Engineering immunity : enhancing T Cell vaccines and combination immunotherapies for the treatment of cancer

Checkpoint blockade with antibodies against CTLA-4 or PD-1 has demonstrated that an endogenous adaptive immune response can be stimulated to elicit durable tumor regressions in metastatic cancer, but these dramatic responses are confined to a minority of patients¹-³. This outcome is likely due in part to the complex network of immunosuppressive pathways present in advanced tumors, which necessitates the development of novel therapeutics and combination immunotherapies to generate a counter-directed network of pro-immunity signals⁴-⁸. In Chapters 2 and 3 of this thesis, we describe methods for enhancing T cell priming against tumor antigens via covalent modification of molecular vaccines to enhance lymphatic drainage, serum stability, or cytosolic access to improve presentation on MHC class I. In Chapter 4, we demonstrate a combination immunotherapy that recruits a diverse set of innate and adaptive effector cells, enabling robust elimination of large tumor burdens that to my knowledge have not previously been curable by treatments relying on endogenous immunity. Maximal anti-tumor efficacy required four components: a tumor antigen targeting antibody, an extended half-life IL-2⁹, anti-ƯPD-1, and a powerful T-cell vaccine¹⁰. This combination elicited durable cures in a majority of animals, formed immunological memory in multiple transplanted tumor models, and induced sustained tumor regression in an autochthonous BRraf[superscript V600E]/Pten[superscript -/-] melanoma model. Finally, in Chapter 5, we show preliminary data on combination immunotherapies used to treat antigenically heterogeneous tumors. Taken together, these data define design criteria for enhancing the immunogenicity of molecular vaccines and elucidate essential characteristics of combination immunotherapies capable of curing a majority of tumors in experimental settings typically viewed as intractable.

Department dc:contributor.department

Massachusetts Institute of Technology. Department of Biological Engineering

Grantor dc:publisher

Massachusetts Institute of Technology

Year dc:date.issued

2017

Author dc:creator

• Moynihan, Kelly D. (Kelly Dare)

Advisor dc:contributor.advisor

• Darrell J. Irvine.

• Biological Engineering.

Statement dc:rights

• MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.

Licence dc:rights.uri

• http://dspace.mit.edu/handle/1721.1/7582

Language dc:language.iso

eng

Handle dc:identifier.uri

http://hdl.handle.net/1721.1/113960

OAI identifier oai:identifier

oai:dspace.mit.edu:1721.1/113960