The systematic translation of cancer genomic data into knowledge of tumor biology and therapeutic avenues remains challenging. Such efforts should be greatly aided by robust preclinical model systems that reflect the genomic diversity of human cancers and for which detailed genetic and pharmacologic annotation is available1. Here we describe the Cancer Cell Line Encyclopedia (CCLE): a compilation of gene expression, chromosomal copy number, and massively parallel sequencing data from 947 human cancer cell lines. When coupled with pharmacologic profiles for 24 anticancer drugs across 479 of the lines, this collection allowed identification of genetic, lineage, and gene expression-based predictors of drug sensitivity. In addition to known predictors, we found that plasma cell lineage correlated with sensitivity to IGF1 receptor inhibitors; AHR expression was associated with MEK inhibitor efficacy in NRAS-mutant lines; and SLFN11 expression predicted sensitivity to topoisomerase inhibitors. Altogether, our results suggest that large, annotated cell line collections may help to enable preclinical stratification schemata for anticancer agents. 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 regimens2.

Large panels of comprehensively characterized human cancer models, including the Cancer Cell Line Encyclopedia (CCLE), have provided a rigorous backbone upon which to study genetic variants, candidate targets, small molecule and biological therapeutics and to identify new marker-driven cancer dependencies. To improve our understanding of the molecular features that contribute to cancer phenotypes including drug responses, here we have expanded the characterizations of cancer cell lines to include genetic, RNA splicing, DNA methylation, histone H3 modification, microRNA expression and reverse-phase protein array data for 1,072 cell lines from various lineages and ethnicities. Integrating these data with functional characterizations such as drug-sensitivity data, short hairpin RNA knockdown and CRISPR–Cas9 knockout data reveals potential targets for cancer drugs and associated biomarkers. Together, this dataset and an accompanying public data portal provide a resource to accelerate cancer research using model cancer cell lines.

Oncogenic mutations in the serine/threonine kinase B-RAF are found in 50–70% of malignant melanomas1. Pre-clinical studies have demonstrated that the B-RAFV600E mutation predicts a dependency on the mitogen activated protein kinase (MAPK) signaling cascade in melanoma1–5—an observation that has been validated by the success of RAF and MEK inhibitors in clinical trials6–8. However, clinical responses to targeted anticancer therapeutics are frequently confounded by de novo or acquired resistance9–11. Identification of resistance mechanisms in a manner that elucidates alternative ‘druggable’ targets may inform effective long-term treatment strategies12. Here, we expressed ~600 kinase and kinase-related open reading frames (ORFs) in parallel to functionally interrogate resistance to a selective RAF kinase inhibitor. We identified MAP3K8 (COT/TPL2) as a MAPK pathway agonist that drives resistance to RAF inhibition in B-RAFV600E cell lines. COT activates ERK primarily through MEK-dependent mechanisms that do not require RAF signaling. Moreover, COT expression is associated with de novo resistance in B-RAFV600E cultured cell lines and acquired resistance in melanoma cells and tissue obtained from relapsing patients following treatment with MEK or RAF inhibition. We further identify combinatorial MAPK pathway inhibition or targeting of COT kinase activity as possible therapeutic strategies for reducing MAPK pathway activation in this setting. Together, these results provide new insights into resistance mechanisms involving the MAPK pathway and articulate an integrative approach through which high-throughput functional screens may inform the development of novel therapeutic strategies.

Focal amplifi cation and activating point mutation of the MET gene are well-characterized oncogenic drivers that confer susceptibility to targeted MET inhibitors. Recurrent somatic splice site alterations at MET exon 14 ( MET ex14) that result in exon skipping and MET activation have been characterized, but their full diversity and prevalence across tumor types are unknown. Here, we report analysis of tumor genomic profi les from 38,028 patients to identify 221 cases with MET ex14 mutations (0.6%), including 126 distinct sequence variants. MET ex14 mutations are detected most frequently in lung adenocarcinoma (3%), but also frequently in other lung neoplasms (2.3%), brain glioma (0.4%), and tumors of unknown primary origin (0.4%). Further in vitro studies demonstrate sensitivity to MET inhibitors in cells harboring MET ex14 alterations. We also report three new patient cases with MET ex14 alterations in lung or histiocytic sarcoma tumors that showed durable response to two different MET-targeted therapies. The diversity of MET ex14 mutations indicates that diagnostic testing via comprehensive genomic profi ling is necessary for detection in a clinical setting. SIGNIFICANCE:Here we report the identifi cation of diverse exon 14 splice site alterations in MET that result in constitutive activity of this receptor and oncogenic transformation in vitro . Patients whose tumors harbored these alterations derived meaningful clinical benefi t from MET inhibitors. Collectively, these data support the role of MET ex14 alterations as drivers of tumorigenesis, and identify a unique subset of patients likely to derive benefi t from MET inhibitors. Cancer Discov; 5(8);

SummaryThe appearance of phosphatidylserine (PS) on the cell surface during apoptosis in thymocytes and cytotoxic T lymphocyte cell lines provokes PS-dependent recognition by activated macrophages. Flow cytometric analysis of transbilayer lipid movements in T lymphocytes undergoing apoptosis reveals that downregulation of the adenosine triphosphate-dependent aminophospholipid translocase and activation of a nonspecific lipid scramblase are responsible for PS reaching the surface from its intracellular location. Both mechanisms are expressed at the same time, and precede DNA degradation, zeiosis, and cell lysis in the apoptotic pathway.