Fischbach, Mathew J

Abstract Forward genetic screens are powerful tools for novel biological discoveries because they do not require a priori knowledge of genes controlling a phenotype of interest. The Sleeping Beauty (SB) transposon system is one of many commonly employed genetic screen tools used to induce both gain and loss of gene function mutations via insertional mutagenesis. In the past, SB screens have been successfully utilized to discover several cancer driver genes that could serve as potential therapeutic targets. More recently, SB technologies have been extended to other applications, including the discovery of mechanisms contributing to drug resistance and novel targets for immunotherapy. Importantly, existing tools for SB screen data analysis do not support data-driven case–control comparisons capable of analyzing screens with this design. To this end, we developed a network-based common insertion site (NetCIS) analysis tool to robustly identify common insertion sites (CISes) in a case–control phenotype selection screen. NetCIS uses an efficient graph-based algorithm for discovering statistically significant CISes that differ between cases and controls. We benchmark NetCIS against other insertional mutagenesis analysis tools using a previously published SB dataset and show that NetCIS is able to prioritize previous biologically validated genes similarly or better than competing methods, is the only method that effectively utilizes a case–control experimental setup, and can identify CISes involving unannotated regions of the genome that are overlooked by existing methods. Code for NetCIS and an accompanying tutorial can be found at https://github.com/RogersLabGroup/NetCIS.

Adoptive cell therapy (ACT) has shown remarkable success in the treatment of some malignancies, particularly leukemia. However, there are multiple factors that limit the durability of ACT in solid tumors, including dose-limiting toxicities, the immunosuppressive tumor microenvironment, and T-cell exhaustion. As the manufacture and preparation of adoptive T-cell therapies allows time and adequate conditions for ex vivo T-cell engineering, forward genetic screens can identify novel genetic targets that could improve their effectiveness. CRISPR is a commonly used functional genomics tool that has been successfully used to both enhance our understanding of mechanisms of resistance and to discover potential genetic edits to improve ACT. A complementary approach, Sleeping Beauty transposon mutagenesis provides additional opportunities to identify novel genetic edits without being constrained by the annotated human genome. Here, we summarize forward genetic screens and their tools to uncover strategies to enhance ACT. Complementary approaches can be combined and improved on to identify translatable genetic editing strategies through studies that accurately recapitulate disease-specific challenges.