Abstract PR014: Design and construction of evolutionary-guided "selection gene drive" therapy

Abstract

Abstract Targeted therapies that are rationally designed to inhibit driver oncogenes generally offer more durable responses for cancer patients compared to standard chemotherapies. However, in virtually all cases, the development of drug resistance inevitably subverts eradication attempts. In tyrosine kinases inhibitors (TKIs), resistance is often addressed with next-generation TKIs or combination therapies. Appropriate treatment strategies are selected based on the nature of resistance outgrowth. However, intra- and intertumoral heterogeneity makes it impossible to predict a priori which resistance variants will drive relapse in a given patient, and thus what therapeutic strategy will be optimal. Here, we propose a resistance-agnostic treatment approach that seeks to leverage evolutionary principles, rather than combat them. We designed and demonstrated the capability of a gene therapy, which we term “dual-switch selection gene drives”, that can be used to engineer cancer cells in order to guide the tumor’s evolutionary trajectory towards eradication. The dual-switch gene drive system is a genetic circuit composed of two genes that can be delivered to tumor cells on a single vector in situ. The “switch one” gene is a drug target analog that acts as an inducible, transient resistance marker, enabling rapid selection of modified cells. The “switch two” gene is the therapeutic payload of the system. Its role is to kill tumor cells by activating an inert small molecule. Importantly, the activity of the therapeutic gene is diffuse, and this bystander effect is maximized by hitchhiking off the inducible resistance gene. We developed stochastic dynamic models of tumor evolution to predict parameter regimes where eradication is possible. With these design criteria, we constructed and evaluated our system. First, we generated a panel of optimized “switch one” genes co-opting the kinase domains for a range of TKI targets, including EGFR, ALK, and RET. We demonstrated that these synthetic genes could induce a conditional resistance phenotype and be used to select for modified cells in a mixed population. Next, we evaluated the suicide gene cytosine deaminase (CD), which converts the inert prodrug 5-FC into the nucleoside analog 5-FU. Cell viability assays for mixed populations of wild-type and CD-expressing cells confirmed a strong bystander effect in this system. Finally, we assembled a single vector harboring both switches. In a pooled experiment, gene drive cells were able to drive the mixed population to eradication, even when pre-existing resistance to the TKI was introduced. Our dual-switch design demonstrates the potential to target pre-existing resistant subpopulations, without foreknowledge of the exact nature of resistance. Given that drug resistance, and thus treatment failure, is inevitable in most cancers, our treatment strategy enables us to decide the terms of relapse. Rather than combat drug resistance, we can leverage it to amplify a therapeutic gene’s effect and ultimately collapse a complex tumor population. Citation Format: Scott M. Leighow, Haider Inam, Justin R. Pritchard. Design and construction of evolutionary-guided "selection gene drive" therapy [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr PR014.