The interpretation of RNAi knockdown experiments can be challenging due to the extensive off-target effects exhibited by siRNAs and shRNAs. This has led to the reporting of results that cannot be independently verified, or to the identification of putative cancer targets that are insufficiently robust to support industrial drug discovery efforts. The problems associated with off target effects are particularly acute in high throughput RNAi screens, whose results often differ wildly between laboratories using different experimental platforms. As a result, the validity of published large-scale RNAi screens has recently been called into question. Here we report results from large scale RNAi screens to identify genes essential for the proliferation or survival of cancer cells. To overcome the inherent liabilities of RNAi screens, we have increased the experimental power by using typically 8, and up to 20 RNAi triggers per gene, and have developed novel statistical algorithms that exploit this increased power. Importantly, this approach allows the calculation of a false discovery rate (FDR) that accurately predicts the ability of results to be confirmed by independent labs using independent reagents, solving a key issue of such screens. Using a stringent FDR cutoff of 5%, known essential genes and driver oncogenes such as KRAS, ERBB2 and BRAF are readily identified, demonstrating the robustness and power of the method. We have also identified a number of novel cancer targets. We present the identification and genetic and pharmacological validation of one of these targets, a kinase present as a fusion partner in multiple fusion oncogenes in primary tumors. Our data demonstrate that large-scale RNAi screens can be a robust and independently verifiable tool to uncover previously unknown cancer vulnerabilities which have yet to be characterized despite extensive genomic sequencing efforts. Citation Format: Astrid A. Ruefli-Brasse, Cynthia Hart, Liza Fajardo, Elissa Swearingen, Linda Wong, Doreen Sakamoto, Kari Hale, Huanying Ge, Jeffery McDowell, Bharath Ramachandran, Elissa Cosgrove, J.E.Vivienne Watson, Seamus Ragan, Seamus Ragan, Paul Kassner, Paul Kassner, Kim Quon. Stringent analysis of large-scale siRNA screens identifies a kinase fusion oncogene. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 2992. doi:10.1158/1538-7445.AM2013-2992

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