Re-Mineralization of Large Pelvic Lytic Lesions By CT Imaging in Patients with Multiple Myeloma: The Arkansas Experience

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 4193-4193
Author(s):  
Meera Mohan ◽  
Rohan Samant ◽  
Larry J Suva ◽  
Corey O Montgomery ◽  
Daisy V. Alapat ◽  
...  
Keyword(s):  
Board Of Directors ◽  
Research Funding ◽  
Bone Destruction ◽  
Patient Characteristics ◽  
University Of Arkansas ◽  
Medical Sciences ◽  
Advisory Committees ◽  
Osteolytic Lesions ◽  
Lytic Lesions

Abstract INTRODUCTION Profound osteolytic lesions are a hallmark of multiple myeloma (MM) bone disease. Bone destruction is associated with severely unbalanced bone remodeling, secondary to the secretion of osteoclast activating factors and significant osteoblast suppression. Lytic lesions of the pelvis are relatively common in MM patients and contribute to increase morbidity due to the high risk of fracture that frequently demands surgical intervention. Since we observed significant improvements in the pelvic CT of patients following total therapy 4 (TT4) we retrospectively analyzed the appearance on pelvic osteolytic lesions by CT during TT4 treatment for myeloma. METHODS The UAMS Myeloma data base was interrogated to identify patients enrolled on the TT4 trial. TT4 is a protocol designed for low risk MM patients as defined by a baseline plasma cell GEP score < than 0.66. The treatment protocol includes two induction chemotherapy cycles followed by tandem autologous bone marrow transplantation, two consolidation cycles and 3 years of maintenance. During treatment, patients were exposed to alkylating agents, IMIDS and proteasome inhibitor agents as well as bisphosphonates. Baseline pelvic osteolytic lesions with > 1 cm in minimal diameter identified by PET/CT or CT of the pelvis were compared to the most recent radiological study available for the same subject. All identified cases were reviewed by radiology faculty to confirm the baseline and follow-up reported findings. Radiological findings were correlated with disease status, molecular subgroup, PET scanning and MRI. RESULTS Sixty-three (63) patients, with a median age of 62 years, were identified for this analysis. Baseline patient characteristics are shown in Table 1. With a median follow up of 41 months, CT studies indicate that 44% (28/63) of patients with large baseline pelvic lytic lesions achieved re-accumulation of radio-dense mineralized tissue at the lytic site. Sixty-eight percent of such patients reached at least VGPR. The average size of the lytic lesions that re-mineralized was 4.0 cm (minimum 1.3 cm - maximum 10 cm). Baseline GEP-defined molecular subgroups and cytogenetic distribution was not different from the entire patient population of TT4. CONCLUSION This study clearly shows that mineral redeposition in large pelvic lytic lesions of MM patients on TT4 is achievable in a significant proportion of individuals. We observed that the amount of re-mineralization was prominent in pelvic lytic lesions with cortical bone destruction. Since flat bones, such as the pelvis, are formed via intramembranous ossification further investigation of the mechanism responsible for this effect is warranted at skeletal sites with different regenerative capacity. These data also suggest that, contrary to much dogma, MM bone lesions can regain matrix mineralization capacity. Table 1. Baseline Patient Characteristics n/N (%) Male 43/63 (69%) IgA Isotype 11/63 (17.5%) IgD Isotype 1/63 (1.6%) IgG Isotype 36/63 (57.1%) Nonsecretory 1/63 (1.6%) Light Chain Isotype 14/63 (22.2%) LDH > = 190 U/L 8/63 (12.7%) Abnormal Cytogenetics 44/63 (69.8%) GEP CD-1 subgroup 4/64 (6.3%) GEP CD-2 subgroup 17/64 (26.6%) GEP HY subgroup 24/64 (37.5%) GEP LB subgroup 8/64 (12.5%) GEP MF subgroup 1/64 (1.6%) GEP MS subgroup 2/64 (3.1%) GEP PR subgroup 5/64 (7.8%) Disclosures Mohan: University of Arkansas for Medical Sciences: Employment. Samant:University of Arkansas for Medical Sciences: Employment. Suva:University of Arkansas for Medical Sciences: Employment. Montgomery:University of Arkansas for Medical Sciences: Employment. Alapat:University of Arkansas for Medical Sciences: Employment. Morello:University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Waheed:University of Arkansas for Medical Sciences: Employment. Thanendrarajan:University of Arkansas for Medical Sciences: Employment. Schinke:University of Arkansas for Medical Sciences: Employment. Heuck:Millenium: Other: Advisory Board; Celgene: Consultancy; Foundation Medicine: Honoraria; Janssen: Other: Advisory Board; University of Arkansas for Medical Sciences: Employment. Jethava:University of Arkansas for Medical Sciences: Employment. Johann:University of Arkansas for Medical Sciences: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment. Davies:University of Arkansas for Medical Sciences: Employment; Celgene: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Onyx: Consultancy. Morgan:CancerNet: Honoraria; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; University of Arkansas for Medical Sciences: Employment; MMRF: Honoraria; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Weismann Institute: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees. Zangari:Novartis: Research Funding; Millennium: Research Funding; Onyx: Research Funding; University of Arkansas for Medical Sciences: Employment.

High Risk Multiple Myeloma Demonstrates Marked Spatial Genomic Heterogeneity Between Focal Lesions and Random Bone Marrow; Implications for Targeted Therapy and Treatment Resistance

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 20-20 ◽  
Author(s):  
Niels Weinhold ◽  
Shweta S. Chavan ◽  
Christoph Heuck ◽  
Owen W Stephens ◽  
Ruslana Tytarenko ◽  
...  
Keyword(s):  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Advisory Board ◽  
Driver Mutations ◽  
University Of Arkansas ◽  
Medical Sciences ◽  
Clonal Heterogeneity ◽  
Advisory Committees ◽  
Site Specific

