Transplant Webinar Series: Ep. 9 Biomarkers for Post-Transplant Immune Injury

Transcription

1 Transplant Webinar Series: Ep. 9 Biomarkers for Post-Transplant Immune Injury

2 Future Webinars Link to register: All Content 2015 Immucor, Inc.

3 Handouts Program-Handouts.aspx All Content 2015 Immucor, Inc.

4 Continuing Education ABHI, ASCLS/P.A.C.E., Florida and California Credits 1.0 Contact Hour or 0.15 continuing education credits (CECs) awarded Each attendee must register to receive CE credits at: Registration deadline is 12 October 2018 Certificates will be sent via only to those who have registered by 26 October 2018 All Content 2015 Immucor, Inc.

5 Presentation Recording Session will be recorded and posted to Immucor s LEARN site. Access information will be sent to each registrant when the recording becomes available CE credits will be issued to anyone who listens to the recording within one year of the original presentation date (today). To access Learn go to: learn.immucor.com All Content 2015 Immucor, Inc.

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7 Questions? You are all muted Q&A following session - Type in questions All Content 2015 Immucor, Inc.

8 Course content is for information and illustration purposes only. Immucor makes no representation or warranties about the accuracy or reliability of the information presented and this information is not to be used for clinical or maintenance evaluations. The opinions contained in this presentation are those of the presenter and do not necessarily reflect those of Immucor. All Content 2015 Immucor, Inc.

9 Immune monitoring after kidney transplantation Maarten Naesens Maarten Naesens, MD PhD 52 nd ERA-EDTA meeting University of Leuven, Belgium London, May 2015

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11 Scoping Paper Work Programme : Personalised Medicine is one of the five research areas within Priority 1

12 The paradigm of personalized medicine PREDICT DIAGNOSE WAIT PREVENT TREAT

13 The paradigm of personalized medicine PREDICT DIAGNOSE PREVENT TREAT

14 Personalized medicine builds on data and s Traditional medicine All patients same treatment Personalized medicine Predictive Data / Biomarkers Predicted benefit from treatment X, not Y Predicted benefit from treatment Y, not X

15 All patients Patients with confirmed disease Risk/susceptibility Risk/susceptibility markers Prognostic Low risk for disease High risk for disease Low risk / good prognosis High risk / bad prognosis Risk/susceptibility Non-invasive diagnostic Predictive Low disease probability High disease probability Predicted benefit from treatment X, not Y Predicted benefit from treatment Y, not X Non-invasive diagnostic Invasive diagnostic Start treatment X Start treatment Y No disease confirmation Disease confirmation Safety Pharmacodynamic / response Monitoring - Disease activity - Pharmacokinetics (exposure) Naesens & Anglicheau J Am Soc Nephrol 2018

16 All patients Patients with confirmed disease Risk/susceptibility Prognostic Low risk for disease High risk for disease Low risk / good prognosis High risk / bad prognosis Risk/susceptibility Non-invasive diagnostic Non-invasive diagnostic markers Predictive Low disease probability High disease probability Predicted benefit from treatment X, not Y Predicted benefit from treatment Y, not X Non-invasive diagnostic Invasive diagnostic Start treatment X Start treatment Y No disease confirmation Disease confirmation Safety Pharmacodynamic / response Monitoring - Disease activity - Pharmacokinetics (exposure) Naesens & Anglicheau J Am Soc Nephrol 2018

17 All patients Patients with confirmed disease Risk/susceptibility Prognostic Low risk for disease High risk for disease Low risk / good prognosis High risk / bad prognosis Risk/susceptibility Non-invasive diagnostic Predictive Low disease probability High disease probability Predicted benefit from treatment X, not Y Predicted benefit from treatment Y, not X Non-invasive diagnostic Invasive diagnostic Invasive diagnostic Start markers treatment X Start treatment Y No disease confirmation Disease confirmation Safety Pharmacodynamic / response Monitoring - Disease activity - Pharmacokinetics (exposure) Naesens & Anglicheau J Am Soc Nephrol 2018

