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Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics
INTRODUCTION: Cellular metabolism is altered during cancer initiation and progression, which allows cancer cells to increase anabolic synthesis, avoid apoptosis and adapt to low nutrient and oxygen availability. The metabolic nature of cancer enables patient cancer status to be monitored by metabolo...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4987388/ https://www.ncbi.nlm.nih.gov/pubmed/27616976 http://dx.doi.org/10.1007/s11306-016-1093-7 |
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author | Armitage, Emily G. Southam, Andrew D. |
author_facet | Armitage, Emily G. Southam, Andrew D. |
author_sort | Armitage, Emily G. |
collection | PubMed |
description | INTRODUCTION: Cellular metabolism is altered during cancer initiation and progression, which allows cancer cells to increase anabolic synthesis, avoid apoptosis and adapt to low nutrient and oxygen availability. The metabolic nature of cancer enables patient cancer status to be monitored by metabolomics and lipidomics. Additionally, monitoring metabolic status of patients or biological models can be used to greater understand the action of anticancer therapeutics. OBJECTIVES: Discuss how metabolomics and lipidomics can be used to (i) identify metabolic biomarkers of cancer and (ii) understand the mechanism-of-action of anticancer therapies. Discuss considerations that can maximize the clinical value of metabolic cancer biomarkers including case–control, prognostic and longitudinal study designs. METHODS: A literature search of the current relevant primary research was performed. RESULTS: Metabolomics and lipidomics can identify metabolic signatures that associate with cancer diagnosis, prognosis and disease progression. Discriminatory metabolites were most commonly linked to lipid or energy metabolism. Case–control studies outnumbered prognostic and longitudinal approaches. Prognostic studies were able to correlate metabolic features with future cancer risk, whereas longitudinal studies were most effective for studying cancer progression. Metabolomics and lipidomics can help to understand the mechanism-of-action of anticancer therapeutics and mechanisms of drug resistance. CONCLUSION: Metabolomics and lipidomics can be used to identify biomarkers associated with cancer and to better understand anticancer therapies. |
format | Online Article Text |
id | pubmed-4987388 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-49873882016-09-07 Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics Armitage, Emily G. Southam, Andrew D. Metabolomics Original Article INTRODUCTION: Cellular metabolism is altered during cancer initiation and progression, which allows cancer cells to increase anabolic synthesis, avoid apoptosis and adapt to low nutrient and oxygen availability. The metabolic nature of cancer enables patient cancer status to be monitored by metabolomics and lipidomics. Additionally, monitoring metabolic status of patients or biological models can be used to greater understand the action of anticancer therapeutics. OBJECTIVES: Discuss how metabolomics and lipidomics can be used to (i) identify metabolic biomarkers of cancer and (ii) understand the mechanism-of-action of anticancer therapies. Discuss considerations that can maximize the clinical value of metabolic cancer biomarkers including case–control, prognostic and longitudinal study designs. METHODS: A literature search of the current relevant primary research was performed. RESULTS: Metabolomics and lipidomics can identify metabolic signatures that associate with cancer diagnosis, prognosis and disease progression. Discriminatory metabolites were most commonly linked to lipid or energy metabolism. Case–control studies outnumbered prognostic and longitudinal approaches. Prognostic studies were able to correlate metabolic features with future cancer risk, whereas longitudinal studies were most effective for studying cancer progression. Metabolomics and lipidomics can help to understand the mechanism-of-action of anticancer therapeutics and mechanisms of drug resistance. CONCLUSION: Metabolomics and lipidomics can be used to identify biomarkers associated with cancer and to better understand anticancer therapies. Springer US 2016-08-16 2016 /pmc/articles/PMC4987388/ /pubmed/27616976 http://dx.doi.org/10.1007/s11306-016-1093-7 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Original Article Armitage, Emily G. Southam, Andrew D. Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics |
title | Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics |
title_full | Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics |
title_fullStr | Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics |
title_full_unstemmed | Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics |
title_short | Monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics |
title_sort | monitoring cancer prognosis, diagnosis and treatment efficacy using metabolomics and lipidomics |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4987388/ https://www.ncbi.nlm.nih.gov/pubmed/27616976 http://dx.doi.org/10.1007/s11306-016-1093-7 |
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