Kooperativer Bibliotheksverbund

In: Journal of Clinical Oncology, American Society of Clinical Oncology (ASCO), Vol. 33, No. 33 ( 2015-11-20), p. 3911-3920

Abstract: At the molecular level, myeloma is characterized by copy number abnormalities and recurrent translocations into the immunoglobulin heavy chain locus. Novel methods, such as massively parallel sequencing, have begun to describe the pattern of tumor-acquired mutations, but their clinical relevance has yet to be established. Methods We performed whole-exome sequencing for 463 patients who presented with myeloma and were enrolled onto the National Cancer Research Institute Myeloma XI trial, for whom complete molecular cytogenetic and clinical outcome data were available. Results We identified 15 significantly mutated genes: 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 nuclear factor-κB (17%) pathways, but although they are prognostically neutral, they 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 favorable overall survival. We combined these novel mutation risk factors with the recurrent molecular adverse features and international staging system to generate an international staging system mutation score that can identify a high-risk population of patients who experience relapse and die prematurely. Conclusion We have refined our understanding of genetic events in myeloma and identified clinically relevant mutations that may be used to better stratify patients at presentation.

Type of Medium: Online Resource

ISSN: 0732-183X , 1527-7755

URL: Article

DOI: 10.1200/JCO.2014.59.1503

Language: English

Publisher: American Society of Clinical Oncology (ASCO)

Publication Date: 2015

detail.hit.zdb_id: 2005181-5

In: Blood, American Society of Hematology, Vol. 126, No. 23 ( 2015-12-03), p. 189-189

