Richardson, Paul G.

Abstract BAFF is a member of the tumor necrosis factor (TNF) family and is critical for the maintenance and homeostasis of normal B-cell development. Importantly, BAFF promotes the generation of rapidly dividing immunoglobulin secreting plasmablasts from activated memory B cells by enhancing their survival. Given that MM is a cancer of plasma cells and that the signaling cascades implicated in receptor ligand interactions of BAFF are crucial in MM cell biology, we hypothesized that this cytokine may play a critical role in MM cell development, survival, and proliferation. We performed gene expression profiling (GEP) on CD 138+ plasma cells isolated from 90 MM patients (45 newly diagnosed and 45 relapsed) and 11 healthy controls using the Affymetrix U133A arrays. Our data demonstrates increased expression of transmembrane activator and calcium modulator and cyclophilin ligand interactor (TACI) and B-cell maturation antigen (BCMA), 2 receptors used by BAFF to exert its effects. Our data also shows an increased expression of a proliferation-inducing ligand (APRIL), another member of the TNF family with homology to BAFF. Expression levels of BAFF and BAFF-R could not be determined because of lack of these probe sets on the Affymetrix U133A arrays. GEP analysis shows increased BCMA expression (p<0.0001, student T test) on newly diagnosed and relapsed MM versus normal plasma cells. Flow cytometry on MM cell lines demonstrated a differential expression of the three receptors of BAFF, with BCMA present on most cell lines but BAFF-R expressed at low levels only on LR5 cells and DOX40 MM cells. In contrast, flow cytometry performed on MM patient cells demonstrated the presence of all 3 receptors on CD 138+ cells. ELISA assays performed on 30 MM sera demonstrated a mean BAFF level of 618 pg/ml (range: 128–2126pg/ml) versus 235pg/ml (range: 158–326pg/ml) in 7 normal donor sera. Fifty six% (17/30) of MM patients had BAFF levels in excess of the highest value noted in normals. To understand the role BAFF might play in the biology of MM, we studied the effects of recombinant BAFF (rh-BAFF) on MM cells directly and in the context of its bone marrow microenvironment. (abstract # 554746) rh-BAFF conferred a survival advantage to MM cells and protected them against dexamethasone-induced cytotoxicity. Importantly, anti-apoptotic proteins Bcl2 and Mcl-1 were upregulated, as were growth and survival signals belonging to the JAK/STAT and MAPKinase pathways. Conversely, neutralizing antibody to BAFF blocked, at least in part, blocked the upregulation of anti-apoptotic proteins with associated growth and survival, confirming that these effects were due to BAFF. Importantly, all of these signals were downregulated even in the presence of bone marrow stromal cells (BMSCs). These data therefore show a role for BAFF mediating MM cell survival and provide the framework for inhibiting BAFF, either alone or in combination with dexamethasone, to improve patient outcome in MM.

