Timothy Hughes_COLT 2014_Session2 - 3

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Risk Profiles, Molecular Targets and Pharmacokinetics :

Risk Profiles, Molecular Targets and Pharmacokinetics Timothy Hughes SAHMRI SA Pathology, University of Adelaide

Optimising CML Therapy:

Optimising CML Therapy Towards an accurate Risk Profile Early Molecular Response Kinase inhibition/ Pharmacokinetics

Optimising CML Therapy:

Optimising CML Therapy Towards an accurate Risk Profile Early Molecular Response Kinase inhibition/ Pharmacokinetics

Spectrum of response to imatinib:

TFR Stable MMR BC CP Spectrum of response to imatinib TFR Stable MMR BC CP Spectrum of response to NIL/DAS Good Risk Profile Poor

imatinib:

TFR Stable MMR BC CP imatinib TFR Stable MMR BC CP NIL/DAS Good Risk Profile Poor

Risk profile not only CML dependent :

CML Biology Host Biology Poor Poor TFR BC CMR CP MMR Good Good Risk profile not only CML dependent

Genes Associated with CML Progression:

Genes Associated with CML Progression Approximately 3,500 genes were significantly associated with progressive disease at a significance level of  P  < 10 −11 . Examples: Deregulated Wnt /beta-catenin, decreased JunB and Fos , increased PRAME Each row represents one sample, and each column represents one gene. Red color indicates overexpression relative to the control pool, and green color indicates low expression. Radich et al. Proc Natl Acad Sci U S A.  2006;103(8 ):2794-9

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Top 200 probes (FDR p<0.05) Blue bar = EMR failure patients Orange bar = EMR achievement patients A specific gene expression signature in blood cells taken at diagnosis is associated with EMR failure in CP-CML patients Chung Kok

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Normalised Enrichment score (NES) Cell cycle pathways Stem cell signalling /phenotype T cell signalling /phenotype EMR failure patient samples had a gene signature associated with down-regulation of T-cells and enrichment for stem cell signalling   Chung Kok

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26.7% 92.0% % patients achieved EMR Time (Months) Training set (n=40) p<0.0001 85.2% % patients achieved EMR Time (Months) Validation set (n=39) 50% p=0.018 N=12 37.0% 88.5% % patients achieved EMR Time (Months) Combined set (n=79) p<0.0001 A. B. C. D. down-regulation up-regulation Standardized centroids score for EMR failure samples Poor risk (n=15) Good risk (n=25) Poor risk (n=12) Good risk (n=27) Poor risk (n=27) Good risk (n=52) Developing a 20-gene signature to predict patient who failed to achieve EMR Chung Kok

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The 20-gene EMR signature predicts MMR and MR 4.5 Good risk signature (n=52) Poor risk signature (n=27) A. MR 4.5 achievement MMR achievement B. 34.0% 77.2% 37.4% 7.4% p=0.00034 Pred. EMR failure Pred. EMR achievement Pred. EMR failure Pred. EMR achievement p=0.0062 Chung Kok

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probability Time (Months) p=0.001 88.7% 59.3% probability 80.8% 44.4% p<0.0001 Time (Months) Event-free survival (EFS) Failure-free survival (FFS) A. B. C. Poor risk signature (n=27) Good risk signature (n=52) 3.8% 7.4% 1.9% 3/79 pts 1/52 pts 2/27 pts Poor survival outcomes in patients predicted as EMR failure   Poor risk signature Good risk signature Chung Kok

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Luminex cytokine assay EGF, Eotaxin , FGF-2, Flt3-Ligand, Fractalkine , G-CSF, GM-CSF, GRO, IFNa2, IFNg , IL-1a, IL-1b, IL-1ra, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-12 p40, IL-12 p70, IL-13, IL-15, IL-17a, IP-10, MCP-1, MCP-3, MDC, MIP-1a, MIP-1b, sCD40L, sIL-2Ra, TGFa , TNFa , TNFb , VEGF Eva Nievergall Measure the concentration of 39 cytokines, chemokines and growth factors simultaneously in one sample Bead based multiplex assay

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up / up, but not significant / down not included in this table: Eotaxin , CX3CL1 ( Fraktalkine ), G-CSF, GM-CSF, IFNg , IL-1b, IL-1ra, IL-3, IL-5, IL-7, IL-9, IL-12 p40, IL-12 p70, IL-13, IL-15, IL-17a, TNFb Eva Nievergall