Abstract: Background: Maximising response in myeloma (MM) patients with effective induction regimens prior to autologous stem cell transplant (ASCT) improves progression-free and overall survival. Triplet regimens combining an immunomodulatory agent (IMiD) and/or proteasome inhibitor (PI) are standard of care, however a more personalised approach is achieved by sequential triplet combinations based on an individual's response. Alternatively, quadruplet regimens may be more effective and new generation PIs such as carfilzomib, with less off-target activity, provide the opportunity to investigate this whilst minimising the risk of increased toxicity. The UK NCRI Myeloma XI trial is a large, phase III study aiming to answer these questions in transplant eligible (TE) patients comparing the quadruplet carfilzomib, cyclophosphamide, lenalidomide and dexamethasone to the sequential strategy of triplet IMiD combinations (with thalidomide or lenalidomide) followed by additional PI triplet therapy for those with a suboptimal response ( 〈 VGPR) prior to ASCT. Methods: In 2013, the TE pathway was amended to include KCRD: carfilzomib 36mg/m2 IV d1-2,8-9,15-16 (20mg/m2 #1d1-2), cyclophosphamide (cyclo) 500mg PO d1,8, lenalidomide (len) 25mg PO d1-21, dexamethasone (dex) 40mg PO d1-4,8-9,15-16). Patients are randomised to this up-front quadruplet or the sequential strategy of CRD: cyclo 500mg PO d1,8, len 25mg PO d1-21 PO daily, dex 40mg PO d1-4, 12-15 or CTD: cyclo 500mg PO d1,8,15 thalidomide 100-200mg PO daily, dex 40mg PO d1-4,12-15 given to max. response - patients with VGPR/CR proceed straight to ASCT, PR/MR are randomised to sequential CVD: cyclo 500mg d1,8,15, bortezomib 1.3mg/m2 IV/SC d1,4,8,11, dex 20mg PO d1,2,4,5,8,9,11,12 or nothing and SD/PD all receive sequential CVD. All treatments are given to max. response prior to ASCT, after which there is a maintenance randomisation. Patients: 1512 patients entered the TE pathway prior to amendment (756 CRD, 756 CTD). Of these, 201 patients with a suboptimal initial response went on to receive CVD, 142 following randomisation (initial response PR/MR) and 59 with NC/PD. 788 (of target n=1036) patients have been randomised post-amendment to date (394 KCRD, 197 CRD, 197 CTD). Results: TE patients receiving treatment prior to the amendment had response rates ≥VGPR: CRD 58% vs CTD 52%. For patients receiving the sequential triplet CVD due to a suboptimal response this was upgraded to ≥VGPR in 49% of those with initial MR/PR, 27% with NC/PD. This suggests the overall ≥VGPR rate to this treatment approach prior to ASCT would be approx. 75%. This now needs to be compared to the alternative approach of an upfront quadruplet. Comparing patients contemporaneously randomised to initial induction the patients receiving KCRD have completed a median 4 cycles (range 1-7), CRD 5 (range 1-10) and CTD 6 (range 1-9). Dose modifications have been required in 62% of patients receiving KCRD (56% to carfilzomib, 42% to lenalidomide) 44% CRD (40% to lenalidomide) and 65% CTD (59% to thalidomide). Data for study drug related toxicity in patients who have completed at least one cycle of initial induction are shown in table 1. Serious adverse events suspected to be due to trial medications have occurred in 37% on KCRD, 32% CRD and 35% CTD. Updated toxicity and preliminary response analysis on 23/09/15 will be presented at the meeting. This will include a response comparison at the end of initial induction regimen i.e. KCRD vs CRD vs CTD for an anticipated 700 contemporaneous patients who will have completed treatment. Updated response to the sequencing approach (with 250 patients having received sequential CVD) will also be presented and compared. Conclusions: In our study KCRD, an outpatient delivered 4-drug regimen combining second generation IMiD and PI drugs, is well-tolerated in TE NDMM patients, comparable to 3-drug regimens. Data will be presented at the meeting to compare the response rates achieved with the different regimens and treatment approaches. On behalf of the NCRI Haemato-oncology CSG Table 1. Comparative toxicities KCRD n=261 CRD n=143 CTD n=142 % (no. of patients) Peripheral neuropathy Sensory Gr II-IV 1.9 (5) 1.4 (2) 8.5 (12) Motor Gr II-IV 3.1 (8) 1 (1) 5.6 (8) VTE all grades 4.2 (11) 4.9 (7) 5.6 (8) Anaemia Gr III-IV 9.2 (24) 4.2 (6) 5.6 (8) Neutropenia Gr III-IV 14.9 (39) 16.1 (22) 13.3 (19) Thrombocytopenia Gr III-IV 8.4 (22) 1.4 (2) 1.4 (2) Infusion reaction Gr III-IV 0.4 (1) - - Disclosures Pawlyn: Celgene: Honoraria, Other: Travel support; The Institute of Cancer Research: Employment. Off Label Use: Carfilzomib as induction treatment for myeloma Lenalidomide and vorinostat as maintenance treatments for myeloma. Davies:University of Arkansas for Medical Sciences: Employment; Celgene: Honoraria; Onyx-Amgen: Honoraria; Takeda-Milenium: Honoraria. Jones:Celgene: Other: Travel support, Research Funding. Kaiser:Janssen: Honoraria; Chugai: Consultancy; Amgen: Consultancy, Honoraria; BristolMyerSquibb: Consultancy; Celgene: Consultancy, Honoraria, Research Funding. Jenner:Takeda: Honoraria; Amgen: Honoraria. Cook:Jazz Pharma: Consultancy, Honoraria, Speakers Bureau; Sanofi: Consultancy, Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria, Speakers Bureau; Amgen: Consultancy, Honoraria, Speakers Bureau; Chugai: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau. Russell:Therakos: Other: shares. Owen:Celgene: Honoraria, Research Funding; Janssen: Honoraria. Gregory:Janssen: Honoraria; Celgene: Honoraria. Jackson:Celgene: Honoraria; Amgen: Honoraria; Takeda: Honoraria. Morgan:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda-Millennium: Honoraria, Membership on an entity's Board of Directors or advisory committees; CancerNet: Honoraria; Weisman Institute: Honoraria; MMRF: Honoraria; MMRF: Honoraria; University of Arkansas for Medical Sciences: Employment; Weisman Institute: Honoraria; CancerNet: Honoraria.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood.V126.23.189.189

Language: English

Publisher: American Society of Hematology

Publication Date: 2015

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: Blood, American Society of Hematology, Vol. 126, No. 23 ( 2015-12-03), p. 2983-2983

