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How previous treatment changes the metabolomic profile in patients with metastatic breast cancer

PURPOSE: Metabolites are in the spotlight of attention as promising novel breast cancer biomarkers. However, no study has been conducted concerning changes in the metabolomics profile of metastatic breast cancer patients according to previous therapy. METHODS: We performed a retrospective, single-ce...

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Autores principales: Nees, Juliane, Schafferer, Simon, Yuan, Baowen, Tang, Quiqong, Scheffler, Matthias, Hartkopf, Andreas, Golatta, Michael, Schneeweiß, Andreas, Burwinkel, Barbara, Wallwiener, Markus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9633507/
https://www.ncbi.nlm.nih.gov/pubmed/35467121
http://dx.doi.org/10.1007/s00404-022-06558-5
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author Nees, Juliane
Schafferer, Simon
Yuan, Baowen
Tang, Quiqong
Scheffler, Matthias
Hartkopf, Andreas
Golatta, Michael
Schneeweiß, Andreas
Burwinkel, Barbara
Wallwiener, Markus
author_facet Nees, Juliane
Schafferer, Simon
Yuan, Baowen
Tang, Quiqong
Scheffler, Matthias
Hartkopf, Andreas
Golatta, Michael
Schneeweiß, Andreas
Burwinkel, Barbara
Wallwiener, Markus
author_sort Nees, Juliane
collection PubMed
description PURPOSE: Metabolites are in the spotlight of attention as promising novel breast cancer biomarkers. However, no study has been conducted concerning changes in the metabolomics profile of metastatic breast cancer patients according to previous therapy. METHODS: We performed a retrospective, single-center, nonrandomized, partially blinded, treatment-based study. Metastatic breast cancer (MBC) patients were enrolled between 03/2010 and 09/2016 at the beginning of a new systemic therapy. The endogenous metabolites in the plasma samples were analyzed using the AbsoluteIDQ(®) p180 Kit (Biocrates Life Sciences AG, Innsbruck) a targeted, quality and quantitative-controlled metabolomics approach. The statistical analysis was performed using R package, version 3.3.1. ANOVA was used to statistically assess age differences within groups. Furthermore, we analyzed the CTC status of the patients using the CellSearch(™) assay. RESULTS: We included 178 patients in our study. Upon dividing the study population according to therapy before study inclusion, we found the following: 4 patients had received no therapy, 165 chemotherapy, and 135 anti-hormonal therapy, 30 with anti-Her2 therapy and 38 had received treatment with bevacizumab. Two metabolites were found to be significantly different, depending on the further therapy of the patients: methionine and serine. Whereas methionine levels were higher in the blood of patients who received an anti-Her2-therapy, serine was lower in patients with endocrine therapy only. CONCLUSION: We identified two metabolites for which concentrations differed significantly depending on previous therapies, which could help to choose the next therapy in patients who have already received numerous different treatments.
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spelling pubmed-96335072022-11-05 How previous treatment changes the metabolomic profile in patients with metastatic breast cancer Nees, Juliane Schafferer, Simon Yuan, Baowen Tang, Quiqong Scheffler, Matthias Hartkopf, Andreas Golatta, Michael Schneeweiß, Andreas Burwinkel, Barbara Wallwiener, Markus Arch Gynecol Obstet Gynecologic Oncology PURPOSE: Metabolites are in the spotlight of attention as promising novel breast cancer biomarkers. However, no study has been conducted concerning changes in the metabolomics profile of metastatic breast cancer patients according to previous therapy. METHODS: We performed a retrospective, single-center, nonrandomized, partially blinded, treatment-based study. Metastatic breast cancer (MBC) patients were enrolled between 03/2010 and 09/2016 at the beginning of a new systemic therapy. The endogenous metabolites in the plasma samples were analyzed using the AbsoluteIDQ(®) p180 Kit (Biocrates Life Sciences AG, Innsbruck) a targeted, quality and quantitative-controlled metabolomics approach. The statistical analysis was performed using R package, version 3.3.1. ANOVA was used to statistically assess age differences within groups. Furthermore, we analyzed the CTC status of the patients using the CellSearch(™) assay. RESULTS: We included 178 patients in our study. Upon dividing the study population according to therapy before study inclusion, we found the following: 4 patients had received no therapy, 165 chemotherapy, and 135 anti-hormonal therapy, 30 with anti-Her2 therapy and 38 had received treatment with bevacizumab. Two metabolites were found to be significantly different, depending on the further therapy of the patients: methionine and serine. Whereas methionine levels were higher in the blood of patients who received an anti-Her2-therapy, serine was lower in patients with endocrine therapy only. CONCLUSION: We identified two metabolites for which concentrations differed significantly depending on previous therapies, which could help to choose the next therapy in patients who have already received numerous different treatments. Springer Berlin Heidelberg 2022-04-25 2022 /pmc/articles/PMC9633507/ /pubmed/35467121 http://dx.doi.org/10.1007/s00404-022-06558-5 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Gynecologic Oncology
Nees, Juliane
Schafferer, Simon
Yuan, Baowen
Tang, Quiqong
Scheffler, Matthias
Hartkopf, Andreas
Golatta, Michael
Schneeweiß, Andreas
Burwinkel, Barbara
Wallwiener, Markus
How previous treatment changes the metabolomic profile in patients with metastatic breast cancer
title How previous treatment changes the metabolomic profile in patients with metastatic breast cancer
title_full How previous treatment changes the metabolomic profile in patients with metastatic breast cancer
title_fullStr How previous treatment changes the metabolomic profile in patients with metastatic breast cancer
title_full_unstemmed How previous treatment changes the metabolomic profile in patients with metastatic breast cancer
title_short How previous treatment changes the metabolomic profile in patients with metastatic breast cancer
title_sort how previous treatment changes the metabolomic profile in patients with metastatic breast cancer
topic Gynecologic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9633507/
https://www.ncbi.nlm.nih.gov/pubmed/35467121
http://dx.doi.org/10.1007/s00404-022-06558-5
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