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n=183 total EMR failure (n=23) transformation mutation MMR by 24 months CMR by 24 months + TGF-α hi /IL-6 hi 20 12 (60%) 3 # 5 9 (45%) 1 (5%) TGF-α hi /IL-6 lo 19 3 (16%) 0 0 12 (63%) 2 (11%) TGF-α lo 144 8 (6%) 2 ## 6 117 (81%) 55 (38%) Overall p value (log rank) < 0.001 * < 0.001 < 0.001 0.004 0.004 High Plasma Levels of TGF-α and IL-6 at Diagnosis Predict Early Molecular Response Failure and Transformation in CML Eva Nievergall

Optimising CML Therapy:

Optimising CML Therapy Towards an accurate Risk Profile Early Molecular Response Kinase inhibition/ Pharmacokinetics

Progression to AP/BCa:

Progression to AP/BC a 3 new on-study progressions to AP/BC were reported since the 4-year analysis, all after discontinuation of study treatment 17 Data cutoff: September 30, 2013 Nilotinib 300 mg BID Nilotinib 400 mg BID Imatinib 400 mg QD New events reported since the 4-year analysis On Core Treatment On Study b P = .0059 P = .0185 P = .0028 P = .0403 4.2% 1.1% 0.7% 7.4% 3.5% 2.1% Patients With Progression to AP/BC, n n = 282 281 283 282 281 283 AP/BC, accelerated phase/blast crisis. a Defined as progression to AP/BC or death due to advanced CML. b On core treatment or during follow-up after discontinuation of core treatment.

Progression to AP/BC on Studya According to Sokal Risk Score:

Progression to AP/BC on Study a According to Sokal Risk Score n = 103 103 104 101 100 101 78 78 78 18 Data cutoff: September 30, 2013 Low Sokal Risk Intermediate Sokal Risk High Sokal Risk All 3 progressions to AP/BC on study reported since the 4-year analysis occurred in patients with high Sokal risk scores at baseline; all 3 patients also had BCR-ABL IS > 10% at 3 months All progressions in patients with low/intermediate Sokal risk scores occurred during the first 2 years on study 1.0% 1.0% 1.0% 2.0% 9.9% 14.1% 5.1% 9.0% Nilotinib 300 mg BID Nilotinib 400 mg BID Imatinib 400 mg QD New events reported since the 4-year analysis Patients With Progression to AP/BC, n a Progression to AP/BC or death due to advanced CML on core treatment or during follow-up after discontinuation of core treatment.

BCR-ABLIS Levels at 3 Months by Sokal Risk Score:

BCR-ABL IS Levels at 3 Months by Sokal Risk Score BCR-ABL IS Level at 3 Months, % a Nilotinib 300 mg BID Nilotinib 400 mg BID Imatinib 400 mg QD Low Sokal risk group n = 97 n = 98 n = 102 ≤ 1% 60.8 60.2 22.5 >1% to ≤ 10% 32.0 34.7 56.9 > 10% 7.2 5.1 20.6 Intermediate Sokal risk group n = 91 n = 90 n = 92 ≤ 1% 62.6 54.4 17.4 >1% to ≤ 10% 29.7 34.4 52.2 > 10% 7.7 11.1 30.4 High Sokal risk group n = 70 n = 72 n = 70 ≤ 1% 41.4 40.3 5.7 >1% to ≤ 10% 44.3 41.7 38.6 > 10% 14.3 18.1 55.7 a Among patients in each Sokal risk group with typical BCR-ABL transcripts at baseline and evaluable BCR-ABL IS levels at 3 months. 19

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≤10% >10% n=406 97% FFS PFS OS MMR .0003 99% <.0001 89% <.0001 83% <.0001 Responses at 4 y P 89% 42% 46% n=100 86% Outcomes at 4 years by BCR-ABL at 3 months ≤10% vs >10%: Australian Data

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0.10 1 1.0 0.01 10 Months since commencing imatinib BCR-ABL1% IS 2 3 4 5 6 7 10 0 100 8 9 0.001 11 12 26 8 34 Molecular response in patients who progressed on imatinib ( ENESTnd & Dasision )

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0.10 1 1.0 0.01 10 BCR-ABL1% IS 2 3 4 5 6 7 10 0 100 8 9 0.001 11 12 26 8 10 16 8 34 Months since commencing imatinib Molecular response in patients who progressed on imatinib ( ENESTnd & Dasision )

