scholarly journals Redefining the Prognostic Significance of t(11;14) Multiple Myeloma

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 43-43
Author(s):  
Susan Bal ◽  
Smith Giri ◽  
Kelly N. Godby ◽  
Luciano J. Costa
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
Real World ◽  
Research Funding ◽  
Prognostic Significance ◽  
Rank Test ◽  
Prognostic Impact ◽  
The Impact ◽  
Standard Risk

Background In the era prior to introduction of novel agents, multiple myeloma (MM) harboring t(11;14) was characterized as standard risk. More recently, its unique biology, predictive ability and the prospect of targeted therapeutic agents have renewed interest in t(11;14) MM. Using a large, contemporary real-world database, we investigated the characteristics and outcomes of t(11;14) MM. Methods We used the Flatiron Health Electronic Health Record (EHR)-derived de-identified database to source patients (pts) with newly diagnosed MM from 1/2011 to 2/2020 with available Fluorescence in situ Hybridization (FISH) results documented within 90 days of diagnosis. We compared characteristics of t(11;14)+ patients [without additional high-risk FISH abnormalities: del(17p), Ch1 abnormality (Ch1a), t(4;14), t(14;16) or t(14;20)] vs. t(11;14)- patients (without additional high risk FISH) vs. del(17p) (irrespective of other abnormality) vs. Ch1a (Ch1a without additional high-risk FISH) vs. high-risk translocations [t(4;14), t(14;16) or t(14;20) without del(17p)]. We subsequently compared real-world progression-free survival (PFS) and overall survival (OS) across these five subsets. Additionally, we assessed the impact of t(11;14) as additional FISH abnormality in patients with del(17p) and in patients with Ch1a. We used Kaplan Meier methods with log-rank test and Cox proportional hazard regression model for survival analysis with date of diagnosis as the index date for follow-up. Results 6039 patients in the database met the inclusion criteria. Overall, 83.6% of patients received initial therapy with immunomodulatory agent (IMiD) and/or proteasome inhibitor (PI); of these 40.3% received combination of IMiD and PI. Overall, 27.1% received autologous hematopoietic cell transplantation. Median follow up was 2.1 years (IQR 0.8-4.0). There were 637 pts in t(11;14)+ group, 3173 in t(11;14)- group, 587 in del(17p), 1205 in Ch1a and 437 with high-risk translocations. The t(11;14)+ group had a higher proportion of men, IgM and light-chain isotype, as well as a higher proportion of patients with serum creatinine ³ 2mg/dl (Table). Patients in t(11;14)+ group had worse PFS (mPFS 3.1 vs. 3.3 years, p=0.02) and worse OS (mOS 5.9 vs. 6.5 years , p=0.04) compared to t(11;14)-, but better PFS and OS than the other three high-risk groups (Figure panels A and B). Worse PFS for t(11;14)+ was demonstrable even after adjustment for sex, age, race/ethnicity, immunoglobulin isotype, stage, comorbidities, and treatment received (adjusted HR=0.87, 95% C.I. 0.77-0.98, P=0.027). We subsequently analyzed the impact of presence of t(11;14) in MM with del(17p) or Ch1a.. The presence of t(11;14) in addition to del(17p) resulted in worse OS compared to del 17p without t(11;14) (mOS 2.8y vs. 3.7y; p=0.04). Indeed, the impact of t(11;14) on del(17p) was comparable to the impact of t(4;14) (Figure, Panel C). There was no difference in survival with concomitant presence of t(11;14) with Ch1a (Figure, Panel D). Conclusion MM with t(11;14) has distinct features at presentation and even when treated with modern therapy carries worse prognosis than otherwise standard-risk MM. The concomitant presence of t(11;14) portends a negative prognostic impact to MM with del(17p) but does not appear to impact MM with Ch1a. When present alongside del17p, t(11;14) behaves like a high-risk translocation and identifies a subset of MM in greatest need of newer therapies. Figure 1 Disclosures Costa: Amgen: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Sanofi: Consultancy, Honoraria; AbbVie: Consultancy; Celgene: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Genentech: Consultancy.

scholarly journals Prognostic Molecular Stratification in Relapsed/Refractory Multiple Myeloma - Results of the Pomalidomide Mukseven (NCT02406222) Biomarker Trial

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 4327-4327
Author(s):  
James Croft ◽  
Andrew Hall ◽  
Amy L Sherborne ◽  
Katrina Walker ◽  
Sidra Ellis ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Flow Cytometry ◽  
T Cell ◽  
High Risk ◽  
Real World ◽  
Research Funding ◽  
Unmet Need ◽  
Employment Equity ◽  
Equity Ownership

