Genotypic tropism testing: evidence-based or leap of faith?
Harrigan, P Richarda; Geretti, Anna Mariab
aBC Centre for Excellence in HIV/AIDS, Vancouver, British Columbia, Canada
bUCL Medical School and Royal Free Hampstead NHS Trust, London, UK.
Received 1 August, 2010
Revised 12 September, 2010
Accepted 15 September, 2010
Correspondence to Dr A.M. Geretti, Department of Virology, Royal Free Hospital, Pond Street, London NW3 2QG, UK. E-mail: email@example.com
Tropism testing in antiretroviral therapy
HIV-1 tropism is largely determined by the specific chemokine co-receptor used in conjunction with the CD4 receptor for entry into target cells. In the early 1990s, the discovery of co-receptor use significantly advanced our understanding of virus–host interactions and disease pathogenesis in HIV infection. Work over the following decade identified a novel class of antiretroviral drugs that, uniquely among available agents, act on the host cell rather than the virus. Although HIV-1 can use several co-receptors for entry, the vast majority of HIV-1 strains can be categorized as :
1. R5: using only CCR5 as a co-receptor
2. X4: using only CXCR4 as a co-receptor
3. Dual-tropic or R5/X4: capable of using both CCR5 and CXCR4, although one co-receptor may be favoured.
Throughout infection, the detection of only R5 virus in plasma is most common. CXCR4-using variants are more likely to be detected in patients with advanced disease and low CD4 cell counts, as either R5/X4 or mixed populations of R5 and X4 strains. The detection of exclusively X4 virus in clinical samples is rare . These properties have been exploited in the development of antiretroviral agents that target the interaction between the virus and the CCR5 co-receptor, including small-molecule CCR5 antagonists and monoclonal antibodies. Maraviroc is the only small-molecule CCR5 antagonist currently licensed for use in patients infected with R5 HIV-1 , and is approved for treatment-experienced patients in Europe and both treatment-naive and treatment-experienced patients in the USA. The development of vicriviroc was halted in July 2010 due to its modest performance in phase 3 trials of treatment-experienced patients (Table 1)  and in a phase 2 trial of treatment-naive patients receiving vicriviroc or tenofovir/emtricitabine with ritonavir-boosted atazanavir . Promising results have recently been reported from phase 1 and phase 2 studies of the dual CCR5/CCR2 antagonist TBR-652 [6,7]. In addition, PRO140, a monoclonal antibody that targets the CCR5 co-receptor, is currently in phase II clinical trials . PRO140 is administered by subcutaneous injection every other week and offers promise as a potent and durable treatment option. Clinical trials of CCR5 antagonists have confirmed the specificity of the antiviral effect for R5 virus (Table 1) [4,9–15]. Since these agents appear to induce little viral load suppression in patients harbouring CXCR4-using variants as the dominant viral species in plasma [12,15], a tropism test is essential prior to CCR5 antagonist use in order to optimize the selection of treatment candidates.
Which assay for tropism testing?
HIV-1 tropism may be observed phenotypically or genotypically, and both methods have their own advantages and drawbacks. Phenotypic tropism tests (PTT) typically produce a recombinant virus containing HIV-1 envelope sequences amplified from the patient's plasma, and observe the virus ability to infect reporter cell lines that express the CD4 receptor with either CCR5 or CXCR4 . The most widely applied phenotypic test to date has been the commercial Trofile assay (Monogram Biosciences, San Francisco, California, USA), which was used to screen treatment-naive and treatment-experienced patients entering pivotal clinical trials of CCR5 antagonists (Table 1) [4,9,11–14]. The Trofile assay showed a lower limit of sensitivity of approximately 10% for consistent detection of CXCR4-using virus in a clonal mixture of R5 and X4 variants . In summer 2008, a modified version of the test known as the enhanced sensitivity Trofile assay (ESTA) superseded the original Trofile as a screening tool. ESTA has a nominal lower limit of sensitivity of 0.3% for detecting CXCR4-using virus within clonal mixtures , but sensitivity with clinical samples varies . ESTA was found to more accurately identify patients likely to show a virological response to maraviroc in a post-hoc re-analysis of the MERIT trial of maraviroc versus efavirenz in treatment-naïve patients [11,19], which used the original Trofile assay to screen patients for inclusion (Table 1). ESTA also showed a marginal benefit over Trofile in a post-hoc re-analysis of the ACTG 5211 trial of vicriviroc in treatment-experienced patients .
