Metabolic Imaging Detects Low Levels of Glycolytic Activity That Vary with Levels of c-Myc Expression in Patient-Derived Xenograft Models of Glioblastoma.
Richard MairAlan J WrightSusana RosDe-En HuTom BoothFelix KreisJyotsna RaoColin WattsKevin M BrindlePublished in: Cancer research (2018)
13C MRI of hyperpolarized [1-13C]pyruvate metabolism has been used in oncology to detect disease, investigate disease progression, and monitor response to treatment with a view to guiding treatment in individual patients. This technique has translated to the clinic with initial studies in prostate cancer. Here, we use the technique to investigate its potential uses in patients with glioblastoma (GB). We assessed the metabolism of hyperpolarized [1-13C]pyruvate in an orthotopically implanted cell line model (U87) of GB and in patient-derived tumors, where these were produced by orthotopic implantation of cells derived from different patients. Lactate labeling was higher in the U87 tumor when compared with patient-derived tumors, which displayed intertumoral heterogeneity, reflecting the intra- and intertumoral heterogeneity in the patients' tumors from which they were derived. Labeling in some patient-derived tumors could be observed before their appearance in morphologic images, whereas in other tumors it was not significantly greater than the surrounding brain. Increased lactate labeling in tumors correlated with c-Myc-driven expression of hexokinase 2, lactate dehydrogenase A, and the monocarboxylate transporters and was accompanied by increased radioresistance. Because c-Myc expression correlates with glioma grade, this study demonstrates that imaging with hyperpolarized [1-13C]pyruvate could be used clinically with patients with GB to determine disease prognosis, to detect early responses to drugs that modulate c-Myc expression, and to select tumors, and regions of tumors for increased radiotherapy dose.Significance: Metabolic imaging with hyperpolarized [1-13C]pyruvate detects low levels of c-Myc-driven glycolysis in patient-derived glioblastoma models, which, when translated to the clinic, could be used to detect occult disease, determine disease prognosis, and target radiotherapy. Cancer Res; 78(18); 5408-18. ©2018 AACR.
Keyphrases
- end stage renal disease
- prostate cancer
- poor prognosis
- chronic kidney disease
- ejection fraction
- newly diagnosed
- primary care
- high resolution
- peritoneal dialysis
- prognostic factors
- early stage
- magnetic resonance
- induced apoptosis
- binding protein
- cell death
- convolutional neural network
- lymph node metastasis
- signaling pathway
- combination therapy
- endoplasmic reticulum stress
- radiation induced
- dna damage
- replacement therapy
- papillary thyroid
- drug induced
- locally advanced