Background Treatment of relapsed/refractory multiple myeloma (RRMM) remains challenging as durable remissions are achieved in patient sub-groups only. Identifying patients that are likely to benefit prior to or early after starting relapse treatments remains an unmet need. MUKseven is a trial specifically designed to investigate and validate biomarkers for treatment optimization in a 'real-world' RRMM population. Design In the randomized multi-center phase 2 MUKseven trial, RRMM patients (≥2 prior lines of therapy, exposed to proteasome inhibitor and lenalidomide) were randomized 1:1 to cyclophosphamide (500 mg po d1, 8, 15), pomalidomide (4 mg days 1-21) and dexamethasone (40 mg; if ≥75 years 20 mg; d1, 8, 15, 21) (CPomD) or PomD and treated until progression. All patients were asked to undergo bone marrow (BM) and peripheral blood (PB) bio-sampling at baseline, cycle 1 day 14 (C1D14, on-treatment) and relapse. For biomarker discovery and validation, IGH translocations were profiled by qRT-PCR, copy number aberrations by digital MLPA (probemix D006; MRC Holland), GEP by U133plus2.0 array (Affymetrix), PD protein markers by IHC and PB T-cell subsets by flow cytometry for all patients with sufficient material. Primary endpoint was PFS, secondary endpoints included response, OS, safety/toxicity and biomarker validation. Original planned sample size was 250 patients but due to a change in UK standard of care during recruitment with pomalidomide becoming available, a decision was made to stop recruitment early. Results In total, 102 RRMM patients were randomized 1:1 between March 2016 and February 2018. Trial entry criteria were designed to include a real-world RRMM population, permitting transfusions and growth factor support. Median age at randomization was 69 years (range 42-88), 28% of patients had received ≥5 prior lines of therapy (median: 3). Median follow-up for this analysis was 13.4 months (95% CI: 12.0-17.5). 16 patients remained on trial at time of analysis (median number of cycles: 19.5; range 8-28). More patients achieved ≥PR with CPomD compared to PomD: 70.6% (95% CI: 56.2-82.5%) vs. 47.1% (CI: 32.9-61.5%) (P=0.006). Median PFS was 6.9 months (CI: 5.7-10.4) for CPomD vs. 4.6 months (CI: 3.5-7.4) for PomD, which was not significantly different as per pre-defined criteria. Follow-up for OS is ongoing and will be presented at the conference. High-risk genetic aberrations were found at following frequencies: t(4;14): 6%, t(14;16)/t(14;20): 2%, gain(1q): 45%, del(17p): 13%. Non-high risk lesions were present as follows: t(11;14): 22%, hyperdiploidy: 44%. Complete information on all high-risk genetic markers was available for 71/102 patients, of whom 12.7% had double-hit high-risk (≥2 adverse lesions), 46.5% single-hit high-risk (1 adverse lesion) and 40.8% no risk markers, as per our recent meta-analysis in NDMM (Shah V, et al., Leukemia 2018). Median PFS was significantly shorter for double-hit: 3.4 months (CI: 1.0-4.9) vs. single-hit: 5.8 months (CI: 3.7-9.0) or no hit: 14.1 months (CI: 6.9-17.3) (P=0.005) (Figure 1A). GEP was available for 48 patients and the EMC92 high-risk signature, present in 19% of tumors, was associated with significantly shorter PFS: 3.4 months (CI: 2.0-5.7) vs. 7.4 (CI: 3.9-15.1) for EMC92 standard risk (P=0.037). Pharmacodynamic (PD) profiling of cereblon and CRL4CRBN ubiquitination targets (including Aiolos, ZFP91) in BM clots collected at baseline and C1D14 is currently ongoing. Preliminary results for the first 10 patients demonstrate differential change of nuclear Aiolos (Figure 1C), with a major decrease in Aiolos H-scores in 7/10 patients from baseline to C1D14 and reconstitution at relapse. T-cell PB sub-sets were profiled at baseline and C1D14 by flow cytometry. Specific sub-sets increased with therapy from baseline to C1D14, e.g. activated (HLA-DR+) CD4+ T-cells, as reported at last ASH. CD4+ T-cell % at baseline was associated with shorter PFS in these analyses in a multi-variable Cox regression model (P=0.005). PD and T-cell biomarker results will be updated and integrated with molecular tumor characteristics and outcome. Discussion Our results demonstrate that molecular markers validated for NDMM predict treatment outcomes in RRMM, opening the potential for stratified delivery of novel treatment approaches for patients with a particularly high unmet need. Additional immunologic and PD biomarkers are currently being explored. Disclosures Croft: Celgene: Other: Travel expenses. Hall:Celgene, Amgen, Janssen, Karyopharm: Other: Research funding to Institution. Walker:Janssen, Celgene: Other: Research funding to Institution. Pawlyn:Amgen, Janssen, Celgene, Takeda: Other: Travel expenses; Amgen, Celgene, Janssen, Oncopeptides: Honoraria; Amgen, Celgene, Takeda: Consultancy. Flanagan:Amgen, Celgene, Janssen, Karyopharm: Other: Research funding to Institution. Garg:Janssen, Takeda, Novartis: Other: Travel expenses; Novartis, Janssen: Research Funding; Janssen: Honoraria. Couto:Celgene Corporation: Employment, Equity Ownership, Patents & Royalties. Wang:Celgene Corporation: Employment, Equity Ownership. Boyd:Novartis: Consultancy, Honoraria; Janssen: Consultancy, Honoraria; Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Pierceall:Celgene: Employment. Thakurta:Celgene: Employment, Equity Ownership. Cook:Celgene, Janssen-Cilag, Takeda: Honoraria, Research Funding; Janssen, Takeda, Sanofi, Karyopharm, Celgene: Consultancy, Honoraria, Speakers Bureau; Amgen, Bristol-Myers Squib, GlycoMimetics, Seattle Genetics, Sanofi: Honoraria. Brown:Amgen, Celgene, Janssen, Karyopharm: Other: Research funding to Institution. Kaiser:Takeda, Janssen, Celgene, Amgen: Honoraria, Other: Travel Expenses; Celgene, Janssen: Research Funding; Abbvie, Celgene, Takeda, Janssen, Amgen, Abbvie, Karyopharm: Consultancy.

scholarly journals Lenalidomide Maintenance Does Not Negatively Impact Overall and Progression Free Survival Using Lenalidomide-Based Regimens for Multiple Myeloma in First Relapse

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 5643-5643 ◽  
Author(s):  
Hannah Cherniawsky ◽  
Zack M. Breckenridge ◽  
Irwindeep Sandhu ◽  
Michael P. Chu ◽  
Joanne D. Hewitt ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Real World ◽  
Research Funding ◽  
Second Line ◽  
Second Line Therapy ◽  
Aggressive Disease ◽  
Line Therapy ◽  
First Relapse ◽  
The Impact

Abstract BACKGROUND Outcomes in multiple myeloma have improved dramatically over the last decade however, optimal sequencing of therapy remains unknown. Specifically, in an era where post-transplant lenalidomide (L) maintenance is now as established standard of care, questions remain around the utility of full dose L-based regimens in second line therapy. In this series, we sought to evaluate the impact of different regimens used at first relapse in patients who received autologous stem cell transplant (ASCT) in the frontline setting treated with and without lenalidomide maintenance (LM). We focused on the impact of L-based therapies in patients relapsing on LM. METHODS Using our prospectively maintained institutional MM database we retrospectively analyzed patients treated at the Cross Cancer Institute from January, 2005 to January, 2016 to ensure 2 years of follow-up for surviving patients. 4 categories were identified based on 2 variables: receipt of LM following 1st line therapy (yes or no) and receipt of L-based 2nd line therapy (yes or no). The primary endpoint was 2nd PFS defined as time of initiation of second line therapy to relapse, death or last follow-up. OS was defined as time of initiation of first line induction therapy to death or last follow-up. Second OS was defined as time of initiation of second line therapy to death or last follow-up. Survival statistics were determined using the Kaplan-Meier method with SPSS software. A p - value of <0.05 was considered significant. RESULTS 213 patients received standard bortezomib-based induction and ASCT of which 132 (62%) received LM. Median follow up for the LM patients was 48 months compared to 74.6 months in non-LM patients. 103 patients (48%) required treatment with second line therapy. Forty-four percent patients were treated with LM while 56% were not. Sixty-nine percent received L-based therapy at relapse, 21% received PI-based therapy and 8% were treated with a PI-IMID combination (table 1). Focusing on the cohort of relapsed patients who received LM (n=44), the median 2nd PFS was 9.3 months in those that received L-based second line therapy vs 4.1 months in those that did not (p = 0.28, figure 1b]. In patients who did not receive LM (n = 55) the median 2nd PFS was 14.0 months in those who received L-based second line therapy vs 6.9 months in those who did not (p = 0.19, figure 1a. Examining all patients who received L-based therapy at relapse there was no difference in 2nd PFS based on whether LM was given (p = 0.42). The median 2nd OS was not statistically significant between the groups (p = 0.39, figure 1b. Patients on LM had a median 2nd OS of 34 months with L-based therapy at relapse compared to 39.2 months without. The median 2nd OS in non-LM patients was 34.5 months in those receiving L-based therapy at first relapse and 23.4 months in those that did not (p=0.10). There was no statistically significant differences in median OS between the 4 groups (p = 0.83). For patients who received LM the median OS was not reached in those receiving L-based therapies at relapse and was 78.1 months in patients who did not. In patients who did not receive LM the median OS was 78.0 months in those receiving L-based therapies at relapse and 69.3 months in those who did not. CONCLUSION Our data suggests that receiving LM does not negatively impact survival outcomes after receiving full dose L-based therapy at relapse. Both median 2nd PFS and 2nd OS were similar with L-based therapies regardless of prior LM. While the 2nd PFS at relapse does fall short of recently published trials in relapsed MM there are some notable confounders here. Firstly, this real-world data includes frailer patients with potentially greater co-morbidities possibly influencing choice and duration of therapy as well as reflect more aggressive disease biology. Secondly, given the relatively short median follow-up of the relapsed LM patients to date, the cohort may be enriched with "early" relapsers (< 2-years) also potentially indicative of biologically more aggressive disease. As such, this may underestimate the true impact of L-based therapies in patients relapsing on LM. Larger series with longer follow-up are necessary to formally examine whether multi-agent L-based regimens confer additional benefit over L-Dexamethasone or non-L based regimens. Real world registries will be useful as prospective trials are unlikely to be done. Disclosures Sandhu: Novartis: Honoraria; Bioverativ: Honoraria; Janssen: Honoraria; Celgene: Honoraria; Amgen: Honoraria. Venner:Janssen: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Amgen: Honoraria; Takeda: Honoraria.