18 All patients Patients with confirmed disease Risk/susceptibility Prognostic Prognostic markers Low risk for disease High risk for disease Low risk / good prognosis High risk / bad prognosis Risk/susceptibility Non-invasive diagnostic Predictive Low disease probability High disease probability Predicted benefit from treatment X, not Y Predicted benefit from treatment Y, not X Non-invasive diagnostic Invasive diagnostic Start treatment X Start treatment Y No disease confirmation Disease confirmation Safety Pharmacodynamic / response Monitoring - Disease activity - Pharmacokinetics (exposure) Naesens & Anglicheau J Am Soc Nephrol 2018

19 All patients Patients with confirmed disease Risk/susceptibility Prognostic Low risk for disease High risk for disease Low risk / good prognosis High risk / bad prognosis Risk/susceptibility Non-invasive diagnostic Predictive markers Predictive Low disease probability High disease probability Predicted benefit from treatment X, not Y Predicted benefit from treatment Y, not X Non-invasive diagnostic Invasive diagnostic Start treatment X Start treatment Y No disease confirmation Disease confirmation Safety Pharmacodynamic / response Monitoring - Disease activity - Pharmacokinetics (exposure) Naesens & Anglicheau J Am Soc Nephrol 2018

20 All patients Patients with confirmed disease Risk/susceptibility Prognostic Low risk for disease High risk for disease Low risk / good prognosis High risk / bad prognosis Risk/susceptibility Non-invasive diagnostic Predictive Low disease probability High disease probability Predicted benefit from treatment X, not Y Predicted benefit from treatment Y, not X Non-invasive diagnostic Invasive diagnostic Start treatment X Start treatment Y No disease confirmation Disease confirmation Safety, pharmacodynamic, monitoring markers Safety Pharmacodynamic / response Monitoring - Disease activity - Pharmacokinetics (exposure) Naesens & Anglicheau J Am Soc Nephrol 2018

21 All patients Patients with confirmed disease Risk/susceptibility Risk/susceptibility markers Prognostic markers Prognostic Low risk for disease High risk for disease Low risk / good prognosis High risk / bad prognosis Non-invasive Risk/susceptibility diagnostic markers Non-invasive diagnostic Low disease probability High disease probability Predicted benefit from treatment X, not Y Predictive Predictive markers Predicted benefit from treatment Y, not X Non-invasive diagnostic Invasive diagnostic Invasive diagnostic markers Start treatment X Start treatment Y No disease confirmation Disease confirmation Safety Pharmacodynamic / response Safety, pharmacodynamic, monitoring markers Monitoring - Disease activity - Pharmacokinetics (exposure)

22 Risk/susceptibility markers Prognostic markers Non-invasive diagnostic markers PERSONALIZED MEDICINE Predictive markers Invasive diagnostic markers Safety, pharmacodynamic, monitoring markers

23 KIDNEY TRANSPLANTATION

24 Risk markers Diagnostic markers Prognostic markers Predictive markers

25 Risk markers

26 We have several widely used susceptibility/risk s in kidney transplantation Number of HLA mismatches Pretransplant PRA% Pretransplant DSA De novo DSA occurrence Success story of HLA genotyping and antibody profiling TRANSPLANTATION MEDICINE = FRONTRUNNER IN PERSONALIZED MEDICINE

27 More personalization in allocation (AM program) leads to better outcome *AM = Eurotransplant Acceptable Mismatch program Heidt et al Kidney Int 2018

28 More personalization in allocation (AM* program) leads to better outcome *AM = Eurotransplant Acceptable Mismatch program Heidt et al Kidney Int 2018

29 More personalization in allocation: a role of high-resolution sequencing? Low resolution Acceptable MM at the antigen level High/allelic resolution Acceptable MM at the epitope level

30 More personalization in allocation: a role of high-resolution sequencing? Low resolution Acceptable MM at the antigen level High/allelic resolution Acceptable MM at the epitope level