There are a number of factors limiting the use of ESTA in routine patient care. Testing is only performed in a central laboratory in California, and is expensive (list price US$1960, per test and transport cost, although it may be available through agreements with ViiV Healthcare at a lower price) and labour-intensive, with a turnaround time of about 4 weeks. The test has a relatively high failure rate  reflecting its complexity and stringent sample collection, storage and transport requirements . A minimal volume of 3 ml of plasma is recommended, which often poses a problem for retrospective testing of stored samples and in children. In addition, there is a minimum viral load requirement of 1000 copies/ml for reliable amplification , thus excluding this approach in a proportion of patients, such as those with early virological failure or those with an undetectable viral load who may be seeking to switch treatment for tolerability reasons. To circumvent this limitation, use of proviral DNA recovered from peripheral blood mononuclear cells (PBMCs) is being explored. Whereas the preliminary findings indicate that proviral DNA is suitable for testing by ESTA , clinical validation data are awaited.
HIV-1 tropism may also be inferred from a genotypic analysis of HIV-1 envelope proteins. Genotypic tropism testing (GTT) offers the advantage of platform portability, low cost (approximately 150 and up to 250 Euro per test), and rapid turnaround. The tests are based on observations that there are certain quantifiable differences between the sequences of R5 and X4 envelopes, which may be incorporated into a predictive algorithm. The determinants of tropism are thought to lie mainly (if not exclusively) in the HIV-1 gp120 V3-loop region, and the amino acid sequence of this region can therefore be used to infer likely co-receptor usage [22–24]. A number of algorithms based on bioinformatic theory, such as geno2pheno[co-receptor] (http://coreceptor.bioinf.mpi-inf.mpg.de/) and position-specific scoring matrices (PSSMs) (http://indra.mullins.microbiol.washington.edu/webpssm/), have been developed to facilitate this prediction. These compare the amino acid sequence of the test sample with sequences known to be associated with X4 or R5 tropism and the results provide an indication of how likely the virus is to use the CXCR4 co-receptor. The algorithms have become increasingly sophisticated over time; for example, the geno2pheno[co-receptor] algorithm allows clinical data (most importantly the nadir CD4 cell count, but also viral load and CD8 cell count) to be included in the model, which may improve predictions [25–27]. Since genotypic resistance testing is already routinely available in many centres, GTT is likely to be more broadly available, in addition to being faster and cheaper than PTT. As well as plasma RNA, proviral DNA amplified from PBMC can be used to determine tropism using genotypic analysis, thus removing the viral load threshold, and making all patients potentially eligible for testing [26–28]. Clinical data in support of this approach are becoming available from small cohort studies [29,30].
Is there sufficient evidence to support genotypic tropism testing in routine practice?
One obvious limitation of GTT is that in its common applications it uses population (‘bulk’) sequencing to produce a consensus sequence from dominant strains within the viral quasispecies. The technique has a lower limit of detection of approximately 10–20%, and is therefore unable to detect CXCR4-using variants if present at low frequency. This limitation can be only partially circumvented by increasing the number of replicate sequences produced from each sample. As also true of PTT, the sensitivity of GTT for low-frequency variants is influenced by the size of the input and declines with diminishing levels of viral load. Many studies evaluating GTT have compared its performance using Trofile or ESTA as a reference, which has obvious limitations as neither Trofile nor ESTA can be regarded as a gold-diagnostic standard. Initial comparative studies did not look promising . Subsequently, concordance between phenotypic and genotypic analyses has increased as the genotypic tests have evolved to the extent that good to excellent agreement with Trofile is now commonly seen [32,33], and good to excellent concordance with ESTA has also been shown in some studies [20,26,34]. However, the most relevant analysis is not measuring concordance between tropism assays, but rather observing how effective an assay is at predicting virological responses to CCR5 antagonist use.
