Virological response after a short-term CCR5 antagonist exposure in ...

1

Virological response after a short-term CCR5 antagonist exposure in HIV-infected patients: 1

Frequency of subjects with virological response and associated factors 2

3

Ezequiel Ruiz-Mateos1,2*, Alejandro González-Serna1,2, Miguel Genebat1, Kawthar Machmach1,2, 4

Francesc Vidal3, Mª Ángeles Muñoz-Fernández4, Sara Ferrando-Martinez1,4, Manuel Leal1*. 5

6

1Laboratory of Immunovirology, Biomedicine Institute of Seville (IBIS), Service of Infectious 7

Diseases, Virgen del Rocío University Hospital, Seville, Spain. 8

2Department of Clinical Biochemistry, Biomedicine Institute of Seville (IBIS)/Virgen del Rocío 9

University Hospital, Seville, Spain. 10

3Hospital Universitari Joan XXIII, IISPV, Universitat Rovira I Virgili, Tarragona, Spain 11

4Laboratorio de Inmuno-Biología Molecular, Gregorio Marañón University Hospital, Madrid, 12

Spain. 13

Running title: Frequency and factors associated with MRV treatment 14

15

*Corresponding authors: Ezequiel Ruiz-Mateos PhD. [email protected] and 16

Manuel Leal MD. [email protected]. Laboratory of Immunovirology, Biomedicine Institute 17

of Seville (IBIS), Service of Infectious Diseases, Virgen del Rocío University Hospital, Seville, 18

Spain. Lab. 211. Planta 2ª. Avd. Manuel Siurot s/n. 41013- Seville – SPAIN. Tel. 0034 19

955923109. Fax. 0034 955013292. 20

21

Copyright © 2011, American Society for Microbiology and/or the Listed Authors/Institutions. All Rights Reserved.Antimicrob. Agents Chemother. doi:10.1128/AAC.00753-11 AAC Accepts, published online ahead of print on 1 August 2011

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

2

ABSTRACT 22

23

The virological response after an eight day Maraviroc monotherapy has been proposed as an 24

alternative method to decide the prescription of CCR5 antagonist to HIV-infected patients. The 25

frequency of eligible patients for a combined antiretroviral therapy which includes Maraviroc 26

based on the result of this clinical test is not well known at the moment. In the same way, 27

clinical and immunovirological factors associated with the virological response after antagonist 28

exposure need to be determined. Ninety consecutive HIV-infected patients were exposed to 29

an eight day Maraviroc monotherapy. Virological response was considered positive if either a 30

reduction of 1 log10 HIV-RNA copies/mL or undetectable viral load (<40 HIV-RNA copies/mL), 31

was achieved. CXCR4 and CCR5 tropic virus levels were determined by using patients’ viral 32

isolates and multiple rounds of infection of indicator cell lines (U87-CXCR4 and U87-CCR5). The 33

frequency of patients with a positive virological response was 72.2% (94.7% and 66.2% for 34

naïve and pretreated patients, respectively). The positive response rates dramatically 35

decreased in patients with lower CD4+ T-cell counts. CXCR4-tropic virus level was the only 36

variable independently associated with the virological response after short-term Maraviroc 37

exposure. Lower CD4+ T-cell strata were associated with higher CXCR4-tropic virus levels. 38

These results support that CCR5 antagonists should be an early treatment option before the 39

expansion of CXCR4-tropic strains. 40

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

3

INTRODUCTION 41

42

To gain entry into cells, HIV uses the CCR5 (R5) and/or CXCR4 (X4) co-receptor as well as the 43

CD4 receptor (1). The selective blocking of R5 by the first commercialized co-receptor 44

antagonist, Maraviroc (MRV) (4), makes the determination of HIV tropism essential before this 45

drug is prescribed to HIV-infected patients (10). To date, the most widely used co-receptor 46

tropism tests are the recombinant phenotypic Trofile assay (Trofile) (24) and its later version, 47

the Enhanced Sensitivity Trofile assay (ESTA) (25). 48

However, Trofile has some limitations such as: it requires samples with more than 1000 HIV-49

RNA copies/mL, around 20% of the results are non-reportable mainly due to low viral loads 50

and limitations regarding the reproducibility of this method have been described in different 51

studies (12, 19). Other methods, such as genotypic tropism test (3, 16, 17) has been proposed 52

as an alternative to the commercialized phenotypic method, however the main caveats of 53

these tests is the low sensitivity to detect Dual/Mixed (DM)/X4 tropic viruses (14). Due to 54

these limitations, a short-term exposure to MRV has been proposed as a method to assay the 55

sensitivity to R5 antagonists (Maraviroc Clinical Test, MCT) (7). This method has the advantage 56

that the outcome is a real time evidence of drug sensitivity and not a tropism result. However, 57

the frequency of subjects with a virological response after the short-term MRV exposure is not 58

well known at the moment. This frequency has been only partially published in smaller set of 59

patients (7, 9) and is unknown in naïve patients. On the other hand, it would be interesting to 60

know the factors that are associated with the virological response experienced after a short-61

term MRV exposure. In this sense, regarding Trofile, CD4 T-cell levels have been independently 62

associated with a DM/X4 tropic result that corresponds to subjects not eligible for R5 63

antagonist treatment (15). However, the clinical and inmunovirological factors that are 64

associated with virological response after MCT are unknown. 65

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

4

Thus, the aims of this work were to analyze the frequency of subjects eligible for R5 antagonist 66

treatment based on MCT and study the clinical and inmunovirological factors associated with 67

the virological response after MCT. 68

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

5

69

METHODS AND MATERIALS 70

71

PATIENTS AND INTERVENTION 72

73

This study was conducted in the Infectious Diseases Service at Virgen del Rocio University 74