31 New risk s in the pipeline for kidney transplantation? Epitope mismatch load 1 Genetic assessment for ahus recurrence Urinary or serum supar for FSGS recurrence 2 FSGS recurrence panel 3 PLA2R and THSD7A antibodies for recurrence of membranous glomerulopathy 4,5 Donor-reactive T-cell response 6 Risk markers 1 Wiebe et al Transplantation 2016; 2 Franco Palacios et al Transplantation 2013; 3 Delville et al Sci Transl Med 2014; 4 Sprangers et al Transplant Rev 2013; 5 Tomas et al J Clin Invest 2016; 6 Gandolfini et al Plos One 2018

32 Risk markers

33 Risk markers Diagnostic markers

34 We have several widely used diagnostic s in kidney transplantation Non-invasive: Serum creatinine/egfr Proteinuria Polyomavirus PCR Urinary mrna markers Urinary mirna markers Urinary protein markers Blood mrna markers

35 Non-invasive diagnostic markers in the pipeline for kidney transplantation 100 Urinary mrna Specificty for acute rejection (%) Sensitivity for acute rejection (%) mrna Perforin Granzyme B PI-9 CD103 FOXP3 CXCL10 NKG2D TIM3 Granulysin Multigene signature Naesens and Anglicheau, J Am Soc Nephrol 2018

36 Non-invasive diagnostic markers in the pipeline for kidney transplantation 100 Urinary mrna Specificty for acute rejection (%) Sensitivity for acute rejection (%) mrna Perforin Granzyme B PI-9 CD103 FOXP3 CXCL10 NKG2D TIM3 Granulysin Multigene signature Naesens and Anglicheau, J Am Soc Nephrol 2018

37 Non-invasive diagnostic markers in the pipeline for kidney transplantation 100 Urinary proteins Specificty for acute rejection (%) Sensitivity for acute rejection (%) Proteins CXCL9 CXCL10 Fractalkine Naesens and Anglicheau, J Am Soc Nephrol 2018

38 Non-invasive diagnostic markers in the pipeline for kidney transplantation 100 Blood mrna Specificty for acute rejection (%) Sensitivity for acute rejection (%) mrna Granzyme B Perforin FasL HLA-DRA Multigene signature Naesens and Anglicheau, J Am Soc Nephrol 2018

39 Non-invasive diagnostic markers in the pipeline for kidney transplantation 100 Blood mrna Trugraf Specificty for acute rejection (%) Sensitivity for acute rejection (%) mrna Granzyme B Perforin FasL HLA-DRA ksort Multigene signature Naesens and Anglicheau, J Am Soc Nephrol 2018

40 The TruGraf assay needs further validation 200 peripheral blood mrna gene-set - early-access clinical programs started - large interventional trials ongoing - prospective, randomized, multi-center clinical trial ongoing Kurian et al Am J Transplant 2014

41 CTOT-08 study yields a novel 57-gene marker for subclinical rejection 57-gene marker Diagnostic accuracy for subclinical TCMR Training set (N=530): NPV: 88% PPV: 61% Validation set (N=138): NPV: 78-80% Sens: 48% PPV: 47-51% Friedewald et al Am J Transplant 2018

42 The ksort assay needs further validation 17 gene-set with published validation in case-control setting Roedder et al PLOS Med 2014

43 We have several widely used diagnostic s in kidney transplantation Non-invasive: Serum creatinine/egfr Proteinuria Polyomavirus PCR Clinical value of novel markers?

44 We have several widely used diagnostic s in kidney transplantation Non-invasive: Serum creatinine/egfr Proteinuria Polyomavirus PCR Clinical value of novel markers? Invasive: Histology of protocol biopsies Histology of for-cause (indication) biopsies

45 Currently used diagnostic s don t capture subclinical injury Creatinine Proteinuria Diagnostic threshold Subclinical Acute dysfunction acute rejection Chronic dysfunction Time BX for cause I-BX I-BX I-BX Nankivell et al. NEJM 2003 Lerut et al. Transplantation 2007 Naesens et al. JASN 2009 Ters et al. AJT 2013