The availability of stored plasma samples from patients enrolled in clinical trials of maraviroc has allowed two retrospective evaluations of GTT in a large number of patients. Importantly, these analyses allow both a comparison of the tropism results given by PTT and GTT, and a comparison of clinical outcomes. The results have demonstrated that GTT, performed using plasma RNA to generate triplicate bulk V3-loop sequences from each patient, and interpreted according to predefined parameters, is similarly predictive of virological outcomes to Trofile in treatment-experienced patient , and equally predictive to ESTA in treatment-naive patients . The first analysis used 1916 screening plasma samples from treatment-experienced patients within the MOTIVATE-1 and MOTIVATE-2 trials  and the sister safety study A4001029 (Table 1) . Importantly, samples from patients who entered in the MOTIVATE trials were screened as R5 by Trofile, whereas those from patients who entered A4001029 were screened as CXCR4-using (‘non-R5’). Prediction of tropism by GTT using the geno2pheno[co-receptor] and PSSM interpretation algorithms was found to have relatively poor sensitivity but high specificity for predicting non-R5 virus relative to Trofile. However, among 1164 patients with clinical outcome data, the phenotypic and genotypic tests had similar ability to predict long-term virological responses . The observation was confirmed in sub-analyses, including evaluation of virological responses according to number of active drugs in the background regimen. Using a similar approach with over 700 plasma samples from treatment-naive patients enrolled in the MERIT trial (Table 1), the post-hoc analysis previously performed with ESTA [11,19] was repeated using GTT . As also seen with ESTA, the genotypic method was found to improve the screening of drug-naïve patients relative to the original Trofile. By excluding patients with non-R5 virus that had been classified as R5 by Trofile, and who would have been ineligible for study entry had the newer assay – either ESTA [11,19] or GTT  – been available, the number of virological failures on maraviroc was reduced. Virological responses (proportion with viral load <400 copies/ml and proportion with viral load <50 copies/ml at week 48) fell within the predefined noninferiority thresholds compared to efavirenz. Importantly, in the two retrospective analyses of GTT, patients with discordant PTT/GTT results did not show a large preferential direction of response [35,36].
An increasing number of prospective cohort studies in both treatment-naive and treatment-experienced patients starting maraviroc also indicate that GTT performed by bulk V3-loop sequencing and interpreted using the geno2pheno[co-receptor] algorithm is reliable in terms of positive predictive value [29,30,37]. These findings have led to the consensus that GTT is suitable for use in routine clinical practice, and guidelines which endorse the role of GTT (performed in triplicate by bulk sequencing and interpreted according to defined parameters) have been recently developed by national and European consensus panels (given below) [38–40].
Recommendations regarding the use of HIV-1 tropism testing in routine clinical practice (adapted from reference ):
1. HIV-1 tropism testing should be performed prior to CCR5 antagonist therapy using a validated phenotypic or genotypic method. GTT offers a more easily accessible, rapid and inexpensive method for tropism diagnostics than phenotypic testing and is the likely preferred option in many settings.
2. Laboratories undertaking genotypic tropism testing should do so under quality assurance schemes and according to the prevailing consensus about preferred methodology for sampling, testing, and interpretation.
3. In treatment-naive patients, tropism testing should be performed immediately prior to the start of therapy whenever CCR5 antagonist use may be considered in the first-line regimen (unlicensed indication in Europe).
4. In treated patients experiencing virological failure, tropism testing should be performed and the results should become available at the same time as those of drug-resistance testing to ensure all available therapeutic options may be considered.
5. In treated patients with suppressed viraemia for whom a switch to a CCR5 antagonist is considered (e.g. due to toxicity), tropism testing may be performed using either PBMC-derived proviral DNA from a current sample, or plasma-derived RNA from a stored sample collected immediately before viral load suppression. The clinical utility of either approach should be monitored closely as supporting evidence is limited.
6. Detection of CXCR4-using virus at any time should be considered long-lasting. No specific recommendations can be made about the longevity of R5 predictions in patients with ongoing virus replication, although a 90-day cut-off has been commonly applied. In patients with a high risk of emergence of CXCR4-using virus (based on a low nadir CD4 cell count) the test should be repeated as near as possible to the start of CCR5 antagonist therapy.
One important consideration is that current PTT and GTT methodologies do not use viable virus for assessing tropism. The assays cannot therefore differentiate between replication-competent and therefore clinically relevant strains, and defective variants that might have a different co-receptor usage but not necessarily impact on virological responses to the antagonist. In this aspect, the assays differ from the original methodology for assessing tropism, which used virus isolates recovered from PBMC to infect immortalized T-cell lines such as H9 or MT-2 cells .
Whereas producing good-quality V3-loop sequences may be achieved easily in laboratories with experience of genotypic resistance testing, it is important that the methodological approach to GTT should follow the prevalent consensus. Evidence indicates that geno2pheno[co-receptor] provides reliable discrimination between R5 and X4 sequences when the assay interpretative parameter, called the false-positive rate (FPR), is set between 5 and 10%. Using data from the MOTIVATE studies in treatment-experienced patients, a loss of antiviral activity with maraviroc was observed at an FPR of 5.75% using the geno2pheno[co-receptor] algorithm and at a cut-off of -4.25 using the PSSM algorithm [42,43]. Nearly complete loss of maraviroc activity was seen in patients with FPRs below 2%. Analysis from the MERIT trial of treatment-naive patients confirmed the utility of the 5.75% cut-off . In addition, to improve sampling of the viral quasispecies and sensitivity for the detection of CXCR4-using virus, replicate testing – typically triplicate – is recommended, whereby samples undergo three separate polymerase chain reaction (PCR) amplifications followed by separate sequencing of the three PCR products . Three separate results are therefore obtained for each sample, and if any sequence is identified as X4, presence of CXCR4-using variants is reported.