Abstract Introduction: Recent next generation sequencing studies have defined the mutation spectrum in multiple myeloma (MM) and uncovered significant intra-clonal heterogeneity, showing that clinically relevant mutations are often only present in sub-clones. Longitudinal analyses demonstrated that tumor clones under therapeutic pressure behave in a "Darwinian" fashion, with shifting dominance of tumor clones over time. Recently, stratification of clonal substructures in distinct areas of the tumor bulk has been shown for multiple cancer types. So far, spatial genomic heterogeneity has not been systematically analyzed in MM. This stratification in space is becoming increasingly important as we begin to understand the contribution of Focal Lesions (FL) to tumor progression and emergence of drug resistance in MM. We have recently shown that high numbers of FL are associated with gene expression profiling (GEP) defined high risk (HR). A comparison of GEP data of 170 paired random bone marrow (RBM) and FL aspirates showed differences in risk signatures, supporting the concept of spatial clonal heterogeneity. In this study we have extended the analysis by performing whole exome sequencing (WES) and genotyping on paired RBM and FL in order to gain further insight into spatial clonal heterogeneity in MM and to find site-specific single nucleotide variant (SNV) spectra and copy number alterations (CNA), which contribute to disease progression and could form the basis of adaptation of the tumor to therapeutic pressure. Materials and Methods: We included 50 Total Therapy MM patients for whom paired CD138-enriched RBMA and FL samples were available. Leukapheresis products were used as controls. For WES we applied the Agilent qXT kit and a modified Agilent SureSelect Clinical Research Exome bait design additionally covering the immunoglobulin heavy chain locus and sequences located within 1Mb of the MYC locus. Paired-End sequencing to a minimum average coverage of 120x was performed on an Illumina HiSeq 2500. Sequencing data were aligned to the Ensembl GRCh37/hg19 human reference using BWA. Somatic variants were identified using MuTect. For detection of CNA we analyzed Illumina HumanOmni 2.5 bead chip data with GenomeStudio. Subclonal reconstruction was performed using PhyloWGS. Mutational signatures were investigated using SomaticSignatures. The GEP70 risk signature was calculated as described previously. Informed consent in accordance with the Declaration of Helsinki was obtained for all cases included in this study. Results: Analyzing RBM and FL WES data, we detected between 100 and 200 somatic SNVs in covered regions, with approximately 30% of them being non-synonymous, and less than 5% stop gained or splice site variants. A comparison of paired RBM and FL WES data showed different extents of spatial heterogeneity. Some pairs had very similar mutation profiles with up to 90% shared variants, whereas others demonstrated marked heterogeneity of point mutations. We did not detect differences in mutational signatures between RBM and FL using the 'SomaticSignatures' package. We found site-specific driver mutations with high variant allele frequencies, indicating replacement of other clones in these areas. For example we observed a clonal KRAS mutation exclusively in the RBM, whereas a NRAS variant was only identified in the paired FL. The same holds true for large-scale CNAs (>1 Mb). We identified a case in which the high risk CNAs gain(1q) and del(17p) were only detectable in the FL. Further examples for site-specific CNAs were a del(10q21) and a gain(4q13) detected in FLs only. As a prominent pattern, we observed outgrowth of sub-clonal RBM CNAs as clonal events in the FL. Based on mutation and CNA data we identified different forms of spatial evolution, including parallel, linear and branching patterns. Of note, a stratified analysis by GEP70-defined risk showed that a more pronounced spatial genomic heterogeneity of SNVs and CNAs was associated with HR disease. Conclusion: We show that spatial heterogeneity in clonal substructure exists in MM and that it is more pronounced in HR. The existence of site-specific HR CNAs and driver mutations highlights the importance of heterogeneity analyses for targeted treatment strategies, thereby facilitating optimal personalized MM medicine. Disclosures Weinhold: University of Arkansas for Medical Sciences: Employment; Janssen Cilag: Other: Advisory Board. Chavan:University of Arkansas for Medical Sciences: Employment. Heuck:Millenium: Other: Advisory Board; Janssen: Other: Advisory Board; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment; Foundation Medicine: Honoraria. Stephens:University of Arkansas for Medical Sciences: Employment. Tytarenko:University of Arkansas for Medical Sciences: Employment. Bauer:University of Arkansas for Medical Sciences: Employment. Peterson:University of Arkansas for Medical Sciences: Employment. Ashby:University of Arkansas for Medical Sciences: Employment. Stein:University of Arkansas for Medical Sciences: Employment. Johann:University of Arkansas for Medical Sciences: Employment. Johnson:University of Arkansas for Medical Sciences: Employment. Yaccoby:University of Arkansas for Medical Sciences: Employment. Epstein:University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Zangari:Novartis: Research Funding; Onyx: Research Funding; Millennium: Research Funding; University of Arkansas for Medical Sciences: Employment. Schinke:University of Arkansas for Medical Sciences: Employment. Thanendrarajan:University of Arkansas for Medical Sciences: Employment. Davies:Millenium: Consultancy; Onyx: Consultancy; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment; Janssen: Consultancy. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:University of Arkansas for Medical Sciences: Employment; MMRF: Honoraria; CancerNet: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Weismann Institute: Honoraria; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Defining the Impact of Tandem Autologous Stem Cell Transplantation in Multiple Myeloma: A Case-Match Analysis in the Total Therapy Trials

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 3182-3182
Author(s):  
Sharmilan Thanendrarajan ◽  
Caleb K. Stein ◽  
Faith E Davies ◽  
Frits van Rhee ◽  
Maurizio Zangari ◽  
...  
Keyword(s):  
Board Of Directors ◽  
Research Funding ◽  
Advisory Board ◽  
P Value ◽  
University Of Arkansas ◽  
Medical Sciences ◽  
Advisory Committees ◽  
Data Set ◽  
Baseline Characteristics ◽  
Total Therapy

