Cargando…
Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem
Tumors are comprised of a multitude of cell types spanning different microenvironments. Mass spectrometry imaging (MSI) has the potential to identify metabolic patterns within the tumor ecosystem and surrounding tissues, but conventional workflows have not yet fully integrated the breadth of experim...
Autores principales: | , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10199024/ https://www.ncbi.nlm.nih.gov/pubmed/37208361 http://dx.doi.org/10.1038/s41467-023-38403-x |
_version_ | 1785044843368546304 |
---|---|
author | Schwaiger-Haber, Michaela Stancliffe, Ethan Anbukumar, Dhanalakshmi S. Sells, Blake Yi, Jia Cho, Kevin Adkins-Travis, Kayla Chheda, Milan G. Shriver, Leah P. Patti, Gary J. |
author_facet | Schwaiger-Haber, Michaela Stancliffe, Ethan Anbukumar, Dhanalakshmi S. Sells, Blake Yi, Jia Cho, Kevin Adkins-Travis, Kayla Chheda, Milan G. Shriver, Leah P. Patti, Gary J. |
author_sort | Schwaiger-Haber, Michaela |
collection | PubMed |
description | Tumors are comprised of a multitude of cell types spanning different microenvironments. Mass spectrometry imaging (MSI) has the potential to identify metabolic patterns within the tumor ecosystem and surrounding tissues, but conventional workflows have not yet fully integrated the breadth of experimental techniques in metabolomics. Here, we combine MSI, stable isotope labeling, and a spatial variant of Isotopologue Spectral Analysis to map distributions of metabolite abundances, nutrient contributions, and metabolic turnover fluxes across the brains of mice harboring GL261 glioma, a widely used model for glioblastoma. When integrated with MSI, the combination of ion mobility, desorption electrospray ionization, and matrix assisted laser desorption ionization reveals alterations in multiple anabolic pathways. De novo fatty acid synthesis flux is increased by approximately 3-fold in glioma relative to surrounding healthy tissue. Fatty acid elongation flux is elevated even higher at 8-fold relative to surrounding healthy tissue and highlights the importance of elongase activity in glioma. |
format | Online Article Text |
id | pubmed-10199024 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-101990242023-05-21 Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem Schwaiger-Haber, Michaela Stancliffe, Ethan Anbukumar, Dhanalakshmi S. Sells, Blake Yi, Jia Cho, Kevin Adkins-Travis, Kayla Chheda, Milan G. Shriver, Leah P. Patti, Gary J. Nat Commun Article Tumors are comprised of a multitude of cell types spanning different microenvironments. Mass spectrometry imaging (MSI) has the potential to identify metabolic patterns within the tumor ecosystem and surrounding tissues, but conventional workflows have not yet fully integrated the breadth of experimental techniques in metabolomics. Here, we combine MSI, stable isotope labeling, and a spatial variant of Isotopologue Spectral Analysis to map distributions of metabolite abundances, nutrient contributions, and metabolic turnover fluxes across the brains of mice harboring GL261 glioma, a widely used model for glioblastoma. When integrated with MSI, the combination of ion mobility, desorption electrospray ionization, and matrix assisted laser desorption ionization reveals alterations in multiple anabolic pathways. De novo fatty acid synthesis flux is increased by approximately 3-fold in glioma relative to surrounding healthy tissue. Fatty acid elongation flux is elevated even higher at 8-fold relative to surrounding healthy tissue and highlights the importance of elongase activity in glioma. Nature Publishing Group UK 2023-05-19 /pmc/articles/PMC10199024/ /pubmed/37208361 http://dx.doi.org/10.1038/s41467-023-38403-x Text en © The Author(s) 2023 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Schwaiger-Haber, Michaela Stancliffe, Ethan Anbukumar, Dhanalakshmi S. Sells, Blake Yi, Jia Cho, Kevin Adkins-Travis, Kayla Chheda, Milan G. Shriver, Leah P. Patti, Gary J. Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem |
title | Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem |
title_full | Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem |
title_fullStr | Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem |
title_full_unstemmed | Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem |
title_short | Using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem |
title_sort | using mass spectrometry imaging to map fluxes quantitatively in the tumor ecosystem |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10199024/ https://www.ncbi.nlm.nih.gov/pubmed/37208361 http://dx.doi.org/10.1038/s41467-023-38403-x |
work_keys_str_mv | AT schwaigerhabermichaela usingmassspectrometryimagingtomapfluxesquantitativelyinthetumorecosystem AT stancliffeethan usingmassspectrometryimagingtomapfluxesquantitativelyinthetumorecosystem AT anbukumardhanalakshmis usingmassspectrometryimagingtomapfluxesquantitativelyinthetumorecosystem AT sellsblake usingmassspectrometryimagingtomapfluxesquantitativelyinthetumorecosystem AT yijia usingmassspectrometryimagingtomapfluxesquantitativelyinthetumorecosystem AT chokevin usingmassspectrometryimagingtomapfluxesquantitativelyinthetumorecosystem AT adkinstraviskayla usingmassspectrometryimagingtomapfluxesquantitativelyinthetumorecosystem AT chhedamilang usingmassspectrometryimagingtomapfluxesquantitativelyinthetumorecosystem AT shriverleahp usingmassspectrometryimagingtomapfluxesquantitativelyinthetumorecosystem AT pattigaryj usingmassspectrometryimagingtomapfluxesquantitativelyinthetumorecosystem |