Differential ICAM3 Gene Expression Correlates with Susceptibility to Natural Killer Cell-Mediated Lysis in Multiple Myeloma

Abstract Introduction We previously reported on the generation of highly activated/expanded natural killer cells (ENKs) after coculture with K562 cells modified to express membrane bound IL15 and 41BB-ligand. These cells have potent antimyeloma properties in vitro, in a NGS mouse model, and are safe when given to advanced multiple myeloma (MM) patients. (Szmania et al, J Immunother 2015) A potential obstacle to the effectiveness of ENK-based immunotherapy of MM is the evasion of immune recognition. We have generated 4 MM cell lines (OPM2, JJN3, ANBL6, and INA-6) which are resistant to ENK-mediated lysis to study mechanisms of resistance. These lines were derived from parental lines by repeated challenge with ENKs and maintained resistance long term when cultured without further exposure to ENKs.(Garg et al, Blood 2012, 120:4020) We have shown by stable isotope labeling with amino acids in cell culture-mass spectrometry, gene expression profiling (GEP), and flow cytometry that ICAM3 is downregulated in the ENK-resistant version of OPM2 (OPM2-R) compared to the parental OPM2. (OPM2-P; Garg et al, Blood 2013, 122:3105) We investigated OPM2-P and OPM2-R by whole exome sequencing (WES) and RNA sequencing (RNAseq) with a focus on ICAM3, evaluated ICAM3 cell surface expression on patient myeloma cells, and studied the importance of ICAM3 expression on ENK functionality. Methods DNA and RNA were extracted from OPM2-P and OPM2-R cells using the Qiagen AllPrep kit. WES libraries were prepared with the Agilent qXT and Agilent SureSelect Clinical Research Exome kits with additional baits covering the Ig and MYC loci. RNAseq libraries were prepared using the Illumina TruSeq stranded mRNA kit. Samples were sequenced 100bp PE on an Illumina HiSeq2500. Samples for WES were sequenced to a mean coverage of >120x and RNAseq to a target of >100M reads. WES data were aligned to the Ensembl GRCh37/hg19 human reference using BWA mem. Somatic variants were called MuTect. RNAseq data were analyzed using Tuxedo Suite. Data were aligned to the Ensembl GRCh37/hg19 human reference using TopHat with Bowtie2. Transcriptome reconstruction, quantification and differential analysis was performed using CuffLinks. ENK-mediated lysis of myeloma cells was measured by 4 hour chromium release assay in the presence of isotype or ICAM3 blocking antibody. Bone marrow aspirates were obtained from MM patients after informed consent in accordance with the Declaration of Helsinki. Primary myeloma cells were selected with CD138-coated immunomagnetic beads and ICAM3 expression was assessed by flow cytometry gated on viable CD138 positive cells. Results There was no mutation in ICAM3 in OPM2-R by WES, but RNAseq found a significant reduction in ICAM3 RNA in OPM2-R compared