Mutanome Engineered RNA Immunotherapy: Towards Patient-Centered Tumor Vaccination

Advances in nucleic acid sequencing technologies have revolutionized the field of genomics, allowing the efficient targeting of mutated neoantigens for personalized cancer vaccination. Due to their absence during negative selection of T cells and their lack of expression in healthy tissue, tumor mutations are considered as optimal targets for cancer immunotherapy. Preclinical and early clinical data suggest that synthetic mRNA can serve as potent drug format allowing the cost efficient production of highly efficient vaccines in a timely manner. In this review, we describe a process, which integrates next generation sequencing based cancer mutanome mapping, in silico target selection and prioritization approaches, and mRNA vaccine manufacturing and delivery into a process we refer to as MERIT (mutanome engineered RNA immunotherapy)

A liposomal RNA vaccine inducing neoantigen-specific CD4+ T cells augments the antitumor activity of local radiotherapy in mice

Antigen-encoding, lipoplex-formulated RNA (RNA-LPX) enables systemic delivery to lymphoid compartments and selective expression in resident antigen-presenting cells. We report here that the rejection of CT26 tumors, mediated by local radiotherapy (LRT), is further augmented in a CD8+ T cell-dependent manner by an RNA-LPX vaccine that encodes CD4+ T cell-recognized neoantigens (CD4 neoantigen vaccine). Whereas CD8+ T cells induced by LRT alone were primarily directed against the immunodominant gp70 antigen, mice treated with LRT plus the CD4 neoantigen vaccine rejected gp70-negative tumors and were protected from rechallenge with these tumors, indicating a potent poly-antigenic CD8+ T cell response and T cell memory. In the spleens of CD4 neoantigen-vaccinated mice, we found a high number of activated, poly-functional, Th1-like CD4+ T cells against ME1, the immunodominant CD4 neoantigen within the poly-neoantigen vaccine. LRT itself strongly increased CD8+ T cell numbers and clonal expansion. However, tumor infiltrates of mice treated with CD4 neoantigen vaccine/LRT, as compared to LRT alone, displayed a higher fraction of activated gp70-specific CD8+ T cells, lower PD-1/LAG-3 expression and contained ME1-specific IFNγ+ CD4+ T cells capable of providing cognate help. CD4 neoantigen vaccine/LRT treatment followed by anti-CTLA-4 antibody therapy further enhanced the efficacy with complete remission of gp70-negative CT26 tumors and survival of all mice. Our data highlight the power of combining synergistic modes of action and warrants further exploration of the presented treatment schema

A transplantable tumor model allowing investigation of NY-BR-1-specific T cell responses in HLA-DRB1*0401 transgenic mice

Background NY-BR-1 has been described as a breast cancer associated differentiation antigen with intrinsic immunogenicity giving rise to endogenous T and B cell responses. The current study presents the first murine tumor model allowing functional investigation of NY-BR-1-specific immune responses in vivo. Methods A NY-BR-1 expressing tumor model was established in DR4tg mice based on heterotopic transplantation of stable transfectant clones derived from the murine H2 compatible breast cancer cell line EO771. Composition and phenotype of tumor infiltrating immune cells were analyzed by qPCR and FACS. MHC I binding affinity of candidate CTL epitopes predicted in silico was determined by FACS using the mutant cell line RMA-S. Frequencies of NY-BR-1 specific CTLs among splenocytes of immunized mice were quantified by FACS with an epitope loaded D-b-dextramer. Functional CTL activity was determined by IFN gamma catch or IFN gamma ELISpot assays and statistical analysis was done applying the Mann Whitney test. Tumor protection experiments were performed by immunization of DR4tg mice with replication deficient recombinant adenovirus followed by s.c. challenge with NY-BR-1 expressing breast cancer cells. Results Our results show spontaneous accumulation of CD8(+) T cells and F4/80(+) myeloid cells preferentially in NY-BR-1 expressing tumors. Upon NY-BR-1-specific immunization experiments combined with in silico prediction and in vitro binding assays, the first NY-BR-1-specific H2-D-b-restricted T cell epitope could be identified. Consequently, flow cytometric analysis with fluorochrome conjugated multimers showed enhanced frequencies of CD8(+) T cells specific for the newly identified epitope in spleens of immunized mice. Moreover, immunization with Ad.NY-BR-1 resulted in partial protection against outgrowth of NY-BR-1 expressing tumors and promoted intratumoral accumulation of macrophages. Conclusion This study introduces the first H2-D-b-resctricted CD8(+) T cell epitope-specific for the human breast cancer associated tumor antigen NY-BR-1. Our novel, partially humanized tumor model enables investigation of the interplay between HLA-DR4-restricted T cell responses and CTLs within their joint attack of NY-BR-1 expressing tumors

