Biology subjects

Jason Moffat

Publications and source records attributed to Jason Moffat.

4 recordsLinked to original sources

bioRxiv2016

A CRISPR screen reveals a WNT7B-FZD5 signaling circuit as a therapeutic opportunity in pancreatic cancer.

AbstractCRISPR-Cas9 genome editing enables high-resolution detection of genetic vulnerabilities of cancer cells. We conducted a genome-wide CRISPR-Cas9 screen in RNF43 mutant pancreatic ductal adenocarcinoma (PDAC) cells, which rely on Wnt signaling for proliferation, and discovered a unique requirement for a WNT7B-FZD5 signaling circuit. Our results highlight an underappreciated level of functional specificity at the ligand-receptor level. We derived a panel of recombinant antibodies that reports the expression of nine out of ten human Frizzled receptors and confirm that WNT7B-FZD5 functional specificity cannot be explained by protein expression patterns. We developed two human antibodies that target FZD5 and robustly inhibited the growth of RNF43 mutant PDAC cells grown in vitro and as xenografts, providing strong orthogonal support for the functional specificity observed genetically. Proliferation of a patient-derived PDAC cell line harboring a RNF43 variant previously associated with PDAC was also selectively inhibited by the FZD5 antibodies, further demonstrating their use as a potential targeted therapy.

Cancer Biology↗

bioRxiv2015

BAGEL: A computational framework for identifying essential genes from pooled library screens.

BackgroundThe adaptation of the CRISPR-Cas9 system to pooled library gene knockout screens in mammalian cells represents a major technological leap over RNA interference, the prior state of the art. New methods for analyzing the data and evaluating results are needed.\n\nResultsWe offer BAGEL (Bayesian Analysis of Gene EssentiaLity), a supervised learning method for analyzing gene knockout screens. Coupled with gold-standard reference sets of essential and nonessential genes, BAGEL offers significantly greater sensitivity than current methods, while computational optimizations reduce runtime by an order of magnitude.\n\nConclusionsUsing BAGEL, we identify ~2,000 fitness genes in pooled library knockout screens in human cell lines at 5% FDR, a major advance over competing platforms. BAGEL shows high sensitivity and specificity even across screens with highly variable reagent quality.

Systems Biology↗

bioRxiv2015

Systematic discovery and classification of human cell line essential genes

The study of gene essentiality in human cells is crucial for elucidating gene function and holds great potential for finding therapeutic targets for diseases such as cancer. Technological advances in genome editing using clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 systems have set the stage for identifying human cell line core and context-dependent essential genes. However, first generation negative selection screens using CRISPR technology demonstrate extreme variability across different cell lines. To advance the development of the catalogue of human core and context-dependent essential genes, we have developed an optimized, ultracomplex, genome-scale gRNA library of 176,500 guide RNAs targeting 17,661 genes and have applied it to negative and positive selection screens in a human cell line. Using an improved Bayesian analytical approach, we find CRISPR-based screens yield double to triple the number of essential genes than were previously observed using systematic RNA interference, including many genes at moderate expression levels that are largely refractory to RNAi methods. We further characterized four essential genes of unknown significance and found that they all likely exist in protein complexes with other essential genes. For example, RBM48 and ARMC7 are both essential nuclear proteins, strongly interact and are commonly amplified across major cancers. Our findings suggest the CRISPR-Cas9 system fundamentally alters the landscape for systematic reverse genetics in human cells for elucidating gene function, identifying disease genes, and uncovering therapeutic targets.

Genomics↗

bioRxiv2014

Measuring error rates in genomic perturbation screens: gold standards for human functional genomics

Technological advancement has opened the door to systematic genetics in mammalian cells. Genome-scale loss-of-function screens can assay fitness defects induced by partial gene knockdown, using RNA interference, or complete gene knockout, using new CRISPR techniques. These screens can reveal the basic blueprint required for cellular proliferation. Moreover, comparing healthy to cancerous tissue can uncover genes that are essential only in the tumor; these genes are targets for the development of specific anticancer therapies. Unfortunately, progress in this field has been hampered by offtarget effects of perturbation reagents and poorly quantified error rates in large-scale screens. To improve the quality of information derived from these screens, and to provide a framework for understanding the capabilities and limitations of CRISPR technology, we derive gold-standard reference sets of essential and nonessential genes, and provide a Bayesian classifier of gene essentiality that outperforms current methods on both RNAi and CRISPR screens. Our results indicate that CRISPR technology is more sensitive than RNAi, and that both techniques have nontrivial false discovery rates that can be mitigated by rigorous analytical methods.

Systems Biology↗