Science Translational MedicineCancer BiologyPeer-reviewed journal article
Lactylation fuels nucleotide biosynthesis and facilitates deuterium metabolic imaging of tumor proliferation in H3K27M-mutant gliomas
Georgios BatsiosiD, Céline TaglangiD, Suresh UduthaiD, Anne Marie GillespieiD, Simon P. RobinsoniD, Timothy Phoenix, Sabine Mueller, Sriram VennetiiD, Carl Koschmann, Pavithra ViswanathiD
Abstract
Oncogenes hyperactive lactate production, but the mechanisms by which lactate facilitates tumor growth are unclear. Here, we demonstrate that lactate is essential for nucleotide biosynthesis in pediatric diffuse midline gliomas (DMGs). The oncogenic histone H3K27M mutation upregulates phosphoglycerate kinase 1 (PGK1) and drives lactate production from [U-13C]-glucose in DMGs. Lactate activates the nucleoside diphosphate kinase NME1 via lactylation and promotes the synthesis of nucleoside triphosphates essential for tumor proliferation. Importantly, we show that this mechanistic link between glycolysis and nucleotide biosynthesis provides a unique opportunity for deuterium metabolic imaging of DMGs. Spatially mapping 2H-lactate production from [6,6-2H]-glucose allows visualization of the metabolically active tumor lesion and provides an early readout of response to standard-of-care radiation and targeted therapy that precedes extended survival and reflects pharmacodynamic alterations at the tissue level in preclinical DMG models in vivo at clinical field strength (3T). In essence, we have identified an H3K27M-lactate-NME1 axis that promotes DMG proliferation and facilitates non-invasive metabolic imaging of DMGs. STATEMENT OF SIGNIFICANCEThis study establishes a role for lactate in driving nucleotide biosynthesis in DMGs. Importantly, imaging lactate production from glucose using DMI provides a readout of tumor proliferation and early response to therapy in clinically relevant DMG models. Our studies lay the foundation for precision metabolic imaging of DMG patients.
- organism: human
- assay: metabolomics
- assay: imaging
- research focus: drug response / drug discovery
- research focus: cell type annotation
- approach: deep learning
- approach: statistical model
- Citations
- 11
- FWCI
- 25.23
- Field percentile
- top 1%
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