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.
An insertional mutagenesis system that uses transposons carrying unique DNA sequence tags was developed for the isolation of bacterial virulence genes. The tags from a mixed population of bacterial mutants representing the inoculum and bacteria recovered from infected hosts were detected by amplification, radiolabeling, and hybridization analysis. When applied to a murine model of typhoid fever caused by Salmonella typhimurium, mutants with attenuated virulence were revealed by use of tags that were present in the inoculum but not in bacteria recovered from infected mice. This approach resulted in the identification of new virulence genes, some of which are related to, but functionally distinct from, the inv/spa family of S. typhimurium.
Elucidation of the mutational landscape of human cancer has progressed rapidly and been accompanied by the development of therapeutics targeting mutant oncogenes. However, a comprehensive mapping of cancer dependencies has lagged behind and the discovery of therapeutic targets for counteracting tumor suppressor gene loss is needed. To identify vulnerabilities relevant to specific cancer subtypes, we conducted a large-scale RNAi screen 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. We describe findings of this screen, outlining the classes of cancer dependency genes and their relationships to genetic, expression, and lineage features. In addition, we describe robust gene-interaction networks recapitulating both protein complexes and functional cooperation among complexes and pathways. This dataset along with a web portal is provided to the community to assist in the discovery and translation of new therapeutic approaches for cancer.
The complete DNA sequence was determined for strain U1102 of human herpesvirus-6, a CD4+ T-lymphotropic virus with disease associations in immunodeficient settings and a possible complicating factor in AIDS. The genome is 159,321 bp in size, has a base composition of 43% G + C, and contains 119 open reading frames. The overall structure is 143 kb bounded by 8 kb of direct repeats, DRL (left) and DRR (right), containing 0.35 kb of terminal and junctional arrays of human telomere-like simple repeats. Since eight open reading frames are duplicated in the repeats, six span repetitive elements and three are spliced, the genome is considered to contain 102 separate genes likely to encode protein. The genes are arranged colinearly with those in the genome of the previously sequenced betaherpesvirus, human cytomegalovirus, and has a distinct arrangement of conserved genes relative to the sequenced gammaherpesviruses, herpesvirus saimiri and Epstein-Barr virus, and the alphaherpesviruses, equine herpesvirus-1, varicella-zoster virus, and herpes simplex virus. Comparisons of predicted amino acid sequences allowed the functions of many human herpesvirus-6 encoded proteins to be assigned and showed the closest relationship in overall number and similarity to human cytomegalovirus products, with approximately 67% homologous proteins as compared to the 21% identified in all herpesviruses. The features of the conserved genes and their relative order suggested a general scheme for divergence among these herpesvirus lineages. In addition to the "core" conserved genes, the genome contains four distinct gene families which may be involved in immune evasion and persistence in immune cells: two have similarity to the "chemokine" chemotactic/proinflammatory family of cytokines, one to their peptide G-protein-coupled receptors, and a fourth to the immunoglobulin superfamily.
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