Management of high-risk disease

Transcription

1 Management of high-risk disease Pieter Sonneveld Erasmus MC Cancer Institute Rotterdam The Netherlands

2 Disclosures Research support : Amgen, Celgene, Janssen, Karyopharm Advisory Boards/Honoraria: BMS, Amgen, Celgene, Janssen Ludwig et al, Blood 2008 Gay et al, Blood 2011 Sonneveld et al, Blood 2016

3 High-Risk Multiple Myeloma In transplant eligible MM patients: OS < 3 yrs In transplant-ineligible patients : OS < 2 yrs Ludwig et al, Blood 2008 Gay et al, Blood 2011 Sonneveld et al, Blood 2016

4 High risk Multiple Myeloma Different genetic and biological groups of tumors (del(17p), hyperdiploidy, translocations t(11;14), t(4;14), t(14;16), t(14;20)), GEP Variable disease course and treatments (Refractory disease, co-morbidity, organ failure, age) Clonal heterogeneity: presence of different (sub)clones in a patient (mutations TP53, NRAS, KRAS, MYC) Development of drug resistance (duration of Rx, clones, toxicity, MRD)

5 What is biological background of High-risk Myeloma Primary genetic events (initiation events) IGH translocations (50%) t(4;14) FGFR3/MMSET (15%) t(6;14) CCND3 (4%) t(11;14) CCND1 (20%) t(14;16) MAF (4%) t(14;20) MAFB Hyperdiploidy (50%) Trisomies of chromosomes 3, 5, 7, 9, 11, 15, 19, 21 Chromosomal copy number Deletion Deletion 1p (30%) CDKN2C, FAF1, FAM46C Deletion 6q (33%) Deletion 8p (25%) Deletion 13 (44%) RB1, DIS3 Deletion 11q (7%) BIRC2/BIRC3 Deletion 14q (38%) TRAF3 Deletion 16q (35%) WWOX, CYLD Deletion 17p (8%) TP53 Secondary genetic events (progression events) Gain Gain 1q ANP32E Gain Gain Gain (40%) CKS1B, LTBR TACI NIK Mutational events and the molecular hallmarks of myeloma A Immortalisation B G1S abnormality C Proliferation D resistance to apoptosis E Abnormal localisation and bone disease F Abnormal PC Differentiation G Abnormal DNA repair H RNA editing I Epigenetic abnormalities J Abnormal Immune surveilance K Abnormal energy metabolism an ADME events Epigenetic events Global hypomethylation from MGUS to myeloma CDKN2C, RB1, Cyclin D, CDKN2A NRAS, KRAS, BRAF, MYC PI3k/AKT NF-κB pathway TRAF, CYLD, IkB DNAH5, DKK1, FRZB XBP1, BLIMP, IRF4 TP53, MRE11, PARP DIS3,FAM46C, LRRK2 UTX,MLL, MMSET, HOXA9, KDM6B 2y translocations t(8;14) c-myc Non IgH translocations Gene specific hypermethylation from myeloma to plasma cell leukaemia CDH1, hmlh1 etc

6 Boyd et al, Leukemia 2011 Prognostic model in myeloma based on co-segregating adverse FISH PFS depends on number of FISH abnormalities lesions: OS : 3 lesions identify Ultra-High Risk patients 9 m 42 m 24 m 61 m

7 Combination of: ISS stage, cytogenetic abnormalities, LDH Palumbo et al. J Clin Oncol 2015;33(26):2863-9

8 Overall survival according to R-ISS stratification Palumbo et al. J Clin Oncol 2015;33(26):2863-9

9 Results of risk classification using gene expression profiling (GEP) R. Kuiper et al, Leukemia 2012 Kuiper et al. Leukemia 2012

10 Overlapping genes in 7 GEP signatures

11 Prognostication based on gene expression EMC92-ISS : Overall survival Size (%) Median OS (months) EMC92-SR, ISS I 38 NR HR EMC92-SR, ISS II ( ) EMC92-SR, ISS III ( ) EMC92-HR ( ) EMC92-SR, ISS I EMC92-SR, ISS II EMC92-SR, ISS III EMC92-HR

