Oncogene-induced reactive oxygen species (ROS) have been proposed to be signaling molecules that mediate proliferative cues. However, ROS may also cause DNA damage and proliferative arrest. How these apparently opposite roles can be reconciled, especially in the context of oncogene-induced cellular senescence, which is associated both with aberrant mitogenic signaling and DNA damage response (DDR)-mediated arrest, is unclear. Here, we show that ROS are indeed mitogenic signaling molecules that fuel oncogene-driven aberrant cell proliferation. However, by their very same ability to mediate cell hyperproliferation, ROS eventually cause DDR activation. We also show that oncogenic Ras-induced ROS are produced in a Rac1 and NADPH oxidase (Nox4)-dependent manner. In addition, we show that Ras-induced ROS can be detected and modulated in a living transparent animal: the zebrafish. Finally, in cancer we show that Nox4 is increased in both human tumors and a mouse model of pancreatic cancer and specific Nox4 small-molecule inhibitors act synergistically with existing chemotherapic agents.

Current methods for detection of copy number variants (CNV) and aberrations (CNA) from targeted sequencing data are based on the depth of coverage of captured exons. Accurate CNA determination is complicated by uneven genomic distribution and non-uniform capture efficiency of targeted exons. Here we present CopywriteR, which eludes these problems by exploiting ‘off-target’ sequence reads. CopywriteR allows for extracting uniformly distributed copy number information, can be used without reference, and can be applied to sequencing data obtained from various techniques including chromatin immunoprecipitation and target enrichment on small gene panels. CopywriteR outperforms existing methods and constitutes a widely applicable alternative to available tools.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0617-1) contains supplementary material, which is available to authorized users.

The multilevel model yields a significant reduction of extreme IC50 estimates, an increase in precision and it runs orders of magnitude faster.