Hospital and the Biomedicine Institute of Seville (IBiS) (Seville, Spain). Ninety consecutive HIV-75

infected patients who underwent MCT from July 2008 until March 2011 were included in the 76

present study. These patients with a median age of 42 [36–46] years had persistently 77

detectable plasma viral loads (>40 HIV-RNA copies/mL) and all of them were asymptomatic at 78

the time of the study. Patients, or legal guardians for those subjects under 18 years old, had 79

given written informed consent and the Ethical Committee of the Hospital approved the study. 80

MCT has been previously described (7). Briefly, patients were exposed to an eight day MRV 81

monotherapy and the subsequent virological response was analyzed. MCT was considered 82

positive if a significant viral load reduction, defined as a reduction ≥1 log10 HIV-RNA copies/mL 83

or undetectable viral load (<40 HIV-RNA copies/mL), was achieved on day eight after adding 84

MRV. Once the MCT result was obtained, a new HAART regimen was started according to the 85

following criteria: (i) previous genotype resistance testing results; (ii) previous antiretroviral 86

exposure; and (iii) response to MCT, in order to include MRV or not in the new HAART. 87

88

METHODS 89

90

X4 and R5 virus levels determination 91

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

6

In a subgroup of these consecutive patients (n=57), the phenotypic tropism test TROCAI was 92

assayed at baseline as previously reported (9). Briefly, TROCAI is based on the production of 93

viral isolates from patients through a co-culture and multiple rounds of infection U87-X4 and 94

U87-R5 indicator cell lines. For the purpose of this study, results were expressed as Log viral 95

load (VL) in the U87-X4 and U87-R5 well supernatant (LogX4VL and LogR5VL, respectively). 96

97

Viral load quantification 98

99

HIV-1 RNA was measured in patients’ fresh plasma and in frozen samples of U87-X4 and U87-100

R5 cell-free supernatants by quantitative PCR (COBAS Ampliprep/COBAS Taqman HIV-1 test, 101

Roche molecular systems, Basel, Switzerland) according to the manufacturers’ instructions. 102

The lower detection limit was 40 HIV-1 RNA copies/mL. Plasma samples were tested for anti-103

Hepatitis C virus (HCV)-antibodies using HCV-ELISA (Siemens Healthcare Diagnosis, USA). A 104

qualitative PCR amplification was performed for plasma HCV RNA amplification (COBAS 105

Amplicor, Roche Diagnosis, Barcelona, Spain) with a lower detection limit of 15 IU/mL. 106

107

CD4-T cell quantification 108

109

CD4 T-cell counts were determined in fresh whole blood using the Epics XL-MCL (Beckman-110

Coulter Inc., California) flow cytometer according to the manufacturers’ instructions. Fresh 111

whole blood was stained with directly conjugated monoclonal antibodies, anti-CD3–112

phycoerytrin (PE) and anti–CD4-fluorescein isothiocyanate (FITC) (BD Bioscience). 113

114

Statistical analysis 115

116

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

7

Statistical analyses were performed using the Statistical Package for the Social Sciences 117

software (SPSS 17.0, Chicago, IL, USA). Median and interquartile ranges were used to describe 118

continuous variables and a percentage for categorical ones. Pearson’s test was used to analyze 119

correlation between variables. Differences between groups were analyzed with Mann-Whitney 120

U test and a bivariate logistic or linear regression analysis when appropriate. To analyze the 121

independent factors associated with MCT response or VL changes after MCT, a multivariate 122

logistic or linear regression analysis, respectively, was assessed with variables showing a p 123

value <0.1 in the bivariate analysis. Variables showing a p value <0.05 were considered 124

statistically significant. 125

126

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

8

127

RESULTS 128

129

Frequency of virological response after MCT 130

Patients’ characteristics at baseline are shown in Table 1. In terms of antiretroviral treatment 131

21% of the patients were naïve. After MRV exposure, 72.2% of the overall patients 132

experienced a virological response (MCT positive subjects), which meant that around three 133

quarters of the patients could benefit from an antiretroviral treatment that includes MRV 134

(Figure 1a). However, we observed different response in pretreated and naïve patients. When 135

we split the populations in these two categories we observed how almost all naïve patients 136

were MCT positive (94.7%) as opposed to what happened in pretreated patients (66.2%) 137

(Figure 1a). Interestingly, when the virological response was analyzed depending on different 138

baseline CD4+ T-cell strata, higher CD4+ T-cell levels were associated with higher percentages 139

of MCT positive subjects. There was a dramatic decrease in MCT positive subjects when CD4+ 140

