Nedd8-activating enzyme inhibitor MLN4924 provides synergy with mitomycin C through interactions with ATR, BRCA1/BRCA2, and chromatin dynamics pathways.

MLN4924 is an investigational small-molecule inhibitor of the Nedd8-activating enzyme currently in phase I clinical trials. MLN4924 induces DNA damage via rereplication in most cell lines. This distinct mechanism of DNA damage may affect its ability to combine with standard-of-care agents and may affect the clinical development of MLN4924. As such, we studied its interaction with other DNA-damaging agents. Mitomycin C, cisplatin, cytarabine, UV radiation, SN-38, and gemcitabine demonstrated synergy in combination with MLN4924 in vitro. The combination of mitomycin C and MLN4924 was shown to be synergistic in a mouse xenograft model. Importantly, depletion of genes within the ataxia telangiectasia and Rad3 related (ATR) and BRCA1/BRCA2 pathways, chromatin modification, and transcription-coupled repair reduced the synergy between mitomycin C and MLN4924. In addition, comet assay demonstrated increased DNA strand breaks with the combination of MLN4924 and mitomycin C. Our data suggest that mitomycin C causes stalled replication forks, which when combined with rereplication induced by MLN4924 results in frequent replication fork collisions, leading to cell death. This study provides a straightforward approach to understand the mechanism of synergy, which may provide useful information for the clinical development of these combinations.

Growth rate analysis and efficient experimental design for tumor xenograft studies.

Human tumor xenograft studies are the primary means to evaluate the biological activity of anticancer agents in late-stage preclinical drug discovery. The variability in the growth rate of human tumors established in mice and the small sample sizes make rigorous statistical analysis critical. The most commonly used summary of antitumor activity for these studies is the T/C ratio. However, alternative methods based on growth rate modeling can be used. Here, we describe a summary metric called the rate-based T/C, derived by fitting each animal's tumor growth to a simple exponential model. The rate-based T/C uses all of the data, in contrast with the traditional T/C, which only uses a single measurement. We compare the rate-based T/C with the traditional T/C and assess their performance through a bootstrap analysis of 219 tumor xenograft studies. We find that the rate-based T/C requires fewer animals to achieve the same power as the traditional T/C. We also compare 14-day studies with 21-day studies and find that 14-day studies are more cost efficient. Finally, we perform a power analysis to determine an appropriate sample size.