Research Briefs

By Andreas von Bubnoff

Predicting the Antiviral Activity of Three-drug Combinations in HAART

Highly active antiretroviral therapy, or HAART, typically combines three antiretroviral drugs (ARVs) as a first-line treatment for HIV infection. It is a very effective way to keep HIV replication under control. So effective, in fact, that the best drug combinations suppress HIV to undetectable levels in most individuals.

What remains relatively unclear is why some but not other drug combinations work. Further, there is still no systematic method for determining which drugs to combine to get the most effective treatments.

Robert Siliciano, a professor of medicine at Johns Hopkins University School of Medicine, and his colleagues seem to have solved both problems. In a paper published in Nature Medicine, they describe a model that predicts how much HIV inhibition might be achieved by any three-drug combinations of the 19 most commonly prescribed ARVs (1).

To create this model, they first measured in an in vitro assay how much each of the 19 ARVs inhibit a single round of HIV replication. They did this for several different concentrations of each drug and plotted out their results in a graph—generating a dose-response curve that describes how viral inhibition varies with each concentration of every studied drug. They found that the shape of the curves differed between the different ARVs. This highlights the importance of using dose-response curves in determining antiviral activity, Siliciano says, because these ARV-specific differences would likely have been missed by the way researchers have previously used to describe antiviral activity: by only focusing on one drug concentration, the so-called IC50, which results in 50% viral inhibition.

Next, the researchers determined the dose-response curves for almost all possible two-drug combinations of those 19 drugs, and compared them with the predictions of the relatively simple mathematical models researchers currently use to predict the potential efficacy of drug combinations. They found that, in more than 40% of the cases, these existing models of combined drug effects were unable to correctly predict their experimental results.

According to Siliciano, these existing models are too simplistic because they are based on two extreme scenarios. One model assumes that the drugs to be combined target the same process in the HIV life cycle, in which case their pairing would have only an additive effect; the other assumes that two drugs target completely different processes in the HIV life cycle, in which case their combined effect should be multiplicative. Siliciano and his colleagues found, however, that in more than 40% of cases, the drug pairs they measured had effects that did not precisely fit either of these scenarios. “The existing models were so bad that we developed our own,” says Siliciano.

To do so, he and his colleagues used the results of their dose-response measurements to determine just where between the extremes the effects of various drug pairs really fell. They then used this information to calculate the inhibitory potential of three-drug combinations, by pulling together what they knew about the inhibitory effects of the drugs in any given three-drug combination alone and their pairwise combinations.

When they tested their predictions for 10 three-drug combinations in their in vitro assay, they found that this predicted HIV inhibition much better than the existing models. Their predictions also correlated very well with the outcomes of 47 clinical trials of three-drug combination regimens.

Before this study, there was no good way to predict the activity of three-drug combinations, says Ruy Ribeiro, a research scientist at the Los Alamos National Laboratory who models HIV treatment and wrote a commentary on the study in the same issue of Nature Medicine. “This gives some sign posts to what drug combinations to try in clinical trials,” he says. The new approach could also make it easier for researchers to identify less expensive drug regimens for use in developing countries, Ribeiro adds, allowing them to devise regimens that cost less but have potentially equivalent effects.

Siliciano, for his part, hopes to mainly use the new approach to improve management of individuals with drug resistance. This should now be possible, he says, by taking into account another recent finding by his group that suggests that resistance mutations in HIV can alter the shape of the dose-response curve (2).

1. Nat. Med.18, 446, 2012
2. Proc. Natl. Acad. Sci.108, 7613, 2011

CD4+ T Cells Can Control Viral Load by Directly Killing HIV-infected Cells

CD4+ T cells are central players in the body’s immune response. Often called “helper” cells, they orchestrate the assault on invading pathogens: They stimulate the development of antibodies in B cells, and send signals to CD8+ T cells, which detect and destroy other infected cells, making them better killers and stimulating the formation of memory cells. But CD4+ T cells are also the primary targets of HIV, which is why they are not believed to play a leading role in controlling infection by that virus. Instead, CD8+ T cells are thought to be the primary agents of HIV suppression, deploying so-called “death” molecules such as perforin, which pops open infected cells, and granzyme B, which forces them to commit suicide.