scholarly journals A Single Center Retrospective Analysis of Daratumumab, Pomalidomide, and Dexamethasone As a Second Line Therapy for Multiple Myeloma

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 31-32
Author(s):  
Lawrence Liu ◽  
Gao Feng ◽  
Mark A. Fiala ◽  
Justin King ◽  
Scott R. Goldsmith ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
Induction Therapy ◽  
Research Funding ◽  
Risk Category ◽  
Advisory Boards ◽  
Line Therapy ◽  
The Difference ◽  
Standard Risk

Introduction: Currently, there are many 2nd-line treatment regimens for relapsed Multiple Myeloma (MM) but no standard therapy. Daratumumab, pomalidomide, and dexamethasone (DPd) is a newer 3-drug regimen approved by the FDA for treatment of multiple myeloma in the 3rd or later lines. The POLLUX trial reported a 12-month PFS of 83% in relapsed (median of one prior treatment line) MM treated with daratumumab, lenalidomide, and dexamethasone but excluded lenalidomide-refractory patients. A meta-analysis by Premkumar et al recently showed that high risk MM, del17p, t(4:14), t(14:16) cytogenetics, had minimal benefit from daratumumab-based therapies as 1st-line but benefited more in the 3rd-line or later setting. Nooka et al. previously reported increased response in daratumumab and pomalidomide naïve patients with relapsed refractory MM: median PFS of 41 months in a cohort of 12 patients. A recent Phase II trial by Siegel et al. demonstrated decreased efficacy of 2nd and 3rd-line DPd (1-year PFS of 45.2% vs 82.8% and ORR of 55.0% and 79.5%) in high risk versus standard risk patients respectively. However, it is unclear whether this pattern is consistent between patients treated with DPd in the 2nd vs 3rd-line. Herein, we report the efficacy of DPd when used in the 2nd versus 3rd-line depending on patient MSMART risk category. Methods: We reviewed pharmacy and institutional records of patients who began treatment with DPd in the 2nd (n = 33) or 3rd-line (n = 17) from April 2016 to March 2019. Patients had at least 1 year of follow up from starting DPd unless they progressed or expired before then. A line of therapy was defined as the therapy received between the events of diagnosis, progression, and/or death. We compared the ORR and 12-month PFS of 2nd-line and 3rd-line DPd. The differences in the 12-month PFS and ORR were compared using Fisher's exact test. Odds ratios (OR) were calculated from univariate/multivariate logistic regressions. Results: Thirty-three patients (23 men and 10 women), with median age of 63 (range 47 - 79) and median ECOG of 1, were treated with DPd as 2nd-line therapy. The 3rd-line DPd group was similar, consisting of 17 patients (14 men and 3 women), with median age of 62 (range 51 - 77) and median ECOG of 1. One patient was excluded from analysis in the 2nd-line group due to loss to follow up. Six patients were censored at time of transplant in the 2nd-line group: 4 (12.1%) received DPd as induction therapy for ASCT and 2 (6.1%) received DPd as maintenance therapy after ASCT. In the 3rd-line group, 2 (11.8%) received DPd as induction therapy and were censored. The most common side effects were cytopenias (35.3%), infections (15.2%), fatigue (8.8%). Most of the patients were daratumumab and pomalidomide naïve except one patient in the 3rd-line DPd group who had prior pomalidomide exposure. Twenty-two (66.7%) patients in the 2nd-line group were IMiD refractory versus 16 (94%) in the 3rd-line group. The 12-month PFS for the 2nd-line group was 40.6% compared with 64.7% in the 3rd-line group and showed a trend towards statistical significance (OR=2.82, p=0.09), and the difference reduced (OR=1.49, p=0.57) after adjusting for M-SMART risk category and t(4:14) cytogenetics. On exclusion of high risk and t(4:14), the 12-month PFS was 61.1% vs 66.7% for 2nd- and 3rd-line respectively (p&gt;0.99). The ORR was 84.9% in the 2nd-line group and 82.2% in the 3rd-line group (OR=1.34, p=0.74). The median follow-up for survivors were 22.3 months (range 2.5-43.4). 30 patients relapsed and 16 patients died during follow-up period. M-SMART high-risk designation (HR 2.56; 95%CI 1.09-6.04) and t(4:14) cytogenetics (HR 3.12; 95%CI 1.32-7.43) were associated with lower PFS. Older age of diagnosis was associated with a lower OS (HR 1.11; 95%CI 1.03-1.20). Conclusion: The difference in length of PFS between 2nd and 3rd- line DPd is likely an artifact of small sample size and differential efficacy of DPd depending on cytogenetics. Our results show comparable efficacy of 2nd to 3rd-line DPd when used in standard risk and non-t(4:14) intermediate risk MM. In patients with high risk or t(4:14) cytogenetics, it may be preferable to use DPd in the 3rd or later line. Disclosures Goldsmith: Wugen Inc.: Consultancy. Wildes:Carevive Systems: Consultancy; Janssen: Research Funding; Seattle Genetics: Consultancy. Schroeder:PBD Incorporated: Research Funding; Janssen: Research Funding; Dova Pharmaceuticals: Other; Astellas: Other; Gilead Sciences Inc: Other; GSK: Other; Celgene: Research Funding; Amgen: Other: served on advisory boards and received honoraria or consultant fees, Research Funding; Takeda: Consultancy, Honoraria, Speakers Bureau; Merck: Consultancy, Honoraria, Speakers Bureau; AbbVie: Consultancy, Honoraria, Speakers Bureau; Pfizer: Other; Genzyme Sanofi: Other: served on advisory boards and received honoraria or consultant fees, Research Funding; Partners Therapeutics: Other; Novo Nordisk: Other; Seattle Genetics: Research Funding; Fortis: Research Funding; Cellect Inc: Research Funding; Incyte Corporation: Other: served on advisory boards and received honoraria or consultant fees, Research Funding; Genentech Inc: Research Funding; FlatIron Inc: Other. OffLabel Disclosure: Daratumumab, pomalidomide, and dexamethasone is approved for treatment of relapsed, refractory multiple myeloma.

