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Early detection of tumor cell death in glioblastoma following treatment with chemoradiation has the potential to distinguish between true disease progression and pseudoprogression. Tumor cell death can be detected noninvasively in vivo by imaging the production of [2,3-2H2]malate from [2,3-2H2]fumarate using 2H magnetic resonance (MR) spectroscopic imaging. We show here that 2H MR spectroscopy and spectroscopic imaging measurements of [2,3-2H2]fumarate metabolism can detect tumor cell death in orthotopically implanted glioblastoma models within 48 hours following the completion of chemoradiation. Following the injection of [2,3-2H2]fumarate into tumor-bearing mice, production of [2,3-2H2]malate was measured in a human cell line–derived model and in radiosensitive and radioresistant patient-derived models of glioblastoma that were treated with temozolomide followed by targeted fractionated irradiation. The increase in the [2,3-2H2]malate/[2,3-2H2]fumarate signal ratio posttreatment, which correlated with histologic assessment of cell death, was a more sensitive indicator of treatment response than diffusion-weighted and contrast agent–enhanced 1H MRI measurements, which have been used clinically to detect responses of glioblastoma to chemoradiation. Overall, early detection of glioblastoma cell death using 2H MRI of malate production from fumarate could help improve the clinical evaluation of response to chemoradiation. Significance: 2H magnetic resonance imaging of labeled fumarate metabolism can detect early evidence of tumor cell death following chemoradiation, meeting a clinical need to reliably detect treatment response in glioblastoma.

Early detection of tumor cell death in glioblastoma following treatment with chemoradiation has the potential to distinguish between true disease progression and pseudoprogression. Tumor cell death can be detected noninvasively in vivo by imaging the production of [2,3-2H2]malate from [2,3-2H2]fumarate using 2H magnetic resonance (MR) spectroscopic imaging. We show here that 2H MR spectroscopy and spectroscopic imaging measurements of [2,3-2H2]fumarate metabolism can detect tumor cell death in orthotopically implanted glioblastoma models within 48 hours following the completion of chemoradiation. Following the injection of [2,3-2H2]fumarate into tumor-bearing mice, production of [2,3-2H2]malate was measured in a human cell line–derived model and in radiosensitive and radioresistant patient-derived models of glioblastoma that were treated with temozolomide followed by targeted fractionated irradiation. The increase in the [2,3-2H2]malate/[2,3-2H2]fumarate signal ratio posttreatment, which correlated with histologic assessment of cell death, was a more sensitive indicator of treatment response than diffusion-weighted and contrast agent–enhanced 1H MRI measurements, which have been used clinically to detect responses of glioblastoma to chemoradiation. Overall, early detection of glioblastoma cell death using 2H MRI of malate production from fumarate could help improve the clinical evaluation of response to chemoradiation.Significance:2H magnetic resonance imaging of labeled fumarate metabolism can detect early evidence of tumor cell death following chemoradiation, meeting a clinical need to reliably detect treatment response in glioblastoma.

Supplementary Data from Imaging Glioblastoma Response to Radiotherapy Using 2H Magnetic Resonance Spectroscopy Measurements of Fumarate Metabolism

Funder: Engineering and Physical Sciences Research Council, Methylcyclopropene (Cyoc)-tagged tetra-acetylated monosaccharides, and in particular mannosamine derivatives, are promising tools for medical imaging of cancer using metabolic oligosaccharide engineering and the extremely fast inverse electron-demand Diels-Alder bioorthogonal reaction. However, the in vivo potential of these monosaccharide derivatives has yet to be fully explored due to their low aqueous solubility. To address this issue, we sought to vary the extent of acetylation of Cyoc-tagged monosaccharides and probe its effect on the extent of glycan labeling in various cancer cell lines. We demonstrate that, in the case of AcxManNCyoc, tri- and diacetylated derivatives generated significantly enhanced cell labeling compared to the tetra-acetylated monosaccharide. In contrast, for the more readily soluble azide-tagged sugars, a decrease in acetylation led to decreased glycan labeling. Ac3ManNCyoc gave better labeling than the azido-tagged Ac4ManNAz and has significant potential for in vitro and in vivo imaging of glycosylated cancer biomarkers.

Introduction: Metabolic adaptation occurs in transformed cells and can be exploited clinically for diagnosis and disease monitoring. Metabolic profiles can be influenced by genetic heterogeneity, both within and between tumors. Breast tumors show considerable intra and inter tumor genomic heterogeneity, which partly accounts for the variable clinical course of the disease and response to treatment. Imaging tumor metabolism may provide a metabolic signature that can be used to stratify patients. Methods: We have investigated eight patient-derived xenograft (PDX) models of breast cancer to determine whether metabolic imaging can be linked to different “integrative clusters” (Int-Cluster), which are defined by their distinctive genomic profiles and clinical outcomes. Metabolic imaging was performed using PET measurements of the uptake, phosphorylation, and trapping of the glucose analog, 2-deoxy-2-[18F]fluorodeoxyglucose ([18F]FDG), catalyzed by hexokinase II, and 13C magnetic resonance spectroscopy (MRS) measurements of hyperpolarized 13C label exchange between [1-13C]pyruvate and the endogenous tumor lactate pool, catalyzed by lactate dehydrogenase A. Results: Lactate labelling was higher in Int-Clusters dominated by ER- basal-like PDXs from patients with a poor short-term prognosis. Lower levels of lactate labelling were observed in Int-Clusters dominated by estrogen receptor positive (ER+) PDXs and the Pam50 subtypes, Luminal A and B, from patients which have an intermediate to good prognosis. More importantly, tumors that had a similar genomic profile nevertheless showed differences in lactate labeling, that was not observed in the [18F]FDGPET measurements. Although lactate labelling was low in the ER+ tumor models, decreases in lactate labeling could be used to detect treatment response, for example to drugs targeted at the most frequently mutated oncogene in this tumor subtype, PI3KCA. Discussion: These results illustrate the potential importance of metabolism-based stratification of breast cancer and demonstrate that metabolic imaging can provide diagnostic information that could be important for non-invasive diagnosis and for designing and monitoring therapeutic strategies. Citation Format: Susana Ros, Alan J. Wright, Flaviu Bulat, Wendy Greenwood, De-en Hu, Maurizio Callari, Ming Li Chia, Violeta Serra, Oscar Rueda, Alejandra Bruna, Carlos Caldas, Kevin M. Brindle. Metabolic heterogeneity in breast cancer integrative clusters to screen metabolic vulnerabilities for diagnosis and treatment response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2817.

Glycosylation is a ubiquitous post‐translational modification, present in over 50 % of the proteins in the human genome,1 with important roles in cell–cell communication and migration. Interest in glycome profiling has increased with the realization that glycans can be used as biomarkers of many diseases,2 including cancer.3 We report here the first tomographic imaging of glycosylated tissues in live mice by using metabolic labeling and a gadolinium‐based bioorthogonal MRI probe. Significant N‐azidoacetylgalactosamine dependent T 1 contrast was observed in vivo two hours after probe administration. Tumor, kidney, and liver showed significant contrast, and several other tissues, including the pancreas, spleen, heart, and intestines, showed a very high contrast (>10‐fold). This approach has the potential to enable the rapid and non‐invasive magnetic resonance imaging of glycosylated tissues in vivo in preclinical models of disease.