Michael D. Jones

TL;DR: The results indicate that large, annotated cell-line collections may help to enable preclinical stratification schemata for anticancer agents and the generation of genetic predictions of drug response in the preclinical setting and their incorporation into cancer clinical trial design could speed the emergence of ‘personalized’ therapeutic regimens.

TL;DR: The original Cancer Cell Line Encyclopedia is expanded with deeper characterization of over 1,000 cell lines, including genomic, transcriptomic, and proteomic data, and integration with drug-sensitivity and gene-dependency data, which reveals potential targets for cancer drugs and associated biomarkers.

TL;DR: A large-scale RNAi screen is conducted 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, outlining the classes of cancer dependency genes and their relationships to genetic, expression, and lineage features.

TL;DR: Jordi Barretina, Giordano Caponigro, Nicolas Stransky, Kavitha Venkatesan, Adam A. Golub, Michael P. Morais, Jodi Meltzer, Judit Jané-Valbuena, Felipa A. Mapa, Joseph Thibault, Eva Bric-Furlong, Pichai Raman, Aaron Shipway, Ingo H. Engels, Jill Cheng, Guoying K. Yu

TL;DR: It is shown that CRISPR-based screens have a significantly lower false-negative rate compared with RNAi- based screens, but have specific liabilities particularly in the interrogation of regions of genome amplification, therefore, this study provides critical insights for applying CRISpr-based screening toward the systematic identification of new cancer targets.