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StandardisedBaseline 100 BCR-ABL1 % IS Can the patients with high risk of poor response be more reliably predicted at 3 months? n=100 Change of BCR-ABL1 level from baseline to 3 months was important for outcome 54% no ELN failure 42% MMR 3 10 0 months EMR failure Branford et al, ASH 2013, 12;122:254

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3 10 0 Can the patients with high ongoing risk of poor response be more reliably predicted at 3 months? months n=79 Halving Time ≤90 days n=19 Halving Time >90 days Standardised Baseline 100 BCR-ABL1 % IS median 32 days (range 16-90) 30% BCR-ABL1 Measuring BCR-ABL1 as a continuous covariate – individuals with the same value at 3 months had better outcomes if their baseline value was higher 120% 45% Rate of reduction was measured by the number of days over which BCR-ABL1 halved: Halving Time Branford et al, ASH 2013, 12;122:254

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3 0 3 0 Compared outcome according to Halving Time at 3 months ≤90 days vs >90 days Branford et al, ASH 2013, 12;122:254

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>10% at 3 months - Warning zone category FFS PFS OS MMR Overall responses at 4 years, n=100 89% 86% 42% 46% 93% .0008 90% .017 53% .017 56% <.0001 ≤90 d vs P n=79 69% 69% 5% 7% > 90 d n=19 Branford et al, ASH 2013, 12;122:254

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>10% at 3 months - Warning zone category FFS PFS OS MMR Overall responses at 4 years, n=100 89% 86% 42% 46% 93% 97% 90% 99% 53% 89% 56% 83% ≤90 d vs <10% n=79 69% 69% 5% 7% >90 d n=19 Branford et al, ASH 2013, 12;122:254

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Outcome BCR-ABL IS < 10% (n=234) BCR-ABL IS > 10% (n =67) p-value Reduction < 0.35 (n=253) Reduction > 0.35 (n=48) p-value 5Y PFS 95% 87% NS 96% 77% < 0.001 5Y OS 97% 90% NS 98% 83% 0.001 Hanfstein B, et al. ASH Annual Meeting. December 7-10, 2013; Abstract 253. 3-Month Response 0.35-fold  BCR-ABL  reduction at 3 months allowed identification of high- and low-risk groups for 5-year survival (HR: 5.6; 95% CI: 2.3-13.4;  P  < 0.001) GUS Reference Gene Stratification Based on 3-month  BCR-ABL  Reduction 0.35-Fold Reduction Predicts PFS and OS Better than  BCR-ABL IS  > 10%

EMR Implications: Conclusion:

EMR Implications: Conclusion Most patients who will progress have EMR failure BUT many patients with EMR failure will do well long term Best discriminator is the tempo of BCR-ABL fall Risks and benefits of switching must be carefully weighed up in each case

Optimising CML Therapy:

Optimising CML Therapy Towards an accurate Risk Profile Early Molecular Response Kinase inhibition/ Pharmacokinetics

PowerPoint Presentation:

31 83 CP-CML patients treated with nilotinib (300mg BID) front line. 11 withdrew for toxicity /intolerance prior to 6 months. All 72 remaining patients achieved ≤ 10% BCR-ABL1 at 3 months. 83 % (60/72) of patients achieved MMR by 12 months . ENESTxtnd sub-study of Australian patients

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%reduction in p- Crkl pCrkl Crkl Day 1 Day 8 Day 29 pCrkl Crkl Day 1 Day 8 Day 29 In vivo kinase inhibition. Early therapeutic measures

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days on 600mg imatinib p- Crkl Crkl 0 7 14 21 28 33 % p- Crkl TIDEL I Substudy – 600mg imatinib

Nilotinib treated patients demonstrate higher levels of in vivo kinase inhibition: Day 8:

Nilotinib treated patients demonstrate higher levels of in vivo kinase inhibition: Day 8 % reduction in P- Crkl Imatinib 600mg n=175 Nilotinib 300mg bid n=72 19% 43% p<0.001 0 20 40 60 80 100 34

MMR by 12 months on nilotinib was associated with a higher level of in vivo kinase inhibition.:

MMR by 12 months on nilotinib was associated with a higher level of in vivo kinase inhibition. % kinase inhibition month 1 10 20 30 40 50 60 70 80 MMR by 12 months No (n=13) Yes (n=53) p=0.001 35 Median level first month 55%.