Abstract Introduction The introduction of melphalan-based high-dose chemotherapy and autologous stem cell transplantation (MEL-ASCT) has markedly improved the survival of patients with multiple myeloma (MM). The initial clinical studies suggested conditioning with melphalan (MEL) 200 mg/m2 was optimum compared to MEL 140mg/m2 or MEL/TBI. Following on from the introduction of a single MEL-ASCT, the use of tandem transplantation was explored and highlighted the potential of this approach to improve outcome. With the introduction of consolidation and maintenance approaches, questions still remain regarding which patients are most appropriate for the tandem approach and what dose of melphalan should be delivered. The Total Therapy (TT) trials were initiated more than 25 years ago and have used tandem MEL-ASCT since their inception. Not all patients treated in our facility received a 2nd MEL-ASCT due to a number of reasons including adverse events during 1st MEL-ASCT or a lack of funding for 2nd ASCT thus limiting access to a tandem treatment approach. A dose-reduced MEL (140 mg/m2) was given to patients with renal impairment or advanced age at 1st and / or 2nd ASCT. Consolidation/Maintenance chemotherapy was introduced from TT2 onwards. This large data set therefore allows us to perform a retrospective pair-matched analysis to address a number of important clinical questions including the role of single versus tandem MEL-ASCT and standard versus dose-reduced tandem MEL-ASCT in the era of novel agents for induction and consolidation/maintenance therapy. Materials and Methods We have analyzed data from 1918 patients who were enrolled in Total Therapy 1 - 6 trials. Given the changing chemotherapy regimens within TT trials due to the introduction of novel agents coupled with diverse baseline characteristics, we designed a retrospective pair-matched analysis framework in order to account for differences in patient and treatment variables. This was achieved by generating identical treatment and control group subsets from within the full data set that are identical across key covariates including baseline characteristics of ISS stage, age, and creatinine; protocol anti-myeloma treatment regimens such as dexamethasone, thalidomide, bortezomib, and lenalidomide; and variations in transplantation such as melphalan dosage. The majority of the patients in the TT trials completed induction chemotherapy and received the 1st MEL-ASCT (TT1: 88.3%, TT2: 86.0%, TT3: 97.6%, TT4: 95.0%, TT5: 100% and TT6: 95.1%). Fewer patients received the 2nd MEL-ASCT (TT1: 66.7%, TT2: 68.2%, TT3: 85.0%, TT4: 70.0%, TT5: 74.0%, and TT6: 52.4%). MEL 200 mg/m2 was the predominant dose, administered with MEL 140 mg/m2 given to a smaller fraction of patients due to age and renal impairment restrictions. TT3 has the highest percentage of patients receiving a 2nd MEL-ASCT at 85.0% and most of those at standard dose (MEL 200 mg/m2). Results After balancing treatment and control groups with identical treatment, baseline characteristics, and dose of 1st ASCT (140 or 200 mg/m2), we found 289 tandem and 289 single transplant pairs with no significant differences across any of our balancing covariates (all paired Wilcoxon rank test p-values = 1.00). Analysis of these pair-matched cases strongly supported tandem transplantation as superior in outcome-cases with tandem transplantation had 5-year OS rate of 74.8% compared to 54.1% in single transplant cases (logrank p-value: 1.44e-06). For cases with tandem transplantation, we pair-matched 164 cases with tandem 200 mg/m2 transplants to 164 cases with either 140 mg/m2 received as 1st ASCT, 2nd ASCT, or both transplants. Analysis of these pair-matched cases strongly supported tandem 200 mg/m2 over 140 mg/m2 as the 5-year OS rates were 78.5% and 63.6%, respectively (logrank p-value: 1.23e-03). Conclusion MEL-ASCT is the backbone for treatment of MM. From our study, there is overwhelming evidence that application of tandem MEL-ASCT delivers superior clinical outcome compared to single MEL-ASCT. In order to achieve the best clinical results tandem MEL-ASCT should be performed using standard dose MEL 200 mg/m2; dose reduction (140 mg/m2) leads to unfavorable clinical outcome. Ongoing analysis aims to reveal the benefits of MEL-ASCT treatment across specific subgroups to better understand differential response and optimal therapy for patients across distinct molecular and risk subgroups. Figure 1. Figure 1. Figure 2. Figure 2. Disclosures Thanendrarajan: University of Arkansas for Medical Sciences: Employment. Stein:University of Arkansas for Medical Sciences: Employment. Davies:Celgene: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Onyx: Consultancy; University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Zangari:Onyx: Research Funding; University of Arkansas for Medical Sciences: Employment; Millennium: Research Funding; Novartis: Research Funding. Heuck:Millenium: Other: Advisory Board; Janssen: Other: Advisory Board; Celgene: Consultancy; Foundation Medicine: Honoraria; University of Arkansas for Medical Sciences: Employment. Schinke:University of Arkansas for Medical Sciences: Employment. Waheed:University of Arkansas for Medical Sciences: Employment. Jethava:University of Arkansas for Medical Sciences: Employment. Weinhold:University of Arkansas for Medical Sciences: Employment; Janssen Cilag: Other: Advisory Board. Matin:University of Arkansas for Medical Sciences: Employment. Mathur:University of Arkansas for Medical Sciences: Employment. Mohan:University of Arkansas for Medical Sciences: Employment. Radhakrishnan:University of Arkansas for Medical Sciences: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; University of Arkansas for Medical Sciences: Employment; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; CancerNet: Honoraria; MMRF: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Weismann Institute: Honoraria.

scholarly journals A Prognostic 51-Gene Signature Linked to Abnormal Metaphase Cytogenetics Identifies Myeloma Patients Who Benefit from Fractionated Melphalan Dosing and Added Bortezomib, Thalidomide and Dexamethasone As Conditioning for Autologous Stem Cell Transplant

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 3181-3181
Author(s):  
Frits van Rhee ◽  
Alan Mitchell ◽  
Maurizio Zangari ◽  
Jeffery Sawyer ◽  
Sarah Waheed ◽  
...  
Keyword(s):  
Board Of Directors ◽  
Clinical Outcomes ◽  
Research Funding ◽  
Gene Signature ◽  
Advisory Board ◽  
Phase Iii ◽  
University Of Arkansas ◽  
Medical Sciences ◽  
Gene Model ◽  
Advisory Committees

Abstract Introduction: Total Therapy 4 (TT4) comprises a randomized phase III trial enrolling 289 patients with gene expression profiling defined low-risk MM in which patients were allocated to a standard arm (TT4-S) or a light arm (TT4-L) with as principal goal to reduce toxicity yet maintain efficacy in TT4-L. Methods: The TT4-S regimen was similar to TT3b and utilized 2 cycles of VDTPACE induction, tandem transplantation with melphalan 200mg/m2, 2 cycles of dose reduced VDTPACE consolidation and 3 years maintenance with VRD. In TT4-L the number of induction and consolidation cycles was reduced to one each and melphalan was given in a fractionated fashion (50mg/m2/d x 4days) to avoid peak levels of melphalan and reduce mucosal toxicity. Bortezomib and thalidomide were added to the fractionated melphalan conditioning regimen to explore synergistic effects and compensate for potential loss of efficacy. Results: Grade ≥3 toxicities in TT4-S and L occurred with similar frequencies. With a median follow-up of 4.5 years, the OS and PFS were similar in TT4-S and TT4-L at 90 and 87% respectively. The same applied to PFS (TT4-S 84% versus TT4-L 79%). The presence of metaphase defined cytogenetic abnormalities (CA) affected clinical outcomes. In TT4-S, patient with CA had a strong trend toward inferior OS compared to patients with no CA (2 year estimate 83 versus 94%, p=0.08), while the reverse applied to TT4-L (95 versus 81%, p=0.07). Non-significant trends in similar directions were noted for PFS. Complete remission duration tended to be inferior in patients with CA-type MM in TT4-S (2 year estimate, 79 vs. 92%, p=013) with no significant differences in TT4-L. Time to relapse was significantly shorter for CA patients on the TT4-S arm (2 year estimate, 15.4 versus 3.9%), but was not affected by CA in the TT4-L (15.8 vs 7.9%, p=0.79. The observation of CA's favorable OS impact in TT4-L was not anticipated. We next analyzed whether the presence or absence of metaphase CA was linked to specific gene probes which could help to explain better outcomes in TT4-L. Among a training set of 266 untreated patients enrolled in TT3a with available baseline GEP studies, 90 (34%) exhibited CA. Among a test set of 164 patients with baseline GEP accrued to TT3b, 67 (41%) qualified as having CA. Fifty-one probes were different in patients with and without CA (q<0.0001). Seven of the 51 genes had functions in DNA replication, recombination, and repair; five in nucleic acid metabolism, and 4 in RNA post-translational modification and RNA damage and repair. Pathway analysis identified a network of eight interrelated genes that were overexpressed in the CA group, indicating that these MM cells have a higher proliferative activity. We next examined clinical outcomes by the GEP51-CA prediction model in the 2 arms of TT4. In TT4-S, GEP51/no-CA had superior OS and PFS compared to GEP51/CA, which was not observed in TT4-L (Figure 1A, B). Conclusions: A prognostic CA-linked GEP signature can identify patients who benefit from conditioning with fractionated melphalan dosing together bortezomib, thalidomide and dexamethasone which negates the adverse impact of CA. Patients who lacked a CA-type gene signature were best served with single high dose melphalan. These exploratory findings need to be confirmed in a prospective randomized trial. Figure 1. PFS according to 51-gene model predicting CA versus no-CA according to arm (TT4-S, 1A; TT4-L, 1B) Figure 1. PFS according to 51-gene model predicting CA versus no-CA according to arm (TT4-S, 1A; TT4-L, 1B) Disclosures van Rhee: University of Arkansa for Medical Sciences: Employment. Mitchell:Cancer Research and Biostatistics: Employment. Zangari:Millennium: Research Funding; Novartis: Research Funding; University of Arkansas for Medical Sciences: Employment; Onyx: Research Funding. Sawyer:University of Arkansas for Medical Sciences: Employment. Waheed:University of Arkansas for Medical Sciences: Employment. Heuck:Millenium: Other: Advisory Board; Janssen: Other: Advisory Board; Celgene: Consultancy; Foundation Medicine: Honoraria; University of Arkansas for Medical Sciences: Employment. Thanendrarajan:University of Arkansas for Medical Sciences: Employment. Schinke:University of Arkansas for Medical Sciences: Employment. Jethava:University of Arkansas for Medical Sciences: Employment. Grazziutti:University of Arkansas for Medical Sciences: Employment. Petty:University of Arkansas for Medical Sciences: Employment. Steward:University of Arkansas for Medical Sciences: Employment. Panozzo:University of Arkansas for Medical Sciences: Employment. Bailey:University of Arkansas for Medical Sciences: Employment. Hoering:Cancer Research and Biostatistics: Employment. Crowley:Cancer Research and Biostatistics: Employment. Davies:University of Arkansas for Medical Sciences: Employment; Celgene: Consultancy; Janssen: Consultancy; Onyx: Consultancy; Millenium: Consultancy. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:MMRF: Honoraria; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Weismann Institute: Honoraria; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; CancerNet: Honoraria; University of Arkansas for Medical Sciences: Employment; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees.