What do we still need to clarify?
Although there is an increasing body of evidence now available in support of GTT, there are still some important practical aspects for users to consider from a methodological as well as clinical perspective. For instance, the cost-effectiveness of replicate testing for samples with a high viral load is not uniformly endorsed, and the caveat remains that prospective data for GTT are limited to small observational cohorts [29,30,37]. Tropism assays should ideally detect X4 variants at levels that may cause virological failure but not exclude patients who are likely to benefit from CCR5 antagonist use. The geno2pheno[co-receptor] interpretation algorithm, for example, allows users to select the FPR, and therefore both the sensitivity for detecting CXCR4-using virus and the probability of classifying an R5 virus falsely as X4. The optimal cut-offs may differ depending on the individual circumstances of the patient. Thus, a lower FPR might be suitable for patients with severely limited therapeutic options, or in the presence of a strongly supportive background regimen, when the presence of a small proportion of ‘unrecognized’ X4 variants may be acceptable. Conversely, a greater degree of certainty of excluding X4 virus would be preferred in patients with a large range of available agents, in order to prevent unnecessary sacrifice of active agents. It is hoped that use of cut-offs could provide a tropism result similar to that seen for resistance tests. Thus, using predefined higher and lower cut-off points, samples with no X4 variants or with X4 variants suggested only above the higher cut-off would fall into a ‘green’ category predictive of a good response to CCR5 antagonists; those with X4 variants suggested below the higher and above the lower cut-off would fall into a ‘yellow’ category predictive of an intermediate response; and those with X4 variants suggested below the lower cut-off would fall into a ‘red’ category predictive of a poor response. For patients falling into the ‘yellow’ category, the clinician would need to fully consider the results of the test in the context of the individual patient's clinical situation before deciding whether a CCR5 antagonist is appropriate. For example, considerations would have to include the number of other active agents in the proposed regimen and the overall genetic barrier of the regimen, as well as the suitability of alternative options. There is a category of ‘high-risk’ patients in whom caution is recommended even when R5 results are obtained as the presence of low-frequency X4 strains is more likely. This includes patients with evidence of significant immune compromise either current or past, typically indicated by a very low nadir CD4 cell count . When available, the nadir CD4 cell count may be used with the geno2pheno[co-receptor] algorithm to improve the system ability to predict likely presence of X4 virus in patients whose predominant sequences are R5.
A significant potential benefit of GTT is the ability to determine tropism in patients with a low or undetectable viral load, by sequencing proviral DNA recovered from PBMC [26–30,33]. Concordance between GTT tropism prediction from plasma RNA and proviral DNA has been reported to be high, and some studies indicate that in fact X4 variants tend to be more commonly found in DNA compared with RNA . It is important to point out, however, that the evidence base in support of tropism prediction from proviral DNA to guide treatment decisions is much smaller than that available for plasma RNA-based testing. Preliminary evidence suggests that the risk of virological rebound is very low in treated patients with a viral load below 50 copies/ml who replace an existing agent with maraviroc following an R5 prediction from proviral DNA-based GTT [29,30]. In small cohort studies, the reported risk of rebound appeared to be very low even within switch regimens that did not include a ritonavir-boosted protease inhibitor (Table 2) .
Whereas these preliminary findings are promising, further clinical evaluation of proviral DNA-based GTT is required, preferably within controlled studies. If using tropism predictions from proviral DNA there is currently an obligation to carefully monitor the response to treatment. An alternative approach for patients with suppressed viraemia is testing of a stored plasma sample collected immediately before viral load suppression. Data from small cohorts of patients have suggested that tropism assignment seldom changes on suppressive treatment [44,45], although further clinical validation is required.
What next for genotypic tropism testing?
