Stroke network performance during the first COVID-19 pandemic stage: A meta-analysis based on stroke network models.

Background: The effect of the COVID pandemic on stroke network performance is unclear, particularly with consideration of drip&ship vs. mothership models.

Aims: We systematically reviewed and meta-analyzed variations in stroke admissions, rate and timing of reperfusion treatments during the first wave COVID pandemic vs.

Effect of COVID-19 on Emergent Stroke Care: A Regional Experience.

Background And Purpose: Anecdotal evidence suggests that the coronavirus disease 2019 (COVID-19) pandemic mitigation efforts may inadvertently discourage patients from seeking treatment for stroke with resultant increased morbidity and mortality. Analysis of regional data, while hospital capacities for acute stroke care remained fully available, offers an opportunity to assess this. We report regional Stroke Team acute activations and reperfusion treatments during COVID-19 mitigation activities.

Defining a Cancer Dependency Map.

Most human epithelial tumors harbor numerous alterations, making it difficult to predict which genes are required for tumor survival. To systematically identify cancer dependencies, we analyzed 501 genome-scale loss-of-function screens performed in diverse human cancer cell lines. We developed DEMETER, an analytical framework that segregates on- from off-target effects of RNAi.

Parallel genome-scale loss of function screens in 216 cancer cell lines for the identification of context-specific genetic dependencies.

Using a genome-scale, lentivirally delivered shRNA library, we performed massively parallel pooled shRNA screens in 216 cancer cell lines to identify genes that are required for cell proliferation and/or viability. Cell line dependencies on 11,000 genes were interrogated by 5 shRNAs per gene. The proliferation effect of each shRNA in each cell line was assessed by transducing a population of 11M cells with one shRNA-virus per cell and determining the relative enrichment or depletion of each of the 54,000 shRNAs after 16 population doublings using Next Generation Sequencing.

A genome-scale RNA interference screen implicates NF1 loss in resistance to RAF inhibition.

RAF inhibitors such as vemurafenib and dabrafenib block BRAF-mediated cell proliferation and achieve meaningful clinical benefit in the vast majority of patients with BRAF(V600E)-mutant melanoma. However, some patients do not respond to this regimen, and nearly all progress to therapeutic resistance. We used a pooled RNA interference screen targeting more than 16,500 genes to discover loss-of-function events that could drive resistance to RAF inhibition.

Systematic investigation of genetic vulnerabilities across cancer cell lines reveals lineage-specific dependencies in ovarian cancer.

A comprehensive understanding of the molecular vulnerabilities of every type of cancer will provide a powerful roadmap to guide therapeutic approaches. Efforts such as The Cancer Genome Atlas Project will identify genes with aberrant copy number, sequence, or expression in various cancer types, providing a survey of the genes that may have a causal role in cancer. A complementary approach is to perform systematic loss-of-function studies to identify essential genes in particular cancer cell types.