Abstract Introduction: We investigated tumor gene expression profiling (PGx) to identify predictive classifiers of response and elucidate the mechanism of efficacy of proteasome inhibition in multiple myeloma (MM) by bortezomib, a first-in-class proteasome inhibitor. Analysis of 44 samples from the SUMMIT phase 2 trial identified predictive classifiers of response in patients (pts) with refractory MM (ASH 2002, Abstr 1519). We now report on the PGx analysis of the SUMMIT-derived classifier in an independent sample set from the APEX phase 3 trial, a multicenter randomized study of 669 pts that demonstrated the superiority of bortezomib to high-dose dex for relapsed MM following 1 to 3 prior therapies (Richardson NEJM 2005). As well, we report on a new classifier of response built by combining samples from SUMMIT and MLN34101-040 (040) (a study of bortezomib in pts who failed dex in APEX or were not eligible for APEX) and tested in the APEX samples. Methods: 93 participating clinical centers collected pretreatment bone marrow aspirates and enriched tumor cells on site before centralized RNA extraction and microarray analysis. Approximately 85% of pts consented to whole-genome analysis. Quality control for RNA integrity and quantity, microarray data quality, and tumor cell purity resulted in 129 patient samples from APEX evaluable for PGx; 67 were from the bortezomib arm and 62 from the dex arm. 48 samples were evaluable from 040. Patient characteristics of this subset were similar to those of the overall study population. Predictive classifiers were identified and tested via separate training and test datasets. Results: Consistent with the SUMMIT analysis, the APEX and 040 datasets exhibit biologic features expected of MM, including the overexpression of translocation target genes such as cyclin D1, MAF, and MMSET/FGFR3. Classifiers built using only the SUMMIT samples predict the outcome of pts in the APEX bortezomib arm with an overall accuracy of 51% (sensitivity [Sn] = 49%, specificity [Sp] = 55%; P = .81) and in the dex arm with an overall accuracy of 56% (Sn = 64%, Sp = 50%; P = .31). If the classifier was built using data from both the SUMMIT and 040 trials (87 total samples), the prediction of response in the APEX bortezomib arm was statistically significant (66% accuracy, Sn = 89%, Sp = 42%; P = .006). The same classifier only predicts the response of dex-treated pts with an overall accuracy of 46% (Sn = 72%, Sp = 28%; P = .88), suggesting specificity for bortezomib. Many of the overexpressed genes associated with bortezomib insensitivity relate to protein synthesis (EIF4B, RPL5) and RNA binding (SFRS10, CPSF6). Future Directions: This work highlights practical and scientific issues that inform future efforts to implement PGx in clinical trials. Predictive accuracy may be influenced by the clinical end point, limited sample size, and/or technical considerations associated with distinct trials and genomic data. The influence of study differences (relating to pts’ time from diagnosis, number of prior therapies, molecular subtypes, or hybridization characteristics) on the ability to build classifiers and identify biologic pathways related to response are being examined; these and potential insights on drug mechanisms will be presented.

Abstract INTRODUCTION: Previous studies have demonstrated the clinical activity of the mTOR inhibitor RAD001 in low- grade lymphomas. Our preclinical studies demonstrated activity of mTOR inhibitors in Waldenstrom Macroglobulinemia (WM) cell lines and patient samples. This phase II study aimed to determine safety and activity of the oral mTOR inhibitor RAD001 (Novartis Pharmaceutical, MA) in patients with relapsed or refractory WM. METHODS: Patients who had at least one previous therapy for WM, and who had symptomatic relapsed or refractory disease were eligible. NCI CTCAE v3.0 was used for toxicity assessment. All patients received daily RAD001 at 10 mg. A cycle was considered 28 days. Patients were allowed to stay on therapy until progression of disease or excessive toxicity. This study was conducted in a collaborative effort between Dana Farber Cancer Institute (DFCI) and Mayo Clinic College of Medicine. Here, we report the data on the patients accrued at DFCI. RESULTS: 19 pts (15 men and 4 women) have been treated to date. All patients had symptomatic disease and required therapy. The median number of lines of prior treatment was 3 (range 1 – 5) including included rituximab, nucleoside analogues (fludarabine or 2-CDA), combination chemotherapy (e.g. CHOP, CVP), chloramucil, and bortezomib. The median IgM at baseline was 3330 mg/dL (range 1010– 7410). The median follow on RAD001 was 8 months (range 3 – 22 months). Eighteen pts are currently evaluable for response. Best responses to RAD001 after 2 cycles using IgM monoclonal protein were as follows: partial remission in 8 (44%), minimal response in 5 (28%). Progressive disease occurred in 4 (22%) and stable disease occurred in 1 (6%). The overall response rate (PR+MR) was 72%. The median duration of response has not been reached (3–22+ months). Patients tolerated therapy well without significant toxicities. Grade 3 and 4 toxicities included grade 4 thrombocytopenia in 1 patient, grade 3 pneumonia in 1 patient, grade 3 hyperglycemia in 1 patient and grade 3 mucositis in 1 patient. Other adverse events of grade 2 or lower included nail cracking, mucositis, diarrhea, and fatigue. Attributable toxicities otherwise proved manageable with appropriate supportive care, and RAD001 was generally well tolerated. One patient enrolled on the study withdrew consent and changed to hospice care within 3 weeks of therapy, and passed away due to disease progression. CONCLUSIONS: The use of the oral RAD001 single agent RAD001 in patients with relapsed or refractory WM was welltolerated and demonstrated significant activity achieving an overall response rate in 72% of patients. Future studies of combination of this agent with rituximab and bortezomib are currently being planned.

