Shaughnessy, John D.

Abstract Dendritic cells (DC) are essential for the long term survival of plasma cells (PC) in the bone marrow and for the maintenance of persistent antibody titers. But the molecular basis for these interactions is not very clear. Both normal and malignant PC (like myeloma) express the T-cell co-stimulatory molecule CD28. Our data show that CD28 expressed on PC play a major role in CD80/CD86 (B7) mediated DC induction of growth factors such as IL-6 and immunosuppressive enzyme indoleamine 2,3 dioxygenase (IDO) as well as in antibody or DC mediated protection of PC in vitro. While IL-6 protected PC in vitro, IDO induced the formation of regulatory T cells in culture. Use of myeloma drug lenalidomide to inhibit DC-B7 expression or anti-CD28(Fab)2 fragments to block CD28-B7 interactions reduced DC ability to protect MM cells or produce IL-6/IDO. Moreover, just like in T-cell models, CD28 activation in malignant PC triggers similar molecular events such as tyrosine phosphorylation and association of p85. We believe that downstream of CD28, while PI3K/Akt governs survival, the Vav1/SLP76 pathway regulate PC proliferation and these form the molecular basis for a bi-directional molecular bridge between the PC and bone marrow microenvironment. Targeting this bridge could form the basis for future therapeutic strategies. Our data suggests a role for CD28-B7 in plasma cell survival by modulating the bone marrow microenvironment.

Abstract Chromosomal translocations involving the immunoglobulin heavy-chain (IgH) locus at 14q32 are genetic hallmarks of human multiple myeloma (MM) and are likely primary oncogenic events in myeloma transformation. Common recurrent translocation partner genes of IgH account for 40–50% of cases and these rearrangements result in the transcriptional dysregulation of various proto-oncogenes such as CCND1, CCND3, FGFR3/MMSET, c-MAF, MAFB, MUM 1(IRF-4), c-MYC and it is becoming clear that these dysregulated genes play important roles in the pathogenesis and the treatment outcome of MM. Although the frequency of other partner genes of IgH translocations may be rare (<1%), it is possible that many genes not currently identified as translocation partners are functionally converged into several signal pathways and play important roles as well. Through global gene expression profiling (GEP) studies of a large population of newly diagnosed MM, we have recently reported that dysregulation of any one of the three D-type cyclins is seen in almost all newly diagnosed MM and most patients with high levels of CCND2 expression was highly correlated with expression of c-MAF, MAFB or FGFR3/MMSET. In order to identify novel translocation partner genes in MM we combined GEP and fluorescence in situ hybridization (FISH) analysis in a large population of newly diagnsoed myeloma. We investigated whether IGH-CCND2 and IGH-MAFA translocations are seen in patients exhibiting high levels of CCND2 expression but not expressing c-MAF, MAFB, or FGFR3/MMSET. We also looked for a breakpoint and targeted gene at a non-random breakpoint at the 11q23 locus in 20 MM patients with 11q23 abnormalities detected by conventional G-banding. Here we report evidence of an IGH-CCND2 fusion in a newly diagnosed case of MM and an IGH-MAFA fusion in a newly diagnosed MM and an MGUS and also mapped the 11q23 breakpoint to within 100 kb in a newly diagnosed MM and a human myeloma cell line, NCU-MM-1 and identified an IGL Pou2AF1 fusion in the NCU-MM-1 line. Importantly these translcoatios do not involve the MLL or ATM genes. These three genes were all highly expressed as detected by GEP or quantitive RT-PCR in the samples in which these genes were translocated to IG loci. Although the frequency of these 3 translocations are very rare, they further the concept of a critical role of CCND2 expression in myelomegenesis and identifed the transcriptional coactivator Pou2AF1, which specifically associates with either OCT1 or OCT2, in the B-cell response to antigens and required for the formation of germinal centers, as a potential new translocation target in myeloma. Finally, our strategy of combining GEP signatures and cytogenetic analyses appears to be a practical means of identifying new IG- mediated translocations in myeloma.

