Abstract A22: Augmentation of a novel adenoviral vaccine strategy by checkpoint inhibitors

Conference Paper

Abstract The immunologic hurdles for a vaccine targeting cancer are much higher than for those targeting an infectious disease. The profoundly immunosuppressive tumor microenvironment, the lack of microbial danger signals, and the need to break tolerance without causing catastrophic autoimmunity are all considerations that must be made when designing an effective anti-cancer vaccine. Immune checkpoint blockade (ICB) including programmed death 1 (PD1) and cytotoxic T-lymphocyte antigen 4 (CTLA-4) monoclonal antibodies have revolutionized cancer treatment as a whole, including the potential for a successful cancer vaccine. Human epidermal growth factor receptor 2 (HER2) is an oncogene that is overexpressed in 20-25% of breast cancers and has been successfully targeted with therapeutic anti-HER2 therapies, particularly antibody combinations like trastuzumab and pertuzumab. However, even the most potent anti-HER2 therapy available is often accompanied by a high rate of recurrence, with the many responders eventually becoming resistant. Given the relative success of combination therapy using antibodies targeting different epitopes of HER2, we hypothesized that a HER2 targeting vaccine approach could further broaden the immune repertoire and reduce rates of resistance and recurrence. We developed both an implantable and a mammary specific spontaneous tumor model driven by an oncogenic isoform of HER2 (HER2Δ16). Using these models we tested a novel adenoviral vaccine platform encoding an inactive HER2Δ16 variant. We have shown that this isoform is significantly more oncogenic than full length HER2 and plays a role in anti-HER2 therapeutic resistance. Using the implantable tumor model, we found that therapeutic vaccination elicits a robust anti-HER2 specific cellular and humoral response, as well as significantly inhibits tumor growth of HER2Δ16-positive tumors. While effective at reducing tumor growth, we observed that our vaccine was typically not capable of eliciting tumor regression in mice, due to the immunosuppressive tumor microenvironment of established tumors. As such, we tested our vaccine platform in combination with two recently approved checkpoint inhibitors anti-CTLA-4 and anti-PD-1. This combination greatly enhanced the HER2-specific immune response as well as the antitumor effect seen post vaccination, with many tumors exhibiting complete regression. Our spontaneous model provides the ideal setting to test our vaccine platform as it is tolerant to human HER2, driven by HER2 expression, and grows at a rate that provides sufficient time to intervene with an immune targeting therapy. Using this model we have further shown that vaccination against HER2Δ16 can prevent spontaneous tumor formation and work is ongoing to test therapeutic vaccine strategies in combination with ICB. Future studies will be focused on determining the exact mechanism of regression and evaluating the impact on de novo and acquired resistance by combining this novel therapeutic platform with current standard of care HER2 targeted therapies. We conclude that the incorporation of ICB can help overcome the immunologic hurdles and augment the utility of therapeutic cancer vaccines. Citation Format: Erika J. Crosby, Gangjun Lei, Junping Wei, Xiao Yi Yang, Tao Wang, Cong-Xiao Liu, H Kim Lyerly, Zachary C. Hartman. Augmentation of a novel adenoviral vaccine strategy by checkpoint inhibitors [abstract]. In: Proceedings of the AACR Special Conference on Tumor Immunology and Immunotherapy; 2017 Oct 1-4; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2018;6(9 Suppl):Abstract nr A22.

Full Text

Duke Authors

Cited Authors

  • Crosby, EJ; Lei, G; Wei, J; Yang, XY; Wang, T; Liu, C-X; Lyerly, HK; Hartman, ZC

Published Date

  • September 1, 2018

Published In

Volume / Issue

  • 6 / 9_Supplement

Start / End Page

  • A22 - A22

Published By

Electronic International Standard Serial Number (EISSN)

  • 2326-6074

International Standard Serial Number (ISSN)

  • 2326-6066

Digital Object Identifier (DOI)

  • 10.1158/2326-6074.tumimm17-a22