This proposal presents a five year research career development program focused on the study of CTL responses to highly ?networked? epitopes as a new set of invariant targets to include in a therapeutic CTL- based vaccine for HIV-1. The candidate is currently an Instructor of Medicine at Harvard Medical School and the Division of Gastroenterology at Massachusetts General Hospital. The outlined proposal builds on the candidate's previous research experience in HIV-1 immunology and biochemistry where he defined CTL epitopes that carry structural and functional constraints, and which are preferentially targeted by individuals who naturally control HIV-1. He is now positioned, under the guidance of his mentor Dr. Bruce Walker at the Ragon Institute of MGH, MIT and Harvard, to determine whether these epitopes could be valuable CTL targets in treatment-suppressed individuals. The proposed experiments and didactic work will position the candidate with a unique set of skills that will enable him transition to independence as a physician-scientist in the field of prophylactic and therapeutic HIV-1 vaccinology. The HIV/AIDS epidemic continues to have enormous medical, societal and economic implications worldwide. While combination anti-retroviral therapy (cART) has helped to greatly reduce the global burden of HIV, the ability of the virus to establish a persistent latent reservoir requires lifelong treatment for HIV-infected individuals. As a result, new modalities that can suppress or eliminate the viral reservoir and thereby limit HIV treatment duration are greatly needed. Recent efforts have been focused on the induction of cytotoxic T cells as potential targets for therapeutic vaccines. However, the accumulation of CTL escape mutations in chronically infected cART-suppressed patients limits the ability to successfully prevent viral rebound following cART cessation. During his postdoctoral fellowship, the candidate developed a new approach known as structure-based network analysis that identifies specific epitopes, presented by a broad array of HLA alleles, which are intolerant to mutations. He also demonstrated that the targeting of highly ?networked? CTL epitopes is able to distinguish individuals who spontaneously control HIV-1 from those with progressive disease. The candidate now hypothesizes that CTL mediated immune responses directed against highly ?networked? epitopes can also suppress viral outgrowth following cART cessation in chronically infected cART-treated individuals. This hypothesis will be tested through the following aims: 1) Perform deep mutational scanning of highly networked epitopes in proviral DNA, 2) Assess whether CTLs targeting highly networked epitopes can suppress viral outgrowth from cART-treated patients and 3) Develop an adenovirus (Ad) vector encoding multiple highly networked epitopes and assess its ability to induce CTL responses in vivo. Effective CTL- mediated responses to highly networked epitopes identified by structure-based network analysis may limit viral rebound from latently infected CD4+ T cells and thereby may guide the rational design of a therapeutic CTL- based vaccine for HIV-1.

Public Health Relevance

The proposed research is relevant to public health due to the significant and unmet need of an HIV-1 cure. The project will apply a new approach known as structure-based network analysis and evaluate whether predicted epitopes can serve as targets for inclusion in a rationally designed, therapeutic CTL-based vaccine for HIV-1. Thus, the proposed work is relevant to the NIH's mission to seek and apply knowledge to lengthen life and reduce illness.

Agency
National Institute of Health (NIH)
Institute
National Institute of Allergy and Infectious Diseases (NIAID)
Type
Clinical Investigator Award (CIA) (K08)
Project #
5K08AI140960-02
Application #
9906843
Study Section
Acquired Immunodeficiency Syndrome Research Review Committee (AIDS)
Program Officer
Lacourciere, Gerard
Project Start
2019-04-05
Project End
2024-03-31
Budget Start
2020-04-01
Budget End
2021-03-31
Support Year
2
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02114