Abstract In an effort to identify novel genetic abnormalities in multiple myeloma (MM) we analyzed an initial set, as part of the Multiple Myeloma Research Consortium (MMRC) Genomics Initiative, of 94 MM patient samples on high-resolution array-based comparative genomic hybridization (aCGH) and gene expression profiling (GEP) technologies. The MMRC Genomics Initiative is a three-year research program spanning a full-spectrum of genomic technologies with the goal of analyzing 250 MM patient samples by 2009. Raw data from the Initiative are released in near real time through the MMRC Multiple Myeloma Genomics Portal. This initial aCGH dataset from the Agilent 244K platform represents the highest resolution gene copy number analysis with corresponding GEP released to date in MM. It has confirmed the cytogenetic definitions of MM with the data set being split between patients with hyperdiploid and non-hyperdiploid MM. Furthermore, the 244K platform has helped to refine minimal regions of change present on 1p, 1q, 6q, 8p, 13q, 14q, and 16q. A comprehensive screen of the dataset for genes residing in regions of homozygous deletion identified 105 genes. The most commonly affected gene was CDKN2C(p18) (8.3%) while 12 other regions were recurrently targeted. Several of these regions were recently implicated in the pathogenesis of MM but the large majority represents novel observations. The aCGH and GEP data were integrated using two different programs developed by the core institutions (The Broad Institute of Harvard & MIT and Translational Genomics Research Institute). First, Genomic Identification of Significant Targets in Cancer (GISTIC), which identifies highly significant regions of change and a limited set of candidate genes within these regions, was used to identify 285 genes associated with DNA content alterations. Second, Breakpoint Expression Correlation (BEC), which identifies dysregulated genes on either side of a copy number alteration, was used to identify 194 genes with expression changes associated with a breakpoint. This latter gene list includes all known IgH translocation target genes identified to date in myeloma. Overlapping the gene lists generated by GISTIC, BEC, and the homozygous deletion screen identified a number of genes previously implicated in MM such as CDKN2C(p18), CYLD, BIRC2/BIRC3, and two novel genes, FAM46C and RNF6. Ongoing data integration with RNAi and high content sequencing projects of the current Initiative holds great promise in furthering our understanding of MM. The MMRC Genomics Initiative and resulting efforts from the myeloma research community will increase our understanding of MM at the molecular level, help to identify new targets, and ultimately lead to the development of better, more effective therapies for myeloma.

Abstract Introduction: Clinical development of bortezomib in multiple myeloma (MM) included pharmacogenomic gene expression profiling (GEP) of pre-treatment tumor biopsies in order to evaluate the feasibility of developing predictive classifiers in prospective clinical trials and to better define the biological pathways related to drug sensitivity. By partitioning the samples into train (n=101) and test (n=80) datasets, statistically significant classifiers of response and survival were identified and then validated [Mulligan G, et al: Blood. 2007; 109:3177–88]. Here we describe specific genes and biological pathways associated with bortezomib efficacy in relapsed MM. Methods: Using tumor GEP data from 188 patients treated with single-agent bortezomib we identified genes associated with overall survival (OS), as well as genes associated with response (R) or progressive disease (PD) after bortezomib therapy. These clinical endpoints were also analyzed with biological pathway algorithms including GSEA [Subramanian A, et al: Proc Natl Acad Sci2005; 102:15545–50] Ingenuity Pathway Analysis and Gene Ontology/GATHER. These results were then compared to GEP data from a patient subset (n=76) treated with single-agent dexamethasone and also cell lines selected for differential sensitivity to bortezomib. Results: A comparison of R and PD highlighted numerous differentially expressed genes; approximately 200 were over-expressed in R and 500 were over-expressed in PD (t-test <0.01). R-associated genes include signaling molecules like TRADD, CFLAR and TANK, while PD-associated genes included oncogenes (NRAS), apoptotic regulators (DAP3) and cancer antigens (CTAG). Pathway tools helped to integrate and extend these observations, consistently identifying NFkB activation and overexpression of adhesion pathways as R-associated. Overexpression of protein synthesis and mitochondrial pathways were PD-associated. The overexpression of pathways such as NFkB, adhesion and cytokines appear linked specifically with bortezomib and not dexamethasone sensitivity. These approaches were also applied to patient survival. In contrast to analyses of single genes, the pathway tools highlighted links between response and survival, including adhesion and inflammatory cytokine pathway expression. Conclusions: This study highlights the diversity of biological pathways expressed in MM and the utility of clinical genomics to associate pathways with activity of single-agent bortezomib.