Abstract: Introduction Hyperdiploidy (HRD) comprises the largest pathogenetic subgroup of myeloma. However, its clinical and molecular characterisation is incomplete. Here, we investigate HRD using a novel high-throughput molecular analysis method (MyMaP - Myeloma MLPA and translocation PCR; Kaiser MF et al., Leukemia 2013; Boyle EM et al., Gen Chrom Canc 2015) in a large cohort of 1,036 patients from the UK NCRI Myeloma XI trial. Materials, Methods and Patients Copy number changes, including gain of chromosomes 5, 9 and 15, as well as translocation status were assayed for 1,036 patients enrolled in the UK NCRI Myeloma XI (NCT01554852) trial using CD138+ selected bone marrow myeloma cells taken at diagnosis. HRD was defined by triploidy of at least 2 of analysed chromosomes 5, 9 or 15. Analysis was performed on standard laboratory equipment with MyMaP, a combination of TC-classification based multiplex qRT-PCR and multiplex ligation-dependent probe amplification (MLPA; MRC Holland). The parallel assessment of multiple loci with copy number alteration (CNA) by MLPA allowed unbiased association studies using a Bayesian approach. Semi-quantitative gene expression data for CCND1 and CCND2 was generated as part of the multiplexed qRT-PCR analysis. Median follow up for the analysis was 24 months. Results Of the 1,036 analysed patients, 475 (46%) were HRD. Of these, 325 (68%) had gain(11q25), 141 (29.7%) gain(1q), 43 (9.1%) del(1p32) and 36 (7.5%) del(17p). Gain(11q25) was significantly associated with HRD (Bayes Factor BF01 〈 0.05) in the entire group of 1,036 cases and occurred in only 17% of non-HRD cases, but frequencies of the other copy number alterations (CNA) were similar to entire group. Although gain(1q) was negatively correlated with gain(11q25) within the HRD group (Corr-0.21, BF=0.0004), the two lesions co-occurred in 73 (15.4%) cases. Analysis of other CNA revealed that del(13q) was significantly less frequent (25%) in HRD cases than in non-HRD (56%) cases (BF 〈 0.0001). Interestingly, del(13q) within HRD was highly associated with gain(1q) (BF 〈 0.0001) and negatively correlated with gain(11q25) (BF 〈 0.0001). Thus, CNA status can help discriminate three distinct molecular subgroups of HRD: gain(11q25), gain(11q25)+gain(1q), gain(1q)[+/-del(13q)]. HRD cases were classified as D1, D2 or D1+D2 according to the TC classification based on qPCR CCND1 and CCND2 expression values and expression was correlated with copy number status. An association of the D1 subtype with gain(11q25) and of D2 with gain(1q) was confirmed. CCND1 expression was significantly (P 〈 0.001) higher in cases with gain(11q) [Mean Relative Quantitative (RQ) value 5,466] than in cases with gain(1q) [Mean RQ value 721] . In contrast, CCND2 expression values were significantly higher in cases with gain(1q) [Mean RQ 8,723] than in cases with gain(11q) [mean RQ 1,087] (P 〈 0.001). Co-occurrence of gain(11q) and gain(1q) was associated with intermediate values with CCND1 mean RQ 5,090 and CCND2 mean RQ 2,776, reminiscent of the D1+D2 subtype. HRD was associated with favourable outcome when compared to non-HRD cases with median PFS 28.8 vs. 21.7 months (P 〈 0.0001) and 24-months OS of 83% vs. 77% (median not reached), respectively. However, cases with t(11;14) had a median PFS of 27.0 months and 24-month OS of 80%, combarable to outcome of the HRD group. Within HRD cases, gain(1q) was associated with shorter PFS (P =0.02) and OS (P =0.009), associating the D2 group with inferior outcome. Presence of del(1p32) was associated with inferior PFS (P =0.01) and OS (P =0.0007) in the HRD subgroup and del(17p) was associated with inferior OS (P =0.04) with a trend for PFS. HRD cases with presence of any of the risk factors gain(1q), del(1p32) or del(17p) in comparison to those without had a median PFS of 25.1 vs 35.1 months (P =0.0001) and 24-month OS of 73.8% vs 89.0% (P 〈 0.0001). Conclusion We describe in a large trial cohort an association between gain(11q25) and the D1 hyperdiploid subtype as well as gain(1q) and the D2 subtype, a finding that has so far only been inferred by gene expression array data in the original TC classification. We also find an association with adverse outcome for the D2/gain(1q) subtype. Our findings demonstrate that the novel molecular approach MyMaP allows precise molecular sub-classification of HRD myeloma. Disclosures Kaiser: BristolMyerSquibb: Consultancy; Chugai: Consultancy; Janssen: Honoraria; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding. Pawlyn:Celgene: Honoraria, Other: Travel support; The Institute of Cancer Research: Employment. Jones:Celgene: Other: Travel support, Research Funding. Savola:MRC Holland: Employment. Owen:Celgene: Honoraria, Research Funding; Janssen: Honoraria. Cook:Takeda Oncology: Consultancy, Research Funding, Speakers Bureau; Amgen: Consultancy, Speakers Bureau; Sanofi: Consultancy, Speakers Bureau; BMS: Consultancy; Celgene: Consultancy, Research Funding, Speakers Bureau; Janssen: Consultancy, Research Funding, Speakers Bureau. Gregory:Janssen: Honoraria; Celgene: Honoraria. Davies:Onyx-Amgen: Honoraria; Celgene: Honoraria; University of Arkansas for Medical Sciences: Employment; Takeda-Milenium: Honoraria. Jackson:Amgen: Honoraria; Takeda: Honoraria; Celgene: Honoraria. Morgan:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Weisman Institute: Honoraria; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda-Millennium: Honoraria, Membership on an entity's Board of Directors or advisory committees; University of Arkansas for Medical Sciences: Employment; CancerNet: Honoraria; MMRF: Honoraria.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood.V126.23.2983.2983

