Abstract
While cancer immunotherapy has transformed oncology, many approved immunotherapies consist of antigen-
agnostic immune modulating agents that are limited by their dependence on pre-existing anti-tumor T cell
responses. Cancer vaccines represent an emerging class of antigen-specific immunotherapies that can initiate
or modulate tumor antigen-specific T cell responses. Evidence from murine studies has shown that these
therapies are effective, and promising data from clinical studies has provided proof of concept that cancer
vaccines are feasible and immunogenic in a patient setting. However, there remains little known about the cellular
mechanisms that underly therapeutic vaccine response, or about how targeting distinct types of tumor antigens,
such as overexpressed tumor-associated self-antigens or mutation-derived neoantigens, impacts the cellular
immune response elicited by cancer vaccines. Further, cancer vaccines are given in a therapeutic setting in
which tumor burden is already present and vaccine antigen-specific T cells may be either naive or antigen
experienced at the time of vaccine priming. While it is known that naive and antigen-experienced T cells respond
to antigen encounter in distinct ways, the impact of pre-vaccine T cell response status on vaccine response is
not well understood. To address this, I have characterized T cell response patterns against a panel of tumor
neoantigens in the murine model MC38 with and without vaccine therapy. This work has identified neoantigens
that are consistently targeted by pre-vaccine T cell responses (termed spontaneous response antigens), or
consistently ignored by T cells in the absence of vaccination, but that can be successfully targeted by therapeutic
vaccines (termed induced response antigens). Ongoing work aims to identify additional spontaneous and
induced response antigens of the tumor-associated antigen and viral antigen classes. This proposed study aims
to evaluate the impact of antigen class and pre-vaccine T cell response status on the cellular immune response
to therapeutic cancer vaccination alone and in combination with PD-1 blockade therapy using dextramer-based
T cell immunophenotyping as well as next-generation immunogenomic and spatial transcriptomic approaches.
Additionally, this proposed project aims to define parameters by which to identify spontaneous and induced
response antigens from tumor genomic and transcriptomic data, allowing for prediction of pre-vaccine response
status of a given tumor antigen based on antigen-intrinsic properties including expression level and MHC binding
stability. This work collectively will help to inform our understanding of how T cells respond to vaccines targeting
antigens with distinct properties, as well as how to identify those antigens, ultimately helping to guide antigen
selection for clinical cancer vaccinations to maximize therapeutic efficacy.