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      Untargeted serum metabolomics reveals potential biomarkers and metabolic pathways associated with esophageal cancer

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          Abstract

          Metabolomics has been reported as an efficient tool to screen biomarkers that are related to esophageal cancer. However, the metabolic biomarkers identifying malignant degrees and therapeutic efficacy are still largely unknown in the disease. Here, GC-MS-based metabolomics was used to understand metabolic alteration in 137 serum specimens from patients with esophageal cancer, which is approximately two- to fivefold as many plasma specimens as the previous reports. The elevated amino acid metabolism is in sharp contrast to the reduced carbohydrate as a characteristic feature of esophageal cancer. Comparative metabolomics showed that most metabolic differences were determined between the early stage (0–II) and the late stage (III and IV) among the 0–IV stages of esophageal cancer and between patients who received treatment and those who did not receive treatment. Glycine, serine, and threonine metabolism and glycine were identified as the potentially overlapped metabolic pathway and metabolite, respectively, in both disease progress and treatment effect. Glycine, fructose, ornithine, and threonine can be a potential array for the evaluation of disease prognosis and therapy in esophageal cancer. These results highlight the means of identifying previously unknown biomarkers related to esophageal cancer by a metabolomics approach.

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          Most cited references39

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          Global Cancer Statistics 2018: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries

          This article provides a status report on the global burden of cancer worldwide using the GLOBOCAN 2018 estimates of cancer incidence and mortality produced by the International Agency for Research on Cancer, with a focus on geographic variability across 20 world regions. There will be an estimated 18.1 million new cancer cases (17.0 million excluding nonmelanoma skin cancer) and 9.6 million cancer deaths (9.5 million excluding nonmelanoma skin cancer) in 2018. In both sexes combined, lung cancer is the most commonly diagnosed cancer (11.6% of the total cases) and the leading cause of cancer death (18.4% of the total cancer deaths), closely followed by female breast cancer (11.6%), prostate cancer (7.1%), and colorectal cancer (6.1%) for incidence and colorectal cancer (9.2%), stomach cancer (8.2%), and liver cancer (8.2%) for mortality. Lung cancer is the most frequent cancer and the leading cause of cancer death among males, followed by prostate and colorectal cancer (for incidence) and liver and stomach cancer (for mortality). Among females, breast cancer is the most commonly diagnosed cancer and the leading cause of cancer death, followed by colorectal and lung cancer (for incidence), and vice versa (for mortality); cervical cancer ranks fourth for both incidence and mortality. The most frequently diagnosed cancer and the leading cause of cancer death, however, substantially vary across countries and within each country depending on the degree of economic development and associated social and life style factors. It is noteworthy that high-quality cancer registry data, the basis for planning and implementing evidence-based cancer control programs, are not available in most low- and middle-income countries. The Global Initiative for Cancer Registry Development is an international partnership that supports better estimation, as well as the collection and use of local data, to prioritize and evaluate national cancer control efforts. CA: A Cancer Journal for Clinicians 2018;0:1-31. © 2018 American Cancer Society.
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            Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry.

            Metabolism has an essential role in biological systems. Identification and quantitation of the compounds in the metabolome is defined as metabolic profiling, and it is applied to define metabolic changes related to genetic differences, environmental influences and disease or drug perturbations. Chromatography-mass spectrometry (MS) platforms are frequently used to provide the sensitive and reproducible detection of hundreds to thousands of metabolites in a single biofluid or tissue sample. Here we describe the experimental workflow for long-term and large-scale metabolomic studies involving thousands of human samples with data acquired for multiple analytical batches over many months and years. Protocols for serum- and plasma-based metabolic profiling applying gas chromatography-MS (GC-MS) and ultraperformance liquid chromatography-MS (UPLC-MS) are described. These include biofluid collection, sample preparation, data acquisition, data pre-processing and quality assurance. Methods for quality control-based robust LOESS signal correction to provide signal correction and integration of data from multiple analytical batches are also described.
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              Esophageal cancer: Risk factors, genetic association, and treatment.

              The poor prognosis and rising incidence of esophageal cancer highlight the need for improved detection and prediction methods that are essential prior to treatment. Esophageal cancer is one of the most fatal malignancies worldwide, with a dramatic increase in incidence in the Western world occurring over the past few decades. Despite improvements in the management and treatment of esophageal cancer patients, the general outcome remains very poor for overall 5-year survival rates (∼10%) and 5-year postesophagectomy survival rates (∼15-40%). Esophageal cancer is often diagnosed during its advanced stages, the main reason being the lack of early clinical symptoms. In an attempt to improve the outcome of patients after surgery, such patients are often treated with neoadjuvent concurrent chemoradiotherapy (CCRT) in order to decrease tumor size. However, CCRT may enhance toxicity levels and possibly cause a delay in surgery for patients who respond poorly to CCRT. Thus, precise biomarkers that could predict or identify patients who may or may not respond well to CCRT can assist physicians in choosing the appropriate therapy for patients. Identifying susceptible gene and biomarkers can help in predicting the treatment response of patients while improving their survival rates.
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                Author and article information

                Contributors
                Journal
                Front Oncol
                Front Oncol
                Front. Oncol.
                Frontiers in Oncology
                Frontiers Media S.A.
                2234-943X
                13 September 2022
                2022
                : 12
                : 938234
                Affiliations
                [1] 1 State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University , Zhengzhou, China
                [2] 2 State Key Laboratory of Bio-Control, School of Life Sciences, Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-sen University, University City , Guangzhou, China
                [3] 3 Henan Key Laboratory of Tumor Epidemiology and College of Public Health, Zhengzhou University , Zhengzhou, China
                [4] 4 Key Laboratory of Functional Protein Research of Guangdong Higher Education Institutes, Department of Biotechnology, College of Life Science and Technology, Jinan University , Guangzhou, China
                [5] 5 Henan Academy of Medical and Pharmaceutical Sciences, Zhengzhou University , Zhengzhou, China
                Author notes

                Edited by: Abolghasem Jouyban, Tabriz University of Medical Sciences, Iran

                Reviewed by: Wimal Pathmasiri, University of North Carolina at Chapel Hill, United States; Reza Ghanbari, Tehran University of Medical Sciences, Iran

                *Correspondence: Jian-ying Zhang, jianyingzhang@ 123456hotmail.com ; Hui Li, lihui32@ 123456sysu.edu.cn

                †These authors have contributed equally to this work

                This article was submitted to Gastrointestinal Cancers: Gastric and Esophageal Cancers, a section of the journal Frontiers in Oncology

                Article
                10.3389/fonc.2022.938234
                9513043
                36176418
                3f7c29c5-528f-4d64-a3bf-7b50d7d33212
                Copyright © 2022 Yang, Wang, Ye, Jiang, Su, Peng, Li and Zhang

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 07 May 2022
                : 16 August 2022
                Page count
                Figures: 10, Tables: 1, Equations: 0, References: 39, Pages: 18, Words: 6654
                Funding
                Funded by: Guangzhou Municipal Science and Technology Project , doi 10.13039/501100010256;
                Categories
                Oncology
                Original Research

                Oncology & Radiotherapy
                esophageal cancer,metabolomics,biomarker,malignant degrees,therapeutic efficacy

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