Occurrence and Prognostic Significance of Cytogenetic Evolution in Patients with Multiple Myeloma

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 4176-4176
Author(s):  
Moritz Binder ◽  
S. Vincent Rajkumar ◽  
Rhett P. Ketterling ◽  
Angela Dispenzieri ◽  
Martha Q. Lacy ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
High Risk ◽  
Risk Stratification ◽  
Research Funding ◽  
Prognostic Significance ◽  
Parameter Estimates ◽  
Nested Models ◽  
Cytogenetic Evolution

Abstract Background: Cytogenetic evaluation, especially using fluorescence in situ hybridization (FISH), at the time of diagnosis is essential for initial risk stratification and the employment of risk-adapted treatment strategies in multiple myeloma. Little is known about the occurrence and prognostic significance of cytogenetic evolution during follow up. Methods: We studied 433 patients who were diagnosed with multiple myeloma between January 2000 and December 2011 and had at least two FISH evaluations at Mayo Clinic Rochester, including the diagnostic specimen. Bone marrow aspirates were evaluated for deletions, monosomies, trisomies, and tetrasomies using chromosome- or centromere-specific FISH probes. IGH rearrangements were evaluated using an IGH break-apart probe and up to five potential partners (FGFR3, CCND1, CCND3, MAF, and MAFB). Cytogenetic evolution was defined as a new deletion, monosomy, trisomy, tetrasomy, or translocation during follow up. Multivariable-adjusted logistic regression models were used to assess the associations between the parameters of interest and the presence of cytogenetic evolution in follow-up specimens. Multivariable-adjusted Cox proportional hazards models were used to assess the effect of cytogenetic evolution on overall survival. All models were adjusted for sex, age, the presence of high-risk FISH abnormalities, and the number of abnormalities at the time of diagnosis. Likelihood ratio tests were used to assess the goodness of fit of nested models. The χ2 or Fisher's exact test was used to assess the distribution of cytogenetic abnormalities in subgroups. Results: The median age at diagnosis was 60 years (32 - 82), 264 (61%) of the patients were male. The median overall survival for the entire cohort was 7.0 years (6.2 - 7.8). At the time of diagnosis, 150 (35%) and 57 (13%) of the 433 patients presented with a hyperdiploid karyotype and cytogenetic high-risk abnormalities, respectively. Independent of each other, the presence of a translocation at the time of diagnosis was associated with decreased odds of cytogenetic evolution during follow up (OR 0.39, 95% CI 0.24 - 0.63, p < 0.001) while the presence of at least one trisomy or tetrasomy at the time of diagnosis was associated with increased odds (OR 2.53, 95% CI 1.37 - 4.70, p = 0.003). A greater proportion of patients presenting with a hyperdiploid karyotype experienced cytogenetic evolution during follow up. Those patients more frequently evolved additional trisomies and tetrasomies, while translocations were more common in those presenting with a non-hyperdiploid karyotype (Table 1). The development of additional abnormalities during the three years following diagnosis (compared to no new abnormalities) was associated with increased subsequent mortality in those who survived at least three years (HR 3.22, 95% CI 1.82 - 5.68, p < 0.001). Including the time between first and last cytogenetic evaluation as a covariate did not significantly change the parameter estimates or improve model fit (p = 0.727). Conclusions: Demographics, risk profile, and overall survival of this cohort reflect the fact that patients had to survive long enough to undergo repeated cytogenetic evaluation. Hyperdiploid and non-hyperdiploid genotypes were associated with distinct behavior regarding cytogenetic evolution during follow up. The identification of cytogenetic evolution was an adverse prognostic factor in those who survived at least three years after diagnosis. These findings emphasize the importance of the dynamics of the underlying clonal disease process for accurate risk assessment and suggest that selected subgroups of patients may benefit from risk stratification during follow up. Table 1. Cytogenetic evolution during follow up in 433 patients with multiple myeloma stratified by karyotype at the time of diagnosis Hyperdiploid (n = 150) Non-hyperdiploid (n = 283) p New abnormality 76 (51%) 108 (38%) 0.012 New monosomy 8 (5%) 24 (8%) 0.243 New trisomy 48 (32%) 55 (19%) 0.004 New tetrasomy 37 (25%) 27 (10%) < 0.001 New deletion 17 (11%) 27 (10%) 0.557 New translocation 1 (1%) 11 (4%) 0.065 Most common new abnormality [type (percent of type in each group)] Monosomy mono(13) (75%) mono(13) (62%) Trisomy tri(11) (22%) tri(3) (22%) Tetrasomy tetra(15) (48%) tetra(15) (30%) Deletion del(17p) (79%) del(17p) (63%) Translocation t(11;14) (100%) t(11;14) (36%) Data are given as count (percent) unless denoted otherwise. Disclosures Binder: American Society of Hematology: Research Funding. Kumar:AbbVie: Research Funding; Onyx: Research Funding; Sanofi: Research Funding; Celgene, Millenium, Sanofi, Skyline, BMS, Onyx, Noxxon,: Other: Consultant, no compensation,; Skyline, Noxxon: Honoraria; Millenium/Takeda: Research Funding; Janssen: Research Funding; Celgene: Research Funding.