to OPM2-P (p <0.008). Loss of ICAM3 expression on OPM2-R correlated with a reduction in sensitivity to ENK-mediated lysis compared to OPM2-P (mean 83%, range 77-88%, N=7 assays; E:T ratio 10:1). Blocking of ICAM3 on OPM2-P similarly reduced susceptibility to ENK-mediated cytotoxicity (mean 45%, range 30-56%, N=4 assays; E:T ratio 10:1). We next examined ICAM3 expression on primary myeloma cells by flow cytometry (N=49; GEP-defined high-risk n=43) and found that there is considerable biological inter-patient variation in ICAM3 expression (median MFI 922; range 97-5882, Figure 1A). Further, the majority of patients studied exhibited ICAM3-negative myeloma subpopulations (0.01%-19.4% of CD138 positive myeloma cells, Figure 1B). Functional studies will be presented to correlate the level of ICAM3 expression on primary myeloma cells with sensitivity to ENK-mediated lysis and resulting data shall be presented. Conclusion Our findings demonstrate that MM patients harbor ICAM3-negative myeloma populations in varying frequencies, and we hypothesize that these cells may be similarly resistant to ENK-mediated lysis. Functional assays exploring this question are in progress. By understanding the mechanisms of ENK resistance and immune escape in MM, we hope to elucidate a surrogate biomarker which will allow us to select subjects who are most likely to benefit from cellular immunotherapeutic strategies for enrollment in future ENK-based clinical trials. Additionally, the ICAM3/LFA-1 interaction is also important for adhesion of T cells to their targets; therefore, down-regulation of ICAM3 may also have functional implications in the efficacy of T cell-based therapies for MM. Disclosures Garg: University of Arkansas for Medical Sciences: Employment. Chavan:University of Arkansas for Medical Sciences: Employment. Stone:University of Arkansas for Medical Sciences: Employment. Stivers:University of Arkansas for Medical Sciences: Employment. Warden:University of Arkansas for Medical Sciences: Employment. Skinner:University of Arkansas for Medical Sciences: Employment. Lingo:University of Arkansas for Medical Sciences: Employment. Greenway:University of Arkansas for Medical Sciences: Employment. Khan:University of Arkansas for Medical Sciences: Employment. Johann:University of Arkansas for Medical Sciences: Employment. Heuck:Millenium: Other: Advisory Board; Celgene: Consultancy; Janssen: Other: Advisory Board; University of Arkansas for Medical Sciences: Employment; Foundation Medicine: Honoraria. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:University of Arkansas for Medical Sciences: Employment; Weismann Institute: Honoraria; MMRF: Honoraria; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; CancerNet: Honoraria; Takeda: 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. Epstein:University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment.

