Epithelial ovarian cancer (EOC) generates multicellular aggregates called spheroids that detach from the primary tumor and disseminate through ascites. Spheroids possess a number of characteristics of tumor dormancy including withdrawal from the cell cycle and resistance to chemotherapeutics. This report systematically analyzes the effects of RNAi depletion of 21 genes that are known to contribute to negative regulation of the cell cycle in 10 ovarian cancer cell lines. Interestingly, spheroid cell viability was compromised by loss of some cyclin-dependent kinase inhibitors such as p57, as well as Dyrk1A, Lin52, and E2F5 in most cell lines tested. Many genes essential for EOC spheroid viability are pertinent to the mammalian DREAM repressor complex. Mechanistically, the data demonstrate that DREAM is assembled upon the induction of spheroid formation, which is dependent upon Dyrk1A. Loss of Dyrk1A results in retention of the b-Myb-MuvB complex, elevated expression of DREAM target genes, and increased DNA synthesis that is coincident with cell death. Inhibition of Dyrk1A activity using pharmacologic agents Harmine and INDY compromises viability of spheroids and blocks DREAM assembly. In addition, INDY treatment improves the response to carboplatin, suggesting this is a therapeutic target for EOC treatment. Loss of negative growth control mechanisms in cancer dormancy lead to cell death and not proliferation, suggesting they are an attractive therapeutic approach. .

The success of CRISPR-mediated gene perturbation studies is highly dependent on the quality of gRNAs, and several tools have been developed to enable optimal gRNA design. However, these tools are not all adaptable to the latest CRISPR modalities or nucleases, nor do they offer comprehensive annotation methods for advanced CRISPR applications. Here, we present a new ecosystem of R packages, called crisprVerse, that enables efficient gRNA design and annotation for a multitude of CRISPR technologies. This includes CRISPR knockout (CRISPRko), CRISPR activation (CRISPRa), CRISPR interference (CRISPRi), CRISPR base editing (CRISPRbe) and CRISPR knockdown (CRISPRkd). The core package, crisprDesign, offers a user-friendly and unified interface to add off-target annotations, rich gene and SNP annotations, and on- and off-target activity scores. These functionalities are enabled for any RNA- or DNA-targeting nucleases, including Cas9, Cas12, and Cas13. The crisprVerse ecosystem is open-source and deployed through the Bioconductor project (https://github.com/crisprVerse).

Background: The use of RNA-sequencing (RNA-seq) in molecular biology research and clinical settings has increased significantly over the past decade. Despite its widespread adoption, there is a lack of simple and interactive tools to analyze and explore RNA-seq data. Many established tools require programming or Unix/Bash knowledge to analyze and visualize results. This requirement presents a significant barrier for many researchers to efficiently analyze and present RNA-seq data. Results: Here we present BEAVR, a Browser-based tool for the Exploration And Visualization of RNA-seq data. BEAVR is an easy-to-use tool that facilitates interactive analysis and exploration of RNA-seq data. BEAVR is developed in R and uses DESeq2 as its engine for differential gene expression (DGE) analysis, but assumes users have no prior knowledge of R or DESeq2. BEAVR allows researchers to easily obtain a table of differentially-expressed genes with statistical testing and then visualize the results in a series of graphs, plots and heatmaps. Users are able to customize many parameters for statistical testing, dealing with variance, clustering methods and pathway analysis to generate high quality figures. Conclusion: BEAVR simplifies analysis for novice users but also streamlines the RNAseq analysis process for experts by automating several steps.

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