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NMR-based metabolomic profiling can differentiate follicular lymphoma from benign lymph node tissues and may be predictive of outcome
Follicular lymphoma (FL) is a cancer of B-cells, representing the second most common type of non-Hodgkin lymphoma and typically diagnosed at advanced stage in older adults. In contrast to the wide range of available molecular genetic data, limited data relating the metabolomic features of follicular...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9117304/ https://www.ncbi.nlm.nih.gov/pubmed/35585165 http://dx.doi.org/10.1038/s41598-022-12445-5 |
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author | Banoei, Mohammad Mehdi Mahé, Etienne Mansoor, Adnan Stewart, Douglas Winston, Brent W. Habibi, Hamid R. Shabani-Rad, Meer-Taher |
author_facet | Banoei, Mohammad Mehdi Mahé, Etienne Mansoor, Adnan Stewart, Douglas Winston, Brent W. Habibi, Hamid R. Shabani-Rad, Meer-Taher |
author_sort | Banoei, Mohammad Mehdi |
collection | PubMed |
description | Follicular lymphoma (FL) is a cancer of B-cells, representing the second most common type of non-Hodgkin lymphoma and typically diagnosed at advanced stage in older adults. In contrast to the wide range of available molecular genetic data, limited data relating the metabolomic features of follicular lymphoma are known. Metabolomics is a promising analytical approach employing metabolites (molecules < 1 kDa in size) as potential biomarkers in cancer research. In this pilot study, we performed proton nuclear magnetic resonance spectroscopy ((1)H-NMR) on 29 cases of FL and 11 control patient specimens. The resulting spectra were assessed by both unsupervised and supervised statistical methods. We report significantly discriminant metabolomic models of common metabolites distinguishing FL from control tissues. Within our FL case series, we also report discriminant metabolomic signatures predictive of progression-free survival. |
format | Online Article Text |
id | pubmed-9117304 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-91173042022-05-20 NMR-based metabolomic profiling can differentiate follicular lymphoma from benign lymph node tissues and may be predictive of outcome Banoei, Mohammad Mehdi Mahé, Etienne Mansoor, Adnan Stewart, Douglas Winston, Brent W. Habibi, Hamid R. Shabani-Rad, Meer-Taher Sci Rep Article Follicular lymphoma (FL) is a cancer of B-cells, representing the second most common type of non-Hodgkin lymphoma and typically diagnosed at advanced stage in older adults. In contrast to the wide range of available molecular genetic data, limited data relating the metabolomic features of follicular lymphoma are known. Metabolomics is a promising analytical approach employing metabolites (molecules < 1 kDa in size) as potential biomarkers in cancer research. In this pilot study, we performed proton nuclear magnetic resonance spectroscopy ((1)H-NMR) on 29 cases of FL and 11 control patient specimens. The resulting spectra were assessed by both unsupervised and supervised statistical methods. We report significantly discriminant metabolomic models of common metabolites distinguishing FL from control tissues. Within our FL case series, we also report discriminant metabolomic signatures predictive of progression-free survival. Nature Publishing Group UK 2022-05-18 /pmc/articles/PMC9117304/ /pubmed/35585165 http://dx.doi.org/10.1038/s41598-022-12445-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Banoei, Mohammad Mehdi Mahé, Etienne Mansoor, Adnan Stewart, Douglas Winston, Brent W. Habibi, Hamid R. Shabani-Rad, Meer-Taher NMR-based metabolomic profiling can differentiate follicular lymphoma from benign lymph node tissues and may be predictive of outcome |
title | NMR-based metabolomic profiling can differentiate follicular lymphoma from benign lymph node tissues and may be predictive of outcome |
title_full | NMR-based metabolomic profiling can differentiate follicular lymphoma from benign lymph node tissues and may be predictive of outcome |
title_fullStr | NMR-based metabolomic profiling can differentiate follicular lymphoma from benign lymph node tissues and may be predictive of outcome |
title_full_unstemmed | NMR-based metabolomic profiling can differentiate follicular lymphoma from benign lymph node tissues and may be predictive of outcome |
title_short | NMR-based metabolomic profiling can differentiate follicular lymphoma from benign lymph node tissues and may be predictive of outcome |
title_sort | nmr-based metabolomic profiling can differentiate follicular lymphoma from benign lymph node tissues and may be predictive of outcome |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9117304/ https://www.ncbi.nlm.nih.gov/pubmed/35585165 http://dx.doi.org/10.1038/s41598-022-12445-5 |
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