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Outcomes of Autologous Transplantation for Treatment-Related AML and MDS in Previously Treated Multiple Myeloma Patients (pts)

Blood ◽

10.1182/blood.v126.23.1997.1997 ◽

2015 ◽

Vol 126 (23) ◽

pp. 1997-1997

Author(s):

Shebli Atrash ◽

Bart Barlogie ◽

Maurizio Zangari ◽

Frits van Rhee ◽

Sarah Waheed ◽

...

Keyword(s):

Multiple Myeloma ◽

Board Of Directors ◽

Standard Therapy ◽

Research Funding ◽

Autologous Transplantation ◽

Case Series ◽

Advisory Board ◽

University Of Arkansas ◽

Medical Sciences ◽

Advisory Committees

Abstract Introduction: Therapy related myelodysplastic syndrome (t-MDS) and acute myeloid leukemia (t-AML) are significant long-term complications of MM treatment. We have treated pts on standard therapy protocols including TT2, TT3, TT4 and TT5. These protocols include an induction, tandem melphalan-based ASCT and consolidation, followed by three years of maintenance. As a part of the protocols, multiple bone marrow examinations including metaphase cytogenetics are performed at regular intervals, giving us the unique opportunity to examine the development of t-MDS/t-AML and understand the efficacy of subsequent treatment. Here we investigate the outcome of t-AML and t-MDS treated with autologous stem cell transplantation (ASCT) in MM patients. Materials and Methods, Results: During the period between 1998 to 2015, a total of 1558 pts were treated for MM with standard therapy protocols. We identified 68 pts out of 1558 who developed t-AML + t-MDS. Thirty-one had a confirmed diagnosis of t-AML, and thirty-seven had a diagnosis of t-MDS. The median age at diagnosis was 60 years (range 45-76). The median time from diagnosis MM of t-AML and t-MDS was 66 months (range, 9.6-155.4) and 63 months (range, 8-130), respectively. Baseline cytogenetics were as follows: complex cytogenetics in 34 pts out of 68, del(7) in 24 pts, del(5) in 17 pts, and del(17p) in 5 pts. Eighteen out of thirty-one t-AML pts were treated with ASCT. The remaining 13 pts did not receive ASCT. The treatment related mortality (TRM) at day100 (D100) in the ASCT group was 33% (6/18 pts). Neutrophil and platelet engraftment was achieved in all 18 pts by D21. Complete remission was achieved in 50% (9 out of 18) of pts. When we compared pts who received ASCT to those who were treated with chemotherapy only, the median overall survival (OS) was 11.28 months after ASCT vs 1.32 months without ASCT (p < 0.05). Nineteen out of thirty seven t-MDS pts were treated with ASCT. When we compared pts who received ASCT to chemotherapy only for t-MDS, there was no difference in survival between the groups. A mortality rate of 47% (9/19) was recorded at D200 after transplantation due to severe infections and lack of engraftment. Conclusion: t-AML and t-MDS treatment is a significant therapeutic challenge for the elderly, who often have poor risk cytogenetic markers, significant comorbidities and a compromised performance status. In our case series of post MM therapy t-AML, ASCT prolonged survival. In contrast, there was no change in survival of t-MDS pts, most likely due to high rate of infectious complications seen in this group. To our knowledge, this is the first analysis suggesting a survival benefit from ASCT in treating t-AML. Although the numbers in our study are small, we recommend that ASCT can be safely considered for t-AML patients who are physically fit, have autologous stem cells in storage and are overseen by a good supportive care team. These results need to be validated in large prospective studies. Disclosures Atrash: University of Arkansas for Medical Sciences: Employment. Barlogie:Millennium: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; European School of Haematology- International Conference on Multiple Myeloma: Other: Travel Stipend; ComtecMed- World Congress on Controversies in Hematology: Other: Travel Stipend; International Workshop on Waldenström's Macroglobulinemia: Other: Travel Stipend; Dana Farber Cancer Institute: Other: Travel Stipend; Multiple Myeloma Research Foundation: Other: Travel Stipend; Myeloma Health, LLC: Patents & Royalties: Co-inventor of patents and patent applications related to use of GEP in cancer medicine licensed to Myeloma Health, LLC. Zangari:Onyx: Research Funding; Novartis: Research Funding; Millennium: Research Funding; University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Waheed:University of Arkansas for Medical Sciences: Employment. Bailey:University of Arkansas for Medical Sciences: Employment. Petty:University of Arkansas for Medical Sciences: Employment. Heuck:Celgene: Consultancy; Janssen: Other: Advisory Board; Millenium: Other: Advisory Board; Foundation Medicine: Honoraria; University of Arkansas for Medical Sciences: Employment. Morgan:Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; MMRF: Honoraria; Weismann Institute: Honoraria; CancerNet: Honoraria; University of Arkansas for Medical Sciences: Employment; Takeda: 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. Jethava:University of Arkansas for Medical Sciences: Employment.

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Gene Expression Profiling of Extramedullary Disease-Related Toward Identification of a Terminal Disease Pathway in Multiple Myeloma

Blood ◽

10.1182/blood.v126.23.1777.1777 ◽

2015 ◽

Vol 126 (23) ◽

pp. 1777-1777

Author(s):

Sarah Waheed ◽

Hongwei Wang ◽

Pingping Qu ◽

Christoph Heuck ◽

Aasiya Matin ◽

...

Keyword(s):