Despite some remaining limitations to be overcome, as the evidence base grows in support of GTT we are becoming increasingly confident in its ability to replace phenotypic methods and in its applicability in different settings. Through collaborative efforts that have led to the development and implementation of standard protocols and quality assurance programmes , we are nearing the time when GTT is widespread in routine diagnostic settings, simplifying the identification of patients suitable for CCR5 antagonist use. Whereas both the geno2pheno[co-receptor] and PSSM have shown a good positive predictive value for responses to maraviroc [42,43], there is a larger and growing clinical evidence in support of the geno2pheno[co-receptor] system [29,30,35–37]. Whether combining different bioinformatic systems may further improve the prediction of clinical outcomes deserves further evaluation. Looking to the future, additional genotypic methods such as ultra-deep sequencing, which can generate thousands of clonal sequences from a single sample, are being developed with improved sensitivity for detecting low-frequency variants of HIV compared with bulk sequencing [33,46–48]. Such approaches, which remain research tools at present, may help further define the clinically relevant cut-offs for X4 variants and improve our understanding of X4 variant evolution.
A further consideration is whether it may be possible in the future to reliably identify patients harbouring non-R5 virus in plasma (or PBMC), in whom a degree of virological activity of CCR5 antagonist therapy might be anticipated. Study A4001029, which enrolled treatment-experienced patients with non-R5 virus by Trofile, did not found evidence of a net virological benefit of maraviroc over placebo (Table 1) . In addition, the ACTG5211 trial found that patients classed as having non-R5 virus by ESTA showed a poor virological response to vicriviroc . Thus, whereas the hypothesis that CCR5 antagonists may retain partial activity in some patients with dominant non-R5 virus in plasma remains biologically plausible , clinical validation data are currently lacking. Finally, there is evidence to indicate that the geno2pheno[co-receptor] interpretation system performs well across a range of different HIV-1 subtypes , further studies, however, are needed to fully explore the influence of subtype on both performance of tropism tests and their predictive value for clinical responses to CCR5 antagonists.
In summary, as the available data are not perfect, implementing GTT in routine practice is both evidence-based and, to an extent, a pragmatic leap of faith. In an ideal scenario, a prospective randomized controlled trial would guide the decision about which approach to tropism testing is the most cost-effective. In the absence of this, we propose that GTT is an acceptable approach for routine clinical practice.
The authors thank the European Taskforce on Tropism Testing and the Writing Committee of the European Guidelines on Tropism Testing for helpful discussions that have informed the content of this article. The article is based partially on the content of a continuing professional development-accredited educational event that took place in London in September 2009 with support by Pfizer. Sue Laing, from ScopeMedical Ltd provided independently funded editorial support to prepare a written summary of the meeting. P.R.H. and A.M.G. jointly prepared and revised the manuscript and are responsible for its entire content.
Financial disclosure: P.R.H.: Consultancy: Pfizer, ViiV Healthcare, Virco. Research support: Abbott, Merck, Pfizer, Quest, ViiV Healthcare. A.M.G.: Consultancy and speakers' bureau: Abbott, Bristol Meyers Squibb, Gilead, Glaxo Smith Kline, Merck, Monogram Biosciences, Pfizer, Tibotec, Roche, ViiV Healthcare, Virco. Research support: Merck, Monogram Biosciences, Pfizer, Roche, Tibotec, ViiV Healthcare.
1. Berger EA, Doms RW, Fenyo EM, Korber BT, Littman DR, Moore JP, et al
. A new classification for HIV-1. Nature 1998; 391:240.
2. Moyle GJ, Wildfire A, Mandalia S, Mayer H, Goodrich J, Whitcomb J, et al
. Epidemiology and predictive factors for chemokine receptor use in HIV-1 infection. J Infect Dis 2005; 191:866–872.
3. Soriano V, Perno CF, Kaiser R, Calvez V, Gatell JM, di Perri G, et al
. When and how to use maraviroc in HIV-infected patients. AIDS 2009; 23:2377–2385.
4. Gathe J, Diaz R, Fatkenheuer G, Zeinecker J, Mak C, Vilchez R, et al. Phase 3 trials of vicriviroc in treatment-experienced subjects demonstrate safety but not significantly superior efficacy over potent background regimens alone. 17th Conference on Retroviruses and Opportunistic Infections
, San Francisco, 16–19 February 2010 [abstract 54LB].
6. Palleja S, Cohen C, Gathe J, Thompson M, DeJesus E, Brinson C, et al. Safety and efficacy of TBR 652, a CCR5 antagonist, in HIV-1-infected, ART-experienced, CCR5 antagonist-naïve patients. 17th Conference on Retroviruses and Opportunistic Infections
, San Francisco, 16–19 February 2010 [abstract 53].