Significantly more patients with high in vivo kinase inhibition at achieve MMR by 12 months:

Significantly more patients with high in vivo kinase inhibition at achieve MMR by 12 months 0 Months since start of therapy 2 4 6 8 10 12 % of patients achieving MMR by 12 mo 0 20 40 60 80 High in vivo kinase inhibition Low in vivo kinase inhibition p<0.001 100 97% n=36 62% n=29 36

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in vivo kinase inhibition vs trough drug levels -20 0 20 40 60 80 0 1000 2000 3000 4000 5000 P=0.0445 R=0.1 % in vivo kinase inhibition Day 8 Trough drug levels ng /ml P<0.001 R=0.5 0 20 40 60 80 100 0 1000 2000 3000 4000 Imatinib 600mg Nilotinib Other factors such as drug transport play a significant role. PK may be the key factor . 37

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% in vivo kinase inhibition 10 20 30 40 50 60 70 80 Trough nilotinib levels ng /ml 0 500 1000 1500 2000 2500 In vivo kinase inhibition is significantly linked to trough nilotinib levels. R=0.55 p<0.001 All patients who achieve trough nilotinib levels of >1000ng/ml achieve >50% kinase inhibition. Trough nilotinib levels >1000ng/ml are not essential for some patients to achieve >50% kinase inhibition. 38

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% in vivo kinase inhibition 10 20 30 40 50 60 70 80 Trough nilotinib levels ng /ml 0 500 1000 1500 2000 2500 Chi Square p =0.027 log rank p<0.001 mutations In vivo kinase inhibition is significantly linked to trough nilotinib levels. 39 no MMR Patients with low in vivo kinase inhibition and low PK are at the highest risk. ~40% no MMR

Early measurement of nilotinib trough levels is superior to later for prediction of MMR:

Early measurement of nilotinib trough levels is superior to later for prediction of MMR 1 month (n) 3 month (n) 6 month (n) 9 month (n) 12 month (n) <1000ng/ml 77% (44) 71% (40) 83% (35) 81% (27) 74% (23) >1000ng/ml 93% (28) 90% (28) 85% (33) 85% (34) 95% (21) P value 0.013 0.146 0.978 0.749 0.05 40

Dasatinib Daily Dose Optimization Based on Residual Drug Levels Resulted in Reduced Risk of Pleural Effusions and High Molecular Response Rates Final Results of the Randomized OPTIM Dasatinib Trial:

Dasatinib Daily Dose Optimization Based on Residual Drug Levels Resulted in Reduced Risk of Pleural Effusions and High Molecular Response Rates Final Results of the Randomized OPTIM Dasatinib Trial Philippe Rousselot, Luigina Mollica On behalf of the French CML (FiLMC) group and the Canadian CML group

Pleural Effusion by Exposure to Dasatinib in Second Line:

Pleural Effusion by Exposure to Dasatinib in Second Line C Nicaise, EHA 2008

OPTIM Dasatinib Trial Design:

OPTIM Dasatinib Trial Design PK PK PK PK PK PK PK PK Amendment Adjustment of the Cmin cutoff value from 5nM to 3nM after 30 pts Inclusion R Not previously treated by TKI Dasatinib 100mg/d [C] min > or = 3 nM < 3 nM A1 A2 B Dasatinib dose adjustment every 2 weeks until optimal Cmin Dasatinib 100 mg/d QD Dasatinib 100 mg/d QD CML CP < 3 months Day 1 Month 6 Month 12 Week 1

Patients Characteristics:

Patients Characteristics TOTAL B (<3nM) A (≥3nM) A1 A2 Patients Jun 09 – Dec 12 288 (289 recruited) 208 81 37 42 Sex ratio M/F 1.3 1.13 1.8 1.2 1.9 Median Age (min-max) 53 (18-90) 49 (18-86) 60 (22-90) 60 (39-90) 59 (22-81) Sokal Low (%) 45 47 42 40 43 Sokal Int (%) 34 31 43 42 44 Sokal High (%) 21 22 15 18 13 p<0.001 By January 2014: Median Follow-up 32 Months (14-57)

Cmin at D15: Randomization:

Cmin at D15: Randomization Median Cmin nM (25-75%) 2 (1.2-3.6) 1.4 (0.8-2.2) 4.8 (3.6-6.2) 5.1 (3.6 -8.2) 4.6 (3.6-5.5) p<0.0001 All B A A1 A2 0 5 10 15 20 3 Cmin nM