Abstract The Multiple Myeloma Research Consortium (MMRC) Genomics Initiative is a three-year program to analyze tumor tissue from hundreds of multiple myeloma (MM) patients via gene expression profiling (GEP), comparative genomic hybridization (aCGH), and exon re-sequencing. In addition, RNAi knockdown of selected genes in MM tumor cell lines is being evaluated to identify potential new targets. All genomic data generated is scheduled for placement in an open-access Multiple Myeloma Genomics Portal pre-publication and in near real-time (www.broad.mit.edu/mmgp). Additionally, samples are also destined for drug validation and correlative science on clinical protocols as this study moves forward. This comprehensive project is spearheaded by the MMRC and conducted via collaboration with the Eli and Edythe L. Broad Institute of MIT and Harvard, the Translational Genomics Research Institute (TGen), Mayo Clinic Arizona, and The Dana-Farber Cancer Center. The study is supported by the collection from member institutions of the MMRC of bone marrow aspirates and matched peripheral blood samples from over 1000 patients. Specific genomic technologies that are currently being employed across this sample set include GEP using Affymetrix Human Genome U133A 2.0 Plus Arrays, and, in parallel, efforts to identify regions of genomic gain and loss are using Agilent Human Genome CGH arrays. In contrast to other large-scale genomic projects based on exon-sequencing of targeted gene sets, this project will be the first to perform genome-scale single molecule sequencing (SMS) of DNA from patient specimens. Results will be targeted against candidate classes of genes (e.g. kinases, phosphatases, known oncogenes and tumor suppressors), and genes from GEP or within candidate regions of copy gain or loss identified by the aCGH experiments. Mutations will be further validated in an independent set of patient specimens. Finally we will attempt to identify points of vulnerability of MM through systematic loss-of-function screens in myeloma cell lines using high-throughput RNA interference (using both shRNA and siRNA platforms). Importantly, data generated from this genomics initiative will ultimately be made public pre-publication through the established MMRC Multiple Myeloma Genomics Portal. Data from all aspects of this project (sample collection and analyte isolation, GEP, aCGH, SMS, RNAi and bioinformatics) will be described in this presentation. The power of this study is the comprehensive collection of gene expression, CGH, and genome sequencing on a single reference set of clinically annotated samples. The addition of RNAi screens makes this a very important and unique data resource, which we hope will help expedite the discovery of novel targeted agents for MM scientific community.