Real-World Experience with Minimal Residual Disease Testing with Next Generation Flow Cytometry and Functional Imaging in Multiple Myeloma

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 17-18
Author(s):  
David Böckle ◽  
Paula Tabares Gaviria ◽  
Xiang Zhou ◽  
Janin Messerschmidt ◽  
Lukas Scheller ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Flow Cytometry ◽  
High Risk ◽  
Functional Imaging ◽  
Real World ◽  
Research Funding ◽  
Residual Disease ◽  
Focal Lesions ◽  
High Risk Disease ◽  
Minimal Residual

Background: Minimal residual disease (MRD) diagnostics in multiple myeloma (MM) are gaining increasing importance to determine response depth beyond complete remission (CR) since novel agents have shown to induce high rates of deep clinical responses. Moreover, recent reports indicated combining functional imaging with next generation flow cytometry (NGF) could be beneficial in predicting clinical outcome. This applies in particular to the subset of patients suffering from relapsed/refractory multiple myeloma (RRMM) who tend to show a higher incidence of residual focal lesions despite serological response. Here, we report our institutions experience with implementing both functional imaging and NGF-guided MRD diagnostics in clinical practice. Methods: Our study included patients with newly diagnosed multiple myeloma (NDMM) and RRMM achieving VGPR, CR or sCR. Bone marrow aspirates were obtained for MRD-testing according to IMWG 2016 criteria. Samples were collected between July 2019 and July 2020 and analyzed with NGF (according to EuroFlowTM guidelines) at a sensitivity level of 10-5. Results were compared to functional imaging obtained with positron emission tomography (PET) and diffusion-weighted magnetic resonance imaging (DW-MRI). High-risk disease was defined as presence of deletion 17p, translocation (14;16) or (4;14). Results: We included 66 patients with NDMM (n=39) and RRMM (n=27) who achieved VGPR or better. In patients with RRMM the median number of treatment lines was 2 (range 2-11). Fifteen patients suffered from high-risk disease. Median age at NGF diagnostics was 64 years (range 31-83). Among patients achieving VGPR (n=27), CR (n=10) and sCR (n=29) seventeen (26%) were MRD-negative by NGF testing. CR or better was significantly associated NGF MRD-negativity (p=0.04). Notably, rates of NGF MRD-negativity were similar among patients with NDMM (28%) and RRMM (26%). Even some heavily pretreated patients who underwent ≥ 4 lines of therapy achieved MRD-negativity on NGF (2 of 9). Functional imaging was performed in 46 (70%) patients with DW-MRI (n=22) and PET (n=26). Median time between NGF and imaging assessment was 2 days (range 0-147). Combining results from imaging and NGF, 12 out of 46 (26%) patients were MRD-negative with both methods (neg/neg). Three patients displayed disease activity as measured with both, imaging and NGF (pos/pos). Twenty-nine of the remaining patients were MRD-positive only according to NGF (pos/neg), while two patients were positive on imaging only (neg/pos). More patients demonstrated combined MRD-negativity on NGF and imaging (neg/neg) in the NDMM setting than in RRMM (32% versus 19%). We also observed that 30% of the patients with high-risk genetics showed MRD-negativity on both imaging and NGF. Of note, none of the patients with very advanced disease (≥4 previous lines) was MRD-negative on both techniques. Conclusion In the clinical routine, MRD diagnostics could be used to tailor maintenance and consolidation approaches for patients achieving deep responses by traditional IMWG criteria. Our real-world experience highlights that MRD-negativity can be achieved in patients suffering from high-risk disease and also in late treatment lines, supporting its value as endpoint for clinical trials. However, our data also support MRD diagnostics to be combined with functional imaging at least in the RRMM setting to rule out residual focal lesions. Future studies using MRD for clinical decision-making are highly warranted. Disclosures Einsele: Takeda: Consultancy, Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Amgen: Consultancy, Honoraria, Research Funding, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; GlaxoSmithKline: Honoraria, Research Funding, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Honoraria, Research Funding, Speakers Bureau; Sanofi: Consultancy, Honoraria, Research Funding, Speakers Bureau. Rasche:Celgene/BMS: Honoraria; GlaxoSmithKline: Honoraria; Oncopeptides: Honoraria; Skyline Dx: Research Funding; Janssen: Honoraria; Sanofi: Honoraria.

Survival in Patients with Newly Diagnosed Myeloma Undergoing Therapy with Lenalidomide and Dexamethasone: Impact of High-Risk Cytogenetic Risk Status on Outcome

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 95-95 ◽  
Author(s):  
Prashant Kapoor ◽  
Shaji Kumar ◽  
Rafael Fonseca ◽  
Martha Q. Lacy ◽  
Thomas E Witzig ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Stratification ◽  
Plasma Cell ◽  
Risk Groups ◽  
Newly Diagnosed ◽  
High Risk Patients ◽  
Risk Patients ◽  
The Impact ◽  
Standard Risk

Abstract Background: Multiple myeloma (MM) is a heterogeneous disease with very divergent outcomes that are dictated in a large part by specific cytogenetic abnormalities, as well as other prognostic factors such as the proliferative rate of marrow plasma cells. Prognostic systems incorporating these factors have shown clinical utility in identifying high-risk patients, and are increasingly being utilized for treatment decision-making. However, the prognostic relevance of these factors may change with the application of novel therapies. The objective of this study was to determine the impact of risk-stratification (incorporating plasma cell metaphase cytogenetics, interphase fluorescent in-situ hybridization (FISH) and the slide-based plasma cell labeling index (PCLI)) in a cohort of patients with newly diagnosed MM treated initially with lenalidomide + dexamethasone (Rev-Dex). Methods: From March 2004 to November 2007, 100 consecutive patients treated with Rev (25mg/day) on days 1 through 21 of a 4-week cycle in combination with dexamethasone as initial therapy for newly diagnosed myeloma, were identified. High-risk MM was defined as presence of any one or more of the following: hypodiploidy, monoallelic loss of chromosome 13 or its long arm (by metaphase cytogenetics only), deletion of p53 (locus 17p13) or PCLI ≥ 3% or immunoglobulin heavy chain (IgH) translocations, t(4;14) (p16.3;q32) or t(14;16)(q32;q23) on FISH. PFS and OS survival estimates were created using the Kaplan Meier method, and compared by log-rank tests. Results: The median estimated follow-up of the entire cohort (N=100) was 36 months. The median PFS was 31 months; the median OS has not been reached. The 2- and 3-year OS estimates were 93% and 83%, respectively. 16% patients were deemed high-risk by at least one of the 3 tests (cytogenetics, FISH or PCLI). Response rates (PR or better) were 81% versus 89% in the high-risk and standard risk groups, respectively, P=NS; corresponding values for CR plus VGPR rates were 38% and 45% respectively. The median PFS was 18.5 months in high-risk patients compared to 37 months in the standard-risk patients (n=84), P<0.001(Figure). Corresponding values for TTP were 18.5 months and 36.5 months, respectively, P=<0.001. OS was not statistically significant between the two groups; 92% 2-year OS was noted in both the groups. Overall, 95 patients had at least one of the 3 tests to determine risk, while 55 patients could be adequately stratified based on the availability of all the 3 tests, or at least one test result that led to their inclusion in the high-risk category. The significant difference in PFS persisted even when the analysis was restricted to the 55 patients classified using this stringent criterion; 18.5 months vs. 36.5 months in the high-risk and standard- risk groups respectively; P<0.001. In a separate analysis, patients who underwent SCT before the disease progression were censored on the date of SCT to negate its effect, and PFS was still inferior in the high-risk group (p=0.002). Conclusion: The TTP and PFS of high-risk MM patients are inferior to that of the standard-risk patients treated with Rev-Dex, indicating that the current genetic and proliferation-based risk-stratification model remains prognostic with novel therapy. However, the TTP, PFS, and OS obtained in high-risk patients treated with Rev-Dex in this study is comparable to overall results in all myeloma patients reported in recent phase III trials. In addition, no significant impact of high-risk features on OS is apparent so far. Longer follow-up is needed to determine the impact of risk stratification on the OS of patients treated with Rev-Dex. Figure Figure