Language: English

Publisher: American Society of Hematology

Publication Date: 2015

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: BMJ Open, BMJ, Vol. 12, No. 6 ( 2022-06), p. e056147-

Abstract: Multiple myeloma is a bone marrow cancer, which predominantly affects older people. The incidence is increasing in an ageing population. Over the last 10 years, patient outcomes have improved. However, this is less apparent in older, less fit patients, who are ineligible for stem cell transplant. Research is required in this patient group, taking into account frailty and aiming to improve: treatment tolerability, clinical outcomes and quality of life. Methods and analysis Frailty-adjusted therapy in Transplant Non-Eligible patients with newly diagnosed Multiple Myeloma is a national, phase III, multicentre, randomised controlled trial comparing standard (reactive) and frailty-adjusted (adaptive) induction therapy delivery with ixazomib, lenalidomide and dexamethasone (IRD), and to compare maintenance lenalidomide to lenalidomide+ixazomib, in patients with newly diagnosed multiple myeloma not suitable for stem cell transplant. Overall, 740 participants will be registered into the trial to allow 720 and 478 to be randomised at induction and maintenance, respectively. All participants will receive IRD induction with the dosing strategy randomised (1:1) at trial entry. Patients randomised to the standard, reactive arm will commence at the full dose followed by toxicity dependent reactive modifications. Patients randomised to the adaptive arm will commence at a dose level determined by their International Myeloma Working Group frailty score. Following 12 cycles of induction treatment, participants alive and progression free will undergo a second (double-blind) randomisation on a 1:1 basis to maintenance treatment with lenalidomide+placebo versus lenalidomide+ixazomib until disease progression or intolerance. Ethics and dissemination Ethical approval has been obtained from the North East—Tyne & Wear South Research Ethics Committee (19/NE/0125) and capacity and capability confirmed by local research and development departments for each participating centre prior to opening to recruitment. Participants are required to provide written informed consent prior to trial registration. Trial results will be disseminated by conference presentations and peer-reviewed publications. Trial registration number ISRCTN17973108 , NCT03720041 .

Type of Medium: Online Resource

ISSN: 2044-6055 , 2044-6055

URL: Article

DOI: 10.1136/bmjopen-2021-056147

Language: English

Publisher: BMJ

Publication Date: 2022

detail.hit.zdb_id: 2599832-8

In: Blood, American Society of Hematology, Vol. 132, No. Supplement 1 ( 2018-11-29), p. 2000-2000

