Targeting of the non-mutated tumor antigen HER2/neu to mature dendritic cells induces an integrated immune response that protects against breast cancer in mice

Introduction: Given their relative simplicity of manufacture and ability to be injected repeatedly, vaccines in a protein format are attractive for breast and other cancers. However, soluble human epidermal growth factor receptor (HER2)/neu protein as a vaccine has not been immunogenic. When protein is directly targeted to antigen uptake receptors, such as DEC205 (DEC), efficient processing and presentation of antigen take place. The aim of this study was to determine the immunogenicity of a HER2 protein vaccine that directly targets to DEC +dendritic cells (DCs) in a mouse breast cancer model.Methods: We genetically engineered the HER2 extracellular domain into a monoclonal antibody specific for DEC (DEC-HER2). Mice of various genetic backgrounds were immunized with DEC-HER2 in combination with DC maturation stimuli (poly IC ± CD40 Ab). Vaccine-induced T cell immunity was determined by analyzing the ability of CD4 +/CD8 +T cell to produce interferon (IFN)-gamma and proliferate upon antigen rechallenge. Sera were assessed for the presence of antigen specific antibody (Ab). For vaccine efficacy, FVB/N mice were immunized with DEC-HER2 in combination with poly IC and protection against neu-expressing mammary tumors was assessed. Protection mechanisms and tumor-specific T cell responses were also evaluated.Results: We demonstrate that DEC-HER2 fusion mAb, but not Ctrl Ig-HER2, elicits strong, broad and multifunctional CD4 +T cell immunity, CD8 +T cell responses, and humoral immunity specific for HER2 antigen. Cross-reactivity to rat neu protein was also observed. Importantly, mice xeno-primed with DEC-HER2 were protected from a neu-expressing mammary tumor challenge. Both CD4 +and CD8 +T cells mediated the tumor protection. Robust anti-tumor T cell immunity was detected in tumor protected mice.Conclusions: Immunization of mice with HER2 protein vaccine targeting DEC +DCs in vivo induced high levels of T- and B-cell immunity. Non-targeted HER2 protein was poorly immunogenic for CD4 +and CD8 +T cells. This vaccination approach provided long-term survival benefit for mice challenged with neu-expressing tumor following as little as 2.7 μg of HER2 protein incorporated in the vaccine. Vaccine-induced CD4 +and CD8 +T cells were both essential for tumor protection. This immunization strategy demonstrates great potential towards the development of vaccines for breast cancer patients

Treml4, an Ig superfamily member, mediates presentation of several antigens to T cells in vivo, including protective immunity to HER2 protein

Members of the triggering expressed on myeloid cells (Trem) receptor family fine-tune inflammatory responses. We previously identified one of these receptors, called Treml4, expressed mainly in the spleen, as well as at high levels by CD8α + dendritic cells and macrophages. Like other Trem family members, Treml4 has an Ig-like extracellular domain and a short cytoplasmic tail that associates with the adaptor DAP12. To follow up on our initial results that Treml4-Fc fusion proteins bind necrotic cells, we generated a knockout mouse to assess the role of Treml4 in the uptake and presentation of dying cells in vivo. Loss of Treml4 expression did not impair uptake of dying cells by CD8α + dendritic cells or cross-presentation of cell-associated Ag to CD8 +T cells, suggesting overlapping function between Treml4 and other receptors in vivo. To further investigate Treml4 function, we took advantage of a newly generated mAb against Treml4 and engineered its H chain to express three different Ags (i.e., OVA, HIV GAGp24, and the extracellular domain of the breast cancer protein HER2). OVA directed to Treml4 was efficiently presented to CD8 + and CD4 + T cells in vivo. Anti-Treml4-GAGp24 mAbs, given along with a maturation stimulus, induced Th1 Ag-specific responses that were not observed in Treml4 knockout mice. Also, HER2 targeting using anti-Treml4 mAbs elicited combined CD4 + and CD8 + T cell immunity, and both T cells participated in resistance to a transplantable tumor. Therefore, Treml4 participates in Ag presentation in vivo, and targeting Ags with anti-Treml4 Abs enhances immunization of otherwise naive mice