Alemtuzumab Plus Oral Dexamethasone, Followed by Alemtuzumab Maintenance or Allogeneic Transplantation in Ultra High-Risk CLL: Interim Analysis of a Phase II Study of the GCLLSG and fcgcll/MW

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 2854-2854 ◽  
Author(s):  
Stephan Stilgenbauer ◽  
Florence Cymbalista ◽  
Véronique Leblond ◽  
Alain Delmer ◽  
Dirk Winkler ◽  
...  
Keyword(s):  
High Risk ◽  
Research Funding ◽  
Response Rates ◽  
Long Term Results ◽  
High Dose ◽  
Significant Difference ◽  
Ultra High Risk ◽  
Grade 3 ◽  
The Impact

Abstract Abstract 2854 Alemtuzumab (A) proved to be efficacious in CLL patients (pts) with very poor prognosis, either due to fludarabine (F) refractoriness or due to unfavorable cytogenetics (17p-). However, rate and duration of remissions still remain unsatisfactory. Therefore, the French and German CLL study groups jointly embarked on this trial, trying to achieve higher overall response rates (ORR) by adding high-dose dexamethasone (D) to A and, simultaneously, investigating the consolidation effect of prolonged A maintenance or allogeneic stem-cell transplantation (allo-SCT), respectively. Induction treatment consisted of subcutaneous A 30 mg weekly × 3 for 28 days, combined with oral D 40 mg on days 1–4 and 15–18, and prophylactic pegfilgrastim 6 mg on days 1 and 15. Depending on the remission status, pts were treated for up to 12 weeks. If CR was documented at 4 or 8 weeks, or at least SD was achieved at 12 weeks, consolidation was scheduled with either allo-SCT or A maintenance with 30 mg every 14 days for up to 2 years (y), at the discretion of pt and physician. Between January 2008 and July 2011, 124 pts were recruited at 26 centers, 120 of whom were eligible. Pts were generally subdivided into three cohorts: 55 pts were refractory (i.e. no response or relapse within 6 months) to regimens containing F or a similar drug (i.e. pentostatin, cladribine, bendamustine). Non-refractory pts all exhibited 17p- and had either untreated (n=39) or relapsed CLL (n = 26) requiring therapy. The median age was high with 66/64/66 y in 17p- 1st line, 17p- relapse, and F-refractory pts, respectively. The three cohorts had 46/54/75% Binet C disease, 41/35/27% B symptoms, 38/42/53% reduced performance status (ECOG 1/2), median thymidine kinase levels of 35/49/24 U/L, median ß2MG levels of 3.8/5.5/4.6 mg/L, and IGHV was unmutated in 89/96/87%. In the F-refractory group, 53% exhibited 17p deletion and 22% had 11q deletion. Pretreated patients had received a median of 3 (F-refractory) or 2 prior lines (17p- relapse). 5 pts had previously undergone autologous and 1 pt allo-SCT. Treatment and efficacy data are currently available for 87 pts who completed induction therapy :17p- 1st-line (n=30), 17p- relapse (n=17), and F-refractory (n=40). Of these, 80/53/55% received the full induction of 12 weeks. ORR (best observed status) was generally high with 97/76/70%. CR was achieved in 20/0/5%. After a median follow-up of 11.8 months (mo), median progression-free survival (PFS) was 16.9/10.4/8.4 mo. Deaths are recorded in 13/27/36% of pts, with median overall survival (OS) not yet reached (>24 mo) in the 17p- 1st line group, and 15/12 mo in 17p- relapse/F-refractory pts. Consolidation treatment was performed as maintenance A (median duration 32 weeks, range 2 – 89) in 34%, and allo-SCT in 30%, with a median age of 66 and 61 y in these subgroups. The main reasons for going off-study without consolidation were death due to infection (14%, n=11, of these 6 without response, and 10 in the F-refractory cohort), CLL progression (12%), and other toxicity (5%). Among the 28 pts not receiving consolidation, there were 19 (68%) deaths, 15 of them in the F-refractory cohort. When comparing A maintenance and allo-SCT for consolidation, there were 9 (35%) and 7 (30%) PD events, respectively and there was so far no significant difference in PFS (median 17 mo in both groups) or OS. During induction, grade 3/4 hematotoxicity consisted of anemia in 28%, neutropenia in 47%, and thrombopenia in 44%. Grade 3/4 non-CMV infection occurred in 29% of 17p- 1st-line, 15% of 17p- relapsed, and 56% of F-refractory pts. CMV reactivation was observed in 54/25/40%, without severe sequelae recorded. During A maintenance, grade 3/4 toxicity consisted of neutropenia in 39% pts and thrombopenia in 4% pts with 6 SAEs (ITP, diarrhea, infection, erythema, tachycardia, and thrombosis). Conclusions: The combination of A and D shows high response rates in ultra high-risk CLL, with promising preliminary findings for PFS and OS, despite the high median age of the pts. The results compare favorably to ORR/CR of 68%/5%, and median PFS of 11.3 mo in the 17p- subgroup of the CLL8 study treated with FCR, consisting of younger pts (median 61 y). In F-refractory CLL however, when compared to the preceding CLL2H study with single agent A, the improved initial response by adding dexamethasone does not seem to translate into improved long-term results. More mature follow-up is needed, especially with respect to the impact of allo-SCT. Disclosures: Stilgenbauer: Amgen: Consultancy, Honoraria, Research Funding; Genzyme: Consultancy, Honoraria, Research Funding. Off Label Use: Alemtuzumab in 1st line CLL treatment. Cymbalista:Roche (d) Mundipharma (e) Genzyme (e): Honoraria, Research Funding. Hinke:WiSP (CRO): Employment.