7. Martin DE, Palleja1 S, Gathe J, Thompson M, Cohen C, De Jesus E, et al. TBR-652, a potent dual chemokine receptor 5/chemokine receptor 2 (CCR5/CCR2) antagonist in phase 2 development for treatment of HIV infection. 18th International AIDS Conference
, Vienna, 18–23 July 2010 [abstract MOAB0104].
8. Jacobson JM, Thompson MA, Lalezari JP, Saag MS, Zingman BS, D'Ambrosio P, et al
. Anti-HIV-1 activity of weekly or biweekly treatment with subcutaneous PRO 140, a CCR5 monoclonal antibody. J Infect Dis 2010; 201:1481–1487.
9. Gulick RM, Lalezari J, Goodrich J, Clumeck N, DeJesus E, Horban A, et al
. Maraviroc for previously treatment patients with R5 HIV-1 infection. N Engl J Med 2008; 359:1429–1441.
10. Fatkenheuer G, Nelson M, Lazzarin A, Konourina I, Hoepelman AI, Lampiris H, et al
. Subgroup analyses of maraviroc in previously treated R5 HIV-1 infection. N Engl J Med 2008; 359:1442–1455.
11. Cooper DA, Heera J, Goodrich J, Tawadrous M, Saag M, Dejesus E, et al
. Maraviroc versus efavirenz, both in combination with zidovudine-lamivudine, for the treatment of antiretroviral-naïve subjects with CCR5-tropic HIV-1 infection. J Infect Dis 2010; 201:803–813.
12. Saag M, Goodrich J, Fätkenheuer G, Clotet B, Clumeck N, Sullivan J, et al
. A double-blind, placebo controlled trial of maraviroc in treatment-experienced patients infected with non-R5 HIV-1. J Infect Dis 2009; 199:1638–1647.
13. Gulick RM, Su Z, Flexner C, Hughes MD, Skolnik PR, Wilkin TJ, et al
. Phase 2 study of the safety and efficacy of vicriviroc, a CCR5 inhibitor, in HIV-1-infected, treatment-experienced patients: AIDS Clinical Trials Group 5211. J Infect Dis 2007; 196:304–312.
14. Suleiman J, Zingman BS, Diaz RS, Madruga JV, DeJesus E, Slim J, et al
. Vicriviroc in combination therapy with an optimized regimen for treatment-experienced subjects: 48-week results of the VICTOR-E1 phase 2 trial. J Infect Dis 2010; 201:590–599.
15. Su Z, Gulick R, Krambrink A, Coakley E, Hughes MD, Han D, et al
. Response to vicriviroc in treatment-experienced subjects, as determined by an enhanced-sensitivity coreceptor tropism assay: reanalysis of AIDS clinical trials group A5211. J Infect Dis 2009; 200:1724–1728.
16. Whitcomb JM, Huang W, Fransen S, Limoli K, Toma J, Wrin T, et al
. Development and characterization of a novel single-cycle recombinant-virus assay to determine human immunodeficiency virus type 1 coreceptor tropism. Antimicrob Agents Chemother 2007; 51:566–575.
17. Reeves JD, Coakley E, Petropoulos CJ, Whitcomb JM. An enhanced-sensitivity Trofile HIV coreceptor tropism assay for selecting patients for therapy with entry inhibitors targeting CCR5: a review of analytical and clinical studies. J Viral Entry 2009; 3:94–102.
18. Strizki JM, McNicholas P, Mann P, Wojcik L, Qiu P, Shen J, et al
. Use of the enhanced sensitivity tropism assay (ESTA) to predict on-treatment detection of CXCR4-using virus and impact on virological outcomes in a vicriviroc (VCV) Phase II treatment-experienced study (Victor-E1) [Abstract]. Antivir Ther 2010; 15(Suppl 2):A18.
19. Saag M, Heera J, Goodrich J, DeJesus E, Clumeck N, Cooper D, et al. Reanalysis of the MERIT study with the enhanced Trofile assay. 48th ICAAC Annual/46th IDSA Annual Meeting
, Washington, 25–28 October 2008 [abstract H-1269].
20. Strang AL, Cameron J, Booth C, Garcia-Diaz AM, Geretti AM. Genotypic prediction of viral co-receptor tropism: correlation with enhanced Trofile [Abstract]. HIV Med 2009; 10(Suppl 1):42.
