          Abstract

          Metabolic reprogramming is increasingly recognised as one of the defining hallmarks of tumorigenesis. There is compelling evidence to suggest that endometrial cancer develops and progresses in the context of profound metabolic dysfunction. Whilst the incidence of endometrial cancer continues to rise in parallel with the global epidemic of obesity, there are, as yet, no validated biomarkers that can aid risk prediction, early detection, prognostic evaluation or surveillance. Advances in high-throughput technologies have, in recent times, shown promise for biomarker discovery based on genomic, transcriptomic, proteomic and metabolomic platforms. Metabolomics, the large-scale study of metabolites, deals with the downstream products of the other omics technologies and thus best reflects the human phenotype. This review aims to provide a summary and critical synthesis of the existing literature with the ultimate goal of identifying the most promising metabolite biomarkers that can augment current endometrial cancer diagnostic, prognostic and recurrence surveillance strategies. Identified metabolites and their biochemical pathways are discussed in the context of what we know about endometrial carcinogenesis and their potential clinical utility is evaluated. Finally, we underscore the challenges inherent in metabolomic biomarker discovery and validation and provide fresh perspectives and directions for future endometrial cancer biomarker research.

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          Genomics, gene expression and DNA arrays.

          Experimental genomics in combination with the growing body of sequence information promise to revolutionize the way cells and cellular processes are studied. Information on genomic sequence can be used experimentally with high-density DNA arrays that allow complex mixtures of RNA and DNA to be interrogated in a parallel and quantitative fashion. DNA arrays can be used for many different purposes, most prominently to measure levels of gene expression (messenger RNA abundance) for tens of thousands of genes simultaneously. Measurements of gene expression and other applications of arrays embody much of what is implied by the term 'genomics'; they are broad in scope, large in scale, and take advantage of all available sequence information for experimental design and data interpretation in pursuit of biological understanding.
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            Amino acids in cancer

            Over 90 years ago, Otto Warburg’s seminal discovery of aerobic glycolysis established metabolic reprogramming as one of the first distinguishing characteristics of cancer1. The field of cancer metabolism subsequently revealed additional metabolic alterations in cancer by focusing on central carbon metabolism, including the citric acid cycle and pentose phosphate pathway. Recent reports have, however, uncovered substantial non-carbon metabolism contributions to cancer cell viability and growth. Amino acids, nutrients vital to the survival of all cell types, experience reprogrammed metabolism in cancer. This review outlines the diverse roles of amino acids within the tumor and in the tumor microenvironment. Beyond their role in biosynthesis, they serve as energy sources and help maintain redox balance. In addition, amino acid derivatives contribute to epigenetic regulation and immune responses linked to tumorigenesis and metastasis. Furthermore, in discussing the transporters and transaminases that mediate amino acid uptake and synthesis, we identify potential metabolic liabilities as targets for therapeutic intervention.
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              ESMO-ESGO-ESTRO Consensus Conference on Endometrial Cancer

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                Author and article information

                Journal
                Metabolites
                Metabolites
                metabolites
                Metabolites
                MDPI
                2218-1989
                31 July 2020
                August 2020
                : 10
                : 8
                : 314
                Affiliations
                [1 ]Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, 5th Floor Research, St Mary’s Hospital, Oxford Road, Manchester M13 9WL, UK; kelechi.njoku@ 123456manchester.ac.uk
                [2 ]Stoller Biomarker Discovery Centre, Institute of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester M13 9PL, UK; tony.whetton@ 123456manchester.ac.uk
                [3 ]School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Oxford Road, Manchester M13 9WL, UK; caroline.sutton@ 123456student.manchester.ac.uk
                [4 ]Department of Obstetrics and Gynaecology, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, UK
                Author notes
                [* ]Correspondence: emma.crosbie@ 123456manchester.ac.uk ; Tel.: +44-0161-701-6942
                Author information
                https://orcid.org/0000-0001-6528-3476
                https://orcid.org/0000-0002-7320-8115
                https://orcid.org/0000-0003-0284-8630
                Article
                metabolites-10-00314
                10.3390/metabo10080314
                7463916
                32751940
                d23e8d51-1448-498b-8a92-a7fdf0dbec5c
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 02 July 2020
                : 27 July 2020
                Categories
                Review

                endometrial cancer,metabolomics,biomarkers,metabolic profiling

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