But helper T cells have recently also been found to play a somewhat more violent part in controlling infections by other viruses, such as influenza. Far from being solely coordinators and assistants, helper T cells participate directly in the killing of infected cells in such cases.

This made Ragon Institute researcher Hendrik Streeck and his colleagues curious about whether some CD4+ T cells might be similarly disposed in HIV-infected people. In a recent paper, they report that the answer, at least in some cases, appears to be yes (1).

Streeck and his colleagues looked at blood samples from 11 volunteers, starting at the time when they had just been infected with HIV. All of them had roughly the same viral load until about two months after they contracted the infection. But four months after that, six of the individuals suppressed their set-point viral load at a level 10-times lower than that of the other five.

Two months after infection—before one group developed a lower set-point viral load—the CD8+ T-cell responses were virtually identical in the two groups, but the researchers already found distinct differences in the HIV-specific CD4+ T-cell responses of the people who would later control their infections more effectively. These individuals had a much larger fraction of HIV-specific CD4+ T cells that carried granules containing granzyme A, a death molecule related to granzyme B, which CD8+ T cells use to kill infected cells. What’s more, high granzyme A levels in HIV-specific CD4+ T cells correlated with about a one-year delay in the onset of disease progression.

This suggested that, like CD8+ T cells, CD4+ T cells can kill HIV-infected cells. In subsequent experiments, the researchers found that, indeed, HIV-specific CD4+ T cells taken from the people who better controlled the virus recognized and killed HIV-infected macrophages in vitro. They also found that HIV-specific CD4+ T cells could inhibit HIV replication in infected CD4+ T cells in vitro. This inhibition did not occur when the MHC class II receptor HLADR was blocked with an antibody, which is consistent with the fact that CD4+ T cells are activated by peptides presented by MHC class II receptors on the surface of antigen-presenting cells.

Together, this suggests a model where HIV-infected cells such as CD4+ T cells or macrophages present HIV peptides via two pathways: through MHC class I molecules to activate CD8+ T cells, and through MHC class II molecules to activate CD4+ T cells (see figure, below). This means, Streeck says, that even if the virus inhibits one pathway—for example by downregulating MHC class I molecules or by developing escape mutations—effective recognition and lysis of the infected cell could still be achieved through the other pathway that involves MHC class II and CD4+ T cells.

Model for Dual-pathway Killing by CD4+ and CD8+ T Cells   

HIV-1 can establish infection within cells that express both MHC class I and class II molecules, such as antigen-presenting macrophages. Antigen presentation by these molecules is critical for recognition by circulating cytolytic CD4+ and CD8+ T cells. Even if the virus were to inhibit recognition through one pathway—for instance by downregulating MHC class I molecules or via the acquisition of escape mutations—effective recognition and lysis of the infected cell (via secretion of molecules like perforin or granzyme as indicated by the pink and yellow spheres) could still be achieved through the other pathway. Adapted fromExpert Review of Vaccines, December 2010, Vol. 9, No. 12, Pages 1453-1463 with permission of Expert Reviews Ltd.

Streeck says these results are consistent with a recently published study that suggests that in the RV144 HIV vaccine trial—the only one so far that has provided evidence of efficacy—the modest protection observed in vaccinated volunteers was in part associated with HIV-specific CD4+ T cells that expressed certain molecular markers that indicate that they were able to kill infected cells (2). Together with his recent study, Streeck says, this suggests that the induction of a CD4+ T-cell response by a vaccine might translate into viral load control and also into protection from infection.

Nichole Klatt, a research fellow in Jason Brenchley’s laboratory at the National Institute of Allergy and Infectious Diseases, who co-wrote a commentary on the study in the same issue of Science Translational Medicine, calls the findings “very important.” Measuring HIV-specific cytolytic CD4+ T cells during acute infection, she suggests, could help determine disease progression. She adds that such cells may also be a valuable target for vaccination strategies. Klatt notes, however, that because CD4+ T cells are also HIV’s primary target, any vaccine that induces their proliferation could also serve up more host cells for the virus. “Further studies should be performed in the SIV model,” says Klatt, to assess the safety of expanding HIV-specific CD4+ T cells to ensure that there are no “increased infection rates due to increased targets.”

1. Sci. Transl. Med. 4, 123ra25, 2012
2. J. Immunol. 188, 5166, 2012