Fitness Screens Map State-Specific Glioblastoma Stem Cell Vulnerabilities.

Glioblastoma (GBM) is the most common and lethal primary brain tumor in adults and is driven by self-renewing glioblastoma stem cells (GSCs) that persist after therapy and seed treatment refractory recurrent tumors. GBM tumors display a high degree of intra- and inter-tumoral heterogeneity that is a prominent barrier to targeted treatment strategies. This heterogeneity extends to GSCs that exist on a gradient between two transcriptional states or subtypes termed developmental and injury-response. Drug targets for each subtype are needed to effectively target GBM. To identify conserved and subtype-specific genetic dependencies across a large and heterogeneous panel of GSCs, we designed the GBM5K targeted gRNA library and performed fitness screens in a total of 30 patient-derived GSC cultures. The focused CRISPR screens identified the most conserved subtype-specific vulnerabilities in GSCs and elucidated the functional dependency gradient existing between the developmental and injury-response states. Developmental-specific fitness genes were enriched for transcriptional regulators of neurodevelopment, whereas injury-response-specific fitness genes were highlighted by several genes implicated in integrin and focal adhesion signaling. These context-specific vulnerabilities conferred differential sensitivity to inhibitors of ß1 integrin, FAK, MEK and OLIG2. Interestingly, the screens revealed that the subtype-specific signaling pathways drive differential cyclin D (CCND1 vs. CCND2) dependencies between subtypes. These data provide biological insight and mechanistic understanding of GBM heterogeneity and point to opportunities for precision targeting of defined GBM and GSC subtypes to tackle heterogeneity.

Proteome-scale discovery of protein degradation and stabilization effectors.

Targeted protein degradation and stabilization are promising therapeutic modalities because of their potency, versatility and their potential to expand the druggable target space1,2. However, only a few of the hundreds of E3 ligases and deubiquitinases in the human proteome have been harnessed for this purpose, which substantially limits the potential of the approach. Moreover, there may be other protein classes that could be exploited for protein stabilization or degradation3-5, but there are currently no methods that can identify such effector proteins in a scalable and unbiased manner. Here we established a synthetic proteome-scale platform to functionally identify human proteins that can promote the degradation or stabilization of a target protein in a proximity-dependent manner. Our results reveal that the human proteome contains a large cache of effectors of protein stability. The approach further enabled us to comprehensively compare the activities of human E3 ligases and deubiquitinases, identify and characterize non-canonical protein degraders and stabilizers and establish that effectors have vastly different activities against diverse targets. Notably, the top degraders were more potent against multiple therapeutically relevant targets than the currently used E3 ligases cereblon and VHL. Our study provides a functional catalogue of stability effectors for targeted protein degradation and stabilization and highlights the potential of induced proximity screens for the discovery of new proximity-dependent protein modulators.

Pervasive mislocalization of pathogenic coding variants underlying human disorders.

Widespread sequencing has yielded thousands of missense variants predicted or confirmed as disease-causing. This creates a new bottleneck: determining the functional impact of each variant - largely a painstaking, customized process undertaken one or a few genes or variants at a time. Here, we established a high-throughput imaging platform to assay the impact of coding variation on protein localization, evaluating 3,547 missense variants of over 1,000 genes and phenotypes. We discovered that mislocalization is a common consequence of coding variation, affecting about one-sixth of all pathogenic missense variants, all cellular compartments, and recessive and dominant disorders alike. Mislocalization is primarily driven by effects on protein stability and membrane insertion rather than disruptions of trafficking signals or specific interactions. Furthermore, mislocalization patterns help explain pleiotropy and disease severity and provide insights on variants of unknown significance. Our publicly available resource will likely accelerate the understanding of coding variation in human diseases.

Survival-based CRISPR genetic screens across a panel of permissive cell lines identify common and cell-specific SARS-CoV-2 host factors.

SARS-CoV-2 depends on host cell components for infection and replication. Identification of virus-host dependencies offers an effective way to elucidate mechanisms involved in viral infection and replication. If druggable, host factor dependencies may present an attractive strategy for anti-viral therapy. In this study, we performed genome wide CRISPR knockout screens in Vero E6 cells and four human cell lines including Calu-3, UM-UC-4, HEK-293 and HuH-7 to identify genetic regulators of SARS-CoV-2 infection. Our findings identified only ACE2, the cognate SARS-CoV-2 entry receptor, as a common host dependency factor across all cell lines, while other host genes identified were largely cell line specific, including known factors TMPRSS2 and CTSL. Several of the discovered host-dependency factors converged on pathways involved in cell signalling, immune-related pathways, and chromatin modification. Notably, the chromatin modifier gene KMT2C in Calu-3 cells had the strongest impact in preventing SARS-CoV-2 infection when perturbed.