T-cell levels were below 200 CD4+ T-cells/µL (Figure 1b). Thus, the high percentage of MCT 141

positive naive patients could be associated with higher baseline CD4+ T-cell levels in this group 142

(Figure 1b). 143

144

Factors associated with the virological response after MCT 145

Our aim was to determine which factors were associated with virological response after MCT. 146

We observed how individuals with no virological response (MCT negative subjects) differed 147

from the MCT positive subjects in several variables; they were mostly pretreated, had been 148

diagnosed for a longer period of time, and the risk of transmission was mainly illicit drug use. 149

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

9

According to results mentioned above, MCT negative subjects showed almost 3 fold lower 150

CD4+ T-cell levels (Table 2). In fact, when we adjusted for all these variables, CD4+ T-cell levels 151

was the only variable independently associated with the virological response after MCT (Table 152

2). Interestingly, in a subgroup of these patients (n=57) we analyzed X4 and R5 virus levels. We 153

expressed the results as the amount of X4/DM (from now on X4) and R5 viruses produced after 154

the infection by the patients’ viral isolates of indicator cell lines that express X4 or R5. We 155

observed that the risk of transmission, time since diagnosis, and CD4+ T-cell levels were 156

associated with virological response after MCT and, in addition, the amount of X4 virus levels 157

was also strongly associated. In this case, however, when all these variables were adjusted, the 158

amount of X4 virus was the only variable independently associated with the virological 159

response after MCT (Table 3). Of note that, despite the high differences observed in X4, R5 160

virus levels were extremely similar between both groups (Figure 2a-b). Remarkably, when 161

patients were grouped based on treatment category, the amount of X4 viruses tended to be 162

lower in naïve patients when compared to pretreated patients (Figure 2c). This trend was 163

similar regarding R5 virus levels (data not shown). Importantly, we also observed higher CD4+ 164

T-cells levels in naïve compared to pretreated patients (Figure 2d). In addition, when patients 165

were divided according to CD4+ T-cell strata, a dramatic increase in X4 virus levels were 166

observed in patients with CD4+ T-cell levels lower than 200 cells/µL and again there were no 167

differences in R5 virus levels based on different CD4+ T-cell levels (Figure 2e-f). 168

MCT result is categorical (MCT positive and negative subjects), but this result can be 169

transformed in a continuous variable that analyzes the viral load changes after eight days drug 170

exposure. We verified how using viral load changes (six subjects with <1000 HIV-RNA 171

copies/mL were excluded of the analysis, n=51) the sexual risk of transmission, CD4+ T-cell 172

counts and X4 virus levels were associated with the viral load changes experienced after the 173

clinical test. In the same way, the amount of X4 virus was the only variable independently 174

associated with the viral load changes after MCT (Table 4).175

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

10

DISCUSSION 176

177

Results presented herein show that around three quarters of HIV-infected patients are eligible 178

for R5 antagonist therapy based on the virological response observed after a short-term 179

exposure to the drug. Furthermore, X4 tropic virus levels are the only variable independently 180

associated with this response. 181

MCT has been proposed as an alternative method to decide the prescription of R5 antagonist 182

treatment in HIV-infected patients. MCT does not give a tropism result but the sensitivity to 183

antiretroviral drug effect (7). MCT can have some potential limitations, as is the development 184

of resistance mutations to MRV during the test. Besides, during MCT the pressure of the R5 185

antagonist could lead to a X4 virus switch. However, no deleterious effects after administering 186

a rescue therapy based on the MCT result have been observed (8). Current studies to address 187

the safety of MCT and development of resistance are in progress at the moment. On the other 188

hand, MCT can overcome the limitations of phenotype and genotype tropism tests which, due 189

to high or low sensitivity in detecting X4-tropic strains, respectively, can render variable rates 190

of discordant results with the virological response after MRV exposure (6, 9). Besides, this 191

clinical approach is easy, cheap and can be performed on subjects with <1000 HIV-RNA 192

copies/mL. Another advantage is that a non-reportable result cannot be obtained when using 193

MCT. All these characteristics make MCT an attractive model to analyze the factors associated 194

with the response after a R5 antagonist exposure. 195

According to this model a high proportion of HIV-infected patients (73.3%) could be treated 196

with a combined antiretroviral therapy (cART) which includes MRV. These results together 197

with the different frequencies of response which depend on the treatment category (naïve 198

versus pretreated patients) have important clinical implications. The fact that the positive 199

response frequencies are higher in naïve subjects and are associated with higher CD4+ T-cells 200

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

11

levels, strongly suggests the use of a cART that includes a R5 antagonist as a first line HIV-201

infection treatment, due to as it is well known R5 tropic virus predominate early in the 202

infection and X4 tropic virus appear in late infection in 50% of the patients (11). These results 203

agree with the clinical trials that show non-inferiority at undetectability (<50 HIV-RNA 204

copies/mL) of a cART which includes MRV versus Efavirenz in naïve patients (2, 20, 21). 205