46 Currently used diagnostic s don t capture subclinical injury Creatinine Proteinuria Treatment Diagnostic threshold Subclinical Acute dysfunction acute rejection Acute pathology Chronic dysfunction BX for cause Time Nankivell et al. NEJM 2003 Lerut et al. Transplantation 2007 Naesens et al. JASN 2009 Ters et al. AJT 2013

47 Currently used diagnostic s don t capture subclinical injury Creatinine Proteinuria Treatment Diagnostic threshold Subclinical Acute dysfunction acute rejection Acute pathology BX for cause Protocol BX P-BX P-BX P-BX P-BX Chronic pathology Time Nankivell et al. NEJM 2003 Lerut et al. Transplantation 2007 Naesens et al. JASN 2009 Ters et al. AJT 2013

48 Immune injury in kidney transplant biopsies is defined according to the Banff classification Haas et al. Am J Transplant 2018

49 Kidney transplant histology is problematic as a diagnostic Shinstock, Sapir-Pichhadze, Naesens et al Am J Transplant 2018

50 Innovative diagnostic s for transplant injury are being developed Haas et al. Banff 2017 paper - Am J Transplant 2018

51 Invasive diagnostic markers in the pipeline for kidney transplantation From MMDx website:

52 Intrarenal NK cell mrna signatures accurately reflect ABMR disease activity 10 8 * NK cells total Activated NK cells Resting NK cells 100 ABMR vs NR Total NK cells 6 4 *** *** * * Sensitivity% /23/45/6 0 1/23/45/6 0 1/23/45/6 Microcirculation inflammation % - Specificity% AUC = 0.98 P = 1.1E-08 Yazdani, Callemeyn et al Kidney Int In press

53 Intrarenal NK cell mrna signatures accurately reflect ABMR disease activity and graft outcome NK cells + Graft survival (%) 50 Low NK cells+ 196 High NK cells+ 86 Log-rank P = 1.7E-03 HR = 3.60 [ ] Low NK cells+ High NK cells Days after biopsy Sensitivity% 50 AUC = 0.74 P = 2.2E % - Specificity% Graft failure 1-year post-biopsy Yazdani, Callemeyn et al Kidney Int In press

54 Risk markers Diagnostic markers

55 Risk markers Diagnostic markers Prognostic markers

56 egfr at 1 year is associated with graft outcome, and is a fair prognostic marker 100 MRDR egfr at 1 year and graft failure >70 ml/min 100 ROC for graft failure 5 year after biopsy according to 1 year MDRD egfr Graft survival (%) log-rank P< Time after biopsy (years) ml/min ml/min ml/min ml/min ml/min <20 ml/min Sensitivity % % - Specificity% AUC=0.77 p< Naesens et al (Unpublished)

57 Proteinuria is a risk factor for graft failure but a poor prognostic marker B Percent survival No. at risk log-rank P < Biopsy time points (N=1335) Time after biopsy (years) Proteinuria < 0.3 g/24h g/24h g/24h >3.0 g/24h C True Positive Fraction (%) Biopsy time points (N=1335) 20 AUC=0.66 (95% CI ) P < Naesens M et al J Am Soc Nephrol 2015

58 The CADI score is a bad prognostic marker, despite the association with graft failure All biopsies: ROC for 5y graft loss 100 Graft survival (%) CADI score in indication biopsy log-rank P< Time after biopsy (years) N=1335 indication biopsies Naesens et al (Unpublished) CADI 0 CADI 1 CADI 2-3 CADI 4-5 CADI 6-7 CADI 8-9 CADI >9 Sensitivity % Sensitivity % % - Specificity% AUC=0.65 p< Late biopsies: ROC for 5y graft loss (>1y) % - Specificity% AUC=0.76 p<0.0001

59 We lack good prognostic s in kidney transplantation egfr Proteinuria Histology have on itself insufficient prognostic capacity We do not identify those the patients that need treatment

