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Serum NMR metabolomics to differentiate haematologic malignancies
Haematological malignancies are a frequently diagnosed group of neoplasms and a significant cause of cancer deaths. The successful treatment of these diseases relies on early and accurate detection. Specific small molecular compounds released by malignant cells and the simultaneous response by the o...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5966245/ https://www.ncbi.nlm.nih.gov/pubmed/29849950 http://dx.doi.org/10.18632/oncotarget.25311 |
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author | Wojtowicz, Wojciech Chachaj, Angelika Olczak, Andrzej Ząbek, Adam Piątkowska, Elżbieta Rybka, Justyna Butrym, Aleksandra Biedroń, Monika Mazur, Grzegorz Wróbel, Tomasz Szuba, Andrzej Młynarz, Piotr |
author_facet | Wojtowicz, Wojciech Chachaj, Angelika Olczak, Andrzej Ząbek, Adam Piątkowska, Elżbieta Rybka, Justyna Butrym, Aleksandra Biedroń, Monika Mazur, Grzegorz Wróbel, Tomasz Szuba, Andrzej Młynarz, Piotr |
author_sort | Wojtowicz, Wojciech |
collection | PubMed |
description | Haematological malignancies are a frequently diagnosed group of neoplasms and a significant cause of cancer deaths. The successful treatment of these diseases relies on early and accurate detection. Specific small molecular compounds released by malignant cells and the simultaneous response by the organism towards the pathological state may serve as diagnostic/prognostic biomarkers or as a tool with relevance for cancer therapy management. To identify the most important metabolites required for differentiation, an (1)H NMR metabolomics approach was applied to selected haematological malignancies. This study utilized 116 methanol serum extract samples from AML (n= 38), nHL (n= 26), CLL (n= 21) and HC (n= 31). Multivariate and univariate data analyses were performed to identify the most abundant changes among the studied groups. Complex and detailed VIP-PLS-DA models were calculated to highlight possible changes in terms of biochemical pathways and discrimination ability. Chemometric model prediction properties were validated by receiver operating characteristic (ROC) curves and statistical analysis. Two sets of eight important metabolites in HC/AML/CLL/nHL comparisons and five in AML/CLL/nHL comparisons were selected to form complex models to represent the most significant changes that occurred. |
format | Online Article Text |
id | pubmed-5966245 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-59662452018-05-30 Serum NMR metabolomics to differentiate haematologic malignancies Wojtowicz, Wojciech Chachaj, Angelika Olczak, Andrzej Ząbek, Adam Piątkowska, Elżbieta Rybka, Justyna Butrym, Aleksandra Biedroń, Monika Mazur, Grzegorz Wróbel, Tomasz Szuba, Andrzej Młynarz, Piotr Oncotarget Research Paper Haematological malignancies are a frequently diagnosed group of neoplasms and a significant cause of cancer deaths. The successful treatment of these diseases relies on early and accurate detection. Specific small molecular compounds released by malignant cells and the simultaneous response by the organism towards the pathological state may serve as diagnostic/prognostic biomarkers or as a tool with relevance for cancer therapy management. To identify the most important metabolites required for differentiation, an (1)H NMR metabolomics approach was applied to selected haematological malignancies. This study utilized 116 methanol serum extract samples from AML (n= 38), nHL (n= 26), CLL (n= 21) and HC (n= 31). Multivariate and univariate data analyses were performed to identify the most abundant changes among the studied groups. Complex and detailed VIP-PLS-DA models were calculated to highlight possible changes in terms of biochemical pathways and discrimination ability. Chemometric model prediction properties were validated by receiver operating characteristic (ROC) curves and statistical analysis. Two sets of eight important metabolites in HC/AML/CLL/nHL comparisons and five in AML/CLL/nHL comparisons were selected to form complex models to represent the most significant changes that occurred. Impact Journals LLC 2018-05-11 /pmc/articles/PMC5966245/ /pubmed/29849950 http://dx.doi.org/10.18632/oncotarget.25311 Text en Copyright: © 2018 Wojtowicz et al. http://creativecommons.org/licenses/by/3.0/ This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/) (CC-BY), which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Research Paper Wojtowicz, Wojciech Chachaj, Angelika Olczak, Andrzej Ząbek, Adam Piątkowska, Elżbieta Rybka, Justyna Butrym, Aleksandra Biedroń, Monika Mazur, Grzegorz Wróbel, Tomasz Szuba, Andrzej Młynarz, Piotr Serum NMR metabolomics to differentiate haematologic malignancies |
title | Serum NMR metabolomics to differentiate haematologic malignancies |
title_full | Serum NMR metabolomics to differentiate haematologic malignancies |
title_fullStr | Serum NMR metabolomics to differentiate haematologic malignancies |
title_full_unstemmed | Serum NMR metabolomics to differentiate haematologic malignancies |
title_short | Serum NMR metabolomics to differentiate haematologic malignancies |
title_sort | serum nmr metabolomics to differentiate haematologic malignancies |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5966245/ https://www.ncbi.nlm.nih.gov/pubmed/29849950 http://dx.doi.org/10.18632/oncotarget.25311 |
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