Identifying potential biomarkers of response to CCR5Δ32 HSCT in HIV infection

While HIV can be effectively suppressed to a chronic, mostly asymptomatic infection with combination antiretroviral therapy (cART), a cure is still needed. Hematopoietic stem cell transplantation (HSCT) from HIV-resistant donors has shown promise and has resulted in HIV remission in five patients. However, this treatment strategy does not guarantee HIV remission; six other patients who received a similar transplant had poor outcomes and died within a year of treatment. These different outcomes may be due to inter-individual differences in HIV infection dynamics that result in heterogeneity of therapeutic responses to HSCT. Using a previously published mechanistic model of HIV infection and virtual populations calibrated from patient data, we performed simulations to understand how different parameters in the model can influence the observed heterogeneity in therapeutic outcomes across virtual patient populations. Our simulations confirmed that discontinuation of cART, without HSCT, always leads to viral rebound, and that time to rebound differs across patients due to the interindividual variability (IIV) in underlying infection dynamics. Extending the duration of cART only slightly increased the predicted median time to rebound and its variance. By contrast, HSCT followed by cART cessation led to HIV remission, but only for a subset of the virtual patients. The proportion of patients predicted to go into remission depends directly on the ratio of donor to host cell immune cells in the post-HSCT chimeric immune system. Of the mechanistic model parameters, no single parameter determined whether a patient was a responder or a non-responder; rather, the interactions between multiple model parameters were crucial in driving treatment responses. In contrast, virtual equivalents of clinically accessible observations, e.g. viral load and cell populations at specific times, were shown to be better predictors than mechanistic model parameters in separating patients into non-responding (viral rebound) and responding (no rebound) clusters.