Lenalidomide (Revlimid), Bortezomib (Velcade) and Dexamethasone (RVD) for Heavily Pretreated Relapsed or Refractory Multiple Myeloma

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 2936-2936
Author(s):  
Victor H Jimenez-Zepeda ◽  
Donna E. Reece ◽  
Suzanne Trudel ◽  
Christine Chen ◽  
Vishal Kukreti
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
Research Funding ◽  
Clinical Characteristics ◽  
Phase 1 ◽  
Prior Exposure ◽  
Rank Test ◽  
Continuous Variables ◽  
Previously Treated ◽  
Grade 3

Abstract Abstract 2936 Almost all patients (pts) with multiple myeloma eventually relapse and remission duration decreases with each regimen. The median Progression Free Survival (PFS) and Overall Survival (OS) in pts with relapsed myeloma refractory to lenalidomide (len) and bortezomib (btz) is poor at 5 and 9 months respectively. A phase 1 study of len plus btz in pts with relapsed or relapsed, refractory MM (RRMM) demonstrated favorable toxicity and promising response and survival further confirmed in a phase 2 study with len, btz and dexamethasone (dex) [RVD]. In this retrospective study, we assessed the efficacy and toxicity profile of RVD therapy for pts with advanced RRMM. We retrospectively reviewed the records of all pts with RRMM treated with RVD at Princess Margaret Hospital between 03/09 and 05/11. Relapse was defined according to the Uniform International Criteria. Pts were given RVD therapy as previous described by Anderson et al and must have completed at least one cycle of RVD therapy. Primary endpoints were response rate (RR), PFS, OS, and toxicity. Pts discontinued therapy if they experienced PD, no additional benefit or unacceptable toxicity. Definitions of response and progression were used according to the EBMT modified criteria with a category of very good partial response (VGPR). To examine variables independently prognostic for PFS and OS, multivariate Cox analysis was performed. Differences in continuous variables between groups were compared using Mann-Whitney or Kruskal-Wallis tests. Survival curves were constructed according to the Kaplan-Meier method and compared using the log rank test. Thirty pts with RRMM received RVD therapy. Clinical characteristics are seen in Table 1. Median age at RVD initiation was 57 yrs (37–76 yrs), and 46.7% were male. Pts received a median of 3 prior therapies (1–6). In many instances, pts previously treated with len had len added to btz + dex at progression (n=6), or pts previously treated with btz had btz added to len + dex, at progression (n=5). Thalidomide (thal), len and btz containing regimens were previously used in 60%, 73.3% and 80% of pts respectively. PR or better was observed in 46.6%. After a median of 4.6 cycles (1–14), VGPR was seen in 4.8%, PR in 33% and SD in 14%. Pts who achieved PR or better experienced a significant improvement in PFS. There was no difference in terms of RR between those pts according to prior exposure to either btz or len (p=0.7 and 0.9 respectively). Eight pts experienced non-hematological grade 3/4 adverse events (26%), including muscle weakness, sepsis and pneumonia but there was no worsening of peripheral neuropathy. Grade 3–4 neutropenia and/or thrombocytopenia were commonly seen in 70% of pts (n=21). Disease progression was seen in 19 pts at a median of 3.9 months. Median PFS for pts previously exposed to len was 2.3 months vs 2.9 months for those with no prior exposure (p=0.75). On the other hand, median PFS for pts previously exposed to btz was 2.1 months vs 3.4 months for those with no prior exposure (p=0.9) In addition, median PFS for pts who achieved at least PR was significantly better at 5.9 vs 2.0 months for those who did not (p<0.005). (Figure 1) FISH cytogenetics studies were available in 19 out of 30 patients at relapse: 5 -normal, 4–13q deletion, 3-p53 deletion and 2 - t(4, 14). High-risk MM pts had a median PFS significantly lower of 0.6 months (CI 95%, 0–1.99) vs 4.7 months for those without high-risk features (CI 2.5–7.0) (p=0.008) (Figure 2) At the time of submission, 13 pts are alive (43.3%) and 7 pts (23%) continue on RVD therapy.Table 1.Clinical characteristics of patients with RRMM treated with RVDClinical characteristic N=30MedianRange%Age5737-76Male46.7%Female53.3%Hemoglobin (g/L)10571-155Creatinine (mmol/L)99.936-383Beta-2 microglobulin (mmol/L)280119-1440Lactate dehydrogenase (U/L)18189-255IgG56.6% (17)IgA23.3% (7)IgM3.3% (1)Light Chain16.6% (5)Kappa (mg/L)4005.3-346063.3% (19)Lambda (mg/L)5145.1-530036.7% (11)KappaLambda*BMPC57%6-95%M-spike serum (g/L)300-77M-spike urine (g/d)0.890-7.9Prior therapies31-6ASCT83.3% (25)Thal60% (18)Len73.3% (22)Btz80% (24)*BMPC, Bone marrow plasma cells In conclusion, RVD is active and well tolerated in pts with RRMM, including pts who have received prior len, btz, thal and ASCT but PFS is short at 3.9 months in this highly advanced disease group of patients. We question whether response is dependent on recognized risk factors such as adverse cytogenetics. Disclosures: Jimenez-Zepeda: J & J: Honoraria. Reece:Bristol, Meyers, Squibb: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Johnson&Johnson: Research Funding; Merck: Honoraria, Research Funding; Otsuka: Honoraria, Research Funding; Millennium: Research Funding; Amgen: Honoraria. Kukreti:Celgene: Honoraria.

Prognostic Impact of Transfusions Intensity on Survival and Development of Thrombocytopenia in Newly Diagnosed Lower-Risk MDS Patients Participating in the European Leukemianet EU-MDS Registry

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1677-1677
Author(s):  
Louise De Swart ◽  
Tom Johnston ◽  
Alexandra Smith ◽  
Pierre Fenaux ◽  
Argiris Symeonidis ◽  
...  
Keyword(s):  
Lower Risk ◽  
Research Funding ◽  
Control Group ◽  
Rapid Decline ◽  
Prognostic Impact ◽  
Platelet Counts ◽  
Risk Of Death ◽  
Increased Risk ◽  
The Impact