On the other hand, to know what factors are associated with virological response after MRV 206

short-term exposure will be particularly interesting in order to optimize R5 antagonist 207

treatment and design strategies to revert factors associated with the absence of response. In a 208

first attempt, CD4+ T-cell levels was the only variable independently associated with the MCT 209

response. These results agree with previous studies that showed CD4+ T-cell levels were 210

associated with Trofile results (15, 23). In these studies, Trofile did not communicate the 211

amount of X4 viraemia, thus the extent to which the X4 viral load influenced the tropism result 212

was unknown. However, in a subgroup of consecutive patients where X4 and R5 virus levels 213

were available, only the X4 virus levels were associated with virological response after being 214

adjusted by CD4+ T-cell levels and type of transmission. This outcome was reproduced when 215

the MCT result was not considered as categorical but as a continuous variable expressed as 216

viral load changes after an eight day MRV exposure. This result may explain the association of 217

high frequencies of response in naïve patients, who tended to have lower X4 virus levels and 218

higher CD4 T-cells levels compared to pretreated patients and in general in those patients 219

with high CD4+ T-cell levels. In fact an inverse correlation was observed between CD4 T-cell 220

and X4 virus levels (r=-0.499; p<0.0001, Pearson test). These results agree with the classic 221

concept of syncitial inducing viral strains associated with the proportion of patients with 222

disease progression and lower CD4 T-cell levels (11). 223

One limitation of our results is the fact of what we have called X4 virus levels is not actually the 224

X4 viral load present in the patient’s peripheral blood but the viral load of the supernatant that 225

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

12

is a result of multiple rounds of infection of the U87-X4 cell line with the patients’ virus isolate. 226

We believe that other methods such as ultra-deep sequencing should be informative in this 227

respect (22), as no quantitative information can be obtained from Trofile. However, the results 228

shown in this work suggest the use of the X4 viral load supernatant as a good surrogate marker 229

for X4 viraemia. It is important to note that no association was found between R5 virus levels 230

and the virological response after MCT. This indicates that the R5 tropic component of the 231

patient’s total viral load is not involved in virological response to R5 antagonists. This means 232

that a MCT positive patient will have very low X4 virus levels, and then the changes in viraemia 233

during MCT will resemble changes in R5 viraemia, the predominant one in this type of patients. 234

While a MCT negative patient has variable X4 virus levels, then the R5 viraemia decreases 235

during MCT will probably be accompanied by increases in X4 viraemia after the R5 antagonist 236

exposure, which will lead to no changes in the final viral load after the test. Thus factors 237

associated with the high levels of X4-tropic viruses at baseline could be associated with the 238

absence of virological response to R5 antagonists. Findings in previous works suggest the 239

importance of X4 density in this process (13). In fact, X4 density on CD4+ T-cell surface has 240

been associated with the emergence of X4-tropic strains during the course of HIV-infection (5). 241

These hypotheses also support the belief that the changes in T-cell subsets proliferation rates 242

which differentially express R5 and X4 favor X4 tropic virus expansion at lower CD4+ T-cell 243

levels (18). 244

In summary, our results demonstrate for the first time that X4 tropic virus levels are 245

independently associated with the absence of response to R5 antagonist therapy. The 246

association of high X4 tropic and low CD4+ T-cell levels agrees with the option of early R5 247

antagonist treatment. Further studies are needed to analyze which factors are associated with 248

the expansion of X4-tropic strains in order to optimize treatment with R5 antagonists and to 249

look for immunotherapeutic strategies to avoid the co-receptor switch during the course of 250

HIV infection. 251

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

13

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

14

252

ACKNOWLEDGEMENTS 253

This study has been supported by Redes Temáticas de Investigación en SIDA (ISCIII RETIC 254

RD06/0006/0021, RD06/0006/0035 and RD06/0006/1004) and by Fondo de Investigación 255

Sanitaria grants PI07/0976 and PS09/01595; and by the Fondos Europeos para el Desarrollo 256

Regional (FEDER). SFM and ERM have grants from the Fondo de Investigaciones Sanitarias 257

(CD10/00382 and CP08/00172, respectively). 258

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

15

259

260

REFERENCES 261

262

1. Berger, E. A., R. W. Doms, E. M. Fenyo, B. T. Korber, D. R. Littman, J. P. Moore, Q. J. 263 Sattentau, H. Schuitemaker, J. Sodroski, and R. A. Weiss. 1998. A new classification 264 for HIV-1. Nature 391:240. 265

2. Cooper, D. A., J. Heera, J. Goodrich, M. Tawadrous, M. Saag, E. Dejesus, N. Clumeck, 266 S. Walmsley, N. Ting, E. Coakley, J. D. Reeves, G. Reyes-Teran, M. Westby, E. Van Der 267 Ryst, P. Ive, L. Mohapi, H. Mingrone, A. Horban, F. Hackman, J. Sullivan, and H. 268 Mayer. 2010. Maraviroc versus efavirenz, both in combination with zidovudine-269 lamivudine, for the treatment of antiretroviral-naive subjects with CCR5-tropic HIV-1 270 infection. J Infect Dis 201:803-13. 271

3. Chueca, N., C. Garrido, M. Alvarez, E. Poveda, J. de Dios Luna, N. Zahonero, J. 272 Hernandez-Quero, V. Soriano, C. Maroto, C. de Mendoza, and F. Garcia. 2009. 273 Improvement in the determination of HIV-1 tropism using the V3 gene sequence and a 274 combination of bioinformatic tools. J Med Virol 81:763-7. 275