12 High-risk in Multiple Myeloma based on ISS / FISH and GEP International Staging System (ISS) 1 Based on b2-microglobulin and albumin FISH 2 t(4;14), t(11;14), t(14;16), t(14;20) add1q, del13q, del17p, hyperdiploidy Multiple abnormalities Revised ISS 3 ISS, LDH, t(4;14), del 17p, t(14;16) Gene Expression Profiling (GEP) 4-7 UAMS-70, UAMS-17, MRC IX-6, UAMS-80, EMC-92, IFM, APEX Ghielmini et al., Blood Greipp et al., JCO Avet-Loiseau, Best Pract Res Clin Haem Palumbo et al, JCO Shaughnessy et al., Blood Dickens et al., Clin Can Res Shaughnessy et al., Blood Kuiper et al., Leukemia 2012

13 Risk stratification approaches International Myeloma Working Group (IMWG) 1 ISS, FISH (del17p, t(4;14), t(14;16)), LDH, IgA, Histology, Cytogenetics, GEP, Labeling index, MRI/PET scan, SNP/CGH msmart (MAYO) High: FISH (del17p, t(14;16), t(14;20)), GEP Interm.: FISH (t(4;14)), Cytogenetic del13, Hypodiploidy, PCLI 3% ISS combined with FISH 3 (EMN, IFM) ISS, FISH (del17, t(4;14)) novel approaches based on microarray technology should be used to achieve a more powerful prediction. 3 1 Mikhael et al., Mayo Clin Proc Munshi et al., Blood Avet-Loiseau et al., Leukemia 2013

14 msmart

15 NGS, targeted sequencing

16 Only a limited set of genes is recurrently mutated in MM Lohr et al., Cancer Cell 2014

17 Are mutations predictive for high-risk disease? Summary of Genome Sequencing in Myeloma There is no unifying mutation in myeloma Most frequently mutated single gene found in 30% Few actionable mutations Programs Identified NF-κB pathway, histone modifying enzymes and RNA processing as enriched pathways Identified BRAF mutations in 4% of myeloma samples Intraclonal heterogeneity identified where mutations are present in variable percentages of the clone

18 Mutations in the Cereblon pathway in 5 % of the patients DDB1 CUL4 * ROC1 * IKZF1/3 * IRF 4 MY C MM cytotoxicity IMiDs * * = gene found mutated in cohort CRBN 1 CUL4B 1 1 IKZF IRF In an untreated patient refractory to Len/Dex induction therapy mutations in CRBN and IRF4 were identified In a refractory patient progressed on Thalidomide and Lenalidomide IKZF3 was mutated. 4 out of 5 IRF4 mutated patients shared a K123R variant

19 Clinical impact of mutations in selected genes PLASMA CEL Walker et al., JCO 33, 3911, 2015

20 Walker et al., 463 pts in MRC-XI JCO significantly mutated genes were identified comprising IRF4, KRAS, NRAS, MAX, HIST1H1E, RB1, EGR1, TP53, TRAF3, FAM46C, DIS3, BRAF, LTB, CYLD and FGFR3. The mutational spectrum is dominated by mutations in the RAS (43%) and NFκB (17%) pathway, which could be targeted therapeutically. Mutations in CCND1 and DNA repair pathway alterations (TP53, ATM, ATR and ZNFHX4 mutations) are associated with a negative impact on survival. In contrast, those in IRF4 and EGR1 are associated with a favourable overall survival.

21 Molecular landscape of del17p MM is characterized by significant FAM46C & KRAS mutations and TRAF3, RB1 and FAM46C deletions (HOVON 87 trial)

22 Can we make a difference in High-risk MM?

23 HOVON-65- / GMMG-HD4-Trial NDMM, transplant eligible, n=824 MM Stage II or III, Age Randomization 3 x VAD 3 x PAD CAD Mobilisation & Leukapheresis MEL PBSCT MEL PBSCT Allogeneic Tx CAD MEL PBSCT MEL PBSCT Thalidomide 50 mg for 2 years Bortezomib 1,3 mg/m 2 for 2 years

24 Outcome of FISH risk groups in HOVON65/GMMG- HD4: effect of drug choice Median PFS (months) OS at 36 months (%) Bort Control p-value Bort Control p-value del(8p21) del(13q14) del(17p13) q q q HD* t(4;14) t(11;14) *HD, hyperdiploid Neben et al, Blood 2011

25 H65/GMMG-HD4: Bortezomib for induction and maintenance single vs double ASCT Rel Risk P-value Treatment VAD single HDT HR 1.00 Ref. PAD single HDT HR 0.86 ns VAD double HDT HR 0.88 ns PAD double HDT HR Sonneveld P, et al. Blood. 2013;122: abstract 404. Updated data presented at ASH 2013.