scholarly journals Profound Impact of Sample Processing Delay on Gene Expression of Multiple Myeloma Plasma Cells

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 2996-2996
Author(s):  
Tobias Meissner ◽  
Anja Seckinger ◽  
Kari Hemminki ◽  
Uta Bertsch ◽  
Asta Foersti ◽  
...  
Keyword(s):  
Gene Expression ◽  
Risk Stratification ◽  
Board Of Directors ◽  
Research Funding ◽  
Plasma Cells ◽  
University Of Arkansas ◽  
Medical Sciences ◽  
Advisory Committees ◽  
Travel Grant ◽  
The Uk

Abstract Introduction: Gene expression profiling (GEP) has significantly contributed to the elucidation of the molecular heterogeneity of multiple myeloma plasma cells (MMPC) and only recently it has been recommended for risk stratification. Prior to GEP MMPC need to be enriched resulting in an inability to immediately freeze bone marrow aspirates or use RNA stabilization reagents. As a result in multi-center MM trials sample processing delay due to shipping may be an important confounder of molecular analyses and risk stratification based on GEP data. In order to determine the impact of "shipping delay" on MMPC gene expression we analyzed a set of 573 newly diagnosed German MM patients including 230 in-house and 343 shipped samples. Materials and Methods: We included publicly available GEP data of newly diagnosed MM patients treated in the GMMG HD4 and MM5 trials. All samples had been processed in a central laboratory in Heidelberg and include 85 HD4 and 145 MM5 in-house and 97 HD4 and 246 MM5 shipped samples. Prediction of sample status was done on publicly available GEP, including data from the UK, UAMS and MMRC. Differential gene expression was assessed using empirical Bayes statistics in linear models for microarray data. Predictor for shipment status was generated on the MM5 cohort using prediction analysis for microarrays. Pathway enrichment analysis was done using WebGestalt. Risk signatures and molecular subgroups were obtained as previously described. Fisher's exact test was used to compare the subgroup distribution between cohorts. If applicable, results were corrected for multiple testing using the Benjamini-Hochberg method. In all statistical tests, an effect was considered statistically significant if the P-value of its corresponding statistical test was not greater than 5%. Results: Applying the Goeman's global teston the MM5 set showed that "shipping delay" significantly impacted global gene expression (P <0.001). Compared to 145 in-house samples, we detected 3301 down-regulated and 3501 up-regulated genes in 246 shipped samples. For 4280 genes we confirmed differential expression in an independent set of 85 in-house and 97 shipped samples. Of these genes 2040 had a >1.5-fold and 826 a >2-fold difference in expression level. Differentially expressed genes were enriched in processes like ribosome biogenesis, cell cycle, and apoptosis. We observed significantly lower proliferation rates in shipped samples (P <0.001). We did not detect significant differences in the distribution of molecular subgroups between in-house and shipped samples in the combined set of HD4 and MM5. Among GEP based risk predictors the IFM-15 seemed to underestimate high risk in shipped samples, whereas the GEP70 and the EMC-92 gene signatures were more robust. In order to provide a tool to assess the "shipping effect" in public repositories, we generated a 17-gene predictor for shipped samples with a 10-fold cross validation error rate of 0.06 for the training set and an error rate of 0.15 for the validation set. Applying the predictor to further publicly available data sets we detected the "shipping effect" signature in 11% of cases of the UAMS set, 94% of the UK set and 57% of the MMRC set. Conclusion: Our study shows that "shipping delay" widely influences gene expression of MMPC with different impact on molecular classification and risk stratification. Based on available data, currently no clear circumvention of the shipping impact on MMPC can be recommended. It should be avoided if possible or at least be taken into account. Disclosures Seckinger: Takeda: Other: Travel grant. Salwender:Celgene: Honoraria; Janssen Cilag: Honoraria; Bristol Meyer Sqibb: Honoraria; Amgen: Honoraria; Novartis: Honoraria. Goldschmidt:Novartis: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Millenium: Honoraria, Research Funding, Speakers Bureau; Onyx: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Bristol-Myers Squibb: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Janssen-Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Amgen: Consultancy, Membership on an entity's Board of Directors or advisory committees; Chugai: Honoraria, Research Funding, Speakers Bureau; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees. Morgan:MMRF: Honoraria; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; University of Arkansas for Medical Sciences: Employment; CancerNet: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Weismann Institute: Honoraria; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees. Hose:Takeda: Other: Travel grant; EngMab AG: Research Funding. Weinhold:Janssen Cilag: Other: Advisory Board; University of Arkansas for Medical Sciences: Employment.