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 Abstract 132 Multiple myeloma (MM), an incurable neoplasia of terminally differentiated plasma cells, are critically dependent on their interactions with bone marrow stromal cells (BMSC) for essential survival signals, growth and immunosuppressive factors. Very little is known about the specific BM cell type or the molecular elements in these interactions, an understanding of which could provide novel targets that could be interdicted to enhance conventional chemotherapy. A potential MM surface protein that could be involved in these interactions is CD28, based on its known pro-survival role in T cells. Clinical studies have shown that expression of CD28 in multiple myeloma highly correlates (p=0.006) with myeloma tumoral expansion. Moreover, CD28+ MM cells invariably express the CD28 ligand CD86. A survival role for MM-CD28 might involve interactions with BM cells that express B7 (CD80/CD86) such as dendritic cells (DCs, that are known to be closely associated with MM cells in the BM) or with CD86+ MM cells themselves. We had previously shown (ASH2008, #I-769) that blocking CD28-CD86 interactions between myeloma cells with high affinity B7 ligand CTLA4Ig (Abatacept®) sensitized myeloma cells to chemotherapy. Now we show that myeloma cells co-cultured with myeloid DCs in vitro derive both direct and indirect survival signals from DCs, and this can be partially blocked by commercially available reagents. Our data show that flow cytometric analysis of mononuclear cells (MNC) from BM aspirates of myeloma patients with increased CD138+ plasma cell populations (9-58%), show an increased CD11b+ (myeloid) population (20-37%) as well, which is in contrast to healthy transplant donor controls (12-15% CD11b+, 4–6% CD138+). Moreover, a larger fraction (11-47%) of the myeloma CD138+ plasma cells expressed CD28 compared to healthy control (3.3-7.7%). Also, when we analyzed gene expression datasets (NCBI #GSE5900 and GSE4204) from plasma cells (PC) of normal donors, monoclonal gammopathy of undetermined significance (MGUS), smoldering myeloma (SM) and newly diagnosed multiple myeloma (MM), we found a progressive increase in patients showing CD28 expression with increasing severity of disease (normal<MGUS<SM<MM) (Fig 1A). When we sorted the highest scoring MM group (n=538) into 8 genetic subgroups as defined earlier, CD28 expression was found to peak in the MF subgroup (typically associated with poor survival in myeloma patients) (Zhan et al. 2006, Blood 108, pp. 2020) relative to total population (p<0.0001) (Fig 1B). Antibody mediated activation of MM-CD28 over 48 hrs increased viability of myeloma cell line MM.1S cultured under serum starvation (3.7%) or with drugs ATO (1.9%), melphalan (18%) or dexamethasone (3.3%) to 66%, 21%, 33% and 11% respectively. Viability of MM.1S cells or primary CD138+ plasma cells (isolated from myeloma BM aspirates) cultured under serum starvation was enhanced >3 fold (p<0.001) when co-cultured with monocyte derived DCs, and in MM.1S this was partially reversed when either MM-CD28 or DC-B7 was blocked (Fig 2). Similar protection of MM.1S was also observed against a gradient of dexamethasone or melphalan. CD28 activation was accompanied by rapid tyrosine phosphorylation of CD28, association of p85 (PI3K), activation of Vav-1 and increase in CD28 associated tyrosine kinase activity, as shown by immunoprecipitation, western and kinase activity assays. We had previously shown that MM-CD28 interaction drive DC production of pro-survival factor IL-6 and immunosuppressive factor IDO via DC-B7 “backsignaling” (ASH2008 #I-769). Now we show that MM induced DC production of IL-6 (8 ng/ml) was partially inhibited in presence of CD28 blocking αCD28(Fab) fragments (3 ng/ml) or with protein kinase C (PKC) inhibitor Bisindolylmaleimide-I (2.1ng/ml). Activity of the immunosuppressive enzyme IDO in these co-cultures was completely inhibited in the presence of a novel IDO inhibitor from Incyte corporation, and this helped partially reverse IDO mediated suppression of T-cell proliferation in proliferation assays using co-culture supernatants. In conclusion, our data characterizes CD28-B7 pathway and DCs in the BM as vital for myeloma survival and also as possible targets to include in future strategies in the treatment of myeloma. FIGURE 1 FIGURE 1. FIGURE 2 FIGURE 2. Disclosures: Boise: University of Chicago: Patents & Royalties.