4. Dorr, P., M. Westby, S. Dobbs, P. Griffin, B. Irvine, M. Macartney, J. Mori, G. Rickett, 276 C. Smith-Burchnell, C. Napier, R. Webster, D. Armour, D. Price, B. Stammen, A. 277 Wood, and M. Perros. 2005. Maraviroc (UK-427,857), a potent, orally bioavailable, and 278 selective small-molecule inhibitor of chemokine receptor CCR5 with broad-spectrum 279 anti-human immunodeficiency virus type 1 activity. Antimicrob Agents Chemother 280 49:4721-32. 281

5. Fiser, A. L., T. Vincent, N. Brieu, Y. L. Lin, P. Portales, C. Mettling, J. Reynes, and P. 282 Corbeau.2010. High CD4+ T-Cell Surface CXCR4 Density as a Risk Factor for R5 to X4 283 Switch in the Course of HIV-1 Infection. J Acquir Immune Defic Syndr. [Epub ahead of 284 print]. 285

6. Genebat, M., E. Ruiz-Mateos, A. Gonzalez-Serna, I. Pulido, M. A. Munoz-Fernandez, 286 S. Ferrando-Martinez, and M. Leal. 2011. Discordance rates between Trofile test and 287 short-term virological response to maraviroc. Antiviral Res 89:182-5. 288

7. Genebat, M., E. Ruiz-Mateos, J. A. Leon, A. Gonzalez-Serna, I. Pulido, I. Rivas, S. 289 Ferrando-Martinez, B. Sanchez, M. A. Munoz-Fernandez, and M. Leal. 2009. 290 Correlation between the Trofile(R) test and virological response to a short-term 291 maraviroc exposure in HIV-infected patients. J Antimicrob Chemother 64:845-9 292

8. Genebat, M., E. Ruiz-Mateos, I. Pulido, A. Gonzalez-Serna, A. Garcia-Perganeda, G. 293 Mendez, M. C. Romero-Sanchez, S. Ferrando-Martinez, and M. Leal. 2010. Long-term 294 immunovirogical effect and tolerability of a maraviroc-containing regimen in routine 295 clinical practice. Curr HIV Res 8:482-6. 296

9. Gonzalez-Serna, A., M. Leal, M. Genebat, M. A. Abad, A. Garcia-Perganeda, S. 297 Ferrando-Martinez, and E. Ruiz-Mateos. 2010.TROCAI (tropism coreceptor assay 298 information): a new phenotypic tropism test and its correlation with Trofile enhanced 299 sensitivity and genotypic approaches. J Clin Microbiol 48:4453-8. 300

10. Hammer, S. M., J. J. Eron, Jr., P. Reiss, R. T. Schooley, M. A. Thompson, S. Walmsley, 301 P. Cahn, M. A. Fischl, J. M. Gatell, M. S. Hirsch, D. M. Jacobsen, J. S. Montaner, D. D. 302 Richman, P. G. Yeni, and P. A. Volberding. 2008. Antiretroviral treatment of adult HIV 303 infection: 2008 recommendations of the International AIDS Society-USA panel. Jama 304 300:555-70. 305

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

16

11. Koot, M., I. P. Keet, A. H. Vos, R. E. de Goede, M. T. Roos, R. A. Coutinho, F. 306 Miedema, P. T. Schellekens, and M. Tersmette. 1993. Prognostic value of HIV-1 307 syncytium-inducing phenotype for rate of CD4+ cell depletion and progression to AIDS. 308 Ann Intern Med 118:681-8. 309

12. Landovitz, R. J., J. B. Angel, C. Hoffmann, H. Horst, M. Opravil, J. Long, W. Greaves, 310 and G. Fatkenheuer. 2008. Phase II study of vicriviroc versus efavirenz (both with 311 zidovudine/lamivudine) in treatment-naive subjects with HIV-1 infection. J Infect Dis 312 198:1113-22. 313

13. Lin, Y. L., P. Portales, M. Segondy, V. Baillat, C. M. de Boever, V. Le Moing, B. Reant, 314 B. Montes, J. Clot, J. Reynes, and P. Corbeau. 2005. CXCR4 overexpression during the 315 course of HIV-1 infection correlates with the emergence of X4 strains. J Acquir Immune 316 Defic Syndr 39:530-6. 317

14. Low, A. J., W. Dong, D. Chan, T. Sing, R. Swanstrom, M. Jensen, S. Pillai, B. Good, and 318 P. R. Harrigan. 2007. Current V3 genotyping algorithms are inadequate for predicting 319 X4 co-receptor usage in clinical isolates. AIDS 21:F17-24. 320

15. Moreno, Clotet, Sarria, Ortega, Leal, A. Rodriguez, and R. Sanchez-de la. 2009. 321 Prevalence of CCR5-tropic HIV-1 among treatment-experienced individuals in Spain. 322 HIV Clin Trials 10:394-402. 323

16. Poveda, E., E. Seclen, M. Gonzalez Mdel, F. Garcia, N. Chueca, A. Aguilera, J. J. 324 Rodriguez, J. Gonzalez-Lahoz, and V. Soriano. 2009. Design and validation of new 325 genotypic tools for easy and reliable estimation of HIV tropism before using CCR5 326 antagonists. J Antimicrob Chemother 63:1006-10. 327