Board Of Directors ◽

Advisory Board ◽

University Of Arkansas ◽

Q Value ◽

Medical Sciences ◽

Training Set ◽

Optimal Cutoff ◽

Advisory Committees ◽

Gene Probes ◽

Test Sets

Abstract Introduction Extramedullary disease (EMD) is a primary disease manifestation of MM, which while not seen frequently at presentation increases in incidence at relapse where its incidence seems to be increasing following the introduction of novel agents. Patients with EMD have a shorter overall survival as well as an increased incidence of anemia, thrombocytopenia, elevated serum lactate dehydrogenase, cytogenetic abnormalities, and high-risk features as determined by gene expression profiling. There is also an increased incidence of the high risk MAF subtypes t (14:16 or 14; 20). Understanding the biology of EMD and identifying its present could give important information about how to improve the outcome of this group. In this work we have used GEP analysis of bone marrow derived plasma cells to predict the presence of EMD so that we can identify the genomic risk factors that define the features of a plasma cell clone, which can develop the capacity to metastasize outside the BM. Materials and Methods We focused on patients treated on TT protocols, at the UAMS, Myeloma Institute between 1989 - 2010, a total of 1154 patients, of which 46 developed EMD before the start of therapy (EMD-1), and 91 developed EMD after registration to UAMS for MM treatment EMD-2. Results We show that most EMD2 cases (57.14%) develop within 3 years after initiation of therapy at the UAMS with few cases developing after this time. Predicting the risk of EMD Combining patients with EMD1 and EMD2 diagnosis within 3 years gave a total of 98 EMD cases. We used 824 samples from 1017 myeloma patients who never developed EMD and had follow up at least 3 years as a comparator group. The data were divided into training (n=619 with 66 EMD cases and 553 controls) and test sets (n=303 with 32 EMD cases and 271 controls). Using the training set, we identified 5 significant gene probes (with a q value < 0.001) and made a score to predict cases and controls. The sensitivity and specificity turned out to be 74.24% and 77.40% in the training set, and 56.25% and 76.75% in the test set, respectively. Predicting the time to EMD2 We tested whether we could predict time to EMD2 based on using baseline GEP samples. In this analysis, all EMD2 cases and controls were included. We divided the data into training (n=743 with 61 EMD2 and 682 controls) and test sets (n=365 with 30 EMD2 and 335 controls). By fitting a uniform Cox regression model to each gene in the training set, we identified 68 gene probes that are associated with time to EMD2 (with a q-value <0.1). We then created a score based on the 68 gene probes and identified an optimal cutoff based on the training set. Applying the optimal cutoff to both training and test sets, we found that the new 68-gene high/low risk model is a good predictor on the cumulative incidence of EMD2 (p value < 0.0001). Conclusion We show that EMD2 cases mostly occur within 3 years of diagnosis and a 68 gene based risk score that can predict a cumulative incidence of EMD. Of the 68 genes that are used to develop the prognostic score for EMD, 6 genes are also part of the 70-gene risk score developed by our group. GEP studies can help us identify EMD-specific gene signature that can further help develop target agents. Figure 1. Figure 1. Disclosures Waheed: University of Arkansas for Medical Sciences: Employment. Wang:Cancer Research and Biostatistics: Employment. Qu:Cancer Research and Biostatistics: Employment. Heuck:Millenium: Other: Advisory Board; Foundation Medicine: Honoraria; Janssen: Other: Advisory Board; University of Arkansas for Medical Sciences: Employment; Celgene: Consultancy. Matin:University of Arkansas for Medical Sciences: Employment. Jethava:University of Arkansas for Medical Sciences: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Hoering:Cancer Research and Biostatistics: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment. Davies:University of Arkansas for Medical Sciences: Employment; Millenium: Consultancy; Onyx: Consultancy; Celgene: Consultancy; Janssen: Consultancy. Morgan:Weismann Institute: Honoraria; University of Arkansas for Medical Sciences: Employment; CancerNet: Honoraria; MMRF: Honoraria; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: 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.

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

Blood ◽

10.1182/blood.v126.23.20.20 ◽

2015 ◽

Vol 126 (23) ◽

pp. 20-20 ◽

Cited By ~ 5

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.

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

Blood ◽

10.1182/blood.v126.23.3182.3182 ◽

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.

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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 ◽

10.1182/blood.v126.23.3181.3181 ◽

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.

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The Composition and Clinical Impact of Focal Lesions and Their Impact on the Microenvironment in Myeloma

Blood ◽

10.1182/blood.v126.23.1806.1806 ◽

2015 ◽

Vol 126 (23) ◽

pp. 1806-1806 ◽

Cited By ~ 1

Author(s):

Shmuel Yaccoby ◽

Joshua Epstein ◽

Sarah K. Johnson ◽

Pingping Qu ◽

Frits van Rhee ◽

...

Keyword(s):

