Correlations of pre-art HIV-DNA with outcome in 1st-line treated ART patients

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1 SESSION 2 ICONA research in HIV and HIV-HCV coinfection Chairs: G. Angarano, C.F. Perno Correlations of pre-art HIV-DNA with outcome in 1st-line treated ART patients Francesca Ceccherini-Silberstein Università degli Studi di Roma Tor Vergata Dipartimento di Medicina Sperimentale e Chirurgia Cattedra di Virologia Roma 29 gennaio 2016

2 ..Patients starting first line HAART with viremia >500,000 copies/ml show a lower and delayed rate of virological response compared with those having lower viremia ranks Probalility to achieve virological response (as HIV RNA<50 copies/ml) after starting HAART Baseline HIV-RNA ranges (cps/ml) Median Time (95% CI) to achieve VU (weeks) Probability Of VU at 48 weeks >500K 23 (21-25) 83% 300K-500K 22 (21-24) 93% 100K-300K 18 (17-20) 93% 30K-100K 15 (14-16) 98% <30K 10 (9-11) 99% P<0.001 at log-rank test K: thousand Time (weeks) No. at risk From Santoro et al., Antivir Ther. 2013

3 HIV DNA levels before and during highly active antiretroviral therapy have been proposed as a new tool for monitoring treatment efficacy

4 Journal of Clinical Microbiology ART-naïve patients achieved virological suppression <50 copies/ml with their first line therapy within 6 months, and maintained always undetectable plasma viremia, with no more than one viral blip.

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6 + 17,75 HIV DNA copies expected 210, , , , ,11 HIV DNA copies expected Ceccherini-Silberstein et al., to be presented at CROI 2016 Methods: HIV + pts of the ICONA cohort, starting 1st-line ART, for whom PBMC or blood sample was stored at BL were analysed. Total HIV-DNA was quantified by using a modified version of the COBAS AmpliPrep/COBAS TaqMan HIV-1 Test, v2.0 (Surdo et al 2015). Results were normalized by CD4 + cells number. A B 10,000,00 0 1,000,00 100,000 R 2 = Experiments: , , ^6 10^5 10^4 10^3 10^2 10^1 8e5 (cells number) ,000 10, ,000 1,000,00 10,000,00 HIV DNA copies observed 0 Figure 2. A) Quantitative HIV DNA in 8e5/LAV cells. The histogram represents results from the best 3 experiments (mean ± SD) in black. Each exctract (200ul) was filled up to 1100ul with human seronegative plasma centrifuged and 0.22μm filtered or negative control from Roche both diluted 1:2 with PS; PS = physiological saline solution.. B) HIV DNA titration curve: Ten different independent quantification results (experiments 1-10) were used to build the titration curve. PL = human seronegative plasma centrifuged and 0.22μm filtered or negative control from Roche both diluted with PS; PS = physiological saline solution. + = in the experiments 2,3 and 4 the results for 10^1 copies were Target Not Detected (TND). Surdo et al Clin Chem Lab Med 2015

7 Ceccherini-Silberstein et al., to be presented at CROI 2016 Methods: HIV + pts of the ICONA cohort, starting 1st-line ART, for whom PBMC or blood sample was stored at BL were analysed. Total HIV-DNA was quantified by using a modified version of the Cobas HIV-1 test (Surdo et al 2015). Results were normalized by CD4 + cells number. Associations between BL DNA levels and pts BL characteristics were evaluated using chi-square/signed-rank test and Pearson correlation. In the overall cohort and in a subset of pts starting modern ART (after 2004), standard survival analysis was used to examine the association between BL HIV-DNA and pre-defined time to event endpoints: viral load (VL) 50 cp/ml, virological rebound defined by a confirmed VL>50 cp/ml after VL 50 cp/ml, gain in CD4 count >200 cells/mm 3 after ART and AIDS diagnosis or serious non-aids or death. Kaplan-Meier curves and Cox regression models were also used.