21. Toma J, Frantzell A, Hoh R, Martin J, Deeks S, Petropoulos C, et al. Determining HIV-1 coreceptor tropism using PBMC proviral DNA derived from aviremic blood samples. 17th Conference on Retroviruses and Opportunistic Infections
, San Francisco, 16–19 February 2010 [abstract 541].
22. Beerenwinkel N, Däumer M, Oette M, Korn K, Hoffmann D, Kaiser R, et al
. Geno2pheno: estimating phenotypic drug resistance from HIV-1 genotypes. Nucleic Acids Res 2003; 31:3850–3855.
23. Jensen MA, Li FS, van 't Wout AB, Nickle DC, Shriner D, He HX, et al
. Improved coreceptor usage prediction and genotypic monitoring of R5-to-X4 transition by motif analysis of human immunodeficiency virus type 1 env V3 loop sequences. J Virol 2003; 77:13376–13388.
24. Low AJ, Marchant D, Brumme CJ, Brumme ZL, Dong W, Sing T, et al
. CD4-dependent characteristics of co-receptor use and HIV type 1 V3 sequence in a large population of therapy-naive individuals. AIDS Res Human Retroviruses 2008; 24:219–228.
25. Sing T, Low AJ, Beerenwinkel N, Sander O, Cheung PK, Domingues FS, et al
. Predicting HIV coreceptor usage on the basis of genetic and clinical covariates. Antivir Ther 2007; 12:1097–1106.
26. Prosperi MC, Bracciale L, Fabbiani M, Di Giambenedetto S, Razzolini F, Meini G, et al
. Comparative determination of HIV-1 co-receptor tropism by enhanced sensitivity Trofile, gp120 V3-loop RNA and DNA genotyping. Retrovirol 2010; 30:56.
27. Soulie C, Fourati S, Lambert-Niclot S, Malet I, Wirden M, Tubiana R, et al
. Factors associated with proviral DNA HIV-1 tropism in antiretroviral therapy-treated patients with fully suppressed plasma HIV load: implications for the clinical use of CCR5 antagonists. J Antimicrob Chemother 2010; 65:749–751.
28. Verhofstede C, Vandekerckhove L, Eygen VV, Demecheleer E, Vandenbroucke I, Winters B, et al
. CXCR4-using HIV Type 1 variants are more commonly found in peripheral blood mononuclear cell DNA than in plasma RNA. J Acquir Immune Def Synd 2009; 50:126–136.
29. Macartney MJ, Cameron J, Strang AL, Garcia A, Booth C, Marshall N, et al. Use of a genotypic assay for prediction of HIV-1 co-receptor tropism and guiding the use of CCR5 antagonists in clinical practice. 8th European HIV Drug Resistance Workshop
, Sorrento, 17–19 March 2010 [abstract 44].
30. Obermeier MJ, Carganico A, Bieniek B, Cordes C, Dupke S, Fisher K, et al
. Genotypic tropism testing from proviral DNA: test characteristics and clinical outcome [abstract]. Antivir Ther 2010; 15(Suppl 2):A132.
31. Low AJ, Dong W, Chan D, Sing T, Swanstrom R, Jensen M, et al
. Current V3 genotyping algorithms are inadequate for predicting X4 co-receptor usage in clinical isolates. AIDS 2007; 21:F17–F24.
32. Poveda E, Seclén E, González M, García F, Chueca N, Aguilera A, et al
. Design and validation of new genotypic tools for easy and reliable estimation of HIV tropism before using CCR5 antagonists. J Antimicrob Chemother 2009; 63:1006–1010.
33. Swenson L, Moores A, Low A, Thielen A, Dong W, Woods C, et al
. Improved detection of CXCR4-using HIV by V3 genotyping: application of population-based and ‘deep’ sequencing to plasma RNA and proviral DNA. J Acquir Immune Def Synd 2010; 54:506–510.
34. Sanchez V, Robeldano C, Ciprian D, Montolio F, Escalano C, Padeilla S, et al
. Evaluation of genotypic algorithms to predict HIV-1 coreceptor usage using Enhanced Sensitivity Trofile HIV coreceptor tropism assay [abstract]. HIV Med 2009; 10(Suppl 2):49.
35. McGovern RA, Thielen A, Mo T, Dong W, Woods CK, Chapman D, et al. Population-based V3 genotypic tropism assay: a retrospective analysis using screening samples from the A4001029 and MOTIVATE studies. AIDS
36. McGovern R, Dong W, Zhong X, Knapp D, Thielen A, Chapman D, et al. Population-based sequencing of the V3-loop is comparable to the Enhanced Sensitivity Trofile Assay in predicting virologic response to maraviroc of treatment-naïve patients in the MERIT trial. 17th Conference on Retroviruses and Opportunistic Infections
, San Francisco, 16–19 February 2010 [abstract 92].