17. Raymond, S., P. Delobel, M. Mavigner, M. Cazabat, C. Souyris, K. Sandres-Saune, L. 328 Cuzin, B. Marchou, P. Massip, and J. Izopet. 2008. Correlation between genotypic 329 predictions based on V3 sequences and phenotypic determination of HIV-1 tropism. 330 AIDS 22:F11-6. 331

18. Ribeiro, R. M., M. D. Hazenberg, A. S. Perelson, and M. P. Davenport. 2006. Naive and 332 memory cell turnover as drivers of CCR5-to-CXCR4 tropism switch in human 333 immunodeficiency virus type 1: implications for therapy. J Virol 80:802-9. 334

19. Schurmann, D., G. Fatkenheuer, J. Reynes, C. Michelet, F. Raffi, J. van Lier, M. 335 Caceres, A. Keung, A. Sansone-Parsons, L. M. Dunkle, and C. Hoffmann. 2007. 336 Antiviral activity, pharmacokinetics and safety of vicriviroc, an oral CCR5 antagonist, 337 during 14-day monotherapy in HIV-infected adults. AIDS 21:1293-9. 338

20. Sierra-Madero, J., G. Di Perri, R. Wood, M. Saag, I. Frank, C. Craig, R. Burnside, J. 339 McCracken, D. Pontani, J. Goodrich, J. Heera, and H. Mayer. 2010. Efficacy and safety 340 of maraviroc versus efavirenz, both with zidovudine/lamivudine: 96-week results from 341 the MERIT study. HIV Clin Trials 11:125-32. 342

21 A. Mills, D. Mildvan, D. Podzamczer, G. Fätkenheuer, M. Leal, S. Than, S. Valluri, C. 343 Craig, J. Heera, S. Portsmouth. 2010. Once-daily maraviroc (MVC) + 344 atazanavir/ritonavir (ATV/r) vs. emtricitabine/tenofovir (TDF/FTC) + ATV/r in 345 treatment naïve patients: a week 24 planned interim analysis. XVIII International AIDS 346 Conference, Vienna, Austria. Abstract THLBB203. 347

22 Swenson, L. C., T. Mo, W. W. Dong, X. Zhong, C. K. Woods, M. A. Jensen, A. Thielen, 348 D. Chapman, M. Lewis, I. James, J. Heera, H. Valdez, and P. R. Harrigan. 2011. Deep 349 sequencing to infer HIV-1 co-receptor usage: application to three clinical trials of 350 maraviroc in treatment-experienced patients. J Infect Dis 203:237-45. 351

23. Waters, L., S. Mandalia, P. Randell, A. Wildfire, B. Gazzard, and G. Moyle. 2008. The 352 impact of HIV tropism on decreases in CD4 cell count, clinical progression, and 353 subsequent response to a first antiretroviral therapy regimen. Clin Infect Dis 46:1617-354 23. 355

24. Whitcomb, J. M., W. Huang, S. Fransen, K. Limoli, J. Toma, T. Wrin, C. Chappey, L. D. 356 Kiss, E. E. Paxinos, and C. J. Petropoulos. 2007. Development and characterization of a 357

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

17

novel single-cycle recombinant-virus assay to determine human immunodeficiency 358 virus type 1 coreceptor tropism. Antimicrob Agents Chemother 51:566-75. 359

25. Wilkin, T. J., M. B. Goetz, R. Leduc, G. Skowron, Z. Su, E. S. Chan, J. Heera, D. 360 Chapman, J. Spritzler, J. D. Reeves, R. M. Gulick, and E. Coakley. 2011. Reanalysis of 361 Coreceptor Tropism in HIV-1-Infected Adults Using a Phenotypic Assay with Enhanced 362 Sensitivity. Clin Infect Dis 52:925-8. 363

364 365

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

18

366

367

Table 1. Baseline characteristics of the patients (n=90)

Characteristic Value

Male sex, n (%) 71 (79)

Age (years) 42 [36–46]

Sexual transmission, n (%) 47 (52)

IDUa

transmission, n (%) 35 (39)

Naïve subjects, n (%) 19 (21)

Time since diagnosis (years) 15 [3-19]

HCV PCR+b, n (%) 31 (34)

CD4+ counts (cells/mL) 309 [175–459]

Plasma VLc (Log HIV-RNA copies/mL) 4.5 [3.7–5.0]

a IDU, intravenous drug use. b

Positive PCR for hepatitis C virus. c VL, Viral Load. Values other than number (percent) are expressed as 368

medians (interquartile range [IQR]). Values other than number (percent) are expressed as medians (interquartile range [IQR]). 369

370

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

19

371

372

Table 2. Factors associated with the virological response after MCT in all the study subjects (n=90).

MCT positive

(n=65)

MCT negative

(n=25)

Bivariate analysis*

p; O.R. (C.I. 95%)

Multivariate analysis**

p; O.R. (C.I. 95%)

Male sex, n (%) 50/65 (77) 21/25 (84) 0.464; 0.635 (0.188–2.140) N.A.¤

Age (years) 42 [35 – 46] 43 [37 – 47] 0.677; 1.009 (0.967–1.054) N.A.

