Deuterium metabolic imaging phenotypes mouse glioblastoma heterogeneity through glucose turnover kinetics
Glioblastomas are aggressive brain tumors with dismal prognosis. One of the main bottlenecks for developing more effective therapies for glioblastoma stems from their histologic and molecular heterogeneity, leading to distinct tumor microenvironments and disease phenotypes. Effectively characterizin...
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eLife Sciences Publications Ltd
2025-03-01
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| author | Rui Vasco Simoes Rafael Neto Henriques Jonas L Olesen Beatriz M Cardoso Francisca F Fernandes Mariana AV Monteiro Sune N Jespersen Tânia Carvalho Noam Shemesh |
| author_facet | Rui Vasco Simoes Rafael Neto Henriques Jonas L Olesen Beatriz M Cardoso Francisca F Fernandes Mariana AV Monteiro Sune N Jespersen Tânia Carvalho Noam Shemesh |
| author_sort | Rui Vasco Simoes |
| collection | DOAJ |
| description | Glioblastomas are aggressive brain tumors with dismal prognosis. One of the main bottlenecks for developing more effective therapies for glioblastoma stems from their histologic and molecular heterogeneity, leading to distinct tumor microenvironments and disease phenotypes. Effectively characterizing these features would improve the clinical management of glioblastoma. Glucose flux rates through glycolysis and mitochondrial oxidation have been recently shown to quantitatively depict glioblastoma proliferation in mouse models (GL261 and CT2A tumors) using dynamic glucose-enhanced (DGE) deuterium spectroscopy. However, the spatial features of tumor microenvironment phenotypes remain hitherto unresolved. Here, we develop a DGE Deuterium Metabolic Imaging (DMI) approach for profiling tumor microenvironments through glucose conversion kinetics. Using a multimodal combination of tumor mouse models, novel strategies for spectroscopic imaging and noise attenuation, and histopathological correlations, we show that tumor lactate turnover mirrors phenotype differences between GL261 and CT2A mouse glioblastoma, whereas recycling of the peritumoral glutamate-glutamine pool is a potential marker of invasion capacity in pooled cohorts, linked to secondary brain lesions. These findings were validated by histopathological characterization of each tumor, including cell density and proliferation, peritumoral invasion and distant migration, and immune cell infiltration. Our study bodes well for precision neuro-oncology, highlighting the importance of mapping glucose flux rates to better understand the metabolic heterogeneity of glioblastoma and its links to disease phenotypes. |
| format | Article |
| id | doaj-art-04fbf5874a9e4df8b0232dfd8ab8ca1f |
| institution | OA Journals |
| issn | 2050-084X |
| language | English |
| publishDate | 2025-03-01 |
| publisher | eLife Sciences Publications Ltd |
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| series | eLife |
| spelling | doaj-art-04fbf5874a9e4df8b0232dfd8ab8ca1f2025-08-20T02:02:20ZengeLife Sciences Publications LtdeLife2050-084X2025-03-011310.7554/eLife.100570Deuterium metabolic imaging phenotypes mouse glioblastoma heterogeneity through glucose turnover kineticsRui Vasco Simoes0https://orcid.org/0000-0001-7574-4723Rafael Neto Henriques1Jonas L Olesen2Beatriz M Cardoso3Francisca F Fernandes4Mariana AV Monteiro5Sune N Jespersen6Tânia Carvalho7Noam Shemesh8https://orcid.org/0000-0001-6681-5876Preclinical MRI, Champalimaud Research, Champalimaud Foundation, Lisbon, Portugal; Neuroengineering and Computational Neuroscience, Institute for Research and Innovation in Health (i3S), Porto, PortugalPreclinical MRI, Champalimaud Research, Champalimaud Foundation, Lisbon, PortugalCenter of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Physics and Astronomy, Aarhus University, Aarhus, DenmarkPreclinical MRI, Champalimaud Research, Champalimaud Foundation, Lisbon, PortugalPreclinical MRI, Champalimaud Research, Champalimaud Foundation, Lisbon, PortugalHistopathology Platform, Champalimaud Research, Champalimaud Foundation, Lisbon, PortugalCenter of Functionally Integrative Neuroscience (CFIN) and MINDLab, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; Department of Physics and Astronomy, Aarhus University, Aarhus, DenmarkHistopathology Platform, Champalimaud Research, Champalimaud Foundation, Lisbon, PortugalPreclinical MRI, Champalimaud Research, Champalimaud Foundation, Lisbon, PortugalGlioblastomas are aggressive brain tumors with dismal prognosis. One of the main bottlenecks for developing more effective therapies for glioblastoma stems from their histologic and molecular heterogeneity, leading to distinct tumor microenvironments and disease phenotypes. Effectively characterizing these features would improve the clinical management of glioblastoma. Glucose flux rates through glycolysis and mitochondrial oxidation have been recently shown to quantitatively depict glioblastoma proliferation in mouse models (GL261 and CT2A tumors) using dynamic glucose-enhanced (DGE) deuterium spectroscopy. However, the spatial features of tumor microenvironment phenotypes remain hitherto unresolved. Here, we develop a DGE Deuterium Metabolic Imaging (DMI) approach for profiling tumor microenvironments through glucose conversion kinetics. Using a multimodal combination of tumor mouse models, novel strategies for spectroscopic imaging and noise attenuation, and histopathological correlations, we show that tumor lactate turnover mirrors phenotype differences between GL261 and CT2A mouse glioblastoma, whereas recycling of the peritumoral glutamate-glutamine pool is a potential marker of invasion capacity in pooled cohorts, linked to secondary brain lesions. These findings were validated by histopathological characterization of each tumor, including cell density and proliferation, peritumoral invasion and distant migration, and immune cell infiltration. Our study bodes well for precision neuro-oncology, highlighting the importance of mapping glucose flux rates to better understand the metabolic heterogeneity of glioblastoma and its links to disease phenotypes.https://elifesciences.org/articles/100570deuterium metabolic imagingglioblastomaglycolysiskinetic modelingmitochondrial metabolism |
| spellingShingle | Rui Vasco Simoes Rafael Neto Henriques Jonas L Olesen Beatriz M Cardoso Francisca F Fernandes Mariana AV Monteiro Sune N Jespersen Tânia Carvalho Noam Shemesh Deuterium metabolic imaging phenotypes mouse glioblastoma heterogeneity through glucose turnover kinetics eLife deuterium metabolic imaging glioblastoma glycolysis kinetic modeling mitochondrial metabolism |
| title | Deuterium metabolic imaging phenotypes mouse glioblastoma heterogeneity through glucose turnover kinetics |
| title_full | Deuterium metabolic imaging phenotypes mouse glioblastoma heterogeneity through glucose turnover kinetics |
| title_fullStr | Deuterium metabolic imaging phenotypes mouse glioblastoma heterogeneity through glucose turnover kinetics |
| title_full_unstemmed | Deuterium metabolic imaging phenotypes mouse glioblastoma heterogeneity through glucose turnover kinetics |
| title_short | Deuterium metabolic imaging phenotypes mouse glioblastoma heterogeneity through glucose turnover kinetics |
| title_sort | deuterium metabolic imaging phenotypes mouse glioblastoma heterogeneity through glucose turnover kinetics |
| topic | deuterium metabolic imaging glioblastoma glycolysis kinetic modeling mitochondrial metabolism |
| url | https://elifesciences.org/articles/100570 |
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