Abstract: INTRODUCTION Features of high risk myeloma (MM) have been studied in detail but patients with longer term responses to first-line therapy are less well characterised. Identification of common features of this group may support optimised management. Here we analysed clinical and genetic characteristics of long-term responders of 4,249 trial patients from the UK MRC Myeloma IX (M-IX) and NCRI Myeloma XI (M-XI) trials. PATIENTS AND METHODS In M-IX patients were randomised between alkylating therapy (CVAD or MP) and thalidomide-based induction therapy (CTD). M-XI patients were randomised between thalidomide and lenalidomide based induction (CTD vs CRD) and a response-based bortezomib (CVD) intensification. Fitter patients received HD-Mel+ASCT consolidation. Patients were then randomised to thalidomide (M-IX) or lenalidomide (M-XI) maintenance or observation. Trials included symptomatic, newly diagnosed patients based on CRAB criteria. This analysis included 1,921 My-IX and 2,328 My-XI patients with median follow-up of 73 and 61 months (m), respectively. Genetic profiling was available for 1,866 patients. Patients with a long-term response post induction (PFS≥48m) were identified and their baseline characteristics, responses and treatment compared to those with PFS 〈 48m. OS difference was compared using the logrank test. Multivariate analysis was performed using logistic regression. RESULTS In M-IX, 283 (25.8%) of transplant-eligible (TE) patients had PFS ≥48m whereas 58 (7%) of transplant non-eligible (TNE) patients reached PFS≥48m. In M-XI 410 (34.2%) patients had PFS≥48m for TE and 116 (10.2%) for TNE. Extended progression free survival translated to overall survival (OS) benefit with a median post progression OS of 36.9m for PFS≥48m vs 16.7m for PFS 〈 48m (p 〈 0.0001) for M-IX. For M-XI, OS data had not reached maturity, however the probability of OS at 2 years post progression for those with PFS≥48m was 60% vs 36% for PFS 〈 48m. Clinical factors including ISS I (P 〈 0.0001) and lower performance status (WHO) (P 〈 0.0001) were positively associated with PFS≥48m. Relative risk by multivariate analyses appeared to be higher for these factors in TNE patients with odds ratio of 1.6 and 1.3 than in the TE group with odds 1.4 and 1.2 across M-IX and XI, respectively. The proportion of patients with a high risk lesion (Adverse translocation, Gain(1q) or Del(17p)) were lower in the PFS≥48m group than 〈 48m: 34.3% vs. 54.5% and 28.8% vs. 54% for TE and 10% vs. 51.2% and 35.4% vs 52.1% for TNE arms of M-IX and M-XI, respectively. 'Double hit' MM (≥2 high risk lesions) was rare with 5.8% of patients PFS≥48m compared to 16.6% of patients PFS 〈 48m across trials (P 〈 0.0001). Absence of gain(1q) was the only genetic factor retained within a multivariable analysis of baseline parameters associated with PFS≥48m in the TNE group, whereas for the TE group absence of all high risk lesions were associated with PFS≥48m (p 〈 0.0001). Hyperdiploidy was positively associated with PFS≥48m in the TE group (P=0.02) only by univariate analysis. The majority of patients with PFS ≥48m showed ≥VGPR after induction +/- consolidation: 211 (76.4%) and 340 (84%) of PFS ≥48m patients in the TE arms and 26 (49.1%) and 87 (76.3%) in the TNE arms of M-IX and M-XI, respectively. 86.7% of patients who achieved a ≥VGPR had a PFS ≥48m in the absence of high risk lesions compared to 72.8% with any high risk lesion present (P=0.004). Some patients with PFS≥48m had only reached PR after induction; 56 (20.3%) and 57 (14.1%) of PFS ≥48m patients in the TE arm and 15 (28.3%) and 24 (21.1%) in the TNE arms of M-IX and M-XI, respectively. Baseline factors that were associated with still being able to achieve PFS≥48m from induction after only achieving a PR included the lack of high risk genetic lesions (P 〈 0.0001) and low ISS (P=0.0002). In M-XI, the proportion of patients who only achieved a PR after induction and reached PFS≥48m was 10.6% for patients randomised to observation and 89.4% for patients with lenalidomide maintenance suggesting maintenance may be of particular benefit in this group. CONCLUSIONS Response assessment after induction+/-HD-Mel consolidation with baseline factors can define a patient group with superior outcomes in both TE and TNE patients and may influence future treatment strategies of MM patients undergoing first line therapy. Further analyses including modelling of predictors of response duration are ongoing and will be presented at the conference. Disclosures Shah: Celgene: Other: Travel, Accommodation expenses; Sanofi: Other: Travel and Accommodation expenses. Striha:Janssen: Research Funding; Abbvie: Research Funding; Celgene: Research Funding; MSD: Research Funding; Amgen: Research Funding. Hockaday:Celgene: Research Funding; Amgen: Research Funding; Abbvie: Research Funding; Janssen: Research Funding; MSD: Research Funding; Millenium: Research Funding. Pawlyn:Celgene Corporation: Consultancy, Honoraria, Other: Travel support; Amgen: Consultancy, Honoraria, Other: Travel Support; Janssen: Honoraria, Other: Travel support; Takeda Oncology: Consultancy, Other: Travel support. Jenner:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Drayson:Abingdon Health: Equity Ownership, Membership on an entity's Board of Directors or advisory committees. Owen:Celgene: Consultancy, Honoraria, Research Funding; Takeda: Honoraria, Other: Travel Support; Janssen: Consultancy, Other: Travel Support. Gregory:Celgene: Consultancy, Honoraria, Research Funding; Merck Sharp and Dohme: Research Funding; Janssen: Honoraria; Amgen: Research Funding. Morgan:Janssen: Research Funding; Takeda: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding. Davies:Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Abbvie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Takeda: Consultancy, Honoraria. Cook:Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Seattle Genetics: Honoraria; Glycomimetics: Consultancy, Honoraria; Takeda: Consultancy, Honoraria, Research Funding, Speakers Bureau; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Sanofi: Consultancy, Honoraria, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Honoraria; Celgene Corporation: Consultancy, Honoraria, Research Funding, Speakers Bureau. Cairns:Celgene: Research Funding; Amgen: Research Funding; Merck Sharp and Dohme: Research Funding. Jackson:Roche: Consultancy, Honoraria, Speakers Bureau; Merck Sharp and Dohme: Consultancy, Honoraria, Speakers Bureau; Amgen: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Other: Travel Support, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Other: Travel Support, Research Funding, Speakers Bureau. Kaiser:Amgen: Consultancy, Honoraria; Takeda: Consultancy, Other: travel support; Janssen: Consultancy, Honoraria; Chugai: Consultancy; Bristol-Myers Squibb: Consultancy, Other: travel support; Celgene: Consultancy, Honoraria, Research Funding.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood-2018-99-110149