IgM Myeloma: A Multicenter Retrospective Study of 159 Patients

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 3276-3276
Author(s):  
Jorge J. Castillo ◽  
Artur J. Jurczyszyn ◽  
Edvan Crusoe ◽  
Jacek Czepiel ◽  
Julio Davila ◽  
...  
Keyword(s):  
Retrospective Study ◽  
Board Of Directors ◽  
Research Funding ◽  
Reference Group ◽  
Estimated Gfr ◽  
Advisory Committees ◽  
Cytogenetic Abnormalities ◽  
Lytic Lesions ◽  
Male Sex

Abstract Introduction: IgM-secreting myeloma is rare, encompassing about 1% of all the myeloma cases. Given its rarity, the characteristics and survival of these patients have not been extensively studied. Therefore, we carried out a multicenter retrospective study in patients with IgM myeloma. Methods: The study protocol was reviewed and approved by the Institutional Review Board of each participating institution. Clinical data were gathered and included age, sex, hemoglobin, calcium, LDH, estimated glomerular filtration rate (GFR), presence of lytic bone lesions, International Staging System score, cytogenetic abnormalities, final outcome and overall survival (OS) time. OS was defined as the time in months from diagnosis to last follow-up or death. The Chi-square and the rank-sum tests were used to compare categorical and continuous variables, respectively. The Kaplan-Meier method was used to estimate OS and the log-rank waas used to compare groups. The Cox proportional-hazard regression method was used to fit univariate and multivariate survival models, reported as hazard ratio (HR) with 95% confidence intervals (CI). All reported p-values are two-sided, and were considered significant if less than 0.05. Results: A total of 159 patients with IgM myeloma from 20 centers from Europe, USA and Latin America were included in this analysis. Patients were diagnosed between 1996 and 2015. The median age at diagnosis was 65 years (range 37-86 years) with a male predominance (68%). The median serum IgM level was 2510 mg/dl (range 27-12,100 mg/dl) with 25% of patients having a serum IgM within normal limits but an IgM monoclonal spike detectable in serum electrophoresis. Hemoglobin levels <10 g/dl were seen in 49 patients (32%), serum calcium was elevated in 24 (16%), estimated GFR of 60 ml/min or less in 56 (37%), lytic lesions were detected in 86 (58%), and serum LDH was elevated in 28 (24%). ISS scores of 1, 2 and 3 were seen in 53 (36%), 63 (43%) and 31 (21%) of patients, respectively. Although immunohistochemistry and/or flow cytometry data were limited, CD20 expression was seen in 15/26 (58%) and cyclin D1 in 10/15 (67%) patients. The most common cytogenetic abnormalities were t(11;14) in 26/67 (39%), del13q in 25/76 (33%) and del17p in 6/76 (8%) patients. 149 patients (94%) received at least one line of systemic therapy for myeloma of which 13 (9%) received rituximab as part of initial therapy. After a median follow-up of 47 months, 74 patients (47%) have died. The median OS was 62 months (95% CI 51-79 months). Cause of death was known in 38 patients, and the most common was myeloma progression (74%). IN the univariate analysis, prognostic factors associated with a worse OS were age (HR 1.03, 95% CI 1.01-1.06; p=0.01) and ISS score (ISS 2: HR 1.43, 95% CI 0.83-2.48; p=0.2, and ISS 3: HR 3.03, 95% CI 1.54-5.98; p=0.001, using ISS 1 as reference group), while male sex was associated with a better OS (HR 0.56, 95% CI 0.34-0.90; p=0.02). Hemoglobin, calcium, estimated GFR and lytic lesions were not associated with OS. In the multivariate analysis, male sex was associated with a better OS (HR 0.57, 95% CI 0.35-0.95; p=0.03) and ISS with worse OS (ISS 2: HR 1.57, 95% CI 0.89-2.74; p=0.12, and ISS 3: HR 2.76, 95% CI 1.38-5.55; p=0.004, using ISS 1 as reference group). Conclusion: Patients with IgM myeloma apparently present with similar clinical characteristics as patients with non-IgM myeloma. Pathologically, CD20 and cyclin D1 expression is common. The most common cytogenetic abnormalities identified were t(11;14) and del13q. Survival does not appear shorter than non-IgM myeloma patients, and the ISS appears to have similar prognostic value. Disclosures Castillo: Millennium: Research Funding; Janssen: Honoraria; Otsuka: Consultancy; Biogen: Consultancy; Abbvie: Research Funding; Pharmacyclics: Honoraria. Ghobrial:Celgene: Honoraria, Research Funding; BMS: Honoraria, Research Funding; Novartis: Honoraria; Takeda: Honoraria; Noxxon: Honoraria; Amgen: Honoraria. Hájek:Celgene: Consultancy, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Janssen: Honoraria; BMS: Honoraria; Takeda: Consultancy. Hungria:International Myeloma Foundation Latin America: Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy; Amgen: Consultancy; Roche: Consultancy; Bristol: Consultancy; Janssen: Consultancy, Speakers Bureau. Niesvizky:Celgene: Consultancy, Research Funding, Speakers Bureau; Takeda: Consultancy, Research Funding, Speakers Bureau; Onyx: Consultancy, Research Funding, Speakers Bureau. Reagan:Alexion: Honoraria; Seattle Genetics: Membership on an entity's Board of Directors or advisory committees. Richardson:Celgene: Membership on an entity's Board of Directors or advisory committees. Spicka:Janssen Cilag: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Millenium: Honoraria. Gertz:Celgene: Honoraria; Med Learning Group: Honoraria, Speakers Bureau; Research to Practice: Honoraria, Speakers Bureau; Alnylam Pharmaceuticals: Research Funding; Novartis: Research Funding; Prothena Therapeutics: Research Funding; Ionis: Research Funding; NCI Frederick: Honoraria; Sandoz Inc: Honoraria; GSK: Honoraria; Annexon Biosciences: Research Funding.

scholarly journals Melphalan Affects Genes Critical for Myeloma Survival, Homing, and Response to Cytokines and Chemokines

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1808-1808
Author(s):  
Shmuel Yaccoby ◽  
Joshua Epstein ◽  
Pingping Qu ◽  
Frits van Rhee ◽  
Maurizio Zangari ◽  
...  
Keyword(s):  
Cell Surface ◽  
Board Of Directors ◽  
Research Funding ◽  
Advisory Board ◽  
Cxcr4 Expression ◽  
Cell Surface Receptors ◽  
University Of Arkansas ◽  
Medical Sciences ◽  
Advisory Committees ◽  
Surface Receptors