26 Impact of bortezomib on outcome in pts with highrisk cytogenetics: Results from 4 European trials (1894 Pts) Median PFS Pts without high-risk cytogenetics Vel-based regimens Non Vel-based regimens 47 mos 38 mos 0.01 Pts with high-risk cytogenetics 32 mos 22 mos < Pts with t(4;14), but no del 17 p 36 mos 24 mos Pts with del 17p, but no t(4;14) 27 mos 19 mos Median OS: 65 MOS 41 MOS Vel-based ASCT does not improved outcome in pts with both t(4;14) and del(17p) (ultra high-risk): median PFS : 21 m Multivariate analysis showed benefit from double ASCT Cavo et al. ASH 2012 (Abstract 749), P

27 De novo strategies in Europe to improve CR: Pilot Trial IFM Induction therapy RVD 3 ASCT Melphalan 200 mg/m 2 Consolidation RVD 2 Response After induction After ASCT After consolidation Maintenance Lenalidomide Best response at any time n % n % n % n % scr CR CR+sCR VGPR PR ORR SD PD MRD NEG 4/ / / /31 68 Total PR, partial response; scr, stringent complete response; SD, stable disease Roussel M, et al. J Clin Oncol 2014;32:2712 8

28 IFM 2009 trial: VRD-HDM vs VRD Attal et al, NEJM 2017

29 Meta-Analysis Lenalidomide Maintenance. OS Median follow-up= 80 months Improvement in median survival of approximately 2.5 years Attal et al, ASH 2016

30 OS. Subgroup Analysis. Attal et al, ASH

31 Design of EMN02 trial 4 VCD + Stem cell apheresis R1 4 VMP HDM 1/2 2 VRD None Lenalidomide R2 HDM/ASCT at 1 st relapse Lenalidomide Registration Induction Stem cell mobilization in all pts Early or late ASCT, once or twice Consolidation Maintenance until relapse MRD [Accessed March 2015] CR CR CR CR

32 PFS by randomization 1 (VMP vs. ASCT) Number at risk ASCT VMP ASCT VMP PFS median, mos NR 42.5 PFS at 3 yrs, % HR (95% CI): 0.73 ( ); p = Time (months) ASCT VMP

33 PFS analysis by patient subgroups

34 PFS by high-risk cytogenetics 1.00 % Probability Number at risk ASCT VMP ASCT VMP PFS median, mos PFS at 3 yrs, % HR (95% CI): 0.53 ( ); p = months ASCT VMP

35 PFS by randomization 1 (HDM-1 vs HDM-2) 1.00 PFS : HDM1 vs HDM2 % Probability Number at risk HDM2 HDM1 HDM-2 HDM-1 PFS median, mos NR NR PFS at 3 yrs, % HR (95% CI): 0.70 ( ); p = months HDM2 HDM1 Median follow-up: 32 months (IQR 26-41)

36 PFS by patient subgroups HDM-1 HDM-2 36 months Patient subgroups n pts n pts HR 95% CI P value HR cytogenetics LDH > upper limit Revised-ISS II BM PC > 60% β2-micro > Age > 55 years

37 PFS by high-risk cytogenetics 1.00 % Probability Number at risk HDM2 HDM1 HDM-2 HDM-1 PFS median, mos PFS at 3 yrs, % HR (95% CI): 0.49 ( ); p = months HDM2 HDM1

38 Cox regression analysis MULTIVARIATE ANALYSIS Variables affecting PFS HR 95% CI P-value Randomization to HDM

39 100 Progression-free free survival no consolidation VRD no consolidation VRD N F Cox LR P=0.045 (adjusted for 1st random.) At risk: VRD no consolidation HR = 0.78 ( ) months EMN / HO95 MM

40 Planned subgroup analysis for PFS PFS from consolidation randomization Characteristic Events/Patients VRD no consol HR & 95% CI (VRD : no consol) Reduction (SD) ISS stage 1 37 / / / / / / 76 Cytogenetic risk: high = del(17p) and/or standard 55 / / 248 high 34 / / 83 unknown 30 / / 110 Intensification randomization VMP 43 / / 155 HDM 72 / / 280 not randomized 4 / 8 2 / 6 Total 119 / / 441 (26%) (32%) no consol VRD better better 25%(16) increase 2P=0.07 EMN02 / HO95 MM 40

