Citations

Abstract BAFF is a member of the tumor necrosis factor (TNF) family and plays a role in B cell survival including MM cells. We have previously established a role for BAFF in localization and survival of MM cells in the bone marrow (BM) microenvironment. (Cancer Res2006; 66(13): 6675–82). Here we validate the role of BAFF in MM patients and demonstrate the in vivo activity of anti-BAFF antibody in a SCID-hu MM model. We first performed gene expression profiling (GEP) on CD 138+ plasma cells isolated from 90 MM patients and 11 healthy controls using the Affymetrix U133A arrays. GEP analysis demonstrated increased BCMA expression (p<0.0001, student T test) on newly diagnosed and relapsed MM versus normal plasma cells. Flow cytometry performed on MM patient cells demonstrated the presence of all 3 receptors on CD 138+ cells. ELISA assays confirmed increased plasma BAFF levels in 51 MM plasma (mean: 1049 pg/ml; range: 176–4252 pg/ml) compared to 11 normal donors (mean: 461pg/ml; range: 317–652pg/ml) [p<0.001]. To understand the functional significance that 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 BM microenvironment. Our data demonstrate that rh-BAFF confers a survival advantage to MM cells and protects them against dexamethasone-induced cytotoxicity. Importantly, anti-apoptotic proteins Bcl2 and XIAP were upregulated, as were growth and survival signals belonging to the AKT and MAPKinase pathways. Because of the survival advantage conferred by BAFF on MM cells we evaluated the use of a clinical grade-neutralizing antibody to BAFF. To evaluate the in vivo activity of anti-Baff in MM we used the SCID-hu model, where MM cells grow in the context of human BM microenvironment. A cohort of SCID-hu mice bearing INA-6 MM cells, were treated i.p. weekly with anti-BAFF neutralizing antibody (10 mg/kg, n=3) or control isotype (10 mg/kg, n=3), respectively, for four weeks. Serum levels of soluble human IL-6 receptor (shuIL-6R) released by MM cells into the murine serum were monitored as a measure of MM growth. At the end of treatment we observed a significant (p=0.048) reduction in shuIL-6R level. This translated into a survival advantage of 3.1 weeks in the anti-BAFF treated animals versus the control group (p= 0.02). We also evaluated in vivo effects of anti-BAFF on the bone compartment by radiographic analysis and tartrate-resistant acid phosphatase (TRAP) staining of human bone implants. Our results demonstrate a decrease in radiologically evident lytic lesions in the anti-BAFF treated animals. This was accompanied by a significant decrease in TRAP + osteoclasts in bone sections from treated mice when compared to control mice. Our data therefore suggests that anti-BAFF antibody may impact MM cell growth directly and/or via effects on the BM microenvironment by impacting bone resorption. Taken together, these data show a role for BAFF mediating MM cell survival and its in vivo anti-tumor activities provide a preclinical rational for its clinical evaluation in MM.

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 Ribonucleotide reductase is the rate-limiting enzyme of deoxynucleoside triphosphate synthesis and is therefore an excellent target for cancer chemotherapy. Inhibition of ribonucleotide reductase results in inhibition of DNA synthesis and has anti-neoplastic effects. Several ribonucleotide reductase inhibitors (RRIs) are already in clinical practice, including Hydroxyurea and Gemcitabine. Here we examine the anti-MM activity of a novel RRI, Didox. Our data shows that Didox has potent cytotoxicity against MM cells in 48-hour cultures. Apoptosis induced in MM cell lines by Didox (200mmol/l), evidenced by increased sub-G1 cell fraction, is caspase dependent, confirmed by blocking experiments with Z-VAD-FMK. Unlike other RRIs which mainly target the pyrimidine metabolism pathway (hydroxyurea and gemcitabine), didox targets both the purine and pyrimidine metabolism pathways in MM, as demonstrated by transcriptional profiling using the Affymetrix U133A 2.0 gene chip. Specifically, our data shows a ≥ 2 fold downregulation of genes in these pathways as early as 12 hours after exposure to Didox. Importantly, ribonucleotide reductase (RR) M1 component transcript was downregulated, associated with downregulation of this enzyme by Western Blot analysis, and inhibition of DNA synthesis. Furthermore, genes involved in DNA repair mechanisms were also downregulated after exposure to Didox, demonstrated by heirachial clustering of gene chip data and further validation by western blotting. Specifically RAD 51 homologue, which is involved in nucleotide excision repair and recombination repair, was downregulated in MM cells both transcriptionally as well as at the protein level. This was accompanied by downregulation of the BCL family protein including Bcl-2, Bclxl, and XIAP both at the transcriptional and post transcriptional levels. Since Didox acts on MM cells by inhibiting DNA synthesis and repair, combination studies with melphalan, an alkylating agent commonly used in MM, were next performed. Our data shows a strong in vitro synergism, with combination indices of <0.7 by the Chou Talahay method. When combined with DNA damaging agents like doxorubicin, additive cytotoxicity was noted. These studies therefore provide the preclinical rationale for evaluation of Didox, alone and in combination with alkylating agents and anthracyclines, to improve patient outcome in MM.

