RESUMO
The ability to understand and predict variable responses to therapeutic agents may improve outcomes in patients with cancer. We hypothesized that the basal gene-transcription state of cancer cell lines, coupled with cell viability profiles of small molecules, might be leveraged to nominate specific mechanisms of intrinsic resistance and to predict drug combinations that overcome resistance. We analyzed 564,424 sensitivity profiles to identify candidate gene-compound pairs, and validated nine such relationships. We determined the mechanism of a novel relationship, in which expression of the serine hydrolase enzymes monoacylglycerol lipase (MGLL) or carboxylesterase 1 (CES1) confers resistance to the histone lysine demethylase inhibitor GSK-J4 by direct enzymatic modification. Insensitive cell lines could be sensitized to GSK-J4 by inhibition or gene knockout. These analytical and mechanistic studies highlight the potential of integrating gene-expression features with small-molecule response to identify patient populations that are likely to benefit from treatment, to nominate rational candidates for combinations and to provide insights into mechanisms of action.
Assuntos
Histona Desmetilases , Monoacilglicerol Lipases , Biomarcadores , Sobrevivência Celular , Combinação de Medicamentos , Histona Desmetilases/metabolismo , HumanosRESUMO
Combinatorial genetic screening using CRISPR-Cas9 is a useful approach to uncover redundant genes and to explore complex gene networks. However, current methods suffer from interference between the single-guide RNAs (sgRNAs) and from limited gene targeting activity. To increase the efficiency of combinatorial screening, we employ orthogonal Cas9 enzymes from Staphylococcus aureus and Streptococcus pyogenes. We used machine learning to establish S. aureus Cas9 sgRNA design rules and paired S. aureus Cas9 with S. pyogenes Cas9 to achieve dual targeting in a high fraction of cells. We also developed a lentiviral vector and cloning strategy to generate high-complexity pooled dual-knockout libraries to identify synthetic lethal and buffering gene pairs across multiple cell types, including MAPK pathway genes and apoptotic genes. Our orthologous approach also enabled a screen combining gene knockouts with transcriptional activation, which revealed genetic interactions with TP53. The "Big Papi" (paired aureus and pyogenes for interactions) approach described here will be widely applicable for the study of combinatorial phenotypes.
Assuntos
Sistemas CRISPR-Cas/genética , Epistasia Genética/genética , Testes Genéticos , RNA Guia de Cinetoplastídeos/genética , Apoptose/genética , Técnicas de Inativação de Genes , Marcação de Genes , Humanos , Aprendizado de Máquina , Quinases de Proteína Quinase Ativadas por Mitógeno/genética , Transdução de Sinais/genética , Staphylococcus aureus/genética , Streptococcus pyogenes/genética , Proteína Supressora de Tumor p53/genéticaRESUMO
CRISPR/Cas9 screening has proven to be a versatile tool for genomics research. Based on unexpected results from a genome-wide screen, we developed a CRISPR/Cas9-mediated approach to mutagenesis, exploiting the allelic diversity generated by error-prone non-homologous end-joining (NHEJ) to identify novel gain-of-function and drug resistant alleles of the MAPK signaling pathway genes MEK1 and BRAF. We define the parameters of a scalable technique to easily generate cell populations containing thousands of endogenous allelic variants to map gene functions. Further, these results highlight an unexpected but important phenomenon, that Cas9-induced gain-of-function alleles are an inherent by-product of normal Cas9 loss-of-function screens and should be investigated during analysis of data from large-scale positive selection screens.
Assuntos
Sistemas CRISPR-Cas , MAP Quinase Quinase 1/genética , Mutagênese , Engenharia de Proteínas/métodos , Proteínas Proto-Oncogênicas B-raf/genética , Alelos , Linhagem Celular Tumoral , Repetições Palindrômicas Curtas Agrupadas e Regularmente Espaçadas , Reparo do DNA por Junção de Extremidades , Biblioteca Gênica , Células HEK293 , Humanos , Mutação INDEL , Indóis/farmacologia , MAP Quinase Quinase 1/química , Fenótipo , Proteínas Proto-Oncogênicas B-raf/química , RNA Guia de Cinetoplastídeos/genética , Proteínas Recombinantes de Fusão/química , Alinhamento de Sequência , Sulfonamidas/farmacologia , Transdução Genética , VemurafenibRESUMO
CRISPR-Cas9-based genetic screens are a powerful new tool in biology. By simply altering the sequence of the single-guide RNA (sgRNA), one can reprogram Cas9 to target different sites in the genome with relative ease, but the on-target activity and off-target effects of individual sgRNAs can vary widely. Here, we use recently devised sgRNA design rules to create human and mouse genome-wide libraries, perform positive and negative selection screens and observe that the use of these rules produced improved results. Additionally, we profile the off-target activity of thousands of sgRNAs and develop a metric to predict off-target sites. We incorporate these findings from large-scale, empirical data to improve our computational design rules and create optimized sgRNA libraries that maximize on-target activity and minimize off-target effects to enable more effective and efficient genetic screens and genome engineering.