ArticleJournal of statistical mechanics (Online)2013
Mathematical modeling of escape of HIV from cytotoxic T lymphocyte responses.
Article in Journal of statistical mechanics (Online), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 37 citations in OpenAlex.
- Modeling the Interplay Between Viral and Immune Dynamics in HIV: A Review and Mrgsolve Implementation and Exploration.Clinical and translational science · 2025Review
- A participant-derived xenograft model of HIV enables long-term evaluation of autologous immunotherapies.The Journal of experimental medicine · 2021Article
- Impact of Oseltamivir Treatment on Influenza A and B Virus Dynamics in Human Volunteers.Frontiers in microbiology · 2021Article
- Dynamics of virus and immune response in multi-epitope network.Journal of mathematical biology · 2018Article
- Modeling the immune response to HIV infection.Current opinion in systems biology · 2018Article
- Tracking HIV-1 recombination to resolve its contribution to HIV-1 evolution in natural infection.Nature communications · 2018Article
- Clonal interference can cause wavelet-like oscillations of multilocus linkage disequilibrium.Journal of the Royal Society, Interface · 2018Article
- Time Intervals in Sequence Sampling, Not Data Modifications, Have a Major Impact on Estimates of HIV Escape Rates.Viruses · 2018Article
- Kinetics of HIV-Specific CTL Responses Plays a Minimal Role in Determining HIV Escape Dynamics.Frontiers in immunology · 2018Article
- Global properties of nested network model with application to multi-epitope HIV/CTL dynamics.Journal of mathematical biology · 2017Article
- Within-Epitope Interactions Can Bias CTL Escape Estimation in Early HIV Infection.Frontiers in immunology · 2017Article
- Relative rate and location of intra-host HIV evolution to evade cellular immunity are predictable.Nature communications · 2016Article
- Investigating the Consequences of Interference between Multiple CD8+ T Cell Escape Mutations in Early HIV Infection.PLoS computational biology · 2016Article
- Broad CTL Response in Early HIV Infection Drives Multiple Concurrent CTL Escapes.PLoS computational biology · 2015Article
- Antibody escape kinetics of equine infectious anemia virus infection of horses.Journal of virology · 2015Article
- Modeling T cell responses to antigenic challenge.Journal of pharmacokinetics and pharmacodynamics · 2014Review
- Modeling viral evolutionary dynamics after telaprevir-based treatment.PLoS computational biology · 2014Article
- Reliable reconstruction of HIV-1 whole genome haplotypes reveals clonal interference and genetic hitchhiking among immune escape variants.Retrovirology · 2014Article
- Pathogen evolution and the immunological niche.Annals of the New York Academy of Sciences · 2014Article
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Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
Abstract
Human immunodeficiency virus (HIV-1 or simply HIV) induces a persistent infection, which in the absence of treatment leads to AIDS and death in almost all infected individuals. HIV infection elicits a vigorous immune response starting about 2-3 weeks post infection that can lower the amount of virus in the body, but which cannot eradicate the virus. How HIV establishes a chronic infection in the face of a strong immune response remains poorly understood. It has been shown that HIV is able to rapidly change its proteins via mutation to evade recognition by virus-specific cytotoxic T lymphocytes (CTLs). Typically, an HIV-infected patient will generate 4-12 CTL responses specific for parts of viral proteins called epitopes. Such CTL responses lead to strong selective pressure to change the viral sequences encoding these epitopes so as to avoid CTL recognition. Indeed, the viral population "escapes" from about half of the CTL responses by mutation in the first year. Here we review experimental data on HIV evolution in response to CTL pressure, mathematical models developed to explain this evolution, and highlight problems associated with the data and previous modeling efforts. We show that estimates of the strength of the epitope-specific CTL response depend on the method used to fit models to experimental data and on the assumptions made regarding how mutants are generated during infection. We illustrate that allowing CTL responses to decay over time may improve the fit to experimental data and provides higher estimates of the killing efficacy of HIV-specific CTLs. We also propose a novel method for simultaneously estimating the killing efficacy of multiple CTL populations specific for different epitopes of HIV using stochastic simulations. Lastly, we show that current estimates of the efficacy at which HIV-specific CTLs clear virus-infected cells can be improved by more frequent sampling of viral sequences and by combining data on sequence evolution with experimentally measured CTL dynamics.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.