8th Annual Retrovirus Conference



Section by Andrew Zolopa, MD

“Virtual Phenotype” Predicts Virologic Outcome
Brendan Larder, PhD from Virco, UK presented a study that evaluated the predictive ability of the Virtual Phenotype (vPT) (abstract 524). Recall that the vPT is simply a "probabilistic estimate" of the actual phenotype (PT) that is derived from a patient’s genotype (GT). (Note: genotype drug resistance testing determines the presence of gene mutations that in other patients previously have been associated with resistance to the drug being tested; whereas, phenotype resistance testing measures the ability of a patient’s HIV strain to grow in the presence of each anti-HIV drug.) Virco maintains a database with thousands of clinical HIV isolates in which both the genotype and PT are determined. The vPT is determined by taking a patient’s GT and matching it with genotypes in the Virco database. The PTs that correspond to those matching genotypes are summed to give an "average PT" (average "fold-change" in susceptibility compared to a reference strain) for each of the drugs. The group at Virco has shown previously that the vPT estimates the actual PT quite well (correlations of 85-90%). The question that remained about the vPT is how well did it predict response to therapy. Dr. Larder evaluated patients from the VIRA 3001 trial in which response to therapy was measured. Using the "DAP analysis," he showed that the vPT was an independent predictor of response and appeared to be better then the GT in this particular study. Interestingly, he also showed that statistically, the vPT predicted VL response (to a level less than 50 copies per milliliter) better than the actual PT.

The vPT does have some advantages over GT tests and PT tests. GTs are complex and difficult for most clinicians to interpret, and new findings make it difficult for many clinicians to keep current. This technology may allow for an objective and quantifiable method to "interpret" the GT in a consistent manner. Second, since it is based on a GT test, it is likely (although not certain) to be cheaper and faster than PT tests. However, there are several caveats to note. First, this study does not prove that the vPT is superior to either genotyping or phenotyping in managing patients. The patients in VIRA 3001 trial were all experiencing "virological failure" with a first-line PI drug-based HAART regimen. Thus, these findings cannot be generalized to all clinical situations. Additional studies using different cohorts need to be evaluated including, ideally, cohorts from independent groups evaluated in a fashion that is "blinded" (patient information unknown by) to the investigators at Virco. Secondly, this study shows predictive capacity but not clinical utility of vPT. We need to see whether vPT-guided HAART leads to better outcomes for patients in a prospective trial compared to PT and or GT. The ACTG is planning such a study. Nonetheless, it appears that as the Virco database grows and the matching of submitted genotypes becomes more sophisticated that there is much promise in this technology. To read about related measurements called "Virtual Inhibitory Quotient" and "In Vivo Potency Index," see page 24.

Phenotypic "Break-Points" for Abacavir Defined
One of the shortcomings of phenotype (PT) tests is the lack of measured "cut-points" or "cut-offs" that define virologic response to a particular drug. Two important cut-points could be defined for each anti-HIV drug. First would be the point at which the response to the drug becomes "attenuated" (weakened, less), but still has some antiviral activity. The second point would be the one at which the drug is unlikely to have much meaningful activity (note this does not include the concept of decreased "fitness," see page 5). Defining these cut-points would require studies that evaluate the baseline phenotype and virologic response to each of the drugs currently used in clinical practice. One of the difficulties in establishing these cut-points is that most patients are treated with combinations of drugs, and therefore, teasing out the contribution that an individual drug makes to viral response is difficult.

In collaboration with researchers at ViroLogic, Randy Lanier, PHD used stored specimens from various studies in which ABC was added to stable background ART as single drug intensification. Therefore, any virologic response observed in these studies was related to ABC. In evaluating 24-week response, he showed that any abacavir phenotype of less than 4.5-fold was associated with a maximal response and that any fold-change greater than 7-fold was associated with "severely" limited or no response. Baseline phenotypes greater than 4.5-fold, but less than 7-fold decreased susceptibility were associated with a partial response. Whether these cut-points would be the same as the Virco PT has yet to be determined.

This is the specific kind of information clinicians require for each of the anti-HIV drugs in use today. With these clinically defined cut-offs, the advantage of phenotype tests over genotype tests might be fully realized as it would be much more difficult to define such cut-off points based upon mutation patterns.

In a separate presentation Dr. P. R. Harrington of Virco in Cambridge, UK reported phenotypic drug resistance cut-offs for 1,000 treatment-naïve patients in North America, Europe and South Africa (abstract 455). As a result, the phenotypic cut-offs for 14 FDA-approved anti-HIV drugs have been modified for the Antivirogram test. The old cut-offs were all 4-fold change. The new ones range from 2-fold to 10-fold change. All Antivirogram test results will now include the new cut-off levels in their reports.

So where do we stand today regarding resistance testing? At present genotype and phenotype drug resistance tests are commercially available, but not yet FDA-approved. The "virtual phenotype" shows promise as a clinically useful tool and should be evaluated further. Measures of "IQ" (inhibitory quotient" might eventually prove to be more useful clinically, but that would require ("PK") blood measurements for each patient be made a part of standard clinical practice. This would likely mean "timed" blood specimens, which adds to the cost and complexity of patient management. However, the potential benefits and costs should be studied further. Yet, the "IQ" measurement is only useful if one can alter the "PK" parameter of the drug. This can be done for many of the currently available single PI drugs with ritonavir "boosting", but may be less applicable for the other available anti-HIV drugs. Lastly, the full potential of phenotype drug resistance testing will only be realized when clinically defined cut-offs are defined for all the drugs used in practice.

