SummaryOne 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.

Purpose The Cancer Esophagus Gefitinib trial demonstrated improved progression-free survival with the epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor gefitinib relative to placebo in patients with advanced esophageal cancer who had disease progression after chemotherapy. Rapid and durable responses were observed in a minority of patients. We hypothesized that genetic aberration of the EGFR pathway would identify patients benefitting from gefitinib. Methods A prespecified, blinded molecular analysis of Cancer Esophagus Gefitinib trial tumors was conducted to compare efficacy of gefitinib with that of placebo according to EGFR copy number gain (CNG) and EGFR, KRAS, BRAF, and PIK3CA mutation status. EGFR CNG was determined by fluorescent in situ hybridization (FISH) using prespecified criteria and EGFR FISH-positive status was defined as high polysomy or amplification. Results Biomarker data were available for 340 patients. In EGFR FISH-positive tumors (20.2%), overall survival was improved with gefitinib compared with placebo (hazard ratio [HR] for death, 0.59; 95% CI, 0.35 to 1.00; P = .05). In EGFR FISH-negative tumors, there was no difference in overall survival with gefitinib compared with placebo (HR for death, 0.90; 95% CI, 0.69 to 1.18; P = .46). Patients with EGFR amplification (7.2%) gained greatest benefit from gefitinib (HR for death, 0.21; 95% CI, 0.07 to 0.64; P = .006). There was no difference in overall survival for gefitinib versus placebo for patients with EGFR, KRAS, BRAF, and PIK3CA mutations, or for any mutation versus none. Conclusion EGFR CNG assessed by FISH appears to identify a subgroup of patients with esophageal cancer who may benefit from gefitinib as a second-line treatment. Results of this study suggest that anti-EGFR therapies should be investigated in prospective clinical trials in different settings in EGFR FISH-positive and, in particular, EGFR-amplified esophageal cancer.