Elucidation of the mutational landscape of human cancer has progressed rapidly and been accompanied by the development of therapeutics targeting mutant oncogenes. However, a comprehensive mapping of cancer dependencies has lagged behind and the discovery of therapeutic targets for counteracting tumor suppressor gene loss is needed. To identify vulnerabilities relevant to specific cancer subtypes, we conducted a large-scale RNAi screen in which viability effects of mRNA knockdown were assessed for 7,837 genes using an average of 20 shRNAs per gene in 398 cancer cell lines. We describe findings of this screen, outlining the classes of cancer dependency genes and their relationships to genetic, expression, and lineage features. In addition, we describe robust gene-interaction networks recapitulating both protein complexes and functional cooperation among complexes and pathways. This dataset along with a web portal is provided to the community to assist in the discovery and translation of new therapeutic approaches for cancer.

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.

No abstract

Despite progress in mechanistic understanding of the RNA interference (RNAi) pathways, the subcellular sites of RNA silencing remain under debate. Here we show that loading of lipid-transfected siRNAs and endogenous microRNAs (miRNA) into RISC (RNA-induced silencing complexes), encounter of the target mRNA, and Ago2-mediated mRNA slicing in mammalian cells are nucleated at the rough endoplasmic reticulum (rER). Although the major RNAi pathway proteins are found in most subcellular compartments, the miRNA- and siRNA-loaded Ago2 populations co-sediment almost exclusively with the rER membranes, together with the RISC loading complex (RLC) factors Dicer, TAR RNA binding protein (TRBP) and protein activator of the interferon-induced protein kinase (PACT). Fractionation and membrane co-immune precipitations further confirm that siRNA-loaded Ago2 physically associates with the cytosolic side of the rER membrane. Additionally, RLC-associated double-stranded siRNA, diagnostic of RISC loading, and RISC-mediated mRNA cleavage products exclusively co-sediment with rER. Finally, we identify TRBP and PACT as key factors anchoring RISC to ER membranes in an RNA-independent manner. Together, our findings demonstrate that the outer rER membrane is a central nucleation site of siRNA-mediated RNA silencing.

One of the most challenging aspects of lung cancer therapy is the rapid acquisition of multidrug-resistant (MDR) phenotype. One effective approach would be to identify and downregulate resistance-causing genes in tumors using small interfering RNAs (siRNAs) to increase the sensitivity of tumor cells to chemotherapeutic challenge. After identifying the overexpressed resistance-related antiapoptotic genes (survivin and bcl-2) in cisplatin-resistant cells, the siRNA sequences were designed and screened to select the most efficacious candidates. Modifications were introduced in them to minimize off-target effects. Subsequently, the combination of siRNA and cisplatin that gave the maximum synergy was identified in resistant cells. We then demonstrated that the combination treatment of the selected siRNAs and cisplatin encapsulated in CD44-targeting hyaluronic acid (HA)-based self-assembling nanosystems reversed the resistance to cisplatin and delayed the tumor growth significantly (growth inhibition increased from 30 to 60%) in cisplatin-resistant tumors. In addition, no abnormalities in body weights, liver enzyme levels or histopathology of liver/spleen tissues were observed in any of the treatment groups during the study period. Overall, we demonstrate that the combination of siRNA-mediated gene-silencing strategy with chemotherapeutic agents constitutes a valuable and safe approach for the treatment of MDR tumors.