The largest gene knock-down experiments performed to date have used multiple short interfering/short hairpin (si/sh)RNAs per gene. To overcome this burden for design of a genome-wide siRNA library, we used the Stuttgart Neural Net Simulator to train algorithms on a data set of 2,182 randomly selected siRNAs targeted to 34 mRNA species, assayed through a high-throughput fluorescent reporter gene system. The algorithm, (BIOPREDsi), reliably predicted activity of 249 siRNAs of an independent test set (Pearson coefficient r = 0.66) and siRNAs targeting endogenous genes at mRNA and protein levels. Neural networks trained on a complementary 21-nucleotide (nt) guide sequence were superior to those trained on a 19-nt sequence. BIOPREDsi was used in the design of a genome-wide siRNA collection with two potent siRNAs per gene. When this collection of 50,000 siRNAs was used to identify genes involved in the cellular response to hypoxia, two of the most potent hits were the key hypoxia transcription factors HIF1A and ARNT.
Cellular levels of key regulatory proteins are controlled via ubiquitination and subsequent degradation. Deubiquitinating enzymes or isopeptidases can potentially prevent targeted destruction of protein substrates through deubiquitination prior to proteasomal degradation. However, only one deubiquitinating enzyme to date has been matched to a specific substrate in mammalian cells and shown to functionally modify it. Here we show that the isopeptidase USP2a (ubiquitin-specific protease-2a) interacts with and stabilizes fatty acid synthase (FAS), which is often overexpressed in biologically aggressive human tumors. Further, USP2a is androgen-regulated and overexpressed in prostate cancer, and its functional inactivation results in decreased FAS protein and enhanced apoptosis. Thus, the isopeptidase USP2a plays a critical role in prostate cancer cell survival through FAS stabilization and represents a therapeutic target in prostate cancer.
Human cells have evolved complex signaling networks to coordinate the cell cycle. A detailed understanding of the global regulation of this fundamental process requires comprehensive identification of the genes and pathways involved in the various stages of cell-cycle progression. To this end, we report a genome-wide analysis of the human cell cycle, cell size, and proliferation by targeting >95% of the protein-coding genes in the human genome using small interfering RNAs (siRNAs). Analysis of >2 million images, acquired by quantitative fluorescence microscopy, showed that depletion of 1,152 genes strongly affected cell-cycle progression. These genes clustered into eight distinct phenotypic categories based on phase of arrest, nuclear area, and nuclear morphology. Phase-specific networks were built by interrogating knowledge-based and physical interaction databases with identified genes. Genome-wide analysis of cell-cycle regulators revealed a number of kinase, phosphatase, and proteolytic proteins and also suggests that processes thought to regulate G 1-S phase progression like receptor-mediated signaling, nutrient status, and translation also play important roles in the regulation of G 2͞M phase transition. Moreover, 15 genes that are integral to TNF͞NF-B signaling were found to regulate G 2͞M, a previously unanticipated role for this pathway. These analyses provide systems-level insight into both known and novel genes as well as pathways that regulate cell-cycle progression, a number of which may provide new therapeutic approaches for the treatment of cancer.high-content screening ͉ network analysis ͉ small interfering RNA ͉ human genome
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