Abstract PS-341 (bortezomib, Velcade™) is a promising novel agent for treatment of advanced multiple myeloma (MM); however, 65% of patients with relapsed refractory disease in a phase II study did not respond. Lysophosphatidic acid (LPA) is a phospholipid which mediates tumor cell migration and invasion. Recent studies have shown that inhibition of LPAAT-β inhibits both Ras/Raf/Erk and PI3K/Akt signaling cascades. We have previously shown that lysophosphatidic acid acyltransferase (LPAAT)-β inhibitor CT-32615 triggers caspase-dependent apoptosis, and can overcome resistance to conventional therapeutics (ie, dexamethasone, doxorubicin, melphalan) in MM cells. In this study, we determined whether CT-32615 could also overcome resistance to PS-341. We first characterized molecular mechanisms of resistance to PS-341 in DHL-4 lymphoma cells. DHL-4 cells express low levels of caspase-3 and caspase-8; furthermore, no cleavage in caspase-8, caspase-9, caspase-3, poly ADP-ribose polymerase (PARP), or DNA fragmentation factor (DFF) 45 is triggered by PS-341 treatment. We have previously shown that PS-341 treatment triggers phosphorylation of c-Jun NH2-terminal kinase (JNK), which subsequently induces caspase-dependent apoptosis; conversely, JNK inhibition blocks PS-341-induced apoptosis. Here we show that PS-341 does not induce phosphorylation of SEK-1, JNK, and c-Jun in DHL-4 cells, suggesting that it does not trigger a stress response. Importantly, CT-32615 inhibits growth of DHL-4 cells in a time- and dose-dependent fashion: a transient G2/M cell cycle arrest induced by CT-32615 is mediated via downregulation of cdc25c and cdc2. CT-32615 triggers swelling and cell membrane destruction in DHL-4 cells, without caspase/PARP cleavage or TUNEL-positivity, suggesting a necrotic response. Our studies therefore demonstrate that LPAAT-β inhibitor CT-32615 triggers necrosis even in PS-341-resistant DHL-4 cells, providing the framework for its evaluation to overcome clinical PS-341 resistance and improve patient outcome.

8014 Background: TCR-MM is defined as being refractory to immunomodulatory agents, proteasome inhibitors, and anti-CD38 mAbs, representing an urgent unmet medical need with a median OS of 3-5 months( Pick M et al, Eur J Haem 2018; Gandhi U et al, ASH 2018). Sd has shown a 26.2% overall response rate (ORR) in 122 patients (pts) with TCR-MM in the Phase 2b STORM study ( Chari A et al, ASH 2018). Here, we evaluate the OS of pts in the STORM study with Sd and in pts with bortezomib, carfilzomib, lenalidomide, pomalidomide, and daratumumab (“penta”)-exposed, TCR-MM from an observational cohort not receiving Sd. Methods: Data were drawn from STORM and a retrospective cohort from the nationally representative Flatiron Health Analytic Database (FHAD). All pts from both sources had penta-exposed TCR-MM. In order to align study populations, OS was evaluated in pts in STORM whose first therapy after their MM reached TCR status was Sd and in pts in the FHAD who received ≥1 therapy after their MM reached TCR status. The index date for this evaluation was the start date of treatment after their MM reached TCR status. A Cox proportional hazards regression model was performed to assess the survival impact of Sd. In STORM, ORR was assessed by an Independent Review Committee based on IMWG criteria. Results: In the FHAD, 69 pts with TCR-MM were identified. Characteristics of the two groups of pts were similar, except that pts in STORM were more heavily pretreated, had a higher frequency of high-risk MM, a longer time since initial diagnosis of MM, and higher baseline hemoglobin and platelet values. Among the 122 pts in STORM, 64 received Sd as their first therapy after their MM became TCR, and ORR was 32.8%. Among the 69 pts from FHAD, 37 received ≥1 therapy after their MM became TCR. Median OS (N = 64) was 10.4 months for pts receiving Sd in STORM and 5.2 months (N = 37) for pts not receiving Sd in FHAD (HR = 0.49, p = 0.0241). Conclusions: The prognosis of TCR-MM in the real-world population appears very poor. Within the limits of this analysis, median OS of pts receiving Sd as their first therapy after their MM becomes TCR is significantly better than those not receiving Sd, suggesting that Sd may be associated with an OS benefit in pts with TCR-MM. Clinical trial information: NCT02336815.