Abstract Introduction: We have previously used global gene expression (GEP)-based clinical pharmacogenomics of dexamethasone, thalidomide, pomalidomide and bortezomib (Bor) to understand their mechanism of actions and how this impacts their clinical efficacy in multiple myeloma (MM) patients. High dose therapy with melphalan (Mel) followed by autologous stem cell transplantation is a major treatment regimen for MM and consequently assessing the pharmacogenomics of Mel is clinically relevant. Importantly not all patients benefit from Mel exposure and, therefore, it remains important to understand the molecular mechanism of its actions and how they underlie treatment resistance. Materials and methods: 252 newly diagnosed MM patients randomized to Total Therapy (TT)4 (GEP70 low-risk, N=210) and TT5 (GEP70 high-risk, n=42) clinical trials received single administration of Bor (1.0mg/m2) followed after 48 hrs latter by a single administration of Mel (10mg/m2). BM aspirates were obtained at baseline, 48 hrs post-Bor and 48 hrs Post-Mel. Purified CD138-selected MM cells underwent GEP analysis using the Affymetrix U133plus2 microarrays and the results generated were analyzed using Gene Set Enrichment Analysis (GSEA) and Ingenuity. The effect of Mel on expression of cell surface receptors in MM cell lines was validated by flow cytometry. Results: Expression of 176 probe sets was changed 48 hours after a single Bor administration at FDR < 0.01, and expression of 5117 additional probe sets was further changed after Mel. Expression of 6309 probe sets was changed when comparing post-Mel to baseline, of these 108 were also changed post-Bor and 4043 overlapped with changes observed between post-Mel and post-Bor. By utilizing GSEA and Ingenuity we identified the top pathways associated with Mel activity including activation of p53, nitrogen metabolism and metabolism of xenobiotics by p450, whereas Bor was associated with proteasome activation. Bor and Mel both downregulated pathways related to cell cycle and DNA replication and damage response. Top listed genes differentially expressed between baseline and post-Mel and/or post-Bor and post-Mel and reportedly linked to MM pathogenesis include underexpression of IRF4, ASPM, MYC and NEK2, and upregulation of TNFSF10 (TRAIL), MDM2, BAX and KLF9. Among the top upregulated genes by Mel were also set of 7 cell surface receptors (MERTK, CXCR4, OGFRL1, INSR, TGFBR2, S1PR1, IL1R2) and 5 cytokines (AREG, TNFSF8, BDNF, IGF1, TNFSF15). We initially focused our analysis on MERTK and CXCR4 which have been previously implicated in MM and whose expression was upregulated by 2.5 (FDR < 4.6x10-39) and 1.8 (FDR < 3.9x10-36) folds, respectively. Increased expression of MERTK and CXCR4 was associated with shorter progression-free survival (PFS) and over survival (OS) in our Total Therapy trials, including analysis restricted to GEP70 high-risk patients in TT3 and TT5. Moreover, GEP of paired MM cell samples obtained from focal lesion and random BM sites of the same patient (n=170) showed reduced CXCR4 expression in MM cells residing within focal lesions (FDR < 6.1x10-5), further implicating intra-patient heterogeneity of CXCR4 expression in distinct BM niches with response to Mel. To validate direct effect of Mel on these factors at the protein level, flow cytometry analysis for MERTK and CXCR4 was performed on MM cell lines (n=3) following treatment with Mel (5-10µM) or Bor (2.5-5nM) for 72 hrs. Mel but not Bor increased mean fluorescent intensity of MERTK and CXCR4 by 3.1±0.5 (p < 0.05) and 5.1±0.5 (p<0.04) folds, respectively, and the percentage of MERTK- and CXCR4-expressing MM cells by 11.9±2.5 (p < 0.04) and 4.1±0.1 (p < 0.002) folds, respectively, compared to control vehicle-treated cells. Conclusions: The upregulation of cell surface receptors and growth factors by Mel suggests that exposure to the drug promotes the retention of MM cells within the BM and their reliance on the BM microenvironment. This pharmacogenomics approach is useful as it can identify previously unrecognized biomarkers and pathways associated with Mel activity and drug resistance in MM patients. Disclosures Epstein: University of Arkansas for Medical Sciences: Employment. Qu:Cancer Research and Biostatistics: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Zangari:Millennium: Research Funding; University of Arkansas for Medical Sciences: Employment; Onyx: Research Funding; Novartis: Research Funding. Heuck:Janssen: Other: Advisory Board; Foundation Medicine: Honoraria; Millenium: Other: Advisory Board; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment. Davies:Millenium: Consultancy; University of Arkansas for Medical Sciences: Employment; Onyx: Consultancy; Celgene: Consultancy; Janssen: Consultancy. Mitchell:Cancer Research and Biostatistics: Employment. Crowley:Cancer Research and Biostatistics: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; CancerNet: Honoraria; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; MMRF: Honoraria; Weismann Institute: Honoraria; University of Arkansas for Medical Sciences: Employment; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees.

Upfront 28-Day Metronomic Therapy for High-Risk Multiple Myeloma (HRMM)

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 1843-1843 ◽  
Author(s):  
Sharmilan Thanendrarajan ◽  
Daisy V. Alapat ◽  
Maurizio Zangari ◽  
Carolina Schinke ◽  
Christoph Heuck ◽  
...  
Keyword(s):  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Advisory Board ◽  
Proliferation Index ◽  
University Of Arkansas ◽  
Medical Sciences ◽  
Advisory Committees ◽  
Cytogenetic Abnormalities ◽  
Metronomic Therapy

Abstract Introduction: Despite major advances in MM therapy with the inclusion of novel agent combinations for induction prior to and after autotransplant-supported high-dose melphalan, the 15% of patients with GEP-defined HRMM continue to fare poorly with PFS and OS not exceeding 2 and 3 years, respectively. This poor outcome has not been improved with less dose-intense and more dose-dense Total Therapy 5. Having previously reported on 16-day metronomic therapy with low-dose doxorubicin (DOX) and cisplatin (DDP) plus VTD (Papanikolaou, Haematologica), we explored further extension of such metronomic treatment to 28 days (metro-28) also in newly diagnosed HRMM patients. Patients and Methods: All patients signed a written informed consent and data analysis was approved by our IRB. In the outpatient setting, a single cycle of metro-28 comprised DOX and DDP each at 1.0mg/m2/d for 28d by continuous infusion (CI), along with VTD (bortezomib 1.0mg/m2 on days 1-4, 7-10, 13-16, 19-22, 25-28; DEX 12mg on days 1-4, 7-10, 13-16, 19-22, 25-28; thalidomide 50-100mg/d x 28d; some patients also received vincristine [VCR] at a flat daily dose of 0.07mg/d x 28d by CI. Results: Fourteen patients were initiated on metro-28. Their characteristics included age >=65y in 12; albumin <3.5g/dL in 8; B2M >5.5mg/L in 7; cytogenetic abnormalities [CA] were present in 10; GEP70 HRMM in 9/13; PR subgroup in 8/13 (Table 1). The median follow up is 11mo. As portrayed in Figure 1A, no patient has died; the 6mo PFS estimate was 85% (Figure 1B); responses included CR in 3/14, VGPR in 7/14 and PR in 10/14 (Figure 1C); and the PR duration estimate at 6mo is 80% (Figure 1D). Of interest, GEP70 scores morphed to low risk in 3/13. Vascular density (CD34) decreased markedly in most patients evaluated. Toxicities were minor; myelosuppression was virtually absent; alopecia was not encountered. Subsequent salvage therapies included repeat metro-28, combination chemotherapy (PACMED) and autotransplants. Conclusion: We conclude that metro-28 is a promising and safe strategy for elderly patients with HRMM, and we hypothesize an anti-angiogenic mechanism of action in addition to direct anti-MM effects. Table 1. Patient characteristics Factor n/N (%) Age >= 65 yr 12/14 (86%) Albumin < 3.5 g/dL 8/14 (57%) B2M >= 3.5 mg/L 9/12 (75%) B2M > 5.5 mg/L 7/12 (58%) Hb < 10 g/dL 10/14 (71%) Cytogenetic Abnormalities 10/14 (71%) CA within 1 Year of Therapy 10/14 (71%) CA within 90 Days of Therapy 9/14 (64%) GEP 70-Gene High Risk 9/13 (69%) GEP PR Subgroup 8/13 (62%) GEP Proliferation Index >= 10 7/13 (54%) GEP Centrosome Index >= 3 7/13 (54%) n/N (%): n- Number with factor, N- Number with valid data for factor Figure 1. Figure 1. Disclosures Thanendrarajan: University of Arkansas for Medical Sciences: Employment. Alapat:University of Arkansas for Medical Sciences: Employment. Zangari:University of Arkansas for Medical Sciences: Employment; Onyx: Research Funding; Millennium: Research Funding; Novartis: Research Funding. Schinke:University of Arkansas for Medical Sciences: Employment. Heuck:Millenium: Other: Advisory Board; Janssen: Other: Advisory Board; Foundation Medicine: Honoraria; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Rosenthal:Cancer Research and Biostatistics: Employment. Epstein:University of Arkansas for Medical Sciences: Employment. Yaccoby:University of Arkansas for Medical Sciences: Employment. Davies:Janssen: Consultancy; Onyx: Consultancy; University of Arkansas for Medical Sciences: Employment; Millenium: Consultancy; Celgene: Consultancy. Morgan:MMRF: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; CancerNet: Honoraria; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Weismann Institute: Honoraria; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; University of Arkansas for Medical Sciences: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment.