High Risk ◽

Board Of Directors ◽

Risk Score ◽

Surface Expression ◽

Advisory Board ◽

University Of Arkansas ◽

Molecular Subgroups ◽

Medical Sciences ◽

Focal Lesions ◽

Advisory Committees

Abstract Introduction: Focal lesions (FL) are detected by magnetic resonance imaging (MRI) and positron emission tomography (PET) and precede the development of osteolytic lesions in multiple myeloma (MM). FLs are absent in most patients with benign disease and their detection is associated with earlier disease progression suggesting that a distinct MM cell niche in the FLs is associated with conditions that promote the transition to MM. Studying the nature of this niche can significantly enhance our understanding of the biology and progression of MM. Methods: Random BM aspiration samples were taken from the posterior superior iliac crest whereas FL samples were sampled under CT guidance from newly diagnosed MM patients. Gene expression profiling (GEP) was performed on CD138-enriched plasma cells (PC, n=170) and non-enriched BM trephine biopsies (n=49) from paired RBM and FL samples from the same patients and from unrelated RBM cases with no detectable FL (n=79). 8-multicolor flow cytometry (MFC) analysis was performed on 25 paired PC samples and selected genes were validated using immunohistochemistry (IHC). Results: AComparison of GEP from paired RBM-PC and FL-PC showed discrepancies in GEP-based risk score and molecular subgroups and lower Polyclonal-PC score (reflecting the proportion of normal PC infiltration) in FL-PC samples (p=0.0001). There is 89% concordance for the GEP70 risk signature with 10 patients having low-risk PCs in RBM but high-risk PCs in the paired FL, and 8 patients showing high-risk PCs in RBM but low-risk PCs in the paired FL samples. In this setting progression-free and overall survival are mediated by the presence of a high-risk score in either sample. When molecular subgroups were identified there were more high risk-associated PR cases in FL samples (n=28) compared to only 16 PR cases in respective paired RBM-PC samples (p=0.005). Flow cytometry data from 25 paired MM cell samples showed consistently lower surface expression of CD138 in FL (p=0.0001). Cases with detectable CD81 had lower CD81 expression on FL-PC (p=0.03). Discrepancies were also observed in cell surface expression of CD38 and CD45. Pathway's analysis was based on of 523 differentially expressed genes between paired FL and RBM-PC samples (n=170; FDR<0.001) after adjusting for the level of normal PC infiltration. The top KEGG-based pathways enrichment analysis were associated with energy and drug metabolism, survival, cell-cell contact interaction and factors involved in activity of dexamethasone (e.g. NR3C1) and IMiDs (e.g. IZKF1), Figure 1A. Differential expression of ABCA1, the most upregulated gene in FL, was validated by IHC in biopsies. To test whether PCs from patients with FL have specific characteristics irrespective of their location, we compared RBM-PC GEP with RBM-PC GEP of unrelated patients with no detectable FLs. We detected increased expression of cell cycle genes in PC from patients with detectable FL. Reduced osteogenesis and interaction with mesenchymal and vascular lineages have been linked with MM cell phenotypes and dissemination in BM. Microenvironmental reactive stroma (e.g. POSTN, collagen genes) and angiogenic (e.g. EDNRA) gene signatures were significantly upregulated in non-enriched FL biopsies albeit expected high proportion of PC in this site, whereas osteoblastic markers such as BGLAP and IBSP were underexpressed in these samples in comparison to paired non-enriched RBM trephine biopsies, Figure 1B. Conclusions: PC in FL and RBM sites of the same patient are heterogeneous in their phenotype, molecular classification based on risk-score and subgroups, and pathways. GEP signatures of MM cells and the stroma in this niches stressing the biological and clinical relevance of FL as a hallmark in MM. Disclosures Yaccoby: University of Arkansas for Medical Sciences: Employment. Epstein:University of Arkansas for Medical Sciences: Employment. Johnson:University of Arkansas for Medical Sciences: Employment. Qu:Cancer Research and Biostatistics: Employment. van Rhee:University of Arkansa for Medical Sciences: Employment. Jethava:University of Arkansas for Medical Sciences: Employment. Stein:University of Arkansas for Medical Sciences: Employment. Mitchell:Cancer Research and Biostatistics: Employment. Heuck:Millenium: Other: Advisory Board; University of Arkansas for Medical Sciences: Employment; Celgene: Consultancy; Janssen: Other: Advisory Board; Foundation Medicine: Honoraria. Davies:Millenium: Consultancy; Janssen: Consultancy; Celgene: Consultancy; University of Arkansas for Medical Sciences: Employment; Onyx: Consultancy. Crowley:Cancer Research and Biostatistics: Employment. Weinhold:Janssen Cilag: Other: Advisory Board; University of Arkansas for Medical Sciences: Employment. Barlogie:University of Arkansas for Medical Sciences: Employment. Morgan:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; CancerNet: Honoraria; Weismann Institute: Honoraria; MMRF: Honoraria; University of Arkansas for Medical Sciences: Employment; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees.

