Normal cells, but not cancer cells, survive severe Plk1 depletion

Therapeutic opportunities to control tumor cell cycles

Tumor cell proliferation is frequently associated to genetic or epigenetic alterations in key cell cycle regulators. Most human tumors deregulate this pathway to sustain proliferation with independence of external mitogenic factors. In addition, the alteration of cell cycle proteins may confer genomic instability that results in additional mutations in these tumor cells. The frequent alteration of the cell cycle in tumor cells has launched the identification for critical cell cycle regulators as anticancer targets. The inhibition of some cell cycle kinases such as cyclin-dependent kinases (CDKs) or the Aurora and Polo mitotic kinases is currently under study in several preclinical and clinical trials. Similarly, the clinical success of microtubule poisons such as taxol has promoted new applied research in mitosis regulation. Recent investigations have suggested new targets of interest including additional kinases, phosphatases and other mitotic regulators such as microtubule motor proteins (kinesins). Current research in this area will undoubtedly result in new and improved targeted therapies for cancer treatment.

High-throughput RNAi screening by time-lapse imaging of live human cells

RNA interference (RNAi) is a powerful tool to study gene function in cultured cells. Transfected cell microarrays in principle allow high-throughput phenotypic analysis after gene knockdown by microscopy. But bottlenecks in imaging and data analysis have limited such high-content screens to endpoint assays in fixed cells and determination of global parameters such as viability. Here we have overcome these limitations and developed an automated platform for high-content RNAi screening by time-lapse fluorescence microscopy of live HeLa cells expressing histone-GFP to report on chromosome segregation and structure. We automated all steps, including printing transfection-ready small interfering RNA (siRNA) microarrays, fluorescence imaging and computational phenotyping of digital images, in a high-throughput workflow. We validated this method in a pilot screen assaying cell division and delivered a sensitive, time-resolved phenoprint for each of the 49 endogenous genes we suppressed. This modular platform is scalable and makes the power of time-lapse microscopy available for genome-wide RNAi screens.