Molecular Subgroups of Hyperdiploidy and Their Prognostic Relevance - an Analysis of 1,036 Myeloma Trial Patients

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 2983-2983
Author(s):  
Martin F Kaiser ◽  
Eileen Mary Boyle ◽  
Brian A Walker ◽  
Dil B Begum ◽  
Paula Proszek ◽  
...  
Keyword(s):  
Board Of Directors ◽  
Copy Number ◽  
Research Funding ◽  
Entire Group ◽  
University Of Arkansas ◽  
Molecular Subgroups ◽  
Medical Sciences ◽  
Advisory Committees ◽  
Qrt Pcr ◽  
The Uk

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.

Deletion of TP53 (17p13) Is Associated with Poor Outcome for Newly Diagnosed High-Risk Multiple Myeloma

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 2982-2982
Author(s):  
Erming Tian ◽  
Joshua Epstein ◽  
Pingping Qu ◽  
Christoph Heuck ◽  
Frits van Rhee ◽  
...  
Keyword(s):  
Bone Marrow ◽  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Chromosome 17 ◽  
University Of Arkansas ◽  
Newly Diagnosed ◽  
Medical Sciences ◽  
Advisory Committees ◽  
Risk Patients

Abstract Introduction In multiple myeloma (MM), deletion of chromosome 17 p13 (del17p) is a poor prognostic feature. The percentage of cells carrying an abnormality has been reported to be important with thresholds of 20% being taken generally but thresholds as high as 60% being suggested more recently. We have reported previously in the Total Therapy (TT)-2 trial (NCT00083551) for newly diagnosed (ND) MM that del17p is an adverse prognostic factor (Blood 112: 4235). The TT3 trial (NCT00081939) incorporated Brtezomib into tandem Melphalan-based autotransplants with DT-PACE for induction/consolidation and Thalidomide and Dexamethasone for maintenance to treat patients with newly diagnosed MM. In more recent iterations of these trials following the introduction of novel agents in induction and during maintenance the impact of carrying del17p has not been studied. In particular we have stratified patients into low- or high-risk molecular subgroups based on the GEP-70 (TT4 protocol [NCT00734877] or TT5 protocol [NCT00869232], respectively). We have used interphase FISH (iFISH) to detect the presence of del17p in baseline bone marrow samples. Method The iFISH slides were prepared with bone marrow aspirates after removing erythrocytes. A specific TP53 probe at chromosome 17 arm p13 combined with a control probe for the ERBB3 locus (HER2, 17q12), in different colors, were hybridized to bone marrow cells. Myeloma PCs were identified by restricted Kappa or Lambda immunoglobulin light-chain staining. We investigated role of 20% cutoffs per ≥100 tumor cells for significant deletion of the TP53 probe. Kaplan-Meier analysis was used to estimate the distributions of overall survival (OS) and progression-free survival (PFS) during the follow-ups. OS was calculated from registration until the date of decease. PFS was similarly calculated, but also incorporated progressive disease as an event. Results We examined 709 baseline samples from TT3, 4, and 5 trials with the two probes at chromosome 17. Overall, 66 of 709 patients (9.3%) had deletion of TP53 locus, including 44 of the 591 (7.5%) of low-risk patients and 20 of the 118 (17.0%) high-risk patients (Table). The range of TP53-deleted cells among newly diagnosed patients is 20-99% (median=75%) overall; 35-100% (median=62%) in TT3-low-risk; 30-97% (median=80%) in TT3-high-risk; 21-99% (median=76%) in TT4; and 20-97% (median=81%) in TT5. Deletion of TP53 was associated with significant shorter OS and PFS in HR patients treated on TT3. The 3 year estimated OS of patients for TT3-HR with del17p was 33% compared with 56% for TT3-LR with del17p, and PFS of patients for TT3-HR with del17p was 25% compared with 51% for TT3-LR with del17p (Figure). The comparison of TT4 to TT5 continued showing short OS in HR patients treated on TT5. The 3 year estimated OS of patients for HRMM with del17p was 17% compared with 75% for TT5 patients without deletion (p=0.0008). But, del17p was neutral in LR patients treated on TT4 (Figure). Conclusion Since the introduction of novel agents during various stages of the disease and a focus on HRMM and LRMM defined by GEP70 we show that while TP53 deletion is an adverse prognostic factor for patients with HRMM it is no longer prognostically relevant in LRMM. Table 1. Patients with iFISH results GEP-70 riskLow ≤0.66 High >0.66 Deletion TP53 in 20-59% PCs (n/N [%]) Deletion TP53 in ≥60% PCs (n/N, [%]) Total TT3 (N=329) Low=256 9/329, [2.7%] 9/329, [2.7%] 18/329, [5.5%] High=73 3/329, [0.9%] 9/329, [2.7%] 12/329, [3.7%] TT4 (N=313) Low=313 5/313, [1.6%] 21/313, [6.7%] 26/313, [8.3%] High=0 0 0 0 TT5 (N=67) Low=22 2/67, [3.0%] 0 2/67, [3.0%] High=45 0 8/67, [11.9%] 8/67, [11.9%] Sum (N=709) Low=591 (83.4%) 14/709, [2.0%] 30/709, [4.2%] High=118 (16.6%) 3/709, [0.4%] 17/709, [2.4%] 66/709 (9.3%) Figure 1. Figure 1. Disclosures Tian: University of Arkansas for Medical Sciecnes: Employment. Epstein:University of Arkansas for Medical Sciences: Employment. Qu:Cancer Research and Biostatistics: Employment. Heuck:Millenium: Other: Advisory Board; Janssen: Other: Advisory Board; Celgene: Consultancy; Foundation Medicine: Honoraria; University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Zangari:University of Arkansas for Medical Sciences: Employment; Millennium: Research Funding; Onyx: Research Funding; Novartis: Research Funding. Hoering:Cancer Research and Biostatistics: Employment. Sawyer:University of Arkansas for Medical Sciences: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:Weismann Institute: Honoraria; CancerNet: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; MMRF: Honoraria; University of Arkansas for Medical Sciences: Employment; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees.