Language: English

Publisher: American Society of Hematology

Publication Date: 2018

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: Clinical Lymphoma Myeloma and Leukemia, Elsevier BV, Vol. 17, No. 1 ( 2017-02), p. e10-

Type of Medium: Online Resource

ISSN: 2152-2650

URL: Article

DOI: 10.1016/j.clml.2017.03.017

Language: English

Publisher: Elsevier BV

Publication Date: 2017

detail.hit.zdb_id: 2540998-0

detail.hit.zdb_id: 2193618-3

In: Clinical Cancer Research, American Association for Cancer Research (AACR), Vol. 22, No. 23 ( 2016-12-01), p. 5783-5794

Abstract: Purpose: Epigenetic dysregulation is known to be an important contributor to myeloma pathogenesis but, unlike other B-cell malignancies, the full spectrum of somatic mutations in epigenetic modifiers has not been reported previously. We sought to address this using the results from whole-exome sequencing in the context of a large prospective clinical trial of newly diagnosed patients and targeted sequencing in a cohort of previously treated patients for comparison. Experimental Design: Whole-exome sequencing analysis of 463 presenting myeloma cases entered in the UK NCRI Myeloma XI study and targeted sequencing analysis of 156 previously treated cases from the University of Arkansas for Medical Sciences (Little Rock, AR). We correlated the presence of mutations with clinical outcome from diagnosis and compared the mutations found at diagnosis with later stages of disease. Results: In diagnostic myeloma patient samples, we identify significant mutations in genes encoding the histone 1 linker protein, previously identified in other B-cell malignancies. Our data suggest an adverse prognostic impact from the presence of lesions in genes encoding DNA methylation modifiers and the histone demethylase KDM6A/UTX. The frequency of mutations in epigenetic modifiers appears to increase following treatment most notably in genes encoding histone methyltransferases and DNA methylation modifiers. Conclusions: Numerous mutations identified raise the possibility of targeted treatment strategies for patients either at diagnosis or relapse supporting the use of sequencing-based diagnostics in myeloma to help guide therapy as more epigenetic targeted agents become available. Clin Cancer Res; 22(23); 5783–94. ©2016 AACR.

Type of Medium: Online Resource

ISSN: 1078-0432 , 1557-3265

URL: Article

DOI: 10.1158/1078-0432.CCR-15-1790

Language: English

Publisher: American Association for Cancer Research (AACR)

Publication Date: 2016

detail.hit.zdb_id: 1225457-5

detail.hit.zdb_id: 2036787-9

In: Blood, American Society of Hematology, Vol. 134, No. Supplement_1 ( 2019-11-13), p. 3153-3153