8 Ceccherini-Silberstein et al., to be presented at CROI 2016 Correlations of baseline HIV-DNA levels with viro-immunologic parameters in 607 HAART naïve patients

9 Log HIV-DNA per 10^6 CD4 Ceccherini-Silberstein et al., to be presented at CROI 2016 Correlations of pre-art HIV-DNA with BL viro-immunologic parameters in 1 st -line treated ART patients A strong and significant correlation (Pearson) was observed with BL HIV-RNA (Rho=+0.41), CD4 (Rho=-0.48) and CD4/CD8 ratio (Rho=-0.40) P <0.001 P <0.001 P <0.001 HIV-RNA log10 copies/ml CD4 count cells/mm3 CD4/CD8 count cells/mm3

10 Log HIV-DNA per 10^6 CD4 Ceccherini-Silberstein et al., to be presented at CROI 2016 Correlations of pre-art HIV-DNA with BL viro-immunologic parameters in 1 st -line treated ART patients A less strong correlation was observed with IL-6 (Rho=+0.15), scd14 (Rho=+0.11) and CD8 (Rho=-0.09) P <0.03 P <0.03 P <0.03 IL-6 log10 ng/ml CD14 log10 ng/ml CD8 count cells/mm3

11 Ceccherini-Silberstein et al., to be presented at CROI 2016 Correlations of pre-art HIV-DNA with outcome in 1 st -line treated ART patients Patients with higher baseline HIV-1 DNA showed a lower and delayed rate of virological response compared with those having lower HIV DNA ranks After 2004 By week 48, 393/607 (65%) achieved HIV- RNA 50 cp/ml and 290/395 (73%) in patients starting ART after 2004.

12 Ceccherini-Silberstein et al., to be presented at CROI 2016 Higher levels of total HIV DNA at baseline correlated with an increased risk of virological rebound After 2004

13 Ceccherini-Silberstein et al., to be presented at CROI 2016 BL HIV-DNA can predict virological and clinical outcome of 1 st -line ART, although not independently of plasma VL and CD4 count Table hazard ratios of various outcomes per log /CD4 HIV DNA higher levels in patients starting 1st line ART after 2004

14 Percentages of patients A strong and significant correlation between HIV DNA levels and the status of patients according to HIV-RNA and CD4 cells 100% 80% 60% 85% HIV-DNA copies / 10 6 CD4 cells <10,000 >10,000 70% 63% 62% p<0.001* 62% 85% 40% 30% 37% 38% 38% 20% 15% 15% No. of patients CD4 cell count (cells/mm 3 ) 0% > <250 > <250 HIV-RNA copies/ml <100, ,000 *By Chi-squared test for trend.

15 Percentages of patients A strong and significant correlation between HIV DNA levels and the status of patients according to HIV-RNA and CD4 cells 100% 80% 60% 85% HIV-DNA copies / 10 6 CD4 cells <10,000 >10,000 70% p=0.016* 63% 62% 62% 85% 40% 30% 37% 38% 38% 20% 15% 15% No. of patients CD4 cell count (cells/mm 3 ) 0% > <250 > <250 HIV-RNA copies/ml <100, ,000 *By Chi-squared test.

16 Percentages of patients A strong and significant correlation between HIV DNA levels and the status of patients according to HIV-RNA and CD4 cells 100% 80% 60% 85% HIV-DNA copies / 10 6 CD4 cells <10,000 >10,000 70% p<0.001* 63% 62% 62% 85% 40% 30% 37% 38% 38% 20% 15% 15% No. of patients CD4 cell count (cells/mm 3 ) 0% > <250 > <250 HIV-RNA copies/ml <100, ,000 *By Chi-squared test.

17 Percentages of patients A strong and significant correlation between HIV DNA levels and the status of patients according to HIV-RNA and CD4 cells 100% 80% 60% 85% HIV-DNA copies / 10 6 CD4 cells <10,000 >10,000 70% 63% 62% p<0.001* 62% 85% 40% 30% 37% 38% 38% 20% 15% 15% No. of patients CD4 cell count (cells/mm 3 ) 0% > <250 > <250 HIV-RNA copies/ml <100, ,000 *By Chi-squared test.

18 Median (IQR) HIV-DNA log 10 copies / 10 6 CD4 cells A strong and significant correlation between HIV DNA levels and the status of patients according to HIV-RNA and CD4 cells *By Jonckheere-Terpstra test for increasing trend. IQR: interquartile range. *By Mann-Whitney test.. p<0.001* No. of patients CD4 cell count (cells/mm 3 ) > <250 > <250 HIV-RNA copies/ml <100, ,000

19 Conclusions Our study shows the potential use of a modified COBAS TaqMan HIV-1 Test for the rapid quantification of total HIV DNA in whole blood or PBMC. Results can be normalized by CD4 + cells number. Pre-ART HIV-DNA content in CD4+ cells strongly correlated with baseline viroimmunologic parameters and inflammation markers. Baseline HIV-DNA was also found to predict virological and clinical outcome of 1stline ART, although not independently of plasma HIV RNA and CD4 count. HIV-RNA quantification in plasma is a useful indicator of extent of viral replication, and remains today a key parameter for assessing the risk of progression, as well as the efficacy of antiviral therapy. High viral load at baseline is consistently associated with higher risk of virological failure. HIV-DNA quantification can be used for measuring the viral burden. Can we individualize therapy for initiation / maintenance /simplification according to HIV DNA levels? HIV-1 DNA is a significant predictor of the duration of viral remission and magnitude of the initial rebound following treatment interruption. Other studies are needed to show the utility of HIV DNA monitoring in the management of HIV patients.

