Abstract Background: In the past decade, immunotherapy has transformed cancer treatment, with the development of immune-checkpoint inhibitors and adoptive cell therapies. A novel frontier is personalized vaccines targeting neoantigens unique to tumor cells. Vaccines based on neoantigens have several advantages. First, neoantigens are exclusively expressed by tumor cells and can, therefore, elicit truly tumor-specific T cell responses, thereby preventing ‘off-target’ damage to nonmalignant tissues. Second, neoantigens are de novo epitopes derived from somatic mutations, which presents the possibility to circumvent T cell central tolerance of self-epitopes and thus induce immune responses to tumors. One of the major challenges is the optimal neoantigen discovery/selection. Our study combines in silico HLA binding models with the 'MHC-PepSeq' platform to enhance neoantigen prediction, creating a personalized neoantigen peptide vaccine. We aim to demonstrate its efficacy in a mouse CT26 colon cancer model. Methods: Our method involved whole exome sequencing of tumor and normal DNA to identify neoantigens expressed in CT26 tumors, generating a peptide library. The peptides were further filtered using an in-silico prediction algorithm and our proprietary peptide-MHC binding assay (PepSeq assay), to determine those exhibiting the highest binding affinity with mice HLAs. Vaccines were prepared by dissolving these peptides in sterile PBS. Mice (BALB/C) were subcutaneously implanted with CT26 tumors, then immunized with the vaccine via IV injection in combination with a TLR7/8 agonist. Mice received a second vaccine dose on Day 14, and some groups were treated with an anti-PD-1 agent. Tumors and spleens from the mice were collected, processed into single-cell suspensions, and analyzed by single-cell sequencing, TCR analysis, IHC, and flow cytometry assays. Peripheral blood mononuclear cells (PBMCs) were collected and utilized in MHC tetramer assays. Results: Preliminary in vivo studies demonstrated significant tumor growth restrictions (TGI around 70%) and prolonged tumor-free survival in some mice. Our data showed the generation of neoantigen-specific T cells in vaccinated mice. Remarkably, vaccinated, tumor-free mice, when re-challenged with the same tumor cells, maintained their tumor-free status, suggesting the vaccine induced post-treatment immunological memory. Combining the vaccine with checkpoint inhibition resulted in better tumor growth restriction in mice (TGI around 93%). Conclusion: Overall, our data suggests that our personalized neoantigen vaccine platform has the potential to evoke robust and durable immune responses and, when paired with suitable complementary therapies and immune adjuvants, may serve as an effective cancer treatment. Citation Format: Tithi Ghosh Halder, Kate Gutowsky, Serina Ng, Trason Thode, Alexis Weston, Erin Kelley, Jorge Soria-Bustos, Jorge A. Giron, Taylor Bargenquast, Mohan Kaadige, Sanjana Tripuraneni, Brian Durbin, Shelby Rheinschmidt, Sydney Adamson, Michael Gordon, Justin Moser, John Altin, Raffaella Soldi, Sunil Sharma. Evaluating the efficacy of personalized neoantigen cancer vaccine in preclinical model: A promising step towards precision immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4107.
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