# Exploiting Highly Networked CTL Epitopes to Achieve a Functional HIV Cure

> **NIH NIH DP2** · MASSACHUSETTS GENERAL HOSPITAL · 2022 · $499,920

## Abstract

ABSTRACT
The HIV/AIDS epidemic continues to have enormous medical, societal and economic implications worldwide.
While combination anti-retroviral therapy (cART) has greatly reduced the global burden of HIV, the ability of the
virus to establish a persistent reservoir within the body requires that HIV-infected individuals remain on lifelong
treatment. As a result, new modalities that can suppress the viral reservoir and thereby limit the requirement of
HIV treatment are greatly needed. Recent efforts have been focused on the induction of cytotoxic T cells
(CTLs) by therapeutic vaccines. However, the accumulation of CTL escape mutations in chronically infected,
cART-suppressed patients has greatly limited the ability of CTLs to successfully prevent viral rebound following
cART cessation. Thus, in order to counteract this viral escape, this DP2 proposal will focus on the study of CTL
responses to a new set of targets, known as `highly networked' epitopes, to determine whether they can form
the basis of a novel therapeutic CTL-based vaccine for HIV. These highly networked epitopes were identified
using an innovative approach known as structure-based network analysis. By applying network theory
principles to HIV protein structure data, the approach was able to identify a set of epitopes that are intolerant to
mutation, but which are also presented by a broad array of HLA alleles. Moreover, the targeting of highly
networked epitopes by functional CTL responses was shown to strongly distinguish individuals who naturally
control HIV from those with progressive disease. Thus, the goal now is to determine whether CTLs directed
against highly networked epitopes can also suppress viral outgrowth following cART cessation in the remaining
~99% of chronically-infected, cART-treated individuals. This will be accomplished by: (i) deep sequencing
highly networked epitopes in proviral DNA derived from peripheral blood and gastrointestinal tissue and (ii)
determining whether CTLs targeting highly networked epitopes can suppress latent virus outgrowth both ex
vivo and in a humanized mouse model. Demonstrating the effectiveness of CTL-mediated responses to highly
networked epitopes will confirm the value of the structure-based network analysis approach to guide the
rational design of a effective, therapeutic CTL-based vaccine for HIV.

## Key facts

- **NIH application ID:** 10475751
- **Project number:** 5DP2AI154421-03
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Gaurav Das Gaiha
- **Activity code:** DP2 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $499,920
- **Award type:** 5
- **Project period:** 2020-09-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10475751

## Citation

> US National Institutes of Health, RePORTER application 10475751, Exploiting Highly Networked CTL Epitopes to Achieve a Functional HIV Cure (5DP2AI154421-03). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10475751. Licensed CC0.

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