20 Acknowledgements: Icona Foundation BOARD OF DIRECTORS A d Arminio Monforte (Vice-President), M Andreoni, G Angarano, A Antinori, F Castelli, R Cauda, G Di Perri, M Galli, R Iardino, G Ippolito, A Lazzarin, CF Perno, F von Schloesser, P Viale SCIENTIFIC SECRETARY A d Arminio Monforte, A Antinori, A Castagna, F Ceccherini-Silberstein, A Cozzi-Lepri, E Girardi, S Lo Caputo, C Mussini, M Puoti STEERING COMMITTEE M Andreoni, A Ammassari, A Antinori, C Balotta, A Bandera, P Bonfanti, S Bonora, M Borderi, A Calcagno, L Calza, MR Capobianchi, A Castagna, F Ceccherini-Silberstein, A Cingolani, P Cinque, A Cozzi-Lepri, A d Arminio Monforte, A De Luca, A Di Biagio, E Girardi, N Gianotti, A Gori, G Guaraldi, G Lapadula, M Lichtner, S Lo Caputo, G Madeddu, F Maggiolo, G Marchetti, S Marcotullio, L Monno, C Mussini, S Nozza, M Puoti, E Quiros Roldan, R Rossotti, S Rusconi, MM Santoro, A Saracino, M Zaccarelli. STATISTICAL AND MONITORING TEAM A Cozzi-Lepri, I Fanti, L Galli, P Lorenzini, A Rodano, M Shanyinde, A Tavelli BIOLOGICAL BANK INMI F. Carletti, S. Carrara, A. Castrogiovanni, A. Di Caro, F. Petrone, G. Prota, S. Quartu, S. Truffa PARTICIPATING PHYSICIANS AND CENTERS ROCHE DIAGNOSTICS UNI MILANO E Merlini M Surdo M Campus D Di Carlo CF Perno A Giacometti, A Costantini, C Valeriani (Ancona); G Angarano, L Monno, C Santoro (Bari); F Maggiolo, C Suardi (Bergamo); P Viale, E Vanino, G Verucchi (Bologna); F Castelli, E Quiros Roldan, C Minardi (Brescia); T Quirino, C Abeli (Busto Arsizio); PE Manconi, P Piano (Cagliari); B Cacopardo, B Celesia (Catania); J Vecchiet, K Falasca (Chieti); L Sighinolfi, D Segala (Ferrara); F Mazzotta, F Vichi (Firenze); G Cassola, C Viscoli, A Alessandrini, N Bobbio, G Mazzarello (Genova); C Mastroianni, V Belvisi (Latina); P Bonfanti, I Caramma (Lecco); A Chiodera, AP Castelli (Macerata); M Galli, A Lazzarin, G Rizzardini, M Puoti, A d Arminio Monforte, AL Ridolfo, R Piolini, A Castagna, S Salpietro, L Carenzi, MC Moioli, C Tincati, G Marchetti (Milano); C Mussini, C Puzzolante (Modena); A Gori, G Lapadula (Monza); N Abrescia, A Chirianni, G Borgia, F Di Martino, L Maddaloni, I Gentile, R Orlando (Napoli); F Baldelli, D Francisci (Perugia); G Parruti, T Ursini (Pescara); G Magnani, MA Ursitti (Reggio Emilia); R Cauda, M Andreoni, A Antinori, V Vullo, A Cristaudo, A Cingolani, G Baldin, S Cicalini, L Gallo, E Nicastri, R Acinapura, M Capozzi, R Libertone, S Savinelli, A Latini (Roma); M Cecchetto, F Viviani (Rovigo); MS Mura, G Madeddu (Sassari); A De Luca, B Rossetti (Siena); P Caramello, G Di Perri, GC Orofino, S Bonora, M Sciandra (Torino); M Bassetti, A Londero (Udine); G Pellizzer, V Manfrin (Vicenza).