Cell-cycle checkpoints are signal-transduction pathways required to maintain genomic stability in dividing cells. Previously, it was reported that two kinases essential for checkpoint signalling, Chk1 and Chk2 are structurally conserved. In contrast to yeast, Xenopus and mammals, the Chk1-and Chk2-dependent pathways in Drosophila are not understood in detail. Here, we report the function of these checkpoint kinases, referred to as Grp/DChk1 and Dmnk/DChk2 in Drosophila Schneider's cells, and identify an upstream regulator as well as downstream targets of Grp/DChk1. First, we demonstrate that S2 cells are a suitable

Purpose: To develop a transgenic mouse model of glioma that can be conveniently used for testing therapy intervention strategies. High-grade glioma is a devastating and uniformly fatal disease for which better therapy is urgently needed. Typical for high-grade glioma is that glioma cells infiltrate extensively into surrounding pivotal brain structures, thereby rendering current treatments largely ineffective. Evaluation of novel therapies requires the availability of appropriate glioma mouse models.Experimental Design: High-grade gliomas were induced by stereotactic intracranial injection of lentiviral GFAP-Cre or CMV-Cre vectors into compound LoxP-conditional mice, resulting in K-Ras v12 expression and loss of p16Ink4a /p19 Arf with or without concomitant loss of p53 or Pten.Results: Tumors reproduced many of the features that are characteristic for human high-grade gliomas, including invasiveness and blood-brain barrier functionality. Especially, CMV-Cre injection into p53; Ink4a/Arf;K-Ras v12 mice resulted in high-grade glioma with a short tumor latency (2-3 weeks) and full penetrance. Early detection and follow-up was accomplished by noninvasive bioluminescence imaging, and the practical utility for therapy intervention was shown in a study with temozolomide. Conclusion:We have developed a realistic high-grade glioma model that can be used with almost the same convenience as traditional xenograft models, thus allowing its implementation at the forefront of preclinical evaluation of new treatments. Clin Cancer Res; 16(13); 3431-41. ©2010 AACR.