Abstract: Background Transplant non-eligible (TNE) myeloma patients are a very heterogeneous group that is not well-defined on the basis of age alone, but rather by the interplay of age, physical function, cognitive function and comorbidity better defined as 'frailty'. The International Myeloma Working Group (IMWG) has published a scoring system for myeloma patient frailty that predicts survival, adverse events and treatment tolerability using age, the Katz Activity of Daily Living (ADL), the Lawton Instrumental Activity of Daily Living (IADL), and the Charlson Comorbidity Index (CCI). It has been proposed to be useful in determining the feasibility of treatment regimens and appropriate dose reductions but has not been validated prospectively. We hypothesize that by defining subgroups of patients based on the IMWG frailty score, and guiding up-front dose adjustments we can personalize therapy to improve treatment tolerability and therefore short-term outcomes, along with quality of life. In addition we plan to compare the use of single agent immunomodulatory (IMiD) based maintenance therapy with an IMiD and proteasome inhibitor maintenance doublet to try and improve long-term outcomes for patients. Study Design and Methods Myeloma XIV (NCT03720041) is a phase III, multi-center, randomized controlled trial to compare standard (reactive) and frailty-adjusted (adaptive) induction therapy delivery with the novel triplet ixazomib, lenalidomide and dexamethasone (IRd), and to compare maintenance lenalidomide (R) to lenalidomide plus ixazomib (IR) in patients with newly diagnosed multiple myeloma not suitable for a stem cell transplant. The trial outline is shown in Figure 1. All participants receive induction treatment with ixazomib, lenalidomide and dexamethasone and are randomized (R1) on a 1:1 basis at trial entry to the use of frailty score-adjusted up-front dose reductions vs. standard up-front dosing followed by toxicity dependent reactive dose modifications during therapy. Following 12 cycles of induction treatment participants alive and progression-free undergo a second randomization (R2) on a 1:1 basis to maintenance treatment with lenalidomide plus placebo versus lenalidomide plus ixazomib. Participants and their treating physicians are blinded to maintenance allocation. The primary objectives of the study are to determine: Early treatment cessation (within 60 days of randomization) for standard versus frailty-adjusted up-front dosingProgression-free survival (PFS, from maintenance randomization) for lenalidomide + placebo (R) versus lenalidomide + ixazomib (IR) The secondary objectives of the study include determining: progression-free survival (PFS) for standard versus frailty-adjusted up-front dosing reductions, overall survival (OS), overall response rate (ORR), treatment compliance and total amount of therapy delivered, toxicity & safety including the incidence of Second Primary Malignancies (SPMs), Quality of Life (QoL), cost-effectiveness of standard versus frailty-adjusted up-front dosing of IRd and cost-effectiveness of IR versus R. Exploratory analyses include the association of molecular subgroups with response, PFS and OS. Seven hundred and forty participants will be enrolled into the trial at R1 to give 80% power to demonstrate a difference in early cessation and ensure that at least 478 participants remain and are randomized at R2 (based on attrition rates in our previous study Myeloma XI). At R2 478 patients will give us 80% power to detect an eight month difference in PFS between R and IR. Disclosures Cairns: Celgene, Amgen, Merck, Takeda: Other: Research Funding to Institution. Pawlyn:Amgen, Janssen, Celgene, Takeda: Other: Travel expenses; Amgen, Celgene, Takeda: Consultancy; Amgen, Celgene, Janssen, Oncopeptides: Honoraria. Royle:Celgene, Amgen, Merck, Takeda: Other: Research Funding to Institution. Best:Celgene, Amgen, Merck, Takeda: Other: Research Funding to Institution. Bowcock:Takeda: Honoraria, Research Funding. Boyd:Takeda: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Drayson:Abingdon Health: Consultancy, Equity Ownership. Henderson:Celgene, Amgen, Merck, Takeda: Other: Research Funding to Institution. Jenner:Abbvie, Amgen, Celgene, Novartis, Janssen, Sanofi Genzyme, Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau. Jones:Celgene: Honoraria, Research Funding. Kaiser:Takeda, Janssen, Celgene, Amgen: Honoraria, Other: Travel Expenses; Celgene, Janssen: Research Funding; Abbvie, Celgene, Takeda, Janssen, Amgen, Abbvie, Karyopharm: Consultancy. Kishore:Celgene, Takeda, Janssen: Honoraria, Speakers Bureau; Celgene, Jazz, Takeda: Other: Travel expenses. Mottram:Celgene, Amgen, Merck, Takeda: Other: Research Funding to Institution. Owen:Janssen: Other: Travel expenses; Celgene, Janssen: Consultancy; Celgene, Janssen: Honoraria; Celgene: Research Funding. Jackson:Celgene, Amgen, Roche, Janssen, Sanofi: Honoraria. Cook:Celgene, Janssen-Cilag, Takeda: Honoraria, Research Funding; Amgen, Bristol-Myers Squib, GlycoMimetics, Seattle Genetics, Sanofi: Honoraria; Janssen, Takeda, Sanofi, Karyopharm, Celgene: Consultancy, Honoraria, Speakers Bureau. OffLabel Disclosure: Frailty adjusted dosing. Ixazomib and lenalidomide combination as maintenance.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood-2019-126207

Language: English

Publisher: American Society of Hematology

Publication Date: 2019

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: Blood, American Society of Hematology, Vol. 124, No. 21 ( 2014-12-06), p. 723-723