8004 Background: The primary objective of this phase 3 trial was to demonstrate progression free survival (PFS) improvement of isatuximab (Isa), a novel anti-CD38 monoclonal antibody, combined with pomalidomide (P)/dexamethasone (d) versus (vs) Pd. Methods: Patients (pts) with RRMM who received ≥2 prior lines, including lenalidomide (len) and a proteasome inhibitor (PI), refractory to last therapy were enrolled. IsaPd arm received Isa 10 mg/kg IV weekly for first 4 weeks (wks), then every 2 wks. Both arms received approved schedules of pom and dex (4mg PO days 1-21; 40mg [20mg if >75 yrs] PO or IV weekly) every 28 days until progression or unacceptable toxicity. Results: 307 pts (154 IsaPd, 153 Pd) were randomized and analyzed (ITT). Patient characteristics were well balanced across arms. Median age: 67 (36-86) yrs; median prior lines of therapy: 3 (2-11); estimated GFR: <60ml/min in 33.9% pts; 92.5% refractory to len, 75.9% to PI; and 19.5% pts had high-risk cytogenetics. At median follow-up of 11.6 months (mos), median PFS was 11.5 mos IsaPd vs 6.5 mos Pd; HR 0.596 (95% CI 0.44-0.81), P=0.001. PFS benefit was consistent across all major subgroups. ORR (≥PR) was 60.4% IsaPd vs 35.3% Pd, P<0.0001. VGPR rate or better was 31.8% IsaPd vs 8.5% Pd, and MRD negativity (NGS, 10-5) was seen in 5.2% IsaPd pts vs 0% Pd. At analysis date, overall survival (OS) was immature (99 events) but a trend to OS improvement in IsaPd (vs Pd) was observed (HR 0.687; 95% CI 0.461-1.023). Median treatment duration was 41 wks IsaPd vs 24 wks Pd; median Isa infusion (inf.) duration was 3.3h at 1st inf. and 2.8h at subsequent inf. Grade ≥3 AEs were observed in 86.8% IsaPd vs 70.5% Pd; 7.2% IsaPd and 12.8% Pd pts discontinued due to AEs; 7.9% IsaPd and 9.4% Pd pts died due to AEs. Inf. reactions were reported in 38.2% (2.6% grade 3-4) IsaPd. Grade ≥3 infections were seen in 42.8% IsaPd and 30.2% Pd, grade ≥3 neutropenia in 84.9% (febrile 11.8%) IsaPd and 70.1% (febrile 2.0%) Pd. Conclusions: IsaPd significantly improved PFS and ORR vs Pd, with a manageable safety profile. IsaPd is an important new treatment option for the management of RRMM. Clinical trial information: NCT02990338.

8592 Background: Accrual to NCI clinical trials(CT)is often slower than planned at times mandating premature closure resulting in loss of valuable resources and delay of scientific progress. Methods: The NCI-MYSC AWG identified 10 potential BtA. SWOG, ECOG and Alliance investigators were queried and agreed that these barriers impede accrual (results stratified for academic and community sites). The MYSC AWG developed in collaboration with NCI and FDA strategies to overcome these barriers. Results: Strategies listed for the 3 most often cited BtA: 1. Reimbursement for CT related expenses:increase awareness of improved reimbursement for phase II CT; tailor reimbursement according to CT complexity; request funds from industry and other sources ( http://biqsfp.cancer.gov ) for qualifying ancillary CT components. 2. Spectrum of available treatment options influences CT participation: educate patients and providers about the significance of a new CT using social media, presentations at national meetings and by adding educational material to CT protocol; encourage opinion leaders and advocacy groups not to promote a new therapy as “standard” in the absence of phase III data. 3. Requirement of CT specific therapy at NCI designated sites only: “MYSC AWG Drug Administration Table” describes NCI/FDA approved rules for CT specific drug administration; CT protocol will outline which standard treatment components of a CT can be administered at any site as long as protocol specific guidelines are followed and conduct is supervised by enrolling investigator. Examples of additional strategies to overcome identified BtA: determine feasibility, indication and insurance coverage of CT specific tests during protocol development; discourage narrow eligibility criteria; avoid competing CT; allow up to 1 cycle of commercially available therapy prior to enrollment; CIRB support for phase II CT. Conclusions: The MYSC Accrual Working Group developed in collaboration with NCI and FDA strategies to overcome barriers to myeloma clinical trial accrual. These strategies may be applicable to NCI-sponsored clinical trials evaluating interventions in other diseases.