Dexamethasone premedication suppresses vaccine-induced immune responses against cancer

Glucocorticosteroids (GCS) have an established role in oncology and are administered to cancer patients in routine clinical care and in drug development trials as co-medication. Given their strong immune-suppressive activity, GCS may interfere with immune-oncology drugs. We are developing a therapeutic cancer vaccine, which is based on a liposomal formulation of tumor-antigen encoding RNA (RNA-LPX) and induces a strong T-cell response both in mice as well as in humans. In this study, we investigated in vivo in mice and in human PBMCs the effect of the commonly used long-acting GCS Dexamethasone (Dexa) on the efficacy of this vaccine format, with a particular focus on antigen-specific T-cell immune responses. We show that Dexa, when used as premedication, substantially blunts RNA-LPX vaccine-mediated immune effects. Premedication with Dexa inhibits vaccine-dependent induction of serum cytokines and chemokines and reduces both the number and activation of splenic conventional dendritic cells (cDC) expressing vaccine-encoded antigens. Consequently, priming of functional effector T cells and therapeutic activity is significantly impaired. Interestingly, responses are less impacted when Dexa is administered post-vaccination. Consistent with this observation, although many inflammatory cytokines are reduced, IFNα, a key cytokine in T-cell priming, is less impacted and antigen expression by cDCs is intact. These findings warrant special caution when combining GCS with immune therapies relying on priming and activation of antigen-specific T cells and suggest that careful sequencing of these treatments may preserve T-cell induction

Mutant MHC class II epitopes drive therapeutic immune responses to cancer

Tumour-specific mutations are ideal targets for cancer immunotherapy as they lack expression in healthy tissues and can potentially be recognized as neo-antigens by the mature T-cell repertoire. Their systematic targeting by vaccine approaches, however, has been hampered by the fact that every patient’s tumour possesses a unique set of mutations (‘the mutanome’) that must first be identified. Recently, we proposed a personalized immunotherapy approach to target the full spectrum of a patient’s individual tumour-specific mutations1. Here we show in three independent murine tumour models that a considerable fraction of non-synonymous cancer mutations is immunogenic and that, unexpectedly, the majority of the immunogenic mutanome is recognized by CD4+ T cells. Vaccination with such CD4+ immunogenic mutations confers strong antitumour activity. Encouraged by these findings, we established a process by which mutations identified by exome sequencing could be selected as vaccine targets solely through bioinformatic prioritization on the basis of their expression levels and major histocompatibility complex (MHC) class II-binding capacity for rapid production as synthetic poly-neo-epitope messenger RNA vaccines. We show that vaccination with such polytope mRNA vaccines induces potent tumour control and complete rejection of established aggressively growing tumours in mice. Moreover, we demonstrate that CD4+ T cell neo-epitope vaccination reshapes the tumour microenvironment and induces cytotoxic T lymphocyte responses against an independent immunodominant antigen in mice, indicating orchestration of antigen spread. Finally, we demonstrate an abundance of mutations predicted to bind to MHC class II in human cancers as well by employing the same predictive algorithm on corresponding human cancer types. Thus, the tailored immunotherapy approach introduced here may be regarded as a universally applicable blueprint for comprehensive exploitation of the substantial neo-epitope target repertoire of cancers, enabling the effective targeting of every patient’s tumour with vaccines produced ‘just in time’

Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community

Key Parameters of Tumor Epitope Immunogenicity Revealed Through a Consortium Approach Improve Neoantigen Prediction

Many approaches to identify therapeutically relevant neoantigens couple tumor sequencing with bioinformatic algorithms and inferred rules of tumor epitope immunogenicity. However, there are no reference data to compare these approaches, and the parameters governing tumor epitope immunogenicity remain unclear. Here, we assembled a global consortium wherein each participant predicted immunogenic epitopes from shared tumor sequencing data. 608 epitopes were subsequently assessed for T cell binding in patient-matched samples. By integrating peptide features associated with presentation and recognition, we developed a model of tumor epitope immunogenicity that filtered out 98% of non-immunogenic peptides with a precision above 0.70. Pipelines prioritizing model features had superior performance, and pipeline alterations leveraging them improved prediction performance. These findings were validated in an independent cohort of 310 epitopes prioritized from tumor sequencing data and assessed for T cell binding. This data resource enables identification of parameters underlying effective anti-tumor immunity and is available to the research community