37. Obermeier MJ, Carganico A, Bieniek B, Cordes C, Dupke S, Golz J, et al
. Update on the Berlin maraviroc cohort: genotypic tropism testing results and therapeutic outcome at weeks 12 and 24 [abstract]. HIV Med 2009; 10(Suppl 2):67.
39. Geretti AM, Mackie N. British HIV Association guidelines on determining HIV-1 tropism in routine clinical practice
. Available at http://www.bhiva.org/Tropism.aspx
. [Accessed Jul 2010]
40. Vandekerckhove L, Wensing AMJ, Kaiser R, Brun-Vezinet F, Clotet B, De Luca A, et al
. European consensus on clinical use and interpretation of HIV-1 tropism testing [Abstract]. HIV Med 2009; 10(Suppl 2):48–49.
41. Schuitemaker H, Koot M, Kootstra NA, Dercksen MW, de Goede RE, van Steenwijk RP, et al
. Biological phenotype of human immunodeficiency virus type 1 clones at different stages of infection: progression of disease is associated with a shift from monocytotropic to T-cell tropic virus population. J Virol 1992; 66:1354–1360.
42. Harrigan PR, McGovern R, Dong W, Mo T, Zhong X, Chapman D, et al
. Optimization of clinically relevant cut-points for the determination of HIV co-receptor usage to predict maraviroc responses in treatment-experienced (TE) patients using population V3 genotyping [Abstract]. HIV Med 2009; 10(Suppl 2):71.
43. Harrigan PR, MOTIVATE Tropism Study Group. Optimisation of clinically relevant cutoffs for determining HIV co-receptor use by population and ‘deep’ sequencing methods. 47th IDSA
, Philadelphia, 29 October–1 November 2009 [abstract 297].
44. Waters L, Scourfield A, Marcano M, Gazzard B, Nelson M. The evolution of co-receptor tropism in patients interrupting suppressive HAART. 16th Conference on Retroviruses and Opportunistic Infections
, Montreal, 8–11 February 2009 [abstract 439a].
45. Seclén E, Del Mar González M, De Mendoza C, Soriano V, Poveda E. Dynamics of HIV tropism under suppressive antiretroviral therapy: implications for tropism testing in subjects with undetectable viraemia. J Antimicrob Chemother 2010; 65:1493–1496.
46. van t Wout AB, Swenson L, Welkers MRA, Dong W, Schuitemaker H, Harrigan PR. Detection of CXCR4-using HIV-1 variants in longitudinally obtained paired plasma and PBMC samples using 454-sequencing [Abstract]. Antivir Ther 2009; 14(Suppl 1):A88.
47. Däumer MP, Kaiser R, Klein R, Lengauer T, Thiele B, Thielen A. Inferring viral tropism from genotype with massively parallel sequencing: qualitative and quantitative analysis [Abstract]. Antivir Ther 2008; 13(Suppl 3):A101.
48. Swenson L, Dong W, Mo T, Woods C, Thielen A, Jensen M, et al. Quantification of HIV tropism by ‘deep’ sequencing shows a broad distribution of prevalence of X4 variants in clinical samples that is associated with virological outcome. 16th Conference on Retroviruses and Opportunistic Infections
, Montreal, 8–11 February 2009 [abstract 680].
49. Ghezzi S, Menzo S, Brambilla A, Bordignon PP, Lorini AL, Clementi M, et al
. Inhibition of R5X4 dualtropic HIV-1 primary isolates by single chemokine co-receptor ligands. Virology 2001; 280:253–261.
50. Lengauer T. Genotypic basis of viral tropism [invited lecture]. 4th International Workshop on Targeting HIV Entry
, Rio Grande, 8–9 December 2008.
genotype; gp120; HIV-1; tropism; V3 loop
© 2011 Lippincott Williams & Wilkins, Inc.
What does "Remember me" mean?
By checking this box, you'll stay logged in until you logout. You'll get easier access to your articles, collections,
media, and all your other content, even if you close your browser or shut down your
To protect your most sensitive data and activities (like changing your password),
we'll ask you to re-enter your password when you access these services.
What if I'm on a computer that I share with others?
If you're using a public computer or you share this computer with others, we recommend
that you uncheck the "Remember me" box.
Highlight selected keywords in the article text.
Data is temporarily unavailable. Please try again soon.