Abstract Purpose: In a previous retrospective study, we have shown that 75% of gastric MALT lymphomas that did not respond to H. pylori eradication could be identified by detection of t(11;18)(q21;q21). The present study examined the value of t(1;14)(p22;q32) in prediction of the response of gastric MALT lymphomas to H. pylori eradication. Patients and Methods: A total of 111 patients with H. pylori-positive gastric MALT lymphoma, who were treated by H. pylori eradication, were screened for BCL10 involved chromosome translocation by BCL10 immunohistochemistry, followed by interphase FISH and real-time quantitative reverse transcription PCR (qRT-PCR). The clinical presentation of 11 cases of MALT lymphoma including 6 from the stomach with known BCL10 involved chromosome translocation was reviewed. Results: Of the 111 cases of gastric MALT lymphoma treated by H. pylori eradication, 75 including 35 from the complete regression group and 40 from the non-responsive group, had adequate specimens for BCL10 immunohistochemistry. Two cases showed strong BCL10 nuclear staining in virtually all tumor cells, similar to that seen in those with t(1;14)(p22;q32). Both were from the H. pylori eradication non-responsive group. Although interphase FISH failed to show evidence of BCL10 gene break or amplification, one case showed an IGH break. This case also showed a high level of BCL10 mRNA expression, compatible to that seen in MALT lymphoma with t(1;14)(p22;q32). 9 of the 11 cases with known BCL10 involved translocation were at stage IIE or above, with three showing agressive clinical presentations. Conclusion: Gastric MALT lymphomas with strong BCL10 nuclear expression or t(1;14)(p22;q32) are mostly likely resistant to H. pylori eradication.

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 PURPOSE: Recent advances in understanding of the molecular alterations that occur at the genetic and epigenetic levels in Multiple Myeloma (MM) have led to major leaps in identifying molecular pathways that regulate progression and resistance to therapeutic agents. However, despite great scientific advances at the genomic level, studies to identify signaling pathways deregulated at the functional proteomic level in MM are limited. In this study, we used a rapid and reproducible antibody-based protein microarray technique to screen the functional differences between malignant plasma cells in samples obtained from patients with MM compared to normal plasma cells (NPC) from the bone marrow of healthy volunteers. METHODS: We determined the protein expression level of 512 polypeptides in 12 samples of newly diagnosed patients with MM using high-throughput proteomic analysis with antibody-based protein microarray. Primary CD138+ sorted MM cells were obtained from the bone marrow of patients after informed consent. MM1.S was used in this study. Using immunohistochemistry and immunoblotting were confirmed. Lentivirus was used to knockdown CRIK. Gene expression datasets from the Mayo Clinic (accession number GSE 6477) and the UAMS (accession number GSE 2658) were obtained from the Gene Expression Omnibus for analysis. The Mayo dataset was generated using Affymetrix U133A platform whereas the UAMS dataset was generated using Affymetrix U133plus 2.0 platform. RESULTS: We identified four subgroups of MM using unsupervised clustering analysis. We confirmed overexpression of some of these proteins including CRIK and CDK4 using immunohistochemistry and immunoblotting. Many of these proteins are known to be deregulated in MM, indicating that this technique can accurately identify proteins that are over or under-expressed in MM in a high-throughput fashion. In addition, we identified novel proteins that are not previously known to be differentially expressed in MM, including the small GTPase member of the Rho family, CRIK protein. We then showed using knockdown of CRIK that this novel protein specifically regulates migration and adhesion in MM. There was no effect on survival of MM cells using the CRIK knockdown. Analyzing the GEP data of the 15 NPC, 46 monoclonal gammopathy of undetermined significance (MGUS) or smoldering myeloma (SMM) and 101 MM samples from the Mayo Clinic, there was a significant increase in expression of CIT from NPC to MM. Among the 351 patients entered into TTII trials from UAMS, CIT expression was similar across the different TC class. Using a cut-off normalized expression level of 1.25 (a level above expression in NPC), MM with a high CIT expression (n=81) had a significantly shorter survival than the other patients. CONCLUSION: In this study, we show that MM cells express a high level of CRIK, and that inhibition of this protein leads to significant inhibition of adhesion and migration of MM cells. In addition, CRIK protein expression correlated with CIT gene expression, with high expression in MM samples compared to NPC. In addition, high CIT expression correlated with poor survival in patients with MM.

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.