1338 Virus like vesicle based multivalent immunotherapy for solid tumors
Year: 2024
Type: conference-abstract
Abstract: Background Targeting multiple immune mechanisms may overcome therapy resistance and further improve cancer immunotherapy for humans. Here we describe the application of virus-like vesicles (VLV) for delivery of three immunomodulators alone and in combination, as a promising approach for cancer immunotherapy. Methods VLV vectors were designed to deliver single chain interleukin (IL)-12, short-hairpin RNA (shRNA) targeting programmed death ligand 1 (PD-L1), and a dominant-negative form of IL-17 receptor A (dn-IL17RA) as a single payload or as the combination payload. This novel agent is designated as ‘CARG-2020’. We used mouse models of colorectal cancer (CRC) and liver cancer to test the efficacy and mechanism of action of the novel agent. Results Intralesional delivery of the VLV vector expressing IL-12 alone as well as the trivalent vector (designated CARG-2020) eradicated large established tumors. However, only CARG-2020 prevented tumor recurrence and provided long-term survival benefit to the tumor-bearing mice, indicating a benefit of the combined immunomodulation. The abscopal effects of CARG-2020 on the non-injected contralateral tumors, as well as protection from the tumor cell re-challenge, suggest immune-mediated mechanism of protection and establishment of immunological memory. Mechanistically, CARG-2020 potently activates Th1 immune mechanisms and inhibits expression of genes related to T cell exhaustion and cancer-promoting inflammation (figure 1). Conclusions The ability of CARG-2020 to prevent tumor recurrence and to provide survival benefit makes it a promising candidate for its development for human cancer immunotherapy. Ethics Approval All mice were kept at a specific-pathogen-free facility, and all mouse experiments were approved by the Institutional Animal Care and Use Committee at UConn Health.
Authors: Elham Ahmadi, Conner Chiari, Kepeng Wang
Institution: UConn Health
Language: English
Subfield: Immunology
Field: Immunology and Microbiology
Domain: Life Sciences
Open Access status: hybrid
OpenAlex ID: W4404065553