Abstract: Aberrant chromosomal translocations are seen in ~40% of presenting patients and predominantly involve the IGH locus at 14q32. The five main translocations involving the IGH locus are t(4;14), t(6;14), t(11;14), t(14;16) and t(14;20), which result in over-expression of MMSET/FGFR3, CCND3, CCND1, MAF and MAFB, respectively. In previous clinical trials we have shown that the t(4;14), t(14;16) and t(14;20) are associated with a poor prognosis. In initial sequencing studies of myeloma it has been noted that the spectrum of mutations fall into two groups, one of which is characterised by an APOBEC signature. This signature comprises of C 〉 T, C 〉 G and C 〉 A mutations in a TpC context and comprises only a subset of samples, with the rest having a rather generic mutation signature representing an intrinsic mutational process occurring as a result of the spontaneous deamination of methylated cytosine to thymine. Whole exome sequencing was performed on 463 presentation patients enrolled into the UK Myeloma XI trial. DNA was extracted from germline DNA and CD138+ plasma cells and whole exome sequencing was performed using SureSelect (Agilent). In addition to capturing the exome, extra baits were added covering the IGH, IGK, IGL and MYCloci in order to determine the breakpoints associated with translocations in these genes. Tumor and germline DNA were sequenced to a median of 60x and data processed to generate copy number, acquired variants and translocation breakpoints in the tumor. Progression-free and overall survival was measured from initial randomization and median follow up for this analysis was 25 months. These combined data allow us to examine the effect of translocations on the mutational spectra in myeloma and determine any associations with progression-free or overall survival. Translocations were detected in 232 (50.1%) patients of which 59 patients (12.7%) had a t(4;14), 86 patients (18.6%) a t(11;14), 17 patients (3.7%) a t(14;16), 5 patients (1%) a t(6;14) and 4 patients (0.9%) a t(14;20). MYC translocations were found in 85 patients (18.4%). Using the tiled regions we were able to detect a mutational signature, kataegis, where regional clustering of mutations can be indicative of somatic genomic rearrangements. We found the hallmarks of kataegis in 15 samples (3.2%), where there was enrichment for TpCpH mutations with an inter-mutational distance 〈 1 kb. Where we detected kataegis surrounding MYC there was also an inter-chromosomal translocation involving either IGK or IGL. Interestingly, the partner chromosomes also showed signs of kataegis e.g. in the t(2;8) kataegis was found at IGK and MYC and in the t(8;22) kataegis was found at MYC and IGL. APOBECs are thought to be involved in the generation of kataegis and as such this co-localisation is indicative of APOBEC involvement in the generation of MYCbreakpoints. We found mutation of translocation partner oncogenes, in particular CCND1 was mutated in 10 patients with the t(11;14). There was an association of mutated CCND1 with a poor prognosis when compared with non-mutated t(11;14) patients (OS median of 20.2 months vs. not reached, p=0.005). Mutations were also seen in FGFR3, MAF and MAFB but only in the samples with the respective translocations. The mutations are likely due to somatic hypermutation mediated by AID, an APOBEC family member. We found that t(14;16) and t(14;20) samples have a significantly higher number of mutations compare to the other translocation groups (p=1.65x10-5). These mutations were enriched for those with an APOBEC signature (T(C 〉 T)A, p=9.1x10-5; T(C 〉 T)T, p=0.0014; T(C 〉 G)A, p=0.001; T(C 〉 G)T, p=0.0064), indicating that the ‘maf’ translocation groups are characterized by APOBEC signature mutations, specifically APOBEC3B. When samples are assigned to either an APOBEC or non-APOBEC group the ‘maf’ translocations account for 66.6% of samples in the APOBEC group but only 1.3% of the non-APOBEC group. Here we show three different mutational signatures mediated by the APOBEC family: translocation partner mutation by AID, APOBEC signature mediated by APOBEC3B, and kataegis mediated by an unknown APOBEC family member. We also show for the first time a clinical impact of APOBEC mutations and their association with a poor prognosis. The poor prognosis of this mutational signature is inextricably linked to a high mutation load and the adverse t(14;16) and t(14;20) translocation subgroups. Disclosures Walker: Onyx Pharmaceuticals: Consultancy, Honoraria.

Type of Medium: Online Resource

ISSN: 0006-4971 , 1528-0020

URL: Article

DOI: 10.1182/blood.V124.21.723.723

Language: English

Publisher: American Society of Hematology

Publication Date: 2014

detail.hit.zdb_id: 1468538-3

detail.hit.zdb_id: 80069-7

In: Haematologica, Ferrata Storti Foundation (Haematologica), Vol. 104, No. 7 ( 2019-07), p. 1440-1450

Type of Medium: Online Resource

ISSN: 0390-6078 , 1592-8721

URL: Article

DOI: 10.3324/haematol.2018.202200

Language: English

Publisher: Ferrata Storti Foundation (Haematologica)

Publication Date: 2019

detail.hit.zdb_id: 2186022-1

detail.hit.zdb_id: 2030158-3

detail.hit.zdb_id: 2805244-4