The Evolving Story of NRTI Drug Resistance
At this Conference, there were several new studies that evaluated the problem of cross-resistance between AZT and D4T and among drugs of the NRTI drug class. Studies are increasingly showing that "TAMs" (thymidine analog mutations) that occur with AZT do confer some cross-resistance to d4T (abstracts 437, 444, others).

Resistance with Kaletra and Amprenavir
The primary mutation patterns associated with resistance to Kaletra were presented by Dr. B. Bernstein of Abbott (abstract 453). Patients from Study M98-863 were treatment-naïve (no previous therapy). In this large, randomized study of 653 patients, the 48 week efficacy of Kaletra based HAART was compared to a NFV (nelfinavir, Viracept, PI drug)-based regimen. Of the subjects randomized to the LPV/RTV regimen, 58 experienced virologic rebound (greater than 400 copies per milliliter). In 37 of these subjects, genotypic resistance results were available and there was no major PI drug-associated resistance mutation identified. However, resistance to 3TC (lamivudine, Epivir, NRTI drug) was identified in 15 of 37 (41%). In contrast, 33% (n=25) of HIV isolates from patients with viral rebound in the NFV arm did have genotypic NFV resistance, and 82% had 3TC resistance. Adherence (measured by pill counts) was similar in both groups, although blood levels of Kaletra to document adherence were not reported. Of the 25 NFV failures with genotypic resistance and whose samples were available, 18 had the classic NFV mutation D30N, 6 had the L90M, and 1 had both.

Dr. S. Brun of Abbott reported in a separate presentation that HIV isolates with median 44-fold decreased susceptibility to Kaletra (resistance) were only 6-fold resistant to amprenavir (APV, Agenerase, PI drug) (abstract 452). Three patients who had not previously taken saquinavir (SQV, Fortovase, PI drug) remained sensitive to SQV. In a related analysis, phenotypic cross-resistance patterns between Kaletra and other PI drugs were evaluated. The results showed that resistance to Kaletra most closely correlated with resistance to RTV and indinavir (Crixivan, PI drug) and less so to APV and SQV. Whether or not APV or SQV can be used to successfully control viral replication after resistance to Kaletra develops has yet to be determined. Abbott reported on 1 patient with 25-fold resistance to Kaletra after failing in study, but remained susceptible to APV (1.0 fold). Subsequent treatment with APV/RTV regimen suppressed viral load to <400 copies/ml after 12 weeks follow-up. Two virus samples from patients failing Kaletra were sensitive to tipranavir.

Drug Resistance Testing: Impact in Prospective Studies
The final results of the HAVANA trial were presented by Dr. C. Tural of Badalona, Spain (abstract 434). Investigators reported that genotype resistance testing (TruGene, VGI), in addition to "expert advice" improve virologic response n this "factorial-designed" study in which patients could receive genotype testing or not, with or without expert advice. This study highlights the importance of being able to properly interpret genotypic resistance tests. Patients receiving “expert advice” were more likely to reach undetectable than patients not receiving expert advice. Expert advice was given from a committee of virologists and clinicians.

There are now more than a half dozen randomized, controlled studies evaluating the impact of drug resistance testing on virologic outcomes compared to "standard of care" (i.e., no resistance testing). Most of these studies have shown a modest (0.5 log or 3-fold) benefit in short-term virologic response among the groups receiving the resistance tests (either genotype or phenotype). To these studies we now add the ARGENTA trial from Italy, as presented by Dr. A. De Luca of Catholic University in Rome (abstract 433).

In this study, patients with ongoing HIV viremia while taking ART were randomized to receive genotype (TruGene, VGI, Visible Genetics) versus standard of care without the benefit of resistance testing. Both groups received expert advice on the new ART regimen. A total of 174 patients were randomized. The median baseline CD4 count was approximately 260 cells per microliter with a viral load of 4.2 log (15,840) copies per milliliter. Approximately half of the patients were taking their first ART regimen, with a quarter taking their 2nd one and another quarter taking their 3rd or higher ART regimen. At baseline, the genotype group had slightly more evidence of drug resistance. Despite these differences, the results were that the genotype arm achieved a significantly better response at month 3, with 27% having an undetectable viral load (limit of 500 copies per milliliter) versus 11% in the SOC ("Standard Of Care" arm, strict ITT analysis, including all patients). At month 3, genotype testing was made available to the SOC arm for those who failed to achieve at least 1-log (10-fold) decline in VL or with a level at least 500 copies per milliliter.

Self-reported adherence appeared to play a role in response rates. Those with good adherence and genotype testing had the best response at month 3 (33% undetectable, same limit), followed by SOC arm patients with good adherence (26% response), and then by the genotyped patients with poorer adherence (18%), and finally those in the SOC arm who reported poor adherence (7%). In "multivariate" statistical analysis, independent predictors of virologic response were: genotype testing; adherence; having a prior history of a viral load less than 500 copies per milliliter; and being on the 1st or 2nd ART regimen.

“Quality Assurance” Issues with Genotype Resistance Testing
There were 2 quality assurance studies presented at the Conference about genotype resistance testing (abstracts 251, 252). The results indicated that at least with the laboratories involved in these comparisons, the genotype results are reasonably comparable from lab to lab. Most of the counted discrepancies at the "amino acid level" (protein building blocks) were detected as mixtures by the labs and that the mixture reported did contain the mutation detected by the reference lab. Overall, it appears that genotyping labs are getting more consistent results as experience grows with these technologies. However, we must await the results of the "ENVA 3 evaluation" for a more definitive comparison of inter-laboratory consistency with genotype resistance testing.

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