Better Assessment Of Drug Resistance May Improve Treatment Of People With HIV
By April Clayton and Courtney McQueen

Results from a recent small Spanish study indicate that a more sensitive technique for detecting drug resistance, called deep sequencing, more accurately identified drug resistance in HIV-positive individuals who had previously been treated with antiretrovirals and were suffering from drug failure.

“Our study suggests that more sensitive genotypic HIV drug resistance assays, such as deep HIV sequencing, may help clinicians design antiretroviral treatment combinations better suited for [patients] infected with multidrug-resistant viruses,” said Dr. Roger Paredes, a key investigator of the study, in correspondence with The AIDS Beacon.

“Deep sequencing may help [clinicians] choose more effective drugs as well as avoid antiretrovirals to which, in fact, the virus is resistant,” he added.

Drug resistance is one of the main causes of antiretroviral drug failure. HIV-positive individuals are considered resistant to an anti-HIV drug if their viral load (amount of HIV in the blood) does not remain low after drug therapy or testing confirms the presence of an HIV strain that is resistant to one or more classes of antiretrovirals.

Resistance testing examines the genes of the HIV in a person’s blood to detect whether the virus has mutations that make it resistant to particular drugs. Previous studies have indicated that even low levels of drug-resistant HIV increase the chances of treatment failure, although those studies have primarily involved previously untreated people with HIV (see related AIDS Beacon news)

The authors of this study investigated whether an enhanced form of resistance testing, known as deep sequencing, could provide better assessments of drug resistance in heavily pre-treated HIV patients when compared to the more traditional form of resistance testing, called population sequencing.

Deep sequencing detects the same mutations as population sequencing but is more sensitive, so it can detect mutations present in 1 percent or more of the HIV circulating in a person’s blood. Population sequencing can usually only detect mutations present in 15 percent or more of the HIV.

Seven HIV-positive individuals participated in the study. Participants had taken a median of 15 antiretroviral drugs for a median of 13 years. The average age of the participants was 44, and five of the seven were male.

All participants had shown resistance to the three main classes of antiretrovirals: nucleoside-reverse transcriptase inhibitors (NRTIs), protease inhibitors, and non-nucleoside reverse transcriptase inhibitors. In addition, all participants had failed salvage therapy with at least one of the following: Prezista (darunavir), Aptivus (tipranavir), Intelence (etravirine), or Isentress (raltegravir).

Results showed that deep sequencing detected all of the drug resistant mutations found by population sequencing, plus additional resistance mutations in six of the seven participants.

In particular, deep sequencing improved the assessment of resistance to Intelence, showing higher risk of resistance in two patients with signs of failing Intelence-based therapy. The technique also slightly modified assessments of HIV resistance against Sustiva (efavirenz), Crixivan (indinavir), and NRTIs in various participants to indicate higher risks of resistance, compared to the population sequencing.

The two methods identified the same participants as having drug resistance to Aptivus and Isentress, and the deep sequencing confirmed that four of five participants who had failed Isentress-based antiretroviral therapy did not show resistance to the drug and could potentially take it again.

Dr. Paredes stated that the researchers are currently conducting a larger study to investigate whether the use of deep sequencing can lead to improved treatment outcomes for treatment-experienced patients starting salvage therapy with Norvir (ritonavir)-boosted protease inhibitors, Intelence, or Isentress.

For more information, please see the study in PLoS One.

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