RESUMEN
One approach to identifying cancer-specific vulnerabilities and therapeutic targets is to profile genetic dependencies in cancer cell lines. Here, we describe data from a series of siRNA screens that identify the kinase genetic dependencies in 117 cancer cell lines from ten cancer types. By integrating the siRNA screen data with molecular profiling data, including exome sequencing data, we show how vulnerabilities/genetic dependencies that are associated with mutations in specific cancer driver genes can be identified. By integrating additional data sets into this analysis, including protein-protein interaction data, we also demonstrate that the genetic dependencies associated with many cancer driver genes form dense connections on functional interaction networks. We demonstrate the utility of this resource by using it to predict the drug sensitivity of genetically or histologically defined subsets of tumor cell lines, including an increased sensitivity of osteosarcoma cell lines to FGFR inhibitors and SMAD4 mutant tumor cells to mitotic inhibitors.
Asunto(s)
Neoplasias/enzimología , Neoplasias/genética , Proteínas Quinasas/metabolismo , Línea Celular Tumoral , Perfilación de la Expresión Génica , Humanos , Mutación , Neoplasias/patología , Proteínas Quinasas/química , Proteínas Quinasas/genética , Interferencia de ARN , ARN Interferente Pequeño/metabolismo , Receptor ErbB-2/antagonistas & inhibidores , Receptor ErbB-2/genética , Receptor ErbB-2/metabolismo , Receptor Tipo 1 de Factor de Crecimiento de Fibroblastos/antagonistas & inhibidores , Receptor Tipo 1 de Factor de Crecimiento de Fibroblastos/genética , Receptor Tipo 1 de Factor de Crecimiento de Fibroblastos/metabolismo , Proteína Smad4/antagonistas & inhibidores , Proteína Smad4/genética , Proteína Smad4/metabolismoRESUMEN
canSAR is a fully integrated cancer research and drug discovery resource developed to utilize the growing publicly available biological annotation, chemical screening, RNA interference screening, expression, amplification and 3D structural data. Scientists can, in a single place, rapidly identify biological annotation of a target, its structural characterization, expression levels and protein interaction data, as well as suitable cell lines for experiments, potential tool compounds and similarity to known drug targets. canSAR has, from the outset, been completely use-case driven which has dramatically influenced the design of the back-end and the functionality provided through the interfaces. The Web interface at http://cansar.icr.ac.uk provides flexible, multipoint entry into canSAR. This allows easy access to the multidisciplinary data within, including target and compound synopses, bioactivity views and expert tools for chemogenomic, expression and protein interaction network data.