Naïve subjects, n (%) 18/65 (28) 1/25 (4) 0.036; 9.191 (1.157–73.048) 0.283; 3.857 (0.328–45.364)

Sexual transmission, n (%) 40/65 (62) 7/25 (28) 0.006; 4.114 (1.505–11.250) 0.406; 1.767 (0.462–6.765)

IDU† transmission, n (%) 22/65 (34) 13/25 (52) 0.117; 0.472 (0.185–1.206) N.A.

Time since diagnosis (years) 12 [2 – 19] 16 [12 – 19] 0.068; 0.944 (0.888–1.004) 0.890; 1.007(0.911–1.114)

HCV PCR+¥ , n (%) 22/65 (34) 9/25 (36) 0.847; 0.910 (0.347–2.387) N.A.

CD4+ counts (cells/mL) 355 [226 – 465] 149 [21 – 320] 0.001; 1.006 (1.002–1.009) 0.011; 1.004 (1.001–1.008)

Plasma VL¶ (Log HIV-RNA

cop./mL)

4.4 [3.7 – 4.9] 4.6 [3.5 – 5.2] 0.557; 0.861 (0.521–1.421) N.A.

*Bivariate and **multivariate analysis were performed using a logistic regression model, variables showing a p<0.1 in the bivariate analysis were included in the 373

multivariate analysis. In the multivariate analysis variables with a p<0.05 were considered statistically significant. ¤ Not applicable. †Injecting drug user. ¥PCR positive for 374

Hepatitis C Virus. ¶VL: Viral load. Values other than number (percent) are expressed as medians (interquartile range [IQR]). 375

376

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

20

377

378

Table 3. Factors associated with the virological response after MCT (n=57).

MCT positive

(n=39)

MCT negative

(n=18)

Bivariate analysis*

p; O.R. (C.I. 95%)

Multivariate analysis**

p; O.R. (C.I. 95%)

Male sex, n (%) 31/39 (80) 15/18 (83) 0.733; 0.775 (0.179–3.348) N.A.¤

Age (years) 42 [36 – 45] 41 [27 – 46] 0.500; 1.017 (0.969–1.067) N.A.

Naïve subjects, n (%) 9/39 (23) 0/18 (0) N.D.€ N.A.

Sexual transmission, n (%) 22/39 (56) 4/18 (22) 0.021; 4.529 (1.261–16.271) 0.221; 19.832 (0.165–2383.7)

IDU† transmission, n (%) 14/39 (36) 9/18 (50) 0.315; 0.560 (0.181–1.737) N.A.

Time since diagnosis (years) 13 [2 – 19] 17 [12 – 18] 0.081; 0.929 (0.855–1.009) 0.428; 1.142 (0.822–1.587)

HCV PCR+¥, n (%) 11/39 (28) 6/18 (33) 0.694; 0.786 (0.236–2.616) N.A.

CD4+ counts (cells/mL) 349 [223 – 432] 105 [14 – 181] <0.0001; 1.010 (1.005–1.015) 0.920; 1.001 (0.989–1.012)

Plasma LogVL¶ (HIV-RNA

cop./mL)

4.6 [4.2 – 5.0] 4.9 [3.7 – 5.2] 0.626; 0.840 (0.415–1.696) N.A.

LogX4VL&

(HIV-RNA cop./mL) 2.8 [1.7 – 3.2] 6.6 [5.4 – 7.6] <0.0001; 0.115 (0.035–0.374) 0.007; 0.096 (0.017 – 0.535)

LogR5VL§ (HIV-RNA cop./mL) 6.6 [5.9 – 7.6] 6.7 [5.7 – 7.4] 0.939; 1.016 (0.675–1.529) N.A.

*Bivariate and **multivariate analysis were performed using a logistic regression model, variables showing a p<0.1 in the bivariate analysis were included in the 379

multivariate analysis. In the multivariate analysis variables with a p<0.05 were considered statistically significant. ¤ Not applicable. € Not determined; this contrast was 380

not possible due to the low number of patients. †Injecting drug user. ¥PCR positive for Hepatitis C Virus. ¶ VL: Viral load. & HIV-RNA copies/mL in the U87-CXCR4 cell line 381

well supernatant. § HIV-RNA copies/mL in the U87-CCR5 cell line well supernatant. In this analysis only patients with X4 and R5 virus levels available were included 382

(n=57). Values other than number (percent) are expressed as medians (interquartile range [IQR]). 383

384

385

386

387

388

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

21

389

390

Table 4. Factors associated with viral load changes after MCT (n=51).

Changes in VL after MCT

Bivariate analysis*

p; B (C.I. 95%)

Multivariate analysis**

p; B (C.I. 95%)

Male sex, n (%) 0.698; -0.118 (-0.727 – 0.491) N.A. ¤

Age (years) 0.961; 0.000 (-0.019 – 0.018) N.A.

Naïve subjects, n (%) 0.297; 0.302 (-0.273 – 0.877) N.A.

