An unbiased approach to defining bona fide cancer neoepitopes that elicit immune-mediated cancer rejection

Autor: Tatiana Shcheglova, Ion I. Mandoiu, Mariam M. George, Sahar Al Seesi, Cory A. Brennick, Jeremy L. Balsbaugh, Ryan P. Englander, Grant L.J. Keller, Andrea Schietinger, Pramod K. Srivastava, Adam T. Hagymasi, Marmar Moussa, Brian M. Baker
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: The Journal of Clinical Investigation
ISSN: 1558-8238
0021-9738
Popis: Identification of neoepitopes that are effective in cancer therapy is a major challenge in creating cancer vaccines. Here, using an entirely unbiased approach, we queried all possible neoepitopes in a mouse cancer model and asked which of those are effective in mediating tumor rejection, and independently, in eliciting a measurable CD8 response. This analysis uncovered a large trove of effective anticancer neoepitopes which have strikingly different properties from conventional epitopes and suggested an algorithm to predict them. It also revealed that our current methods of prediction discard the overwhelming majority of true anticancer neoepitopes. These results from a single mouse model were validated in another, antigenically distinct mouse cancer model, and are consistent with data reported in human studies. Structural modeling showed how the MHC I-presented neoepitopes have an altered conformation, higher stability, or increased exposure to T cell receptors as compared to the un-mutated counterparts. T cells elicited by the active neoepitopes identified here demonstrated a stem-like early dysfunctional phenotype associated with effective responses against viruses and tumors of transgenic mice. These abundant anticancer neoepitopes, which have not been tested in human studies thus far, can be exploited for the generation of personalized human cancer vaccines.
Databáze: OpenAIRE