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

Blood ◽

10.1182/blood.v126.23.2996.2996 ◽

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.

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High Bcl-2/Mcl-1 Gene Expression Ratio Identifies Molecular Sub-Groups of Multiple Myeloma Patients Extremely Sensitive to ABT-737

Blood ◽

10.1182/blood.v116.21.4061.4061 ◽

2010 ◽

Vol 116 (21) ◽

pp. 4061-4061

Author(s):

Linda Bodet ◽

Catherine Pellat-Deceunynck ◽

Patricia Gomez-Bougie ◽

Christelle Dousset ◽

Cyrille Touzeau ◽

...

Keyword(s):

Gene Expression ◽

Multiple Myeloma ◽

Board Of Directors ◽

High Sensitivity ◽

Myeloma Cell ◽

Advisory Committees ◽

Expression Ratio ◽

Myeloma Cells ◽

High Affinity ◽

Highly Sensitive

Abstract Abstract 4061 Multiple myeloma (MM) is a plasma cell malignancy presently incurable with heterogeneity in molecular abnormalities and treatment response. While the importance of Mcl-1 in maintaining survival of Human myeloma cell lines (HMCLs) has been well documented we recently identified a sub-group of HMCLs that highly expressed Bcl-2. This finding prompted us to investigate the sensitivity of HMCLs to ABT-737, a cell-permeant compound that binds with high affinity to Bcl-2 and antagonizes its anti-apoptotic function. The effect of ABT-737 on myeloma cell viability was assessed by APO2.7-PE staining on a large panel of HMCLs (n=26) representative of Multiple Myeloma molecular heterogeneity. We found 7 HMCLs highly sensitive to ABT-737 with an EC50 ranging from 7±0.4nM to 150±7.5nM. Myeloma cell death induced by ABT-737 occurred as early as 4 hours after treatment and led to Bax and Bak activation. While all these sensitive cell lines expressed a high level of Bcl-2, only Bcl-2/Mcl-1 gene expression ratio allowed the discrimination of highly ABT-737 sensitive from resistant HMCLs. High sensitivity (EC 50 <150 nM) was correlated to a ratio > 0.4. This result is in agreement with the high affinity of ABT-737 for Bcl-2 in contrast to Mcl-1. Induction of apoptosis may be due to the displacement of Bim, Puma or Bik from their endogenous complexes with Bcl-2, as demonstrated by immunoprecipitation assays. Interestingly, we demonstrated that all sensitive HMCLs harbored a t(11;14) while 77% (7 out of 9) of t(11;14) HMCLs are sensitive to ABT-737. Then, interrogation of the public expression database of MM patients showed that the Bcl-2/Mcl-1 ratio of both t(11;14) (median 0.29, range 0.05–0.71) and hyperdiploid (median 0.24, range 0.04–0.79) patients was significantly higher to all other groups of patients (p<.001). In order to fairly identify MM patients expressing high Bcl-2/Mcl-1 ratio we set up a flow cytometry assay. Preliminary results confirmed that primary myeloma cells with a high Bcl-2/Mcl-1 ratio are also highly sensitive to ABT-737. Altogether, the very high sensitivity of Bcl-2 high Mcl-1weak HMCLs and primary myeloma cells to ABT-737 (similar to the one of CLL) supports the idea of a clinical trial using Bcl-2 antagonists in a selected subset of t(11;14) and hyperdiploid Multiple Myeloma patients. Disclosures: Avet-Loiseau: Celgene: Membership on an entity's Board of Directors or advisory committees; Janssen-Cilag: Membership on an entity's Board of Directors or advisory committees.

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

Blood ◽

10.1182/blood.v126.23.1808.1808 ◽

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.

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Flow Cytometry Defined Cytoplasmic Immunoglobulin Index Is a Major Prognostic Factor for Progression of Asymptomatic Monoclonal Gammopathies to Clinical Multiple Myeloma

Blood ◽

10.1182/blood.v124.21.2079.2079 ◽

2014 ◽

Vol 124 (21) ◽

pp. 2079-2079

Author(s):

Xenofon Papanikolaou ◽

Adam Rosenthal ◽

Rashid Z Khan ◽

Joshua Epstein ◽

Christoph Heuck ◽

...