41 Treatment of multiple myeloma with high-risk cytogenetics: a consensus of the International Myeloma Working Group Pieter Sonneveld, Hervé Avet-Loiseau, Sagar Lonial, Saad Usmani, David Siegel, Kenneth C. Anderson, Wee-Joo Chng, Philippe Moreau, Michel Attal, Robert A. Kyle, Jo Caers, Jens Hillengass, Jesús San Miguel, Niels W. C. J. van de Donk, Hermann Einsele, Joan Bladé, Brian G. M. Durie, Hartmut Goldschmidt, María-Victoria Mateos, Antonio Palumbo, Robert Orlowski Blood : ; doi: /blood

42 Consensus statement. Combining a proteasome inhibitor with lenalidomide and dexamethasone greatly reduces the adverse effect of t(4;14) and del(17p) on PFS in NDMM. Carfilzomib with lenalidomide and dexamethasone seems effective in patients with HR cytogenetics. However, with exception of Aspire and Tourmaline, most data were obtained in nonrandomized studies and long-term follow-up has not been reported. The group advises treating NDMM patients with HR cytogenetics with the combination of a proteasome inhibitor with lenalidomide or pomalidomide and dexamethasone IMWG consensus, Blood 2016.

43 Consensus statement. HDT with ASCT is standard therapy for TE patients with NDMM. It contributes to improved outcome across prognostic groups. Double HDT/ASCT combined with bortezomib may improve PFS in patients with t(4;14) or del(17p), and in those with both abnormalities. Although results from stratified randomized trials are not yet fully available, HDT plus double ASCT is recommended for patients with HR cytogenetics IMWG consensus, Blood 2016.

44 Recommendations anno 2017 in High-risk MM TE patients with High-risk disease should be treated : With triplet induction incl PI and IMID Once or twice HDM/ASCT Consolidation Maintenance? NTE patients should be treated: With triplet therapy or Rd 9 courses or continuously

45 New treatment concepts anno 2017 in High-risk MM

46 M-protein (g/l) 1. Aim of continuous therapy: Extend remission duration with limited toxicity ACTIVE MYELOM A 1 st Maintain/deepen response with longterm treatment remissio n 1. RELAPSE 2 nd remissio n 2. RELAPSE 3 rd remissio n 3. RELAPSE First-line therapy Second line Third line Fourth line 46

47 PFS & OS According to Score Groups based on: < CR at induction; Del(17p) and/or t(4;14); ISS 3 ULTRA HIGH-RISK PFS score 0 vs 1 p = score 1 vs 2 p < score 2 vs 3 p = score 0 61 mo score 1 56 mo score 2 36 mo score 3 26 mo Months OS score 0 vs 1 p = score 1 vs 2 p < score 2 vs 3 p = score 0 84% score 1 81% score 2 56% score 3 33% Months Cavo et al, Cavo ASH ASH

48 Myeloma XI trial outline 48 R 1:1 Induction 1 Induction 2 Maintenance CTD CRD Max. response PD SD MR PR VGPR CR R 1:1 CVD No CVD ASCT (if TE) R 1:1 Lenalidomide Observation Charlotte Pawlyn Monday Dec 5 th 5:15pm Seaport Ballroom Gareth Morgan Monday Dec 5 th 5:00pm Seaport Ballroom

49 IFM 2009 trial: VRD-HDM vs VRD Attal et al, NEJM 2017

50 2. MRD; IFM 2009-PFS according to MRD (NGS-10-6 ) and treatment arm. H. Avet-Loiseau et al, ASH 2016

51 MRD with KRd in NDMM Zimmerman et al. Blood (ASH Annual Meeting Abstracts) 2016;128:675

52 MRD negative, % MRD negative, % Proportion of MRD-negative Patients at 10 4, 10 5, and 10 6 Thresholds Sensitivity threshold 31.8 *** 3.6X 8.8 POLLUX 24.8 *** 4.4X *** 4.8X 2.5 DRd Rd DRd Rd DRd Rd *** 5.1X 3.6 CASTOR 10.4 ** 4.3X * 5.5X 0.8 DVd Vd DVd Vd DVd Vd Daratumumab in combination with standard of care significantly improved MRD-negative rates at all thresholds P values calculated using likelihood-ratio chi-square test. H. Avet-Loiseau et al, ASH 2016 *** P < ** P <0.005 * P <0.05