The Impact of Combination Chemotherapy and Tandem Stem Cell Transplant on Clonal Substructure and Mutational Pattern at Relapse of MM

Blood ◽  
2015 ◽  
Vol 126 (23) ◽  
pp. 372-372 ◽  
Author(s):  
Christoph Heuck ◽  
Niels Weinhold ◽  
Erich Allen Peterson ◽  
Michael Bauer ◽  
Caleb K. Stein ◽  
...  
Keyword(s):  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Clonal Evolution ◽  
Advisory Board ◽  
Proliferation Index ◽  
University Of Arkansas ◽  
Medical Sciences ◽  
Advisory Committees ◽  
The Impact

Abstract Introduction: Next generation sequencing of over 800 newly diagnosed multiple myeloma (NDMM) cases has established the mutational landscape and key cancer driver pathways. The mutational basis of relapse has not been systematically studied. Two previous studies (Keats et al.; Bolli et al.) identified 4 patterns of clonal evolution. Neither study included uniformly treated patients and looked at the impact of therapy on clonal structure at relapse. Understanding the mutational patterns underlying relapse and how they relate to specific therapies is crucial in order to improve MM outcomes, especially for high-risk (HR) MM. In this study we compare the clonal structure at presentation (PRES) and at relapse (REL), after exposure to Total Therapy (TT). Materials and Methods: We studied 33 pairs of tumor samples collected at PRES and REL. 9 patients were treated on TT2, 13 on TT3, 10 on TT4 and 1 on TT5-like regimen. Eleven patients had HR disease at PRES. DNA was extracted from CD138+ selected cells from random bone marrow aspirates. Germline controls were obtained from leukapheresis products. Whole exome sequencing libraries were prepared using the Agilent qXT kit and the Agilent SureSelect Clinical Research Exome kit with additional baits covering the Ig and MYC loci. All samples were sequenced on an Illumina HiSeq2500 to a median depth of 120x. Sequencing data were aligned to the Ensembl GRCh37/hg19 human reference using BWA. Somatic variants were called using MuTect. Translocations were identified using MANTA. Copy number variations were inferred using TITAN. Gene expression profiles (GEP), generated using the Affymetrix U133plus2 microarray, were available for all tumor samples. Nonnegative matrix factorization (NMF) was used to define mutation signatures. Results: The median time to progression was 30 months with a median follow up of 9.5 years. 22 cases achieved a complete remission (CR) or near CR. There were 11 cases of HR at PRES. Of the 22 cases with low risk (LR) MM, 7 relapsed with HR disease. There were on average 478 SNVs per sample at PRES and 422 at REL. All but 2 cases had evidence of new mutations at REL. There were no consistent patterns or number of mutation associated with REL or GEP-defined risk. Patients of the MF molecular subgroup had more mutations compared to other molecular subgroups (657 vs. 379) and were enriched for mutations with an APOBEC signature. We did not detect any mutation signature consistent with chemotherapy-induced alterations, providing evidence that TT itself does not cause additional mutations. Primary recurrent IgH translocations called by MANTA were confirmed by GEP data. A number of new translocations were identified , several only at REL. In particular we demonstrate a case with a newly acquired MYC translocation at relapse, indicating that it contributed to progression. We identified 5 patterns of clonal evolution (Figure 1): A) genetically distinct relapse in 3 patients, B) linear evolution in 8 patients, C) clonal selection in 9 patients, D) branching evolution in 11 patients, and E) stable clone(s) in 2 patients. Patterns A (distinct) and B (linear) were associated with low risk and longer survival, whereas patterns D (branching) and E (stable) were associated with high risk and shorter time to relapse and overall survival (Table 1). Conclusion: This is the first study to systematically analyze the pattern of clonal evolution using NGS in patients treated with combination chemotherapy and tandem ASCT. We identified 5 patterns of evolution, which correlate with survival. We identified 3 cases with a loss of the original clone and emergence of a new clone, suggesting high effectiveness of Total Therapy for those patients. The persistence of major clones despite multi agent chemotherapy in most other cases supports a concept of a tumor-initiating cell population that persist in a protective niche, for which new therapies are needed. Table 1. Pattern of Evolution GEP70 Pres.(high risk: ≥0.66) Proliferation Index Pres. GEP70 Rel.(high risk: ≥0.66) Proliferation Index Rel Mean OS Mean TTR A: distinct (n=3) -0.690 -3.34 -0.015 2.04 8.18 5.00 B: linear (n=8) -0.171 -0.34 0.618 9.22 5.70 4.05 C: selection (n=9) 0.366 3.20 0.569 6.97 3.95 2.64 D: branching (n=11) 0.710 5.17 1.173 11.15 3.84 2.21 E: stable (n=2) 1.532 7.42 1.124 2.54 0.96 0.35 Pres.: Presentation; Rel.: Relapse; OS: Overall Survival; TTR: Time to Relapse Figure 1. Patterns of Relapse Figure 1. Patterns of Relapse Disclosures Heuck: Foundation Medicine: Honoraria; Millenium: Other: Advisory Board; Janssen: Other: Advisory Board; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment. Weinhold:Janssen Cilag: Other: Advisory Board; University of Arkansas for Medical Sciences: Employment. Peterson:University of Arkansas for Medical Sciences: Employment. Bauer:University of Arkansas for Medical Sciences: Employment. Stein:University of Arkansas for Medical Sciences: Employment. Ashby:University of Arkansas for Medical Sciences: Employment. Chavan:University of Arkansas for Medical Sciences: Employment. Stephens:University of Arkansas for Medical Sciences: Employment. Johann:University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Waheed:University of Arkansas for Medical Sciences: Employment. Johnson:University of Arkansas for Medical Sciences: Employment. Zangari:University of Arkansas for Medical Sciences: Employment; Millennium: Research Funding; Onyx: Research Funding; Novartis: Research Funding. Matin:University of Arkansas for Medical Sciences: Employment. Petty:University of Arkansas for Medical Sciences: Employment. Yaccoby:University of Arkansas for Medical Sciences: Employment. Davies:University of Arkansas for Medical Sciences: Employment; Millenium: Consultancy; Janssen: Consultancy; Onyx: Consultancy; Celgene: Consultancy. Epstein:University of Arkansas for Medical Sciences: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:Weismann Institute: Honoraria; MMRF: Honoraria; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; University of Arkansas for Medical Sciences: Employment; CancerNet: Honoraria; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees.

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