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Pantel, Sarah

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Pantel

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Pantel, Sarah

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    Parallel genome-scale loss of function screens in 216 cancer cell lines for the identification of context-specific genetic dependencies
    (Nature Publishing Group, 2014) Cowley, Glenn S; Weir, Barbara Ann; Vazquez, Francisca; Tamayo, Pablo; Scott, Justine A; Rusin, Scott; East-Seletsky, Alexandra; Ali, Levi D; Gerath, William FJ; Pantel, Sarah; Lizotte, Patrick H; Jiang, Guozhi; Hsiao, Jessica; Tsherniak, Aviad; Dwinell, Elizabeth; Aoyama, Simon; Okamoto, Michael; Harrington, William; Gelfand, Ellen; Green, Thomas M; Tomko, Mark J; Gopal, Shuba; Wong, Terence C; Li, Hubo; Howell, Sara; Stransky, Nicolas; Liefeld, Ted; Jang, Dongkeun; Bistline, Jonathan; Hill Meyers, Barbara; Armstrong, Scott A; Anderson, Ken C; Stegmaier, Kimberly; Reich, Michael; Pellman, David; Boehm, Jesse S; Mesirov, Jill P; Golub, Todd; Root, David E; Hahn, William
    Using a genome-scale, lentivirally delivered shRNA library, we performed massively parallel pooled shRNA screens in 216 cancer cell lines to identify genes that are required for cell proliferation and/or viability. Cell line dependencies on 11,000 genes were interrogated by 5 shRNAs per gene. The proliferation effect of each shRNA in each cell line was assessed by transducing a population of 11M cells with one shRNA-virus per cell and determining the relative enrichment or depletion of each of the 54,000 shRNAs after 16 population doublings using Next Generation Sequencing. All the cell lines were screened using standardized conditions to best assess differential genetic dependencies across cell lines. When combined with genomic characterization of these cell lines, this dataset facilitates the linkage of genetic dependencies with specific cellular contexts (e.g., gene mutations or cell lineage). To enable such comparisons, we developed and provided a bioinformatics tool to identify linear and nonlinear correlations between these features.