A Statin-Loaded Reconstituted High-Density Lipoprotein Nanoparticle Inhibits Atherosclerotic Plaque Inflammation

Inflammation is a key feature of atherosclerosis and a target for therapy. Statins have potent anti-inflammatory properties but these cannot be fully exploited with oral statin therapy due to low systemic bioavailability. Here we present an injectable reconstituted high-density lipoprotein (rHDL) nanoparticle carrier vehicle that delivers statins to atherosclerotic plaques. We demonstrate the anti-inflammatory effect of statin-rHDL in vitro and show this effect is mediated through inhibition of the mevalonate pathway. We also apply statin-rHDL nanoparticles in vivo in an apolipoprotein E-knockout mouse model of atherosclerosis and show they accumulate in atherosclerotic lesions where they directly affect plaque macrophages. Finally we demonstrate that a three-month low-dose statin-rHDL treatment regimen inhibits plaque inflammation progression, while a one-week high-dose regimen markedly decreases inflammation in advanced atherosclerotic plaques. Statin-rHDL represents a novel potent atherosclerosis nanotherapy that directly affects plaque inflammation

Role of in silico structural modeling in predicting immunogenic neoepitopes for cancer vaccine development

In prior studies, we delineated the landscape of neoantigens arising from nonsynonymous point mutations in a murine pancreatic cancer model, Panc02. We developed a peptide vaccine by targeting neoantigens predicted using a pipeline that incorporates the MHC binding algorithm NetMHC. The vaccine, when combined with immune checkpoint modulators, elicited a robust neoepitope-specific antitumor immune response and led to tumor clearance. However, only a small fraction of the predicted neoepitopes induced T cell immunity, similarly to that reported for neoantigen vaccines tested in clinical studies. While these studies have used binding affinities to MHC I as surrogates for T cell immunity, this approach does not include spatial information on the mutated residue that is crucial for TCR activation. Here, we investigate conformational alterations in and around the MHC binding groove induced by selected minimal neoepitopes, and we examine the influence of a given mutated residue as a function of its spatial position. We found that structural parameters, including the solvent-accessible surface area (SASA) of the neoepitope and the position and spatial configuration of the mutated residue within the sequence, can be used to improve the prediction of immunogenic neoepitopes for inclusion in cancer vaccines

A Random Forest Genomic Classifier for Tumor Agnostic Prediction of Response to Anti-PD1 Immunotherapy.

Tumor mutational burden (TMB), a surrogate for tumor neoepitope burden, is used as a pan-tumor biomarker to identify patients who may benefit from anti-program cell death 1 (PD1) immunotherapy, but it is an imperfect biomarker. Multiple additional genomic characteristics are associated with anti-PD1 responses, but the combined predictive value of these features and the added informativeness of each respective feature remains unknown. We evaluated whether machine learning (ML) approaches using proposed determinants of anti-PD1 response derived from whole exome sequencing (WES) could improve prediction of anti-PD1 responders over TMB alone. Random forest classifiers were trained on publicly available anti-PD1 data (n = 104), and subsequently tested on an independent anti-PD1 cohort (n = 69). Both the training and test datasets included a range of cancer types such as non-small cell lung cancer (NSCLC), head and neck squamous cell carcinoma (HNSCC), melanoma, and smaller numbers of patients from other tumor types. Features used include summaries such as TMB and number of frameshift mutations, as well as more gene-level features such as counts of mutations associated with immune checkpoint response and resistance. Both ML algorithms demonstrated area under the receiver-operator curves (AUC) that exceeded TMB alone (AUC 0.63 human-guided, 0.64 cluster, and 0.58 TMB alone). Mutations within oncogenes disproportionately modulate anti-PD1 responses relative to their overall contribution to tumor neoepitope burden. The use of a ML algorithm evaluating multiple proposed genomic determinants of anti-PD1 responses modestly improves performance over TMB alone, highlighting the need to integrate other biomarkers to further improve model performance