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Metabolic phenotyping for monitoring ovarian cancer patients
Epithelial ovarian cancer (EOC) is the most deadly of the gynecological cancers. New approaches and better tools for monitoring treatment efficacy and disease progression of EOC are required. In this study, metabolomics using rapid resolution liquid chromatography mass spectrometry was applied to a...
Autores principales: | , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4800393/ https://www.ncbi.nlm.nih.gov/pubmed/26996990 http://dx.doi.org/10.1038/srep23334 |
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author | Ke, Chaofu Li, Ang Hou, Yan Sun, Meng Yang, Kai Cheng, Jinlong Wang, Jingtao Ge, Tingting Zhang, Fan Li, Qiang Li, Junnan Wu, Ying Lou, Ge Li, Kang |
author_facet | Ke, Chaofu Li, Ang Hou, Yan Sun, Meng Yang, Kai Cheng, Jinlong Wang, Jingtao Ge, Tingting Zhang, Fan Li, Qiang Li, Junnan Wu, Ying Lou, Ge Li, Kang |
author_sort | Ke, Chaofu |
collection | PubMed |
description | Epithelial ovarian cancer (EOC) is the most deadly of the gynecological cancers. New approaches and better tools for monitoring treatment efficacy and disease progression of EOC are required. In this study, metabolomics using rapid resolution liquid chromatography mass spectrometry was applied to a systematic investigation of metabolic changes in response to advanced EOC, surgery and recurrence. The results revealed considerable metabolic differences between groups. Moreover, 37, 30, and 26 metabolites were identified as potential biomarkers for primary, surgical and recurrent EOC, respectively. Primary EOC was characterized by abnormal lipid metabolism and energy disorders. Oxidative stress and surgical efficacy were clear in the post-operative EOC patients. Recurrent EOC patients showed increased amino acid and lipid metabolism compared with primary EOC patients. After cytoreductive surgery, eight metabolites (e.g. l-kynurenine, retinol, hydroxyphenyllactic acid, 2-octenoic acid) corrected towards levels of the control group, and four (e.g. hydroxyphenyllactic acid, 2-octenoic acid) went back again to primary EOC levels after disease relapse. In conclusion, this study delineated metabolic changes in response to advanced EOC, surgery and recurrence, and identified biomarkers that could facilitate both understanding and monitoring of EOC development and progression. |
format | Online Article Text |
id | pubmed-4800393 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-48003932016-03-22 Metabolic phenotyping for monitoring ovarian cancer patients Ke, Chaofu Li, Ang Hou, Yan Sun, Meng Yang, Kai Cheng, Jinlong Wang, Jingtao Ge, Tingting Zhang, Fan Li, Qiang Li, Junnan Wu, Ying Lou, Ge Li, Kang Sci Rep Article Epithelial ovarian cancer (EOC) is the most deadly of the gynecological cancers. New approaches and better tools for monitoring treatment efficacy and disease progression of EOC are required. In this study, metabolomics using rapid resolution liquid chromatography mass spectrometry was applied to a systematic investigation of metabolic changes in response to advanced EOC, surgery and recurrence. The results revealed considerable metabolic differences between groups. Moreover, 37, 30, and 26 metabolites were identified as potential biomarkers for primary, surgical and recurrent EOC, respectively. Primary EOC was characterized by abnormal lipid metabolism and energy disorders. Oxidative stress and surgical efficacy were clear in the post-operative EOC patients. Recurrent EOC patients showed increased amino acid and lipid metabolism compared with primary EOC patients. After cytoreductive surgery, eight metabolites (e.g. l-kynurenine, retinol, hydroxyphenyllactic acid, 2-octenoic acid) corrected towards levels of the control group, and four (e.g. hydroxyphenyllactic acid, 2-octenoic acid) went back again to primary EOC levels after disease relapse. In conclusion, this study delineated metabolic changes in response to advanced EOC, surgery and recurrence, and identified biomarkers that could facilitate both understanding and monitoring of EOC development and progression. Nature Publishing Group 2016-03-21 /pmc/articles/PMC4800393/ /pubmed/26996990 http://dx.doi.org/10.1038/srep23334 Text en Copyright © 2016, Macmillan Publishers Limited http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Ke, Chaofu Li, Ang Hou, Yan Sun, Meng Yang, Kai Cheng, Jinlong Wang, Jingtao Ge, Tingting Zhang, Fan Li, Qiang Li, Junnan Wu, Ying Lou, Ge Li, Kang Metabolic phenotyping for monitoring ovarian cancer patients |
title | Metabolic phenotyping for monitoring ovarian cancer patients |
title_full | Metabolic phenotyping for monitoring ovarian cancer patients |
title_fullStr | Metabolic phenotyping for monitoring ovarian cancer patients |
title_full_unstemmed | Metabolic phenotyping for monitoring ovarian cancer patients |
title_short | Metabolic phenotyping for monitoring ovarian cancer patients |
title_sort | metabolic phenotyping for monitoring ovarian cancer patients |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4800393/ https://www.ncbi.nlm.nih.gov/pubmed/26996990 http://dx.doi.org/10.1038/srep23334 |
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