A negative genetic interaction map in isogenic cancer cell lines reveals cancer cell vulnerabilities. Issue 1 (8th October 2013) - Vizeacoumar, Franco J; Arnold, Roland; Vizeacoumar, Frederick S; Chandrashekhar, Megha; Buzina, Alla; Young, Jordan T F; Kwan, Julian H M; Sayad, Azin; Mero, Patricia; Lawo, Steffen; Tanaka, Hiromasa; Brown, Kevin R; et al.
Abstract : Improved efforts are necessary to define the functional product of cancer mutations currently being revealed through large‐scale sequencing efforts. Using genome‐scale pooled shRNA screening technology, we mapped negative genetic interactions across a set of isogenic cancer cell lines and confirmed hundreds of these interactions in orthogonal co‐culture competition assays to generate a high‐confidence genetic interaction network of differentially essential or differential essentiality (DiE) genes. The network uncovered examples of conserved genetic interactions, densely connected functional modules derived from comparative genomics with model systems data, functions for uncharacterized genes in the human genome and targetable vulnerabilities. Finally, we demonstrate a general applicability of DiE gene signatures in determining genetic dependencies of other non‐isogenic cancer cell lines. For example, the PTEN −/− DiE genes reveal a signature that can preferentially classify PTEN ‐dependent genotypes across a series of non‐isogenic cell lines derived from the breast, pancreas and ovarian cancers. Our reference network suggests that many cancer vulnerabilities remain to be discovered through systematic derivation of a network of differentially essential genes in an isogenic cancer cell model. Abstract : This study defines a network of synthetic sick/lethal interactions with a set of query genes in a series of isogenic cancer cell lines. Analysis of differential essentiality reveals general properties in genetic interaction networks derived from studies on model organisms. Synopsis: This study defines a network of synthetic sick/lethal interactions with a set of query genes in a series of isogenic cancer cell lines. Analysis of differential essentiality reveals general properties in genetic interaction networks derived from studies on model organisms. This study defined about 200 negative genetic interactions in the isogenic cancer cell line background. Mapping of negative genetic interactions in a systematic fashion in isogenic cancer cell lines has revealed novel functions for several uncharacterized genes. This study demonstrates that differential essentiality profiles derived from isogenic cancer cell lines can be used to classify genetic dependencies in non‐isogenic cancer cell lines.