Cmin During 12 Months Arm B:

D15 Month 3 Month 9 Month 6 Month 12 p=0.17 NS Cmin During 12 Months Arm B CH Versailles / INSERM CIC 1402 – Poitiers –FR (June 11, 2014)

Cmin During 12 Months Non Adapted Arm A2:

p=0.41 NS D15 Month 3 Month 9 Month 6 Month 12 Cmin During 12 Months Non Adapted Arm A2 CH Versailles / INSERM CIC 1402 – Poitiers –FR (June 11, 2014)

Cmin During 12 Months Adapted Arm A1:

Cmin During 12 Months Adapted Arm A1 D15 Month 3 Month 9 Month 6 Month 12 p<0.001 CH Versailles / INSERM CIC 1402 – Poitiers –FR (June 11, 2014)

Dasatinib Treatment in Arms A1 and A2:

Dasatinib Treatment in Arms A1 and A2 Treatment Arm Mean dose (mg/d) Dose intensity (mg/d) Discontinuation Rate Arm A1 (adapted) 51 57 13% Arm A2 (non adapted) 92 96 27%

Cumulative Incidence of All Grades Pleural Effusions by 36 Months :

Cumulative Incidence of All Grades Pleural Effusions by 36 Months All Patients : 16.2% 0 6 12 18 24 30 36 42 48 54 60 0 10 20 30 40 50 60 70 80 90 100 Months Percent with pleural effusion

Cumulative Incidence of All Grades Pleural Effusions by 36 Months :

Cumulative Incidence of All Grades Pleural Effusions by 36 Months Patients with low Cmin values at D15 (arm B): 11.4% Patients with high Cmin values at D15 (arms A1 and A2): 29.6% A1 and A2 arms B arm Gray test p=0.006 0 6 12 18 24 30 36 42 48 54 60 0 10 20 30 40 50 60 70 80 90 100 Months Percent with pleural effusion

Cumulative Incidence of All Grades Pleural Effusions by 36 Months:

Patients with dose adaptation (arm A1): 11% Patients without dose adaptation (arm A2): 45% Cumulative Incidence of All Grades Pleural Effusions by 36 Months Gray test p=0.008 A1 arm A2 arm 0 6 12 18 24 30 36 42 48 54 60 0 10 20 30 40 50 60 70 80 90 100 Months Percent with pleural effusion Arm Total Events Competing events A1 38 4 2 A2 42 16 7

Overall Molecular Responses: Month 3 (not done = failure):

Overall Molecular Responses: Month 3 (not done = failure) 3 Months > 10% MR2 MR3 MR4 MR4.5 0 10 20 30 40 50 60 70 80 90 100 ALL B A1 A2 % Responses

Overall Molecular Responses: Month 12 (not done = failure):

Overall Molecular Responses: Month 12 (not done = failure) > 10% MR2 MR3 MR4 MR4.5 0 10 20 30 40 50 60 70 80 90 100 12 Months % Responses ALL B A1 A2

Conclusions:

Conclusions Dasatinib dose optimization is an efficient strategy to overcome the risk of pleural effusion in high risk patients (defined by a Cmin value ≥ 3nM) and to reduce the discontinuation rate The proportion of patients eligible to dasatinib dose optimization is increasing with age (up to 43% over 60y) reflecting the CP-CML population A personalized dasatinib dose schedule in this high- risk population may be close to 50-60 mg/d and remains associated with high levels of deep molecular responses

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Deb White Sue Branford Devendra Hiwase David Ross David Yeung Michael Osborn Agnes Yong Andrew Grigg Robin Filshie Chris Arthur Tony Mills Jeff Szer Kerry Taylor Richard Herrmann David Joske John Seymour Chris Arthur Mark Hertzberg David Ma Anthony Schwarer Peter Browett Ken Bradstock David Ritchie Andrew Roberts Keith Fay Con Tam Simon Durrant Henry Januszewicz Craig Underhill Scott Dunkley Samar Issa Yiu Lam Kwan Judith Trottman Cecily Forsyth John Taper James Morton Julian Cooney Michael Leahy Phil Rowling John Catalano Steven Opat Kate Burbury International Andreas Hochhaus Giuseppe Saglio Jerry Radich Jeff Lipton Pierre Laneuville Michael Mauro Delphine Rea Francois Mahon Jorge Cortes

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