NOV 08, 2019

Algorithm Predicts Response to HIV Immunotherapy

WRITTEN BY: Kara Marker

Blood samples from HIV patients produced the data necessary for two scientists to build a mathematical model for predicting how HIV patients will respond to an immune-boosting treatment originally designed for cancer patients. Researchers are hopeful that the new treatment will be especially beneficial for HIV patients struggling to manage their infection.

Depending on the type of test, an HIV diagnosis may come from identifying HIV in the blood or identifying antibodies and antigens associated with an HIV infection. HIV treatments are focused on preventing the viral infection from transitioning into acquired immunodeficiency syndrome (AIDS), helping those infected live normal lives. Antiretroviral therapy is a daily treatment used to treat HIV and prevent HIV-positive individuals from spreading the virus to others.

While modern medicine helps HIV patients avoid AIDS and live longer, HIV patients are also at an increased risk for cancer because of the toll taken by the immune system to fight HIV. T cells deteriorate over time, a phenomenon literally called “T cell exhaustion.” Immunotherapy initially developed for cancer patients refreshes exhausted T cells with checkpoint inhibitors, increasing their proliferation and enhancing their function.

In the present study, researchers took blood samples from HIV patients, triggered T cell activity with checkpoint inhibitors, and observed the aftermath. They used the data to build a mathematical model to predict how HIV patients at different stages of disease progression would respond to checkpoint inhibitor immunotherapy.

"We predicted how much the virus is reduced and how many CD4 T cells increase in the patient, which has a clinical significance,” explained Gennady Bocharov.

The results were largely positive, showing that most HIV patients will benefit from checkpoint inhibitor immunotherapy. Just how responsive the HIV patient is depends on how responsive the immune system is to the checkpoint inhibitors. Early predictions from the new mathematical suggest that HIV patients currently struggling to manage HIV may be particularly good candidates for this immunotherapy.

"Our general approach can be extended to other immunotherapies and is an important step forward towards personalized treatment strategies in infectious diseases and cancers,” Bocharov said.

Sources: Universitat Pompeu Fabra, PLoS Computational Biology, Centers for Disease Control and Prevention, HIV.gov