9/30/2016 Disclosures F Vincenti University of California San Francisco, San Francisco, United States – I have received grants and/or research support from: • Astellas • Alexion • Immucor • Bristol-Myers Squibb • Genentech • Novartis Flavio Vincenti 1 2 Personalized/Individualized Medicine vs Two Important Initiatives in Kidney Precision Medicine Transplantation at UCSF � Personalized medicine has been practiced in � Apply Precision Medicine to transplantation transplantation (i.e. low risk vs high risk) � Use cellular therapies to control alloimmune response � Precision medicine requires new diagnostics or biomarkers to select or modify immunosuppression regimens preferable with novel therapies 3 4 1
9/30/2016 THE NEED FOR PRECISION MEDICINE � Can we apply genomic and biomarker information in Deceased SCD selecting therapy that improves clinical care and Living Donor outcomes in transplantation? � The need: biomarkers that are accurate, reliable and are associated with events and endpoints that may lead to better patient outcome 5 6 Adjusted Rate of Allograft Failure in the USA Without New Biomarkers it will be Difficult to Develop Novel Therapies for Precision Medicine in Transplantation Patients aged ≥18 years at transplant; adjusted by age, gender, and race United States Renal Data System; 2013 Annual Data Report. Available at: www.usrds.org/2013/slides/vol2_chap07_13.zip 7 8 2
9/30/2016 Rear View Mirror Strategies Do Not Work 9 10 Methods Results � The Clinical Trials in Organ Transplantation-09 CTOT � The study was terminated prematurely because of Trial was a randomized, prospective study of non unacceptable rates of AR (4 of 14) and/or de novo sensitized primary recipients of living donor kidney DSAs (5 of 14) in the tacrolimus withdrawal arm. transplants. Subjects received rabbit anti-lymphocyte globulin, tacrolimus, mycophenolate mofetil, and prednisone. � Six months post-transplantation, subjects without de novo donor-specific antibodies (DSAs), AR, or inflammation at protocol biopsy were randomized to wean off or remain on tacrolimus. 11 12 3
9/30/2016 Lack of Biomarkers Has Halted Development Conclusions of Several Promising Drugs � Sotrastaurin – a CNI alternative targeting PKC ….past performance does not predict future results in � Alefacept – targeting memory cells manupulating immunosuppresion regimens.Safe and � ASKP1240 – inhibits the CD40-CD154 pathway effective application of novel regimens or drug elimination require reliable biomarkers. 13 14 Biomarkers and Belatacept 15 16 4
9/30/2016 BENEFIT Belatacept potently and selectively Time to Death or Graft Loss From blocks T-cell activation Randomization to Month 84 1.00 Belatacept 0.90 Selective co-stimulation blocker Survival Probability 0.80 0.70 0.60 0.50 Belatacept MI 0.40 Belatacept LI CsA 0.30 0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 Months N at risk Belatacept MI 219 212 208 206 204 202 199 153 151 149 146 142 135 131 128 Belatacept LI 226 220 218 216 213 209 204 165 161 159 152 151 142 139 137 CsA 221 208 206 202 199 197 186 137 123 117 112 107 102 100 92 • No cell division Month 60 Month 84 • No cytokine P-value HR (95% CI) P-value HR (95% CI) production Bela MI vs. CsA 0.0100 0.521 (0.306, 0.889) Bela MI vs. CsA 0.0225 0.573 (0.348, 0.946) • Anergy Bela LI vs. CsA 0.0045 0.477 (0.277, 0.819) Bela LI vs. CsA 0.0210 0.570 (0.348, 0.935) • Apoptosis. Bela=belatacept; CI=confidence interval; CsA=cyclosporine A; HR=hazard ratio; LI=less intensive; MI=more intensive. 17 18 Kaplan-Meier Analysis of Estimated Mean GFR Over 84 Months: BENEFIT Cumulative De Novo DSA Over Time MEM With Imputation* 90 Estimated mean GFR, mL/min/1.73m 2 50 Belatacept MI 80 Belatacept LI CsA 70 Cumulative Event Rate % 40 60 P-value HR (95% CI) Bela MI vs. CsA <0.0001 0.097 (0.029, 0.320) 50 Bela LI vs. CsA <0.0001 0.245 (0.111, 0.539) 30 40 30 Belatacept MI 20 20 Belatacept LI (95% CI) 10 P<0.001 for overall treatment effect CsA 10 0 0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 Month 0 0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 Belatacept MI Belatacept LI CsA Months GFR Difference vs. CsA GFR Difference vs. CsA GFR N at risk Month 12 64.3 14.5 63.8 14.0 49.8 Belatacept MI 219 