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Merck
  • Integrated analysis identifies different metabolic signatures for tumor-initiating cells in a murine glioblastoma model.

Integrated analysis identifies different metabolic signatures for tumor-initiating cells in a murine glioblastoma model.

Neuro-oncology (2014-05-27)
Isako Saga, Shunsuke Shibao, Jun Okubo, Satoru Osuka, Yusuke Kobayashi, Sachiko Yamada, Satoshi Fujita, Kenichi Urakami, Masatoshi Kusuhara, Kazunari Yoshida, Hideyuki Saya, Oltea Sampetrean
要旨

The metabolic preference of malignant glioma for glycolysis as an energy source is a potential therapeutic target. As a result of the cellular heterogeneity of these tumors, however, the relation between glycolytic preference, tumor formation, and tumor cell clonogenicity has remained unknown. To address this issue, we analyzed the metabolic profiles of isogenic glioma-initiating cells (GICs) in a mouse model. GICs were established by overexpression of H-Ras(V12) in Ink4a/Arf-null neural stem cells. Subpopulations of these cells were obtained by single-cell cloning, and clones differing in extracellular acidification potential were assessed for metabolic characteristics. Tumors formed after intracranial implantation of these clones in mice were examined for pathological features of glioma and expression of glycolytic enzymes. Malignant transformation of neural stem cells resulted in a shift in metabolism characterized by an increase in lactic acid production. However, isogenic clonal populations of GICs manifested pronounced differences in glucose and oxygen consumption, lactate production, and nucleoside levels. These differences were paralleled by differential expression of glycolytic enzymes such as hexokinase 2 and pyruvate kinase M2, with this differential expression also being evident in tumors formed by these clones in vivo. The metabolic characteristics of glioma cells appear early during malignant transformation and persist until the late stages of tumor formation. Even isogenic clones may be heterogeneous in terms of metabolic features, however, suggesting that a more detailed understanding of the metabolic profile of glioma is imperative for effective therapeutic targeting.

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