Keyword(s):

Gene Expression ◽

Multiple Myeloma ◽

Flow Cytometry ◽

Board Of Directors ◽

Expression Profiling ◽

Research Funding ◽

Plasma Cells ◽

Time To Progression ◽

Advisory Committees ◽

Discrimination Method

Abstract Progression of Asymptomatic Monoclonal Gammopathies to Myeloma requiring treatment -Clinical Multiple Myeloma (CMM)- is an important issue in current clinical investigation toward secondary prevention, i.e. treating high-risk AMG. Several predictive models have been published, including one that incorporated gene expression profiling (GEP) of plasma cells (PC) where a GEP70 score ≥0.26 was linked to higher AMG-CMM progression in a multivariate model (Dhodapkar, Blood 2014). We have applied 2-parameter flow cytometry of DNA and cytoplasmic immunoglobulin (FDC) of bone marrow aspirates as part of baseline staging of all patients with plasma cell dyscrasia. A modification introduced in August 2006 on the doublet discrimination method increased accuracy and reproducibility of FDC results considerably and allowed for the detection of a plasma cell population with a low CI<2.8 as an independent predictor of PFS and OS in newly studies of newly diagnosed CMM treated with TT3b even in the context of GEP70 risk (Papanikolaou, ASH 2012). Realizing the importance of the FDC derived CI in CMM, we assessed whether FDC data from the observational AMG protocol S0120 could identify a population of patients with a high risk for progression to CMM. Out of 252 eligible patients, 130 had an FDC sample taken within 30 days prior to enrollment date and analyzed under the modified doublet discrimination method. FDC identified a light chain restricted population (LCR) in 121 patients. The number of distinct DNA stem lines in the flow cytometry assay, the percentage of LCR plasma cells (LCR%), their ploidy status and respective CI, were evaluated alone and in relation with clinical, laboratory and genetic parameters known to affect progression of AMG to CMM. For continuous FDC variables, the running log-rank statistics were used to determine the optimal cut-off points. In univariate analysis, the existence of at least two distinct DNA stem lines (HR: 3.3, P=0.002), a FDC LCR population of plasma cells >17% (HR: 6.76, P<0.001) and the presence of a LCR population with a CI<3.6 (HR: 6.42, P<0.001) (Figure 1) were statistically significant along with other clinical factors of established prognostic value. A M component> 3g/dL (HR: 12.5, P<0.001), an involved light chain level >10mg/dL (HR: 2.8, P=0.019), a GEP70 score ≥0.26 (HR: 8.22, P<0.001) and the presence of a LCR population with a CI < 3.6 (HR:4.15, P=0.002) survived in the multivariate analysis. To further confirm importance of a low CI to CMM progression, we compared the CI of S0120 with the TT3b patients. The CI was significantly lower in TT3b cases regardless of when the comparison was made for all patients or for strictly aneuploidy cases (P<0.0001) to exclude the possibility that the CI difference reflects the lower percentage of normal plasma cells found in CMM. In conclusion, FDC is an easily applicable, fast and low-cost test, which offers valuable prognostic information even in the era of gene expression profiling and other cytogenetic testing strategies. The identification of a low CI as a risk factor suggests that, progression of AMG to CMM is characterized by the emergence of a low immunoglobulin producing myeloma cell population. Figure 1: Time to progression requiring myeloma therapy by CI, S0120 Figure 1:. Time to progression requiring myeloma therapy by CI, S0120 Disclosures Heuck: Celgene: Honoraria; Foundation Medicine: Honoraria; Millennium: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees. Dhodapkar:Celgene: Research Funding. Zangari:Norvartis: Membership on an entity's Board of Directors or advisory committees; Onyx: Research Funding; Millennium: Research Funding. Morgan:Celgene Corp: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees; Janssen: Membership on an entity's Board of Directors or advisory committees; Myeloma UK: Membership on an entity's Board of Directors or advisory committees; International Myeloma Foundation: Membership on an entity's Board of Directors or advisory committees; The Binding Site: Membership on an entity's Board of Directors or advisory committees; MMRF: Membership on an entity's Board of Directors or advisory committees.

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