Abstract Background The outcome of lower-risk MDS patients with red blood cell transfusions (RBCT) dependency is inferior to that of RBCT independent patients, but whether the intensity of RBCT is important for prognosis is unknown. The EUMDS Registry is a non-interventional, observational longitudinal study enrolling patients with lower-risk MDS from 142 sites in 17 countries as described elsewhere (1). The EUMDS registry has accrued 1,902 patients as of July 21, 2015. We hypothesized that RBCT intensity is an independent prognostic factor for survival. Methods We first assessed the impact of RBCT intensity in the first year post-diagnosis (1yrPD) on progression-free survival among the 1034 patients who survived at least 1yrPD and had potential for a further year of follow-up. Secondly, we developed a longitudinal model of platelet counts throughout follow-up for 1660 patients in the registry with potential for at least one year follow-up. Results Among the 1034 patients, 323 patients had died: 67 after progression to higher-risk MDS/AML and 256 without progression. A further 41 surviving patients had progressed to AML. The overall 5-year survival was 52%. In a proportional hazards regression model (Table), the risk of death or progression increased in a non-linear fashion with age at diagnosis (p<0.001). The risk of death was increased in the intermediate IPSS-R risk group compared to low risk. Patients with RARS and 5q- syndrome had a better outcome compared to RCMD. Increased RBCT intensity in 1yrPD (Table, Figure) was strongly associated with an increased risk of death (p<0.001). In the 1660 patients no significant decline in platelet counts was observed (0.16x109 platelets/l average monthly decline, p=0.16) among patients who were not RBC transfused at any time during follow-up. However platelet counts of patients receiving RBCT declined more quickly (p<0.0001) at an average rate of 1.14x109 platelets/l/month. Among the 920 RBCT dependent patients, lower platelet counts were associated with receiving more RBCT units in the preceding six months. 185 Patients had at least 2 observations both before and after becoming RBCT dependent, defined as 1st RBCT. 50% of these patients had a decreasing trend of platelets prior to their 1st RBCT and 67% had a decreasing slope of platelets after their 1st RBCT. In the control group of RBC untransfused patients, decreasing slopes of platelets occurred in around 50% of the patients throughout the whole observation period of 4 visits. Logistic regression of the risk of having a post-1st RBCT decreasing trend in platelets showed that transfused patients were at a greater risk (OR=1.7, 95% CI: 1.1-2.7) of having a post-1st RBCT decreasing trend in platelets than untransfused patients. Conclusion These multivariate regression models including age, sex, country, IPSS and WHO classification showed that more intensive RBCT treatment is associated with poor prognosis and a more rapid decline of platelets. This indicates that the intensity of RBCT should be incorporated in the regular prognostic scoring systems and the choice of therapeutic interventions. (1): De Swart L et al. Br J Haematol 2015; 170: 372-83. Disclosures Fenaux: NOVARTIS: Honoraria, Research Funding; CELGENE: Honoraria, Research Funding; JANSSEN: Honoraria, Research Funding; AMGEN: Honoraria, Research Funding. Hellström-Lindberg:Celgene Corporation: Research Funding. Sanz:JANSSEN CILAG: Honoraria, Research Funding, Speakers Bureau. Mittelman:Roche: Research Funding; Novartis Pharmaceuticals Corporation: Research Funding; GlaxoSmithKline: Research Funding; Johnson & Johnson: Research Funding, Speakers Bureau; Celgene: Research Funding, Speakers Bureau; Amgen: Research Funding. Almeida:Bristol Meyer Squibb: Speakers Bureau; Shire: Speakers Bureau; Celgene: Consultancy; Novartis: Consultancy. Park:Hospira: Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Research Funding. Itzykson:Oncoethix: Research Funding. de Witte:Novartis: Research Funding.

A 13-Glycosylation Gene Signature in Multiple Myeloma Can Predicts Survival and Identifies Candidates for Targeted Therapy (GiMM13)

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 4423-4423 ◽  
Author(s):  
Caoilfhionn Connolly ◽  
Alokkumar Jha ◽  
Alessandro Natoni ◽  
Michael E O'Dwyer
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
High Risk ◽  
Research Funding ◽  
Gene Signature ◽  
Gene Set Enrichment Analysis ◽  
Rank Test ◽  
P Value ◽  
Log Rank Test ◽  
Novel Approach

Abstract Introduction Advances in genomics have highlighted the potential for individualized prognostication and therapy in multiple myeloma (MM). Previously developed gene expression signatures have identified patients with high risk (Kuiper et al, Blood 2016) however, they provide few insights into underlying disease biology thereby limiting their use in informing treatment decisions. Glycosylation is deregulated in MM (Glavey et al), and potential consequences include altered cell adhesion, signaling, immune evasion and drug resistance. In this study we have utilized RNA sequencing data from the IA7 CoMMpass cohort to characterize the expression profile of genes involved in glycosylation. This represents a novel approach to identify a distinct molecular pathway related to outcome, which is potentially actionable. Methods A pathway based approach was adopted to evaluate genes implicated in glycosylation, including the generation of selectin ligands. A literature review and KEGG pathway analysis of pathways relating to O-glycans, N-glycans, sialic acid metabolism, glycolipid synthesis and metabolism was completed. RNA Cufflinks-gene level FPKM expression of 458 patients enrolled in the IA7 cohort of the Multiple Myeloma Research Foundation (MMRF) CoMMpass trial (NCT145429) were analysed as derivation cohort. We developed expression cut-offs using a novel approach of adjusted existing linear regression model to define the gene expression cut-off by applying 3rd Quartile data (q1+q2/2-qmin). The analysis of overall survival (OS) was completed using adjusted 'kpas' R-package according to our cut-off model. Association between individual transcripts and OS was analyzed with log-rank test. Genes with p-value <0.2 were used in subsequent prioritization analysis. This cut-off methodology was employed to define the nearest neighbor for a gene for Gene Set Enrichment Analysis (GSEA). As far as 4th neighbor above and below the cut off was used to have centrally driven gene selection method for prioritization. The gene signature was validated in GSE2658 (Shaughnessy et al) dataset. Results Initial analysis yielded 184 prospective genes. 147 were significant on univariate analysis. Following further prioritization of these genes, we identified thirteen genes that had significant impact upon outcomes (GiMM13). Figure 1 reveals that GiMM13 signature has a significant correlation with inferior OS (HR 4.66 p-value 0.022). The prognostic impact of stratifying GiMM13 positive (High risk) or GiMM13 negative (Low risk) by ISS stage was evaluated. In Table 1. Kaplan Meier estimates generated for GiMM13 (High) or GiMM13 (Low) stratified by ISS are compared statistically using the log rank test. The prognostic ability of GiMM13 to synthesize distinct subgroups relative to each ISS stage is shown in Figure 2. ISS1-Low is the the lowest risk group with best prognosis. Hazard ratios relative to the ISS1-Low group were 1.8, p-value 0.029 (ISS2-Low), 2.1, p-value 0.031 (ISS3-Low), 4.3, p-value 0.04 (ISS1-HR), 5.9, p-value 0.039 (ISS2-HR) and 3.1, p-value 0.001 (ISS3-HR). The GiMM13 signature enhances the prognostic ability of ISS to identify patients with inferior or superior outcomes respectively. Conclusion While the therapeutic armamentarium for MM has expanded considerably, the significant molecular heterogeneity in the disease still poses a significant challenge. Our data suggests aberrant transcription of glycosylation genes, involved predominantly in selectin ligand synthesis, is associated with inferior survival outcomes and may help identify patients likely to benefit from treatment with agents targeting aberrant glycosylation, e.g. E-selectin inhibitor. Consistent with recent findings in chemoresistant minimal residual disease (MRD) (Paiva et al, Blood 2016), it would appear that O-glycosylation, rather than N-glycosylation is most significantly implicated in this biological processes conferring inferior outcomes. In conclusion, using a novel pathway-based approach to identify a 13-gene signature (GiMM13), we have developed a robust tool that can refine patient prognosis and inform clinical decision-making. Acknowledgment These data were generated as part of the Multiple Myeloma Research Foundation Personalized Medicine Initiatives (https://research.themmrf.org and www.themmrf.org). Disclosures O'Dwyer: Glycomimetics: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding.

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