60 Several prognostic markers are independent risk factors for graft failure Hazard ratio (95% CI) for kidney graft loss Proteinuria vs. <0.3 g/24h vs. <0.3 g/24h >3.0 vs. <0.3 g/24h egfr microcirc. inflammation IFTA Transplant glomerulopathy GNF PVAN vs. >45 ml/min/m vs. >45 ml/min/m2 <15 vs. >45 ml/min/m2 g+ptc 2 vs. <2 Banff grade 1 vs. 0 Banff grade 2-3 vs. 0 Banff grade 1 vs. 0 Banff grade 2-3 vs. 0 Present vs. absent Present vs. absent Prognostic model? Decide who to treat From Naesens et al J Am Soc Nephrol 2015

61 Mathematical integration allows estimating individual prognosis Loupy et al under review

62 Mathematical integration allows estimating individual prognosis Loupy et al under review

63 Prognostic markers in the pipeline for kidney transplantation Edmonton ABMR molecular score 1 Edmonton classifier for graft loss 2 GOCAR 13-geneset 3 1 Loupy et al JASN 2013; 2 Einecke et al J Clin Invest 2010; 3 O Connell Lancet 2016

64 Molecular ABMR score predicts graft failure better than histology of ABMR INTERCOM STUDY (multicenter) ABMR Score - Histology - ABMR Score - Histology + ABMR Score + Histology + ABMR Score + Histology - ABMR score for graft loss: Sensitivity = 75% Specificity = 81% PPV = 48% NPV = 93% Halloran et al Am J Transplant 2013 ROC AUC=0.81

65 Molecular Risk score predicts graft outcome better than histology or proteinuria Low risk score Survival probability High risk score AUC=0.83 Time after biopsy Einecke et al J Clin Invest 2010 Risk score for graft loss: Early biopsies: Late biopsies: Sensitivity = 100% Sensitivity = 83% Specificity = 41% Specificity = 63% PPV = 5% PPV = 47% NPV = 100% NPV = 90%

66 GoCAR score predicts CADI better than clinical and pathological parameters O Connell, Zhang et al Lancet 2016

67 GoCAR score predicts graft outcome with reasonable accuracy O Connell, Zhang et al Lancet 2016 GoCAR score for graft loss: PPV =? NPV =? ROC AUC=0.84

68 Risk markers Diagnostic markers Prognostic markers

69 Risk markers Diagnostic markers Prognostic markers Predictive markers

70 Prognostic test = risk for graft failure Predictive test = success of therapy Patients with confirmed disease Prognostic Prognostic Low risk / good prognosis High risk / bad prognosis Naesens & Anglicheau J Am Soc Nephrol 2018

71 Prognostic test = risk for graft failure Predictive test = success of therapy Patients with confirmed disease Prognostic Prognostic Low risk / good prognosis High risk / bad prognosis Predictive Predictive Predicted benefit from treatment X, not Y Predicted benefit from treatment Y, not X Naesens & Anglicheau J Am Soc Nephrol 2018 Start treatment X Start treatment Y

72 Prognostic test = risk for graft failure Predictive test = success of therapy Patients with confirmed disease Prognostic Prognostic Low risk / good prognosis High risk / bad prognosis Predictive Predictive Predicted benefit from treatment X, not Y Predicted benefit from treatment Y, not X Naesens & Anglicheau J Am Soc Nephrol 2018 Start treatment X Start treatment Y

73 Risk/susceptibility markers Prognostic markers Non-invasive diagnostic markers PERSONALIZED MEDICINE Predictive markers Invasive diagnostic markers Safety, pharmacodynamic, monitoring markers KIDNEY TRANSPLANTATION

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78 Continuing Education ABHI, ASCLS/P.A.C.E., Florida and California Credits 1.0 Contact Hour or 0.15 continuing education credits (CECs) awarded Each attendee must register to receive CE credits at: Registration deadline is 12 October 2018 Certificates will be sent via only to those who have registered by 26 October 2018 All Content 2015 Immucor, Inc.

79 Future Webinars Link to register: All Content 2015 Immucor, Inc.

80 All Content 2015 Immucor, Inc.