Sexual transmission, n (%) 0.022; 0.469 (0.042 – 0.897) 0.672; 0.077 (-0.286 – 0.440)

IDU† transmission, n (%) 0.205; -0.289 (-0.742 – 0.164) N.A.

Time since diagnosis (years) 0.169; -0.021 (-0.050 – 0.009) N.A.

HCV PCR+¥, n (%) 0.243; -0.289 (-0.779 – 0.202) N.A.

CD4+ counts (cells/mL) 0.001; 0.002 (0.001 – 0.003) 0.346; 0.001 (-0.001 – 0.002)

Plasma LogVL¶ (HIV-RNA

cop./mL)

0.523; -0.120 (-0.497 – 0.256) N.A.

LogX4VL&

(HIV-RNA cop./mL) <0.0001; -0.263 (-0.338 – -0.187) <0.0001; -0.234 (-0.322 – -0.146)

LogR5VL§ (HIV-RNA cop./mL) 0.227; -0.089 (-0.253 – 0.074) N.A.

*Bivariate and **multivariate analysis were performed using a linear regression model, variables showing a p<0.1 in the bivariate analysis were 391

included in the multivariate analysis. In the multivariate analysis variables with a p<0.05 were considered statistically significant. ¤ Not applicable. 392

†Injecting drug user. ¥PCR positive for Hepatitis C Virus. ¶ VL: Viral load. & HIV-RNA copies/mL in the U87-CXCR4 cell line well supernatant. § HIV-RNA 393

copies/mL in the U87-CCR5 cell line well supernatant. In this analysis only patients with X4 and R5 virus levels available and with >1000 HIV RNA 394

copies/mL were included (n=51). Values other than number (percent) are expressed as medians (interquartile range [IQR]). 395

396

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

22

397

Figure legends 398

399

Figure 1. Frequency of virological response after MCT. a) Percentage of subjects with a 400

virological response after a short-term MRV exposure (MCT positive). Black bar represents the 401

percentage of MCT positive subjects in the total population. The population was also split in 402

pretreated and naïve patients (grey bars). b) Percentage of MCT positive subjects depending 403

on different baseline CD4+ T-cell strata, values in the “X” axis represent number of cells/ µL. 404

Black bars depict the total number of subjects, while grey bars represent only naïve subjects. 405

We did not observed any naïve subjects in the lower CD4+ T-cell strata, n=0 (<100 and 100-199 406

cells/µL). 407

408

Figure 2. X4 and R5 virus levels and CD4+ T-cell levels depending on treatment category. Log 409

viral load in the U87-X4 and U87-R5 well supernatant were used to express X4 and R5 virus 410

levels depending on: a) MCT positive patients (n=39) presented significantly lower X4 virus 411

levels than MCT negative patients (n=18). b) R5 virus levels were similar in patients with 412

different response after MCT. c) Naïve patients (n=9) presented a trend to have lower X4 virus 413

levels than pretreated patients (n=48). d) In addition, naïve patients (n=19) showed higher 414

CD4+ T-cell levels compared to pretreated patients (n=71) e) Patients with the lower CD4+ T-415

cell strata (<100 (n=11) and 100-199 CD4+ T-cell/µL (n=11)) presented significantly higher X4 416

virus levels than patients with higher CD4+ T-cell strata (200-350 (n=15) and >350 (n=20)). f) 417

On the contrary, R5 virus levels were independent of the CD4+ T-cells strata. Black bar 418

represents the median. Mann-Whitney U-test was used. 419

420

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

� � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �� �� �� �� �� � � � � � � ! " # $ % & ' % ( � � ! ) * $ ) % ' " " � � ! ( � $ � ) '+ ,-./0 1234 54 67

8 9 : : 9 : : ; 9 < < = : : ; > ? : @ > ? ::= :A :B :C :9 : :D E F G H I J K E G L M N F N H I O K E D LP P F N H I D D K D M LE N N H I O K O L P Q F D H I J G K J R L R D F J H I E D K E J LS T

U V N U V NW X Y Z [ \ ] ^ _ ` ` a b c d ef ` ` g h i j _ k i al h m n _ g h i j _ k i aopqr stuvwv xy

on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from

� � � � � � � � � � � � � � � � � � � ����� � �� � � � � � � � � �� ����� !"�#$%" &'() *�+, -./ 0�1� � � � � � � � � � � � � � � � � � � ����� � �2 � 3 4 5 6 7 5 89 :;<=>?@A9BCDA E?FG H:IJ KLM N9O

P Q � � Q � � � � R S � T � ����� � �U � 3 4 5 6 5 7 89 :;<=>VWA9BCDA E?FG H:IJ KLM N9OX Y Z [ Y Z \ [ Z ] ^ \ _ ` Zab a ac a ad a ae a af a ag a ah a ai a aj a ab a a ak l m n o p o o qrst uv wxyzz {| xyzz {} ~��

� � � � � � �

� � � � � � � � � � � � � � ����� � �� � � � � � � �� � � � � � � � � � � � � �� ����� !"�#$%" &'() *�+, -./ 0�1� � � � � � � � � � � � � � ����� � �� � � � � � � �

� �����'�"�#$%" &'() *�+, -./ 0�1 on March 25, 2018 by guest

http://aac.asm.org/

Dow

nloaded from