182 174 168 163 158 156 148 147 144 141 136 130 127 124 Belatacept LI 226 187 183 180 178 169 165 158 154 152 145 143 138 133 130 Month 36 64.8 20.5 65.2 20.9 44.3 CsA 215 186 171 159 150 143 136 124 115 108 103 97 92 90 85 Month 60 63.9 24.8 65.2 26.1 39.1 Month 84 62.0 25.4 63.3 26.7 36.6 *GFR values that were missing due to death or graft loss were imputed as 0. Bela=belatacept; CI=confidence interval; CsA=cyclosporine A; DSA=donor-specific antibody; HR=hazard ratio; LI=less intensive; 19 20 CsA=cyclosporine A; GFR=glomerular filtration rate; LI=less intensive; MEM=mixed effects modeling; MI=more intensive. MI=more intensive. 5
9/30/2016 BENEFIT Acute Rejection Belatacept MI Belatacept LI CsA (N=219) (N=226) (N=221) 100 Banff grade of acute rejection*, n Probability of Acute Rejection, % Mild acute (IA) 7 (3.2) 4 (1.8) 6 (2.7) Mild acute (IB) 3 (1.4) 8 (3.5) 7 (3.2) 80 Moderate acute (IIA) 18 (8.2) 17 (7.5) 7 (3.2) Can we apply precision Moderate acute (IIB) 22 (10.0) 10 (4.4) 3 (1.4) Severe acute (III) 3 (1.4) 1 (0.4) 0 (0.0) 60 medicine to belatacept therapy? P-value HR (95% CI) Belatacept MI Bela MI vs. CsA 0.0001 2.649 (1.596, 4.397) Belatacept LI 40 Bela LI vs. CsA 0.0302 1.905 (1.124, 3.232) CsA 20 0 0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 Months N at risk Belatacept MI 219 154 147 144 140 137 136 128 127 125 122 117 111 108 105 Belatacept LI 226 168 164 162 160 157 155 149 144 142 137 135 130 125 122 CsA 221 180 167 156 147 141 135 123 115 110 106 101 96 94 89 For patients with an event, the time to event was defined as minimum of event date and date of last dose (transplant date for non-treated patients) plus 56 days. For patients without an event, the time to event was defined as last follow-up date for on-treatment patients, date of last dose plus 56 days for off-treatment patients, and transplant date plus 56 days for non-treated patients. Between Month 36 and Month 84, 0 belatacept MI-treated, 1 (grade IIA) belatacept LI-treated, and 2 (grade IA [n=1], grade IIA [n=1]) CsA-treated patients experienced acute rejection. *Three patients (n=1 [grade IIA], belatacept MI; n=2, CsA [n=1, grade IA; n=1, grade IIA]) experienced acute rejection more than 56 days after treatment discontinuation. Bela=belatacept; CI=confidence interval; CsA=cyclosporine A; HR=hazard ratio; LI=less intensive; MI=more intensive. 21 22 UCSF Histology Representative images from a Belatacept (a) and CNI (b) patient with acute cellular rejection featuring CD57 (brown) and CD4 (red) positive cells in the cellular infiltrate. Semiquantitative analysis showed a higher density of CD57 positive cells in the Belatacept patients. 23 24 6
9/30/2016 APPLYING PRECISION MEDICINE Personalizing Costimulation CD4 gate CD4 TEMRA gate Blockade Efficacy in Renal TEMRA- TEMRA+ Transplantation (PACER) Total=105 19.2% TEMRA CCR7 CD57 Select patients for belatacept who 9.75% lack CD57+ PD1- CD4+ cells by flow PD-1 CD45RA and post transplant monitoring with kSORT 25 kSORT (Kidney Solid Organ Response Test) *moderate %CD57+PD1- in CD4 *very high %CD57+PD1- in *low %CD57+PD1- in CD4 TEMRA TEMRA CD4 TEMRA Application of the kSORT blood assay for the non-invasive prediction of histological rejection Example of 3 Patients with Different Risk Profiles for Belatacept 27 28 7
9/30/2016 kSORT validated in pediatric and adult populations, Kidney- Solid Organ Response Test (kSORT) LD and DD recipients; independent of Rx The answer in a drop of blood ….. N=558 biopsy matched blood samples profiled by QPCR 8 programs; US, EU, Mexico , ADULT and 17 gene PCR test 17 gene PCR test PEDS measuring graft measuring graft immune immune activation by activation by CFLAR, DUSP1, IFNGR1, ITGAX, MAPK9, NAMPT, NKTR, RNA isolated RNA isolated N=367 biopsy PSEN1,CEACAM4, EPOR, GZMK, matched blood from whole from whole RARA, RHEB, RXRA, SLC25A37, samples profiled by RNF130, RYBP blood blood QPCR 12 programs; US,, PEDS Roedder et al, Plos Medicine, 2014; Li et al, AJT, 2012 29 30 QPCR Validation: SNSO1 NIH Trial N=367 blood samples matched with renal allograft biopsies, central read (R. Sibley, Stanford); NIH SNSO1 clinical trial BLINDED ANALYSIS BY Rho/NIH 31 32 8
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