53 3. Treat 1 st relapse agressively First relapse after IMiD-based induction First relapse after Bortezomib-based induction Doublets Kd / Vd Pomalidomide-Dex (as a backbone) + Cyclo or Ixa or Bort or Dara or Elo Triplets based on Bortezomib DaraVD or PanoVD or EloVD or VCD Rd At second or subsequent relapse Daratumumab (single agent or combination) Triplets (with Rd as backbone) DaraRd or KRd or IxaRd or EloRd Clinical trial ESMO Guidelines 2017; Ann Oncol, in press RELAPSE / REFRACTORY MULTIPLE MYELOMA

54 4. Towards a risk-guided treatment algorythm Adverse All in one, Experimental Allo- SCT Diagnosis Risk by FISH, NGS, Clones, GEP Gentle MRD+ Good-risk All in one Cure 1 st relapse RRMM Risk by FISH, NGS, Clones, GEP Standard-risk Full options Adverse Gentle, Trial

55 Main targets and therapeutic agents in MM: can they abrogate High-risk? Red: approved; Green: in phase III Ocio E, et al. Leukemia Epub November 20.

56 Network Meta-Analysis Comparison of Current Treatment Options for RRMM A network meta-analysis comparing relative efficacy outcomes between phase 3 randomized controlled trials in RRMM identified DRd as providing the greatest PFS benefit KRd, ERd, DVd, and IRd were grouped as being the second-best option on the basis of their similarity in ranking Rd-based triplet regimens constitute the 3 most effective treatment regimens This may be related to the longer treatment durations observed clinically with lenalidomide compared with bortezomib Relative Efficacy of Current Treatment Options for RRMM DRd, daratumumab + lenalidomide/dexamethasone; DVd, daratumumab + bortezomib/dexamethasone; ERd, elotuzumab + lenalidomide/dexamethasone; IRd ixazomib + lenalidomide/dexamethasone; KRd, carfilzomib + lenalidomide/dexamethasone; PFS, progression-free survival; Rd, lenalidomide/dexamethasone; RRMM, relapsed/refractory multiple myeloma. 1. van Beurden-Tan CH et al. J Clin Oncol [Epub ahead of print].

57 Stratify by: dara treatment, response, MRD status VTD with or without daratumumab in transplant eligible NDMM IFM/HOVON R Induction 4 cycles VTD + Dara VTD Molecular profiling of MM HDM ASCT Endpoints: scr PFS, OS Dara, daratumumab; NGS, next generation sequencing Consolidation 2 cycles VTD + Dara VTD R Maintenance 2 yrs Dara Observation MRD by flow & NGS

58 Clinical approaches to improve results in high-risk MM: Induction/consolidation therapies 2-drugs 3-drugs 4-drugs Thalido mide based TD TAD CTD Lenalido mide based RD Rd RAD RCD BiRD Bortezomib based VD PAD VCD Bortezomib + IMiD based VTD VRD VTDC RVDC Note: Not all agents may be indicated for listed combinations or settings BiRD, clarithromycin, lenalidomide, dexamethasone; CTD, cyclophosphamide, thalidomide, dexamethasone; IMiD, immunomodulatory drug; PAD, bortezomib, doxorubicin, dexamethasone; RAD, lenalidomide, adriamycin, dexamethasone; RCD, lenalidomide, cyclophosphamide, dexamethasone; Rd, lenalidomide, low-dose dexamethasone; RD, lenalidomide, high-dose dexamethasone; RVDC, lenalidomide, bortezomib, dexamethasone, cyclophosphamide; TAD, thalidomide, adriamycin, dexamethasone; TD, thalidomide, dexamethasone; VCD, bortezomib, cyclophosphamide, dexamethasone; VD, bortezomib, dexamethasone; VRD, bortezomib, lenalidomide, dexamethasone; VTD, bortezomib, thalidomide, dexamethasone; VTDC, bortezomib, thalidomide, dexamethasone, cyclophosphamide Based on Ludwig H, et al. Oncologist 2012;17: Future Dara-Rd Dara-Vd (Elo-Rd) Dara-VTD Dara-KRd

59 Greetings from Rotterdam