Greipp, Philip R.

Abstract Background: Thalidomide and dexamethasone combination has been shown to be an effective therapy for multiple myeloma (MM). In newly diagnosed patients with MM, the combination results in overall response rates of over 70% of patients. However, a considerable number of patients do not respond and will need to proceed to other therapies. The ability to identify patients who are unlikely to respond to particular therapies will allow tailoring of therapeutic approaches and in turn will reduce unnecessary toxicity and morbidity from lack of rapid disease control. With the availability of new technology such as gene expression profiling (GEP), this has become a possibility. We employed this approach to identify genes that can reliably predict lack of response to the thalidomide dexamethasone combination. Methods: Patient samples from the Eastern Co-operative Oncology Group clinical trial (E1A00), that compared thalidomide-dexamethasone combination with dexamethasone, and patient samples from the phase II Mayo Clinic study of thalidomide and dexamethasone, both for newly diagnosed MM, were used for this study. Thirty newly diagnosed patients who were evaluable for response were included in the analysis. GEP was performed using the Affymetrix U133A microarray platform as per manufacturer’s recommendation. The Affymetrix output (CEL files) was imported into Genespring 7.2 (Agilent Technologies) microarray analysis software, normalized across chips using GCRMA followed by per gene normalization to median. For the purposes of this study, responses were defined as reduction in the serum paraprotein (or the urinary M protein in the absence of a serum M protein) of >=50% (PR), 25 to 49% (MR), increase of >=50% (PD) and stable disease for the remaining. Results: Five of the 30 patients had no response to the thalidomide Dexamethasone therapy. Using the class prediction tool available in Genespring (Support Vector Machines), we identified 25 genes that reliable predicted non responders (PD, NC) from the responders (MR, PR, and CR). See table for a list of predictive genes with identified genes. Conclusion: Using a combination of two datasets we have identified a set of genes that can be used to reliably predict lack of response to thalidomide and dexamethasone in patients with newly diagnosed MM. We think that this represents a step towards creation of custom microarrays spotted with genes that are capable of predicting lack of response (or response) for the purpose of tailoring therapy to the patient. Gene Predictive strength hypothetical protein FLJ20719 1.655 Tubulin alpha 6 1.653 SEC3-like 1 (S. cerevisiae) 1.649 Ribosomal protein L18 1.546 Ribosomal protein L4 1.432 Tubulin alpha 6 1.409 cleavage stimulation factor 1.393 Tubulin, alpha, ubiquitous 1.393 CD99 antigen 1.38 hmel2 1.346 Leptin receptor 1.291 Integrin-linked kinaseSMC4 structural maintenance of chromosomes 4-like 1 1.269 Cornichon homolog 1.255 Williams-Beuren syndrome chromosome region 5 1.217 Ubiquitin specific protease 1 1.2 Sarcoma antigen NY-SAR-91 1.2

Abstract Bank On A CureTM is a collaborative project initiated with the International Myeloma Foundation to develop a DNA bank through international cooperation. The Bank provides a resource for the development of cooperative partnerships to assess genetic associations with disease etiology and outcomes. It is well established that genetic variation can have a significant ethnic association, and such variations may account for differences in disease incidence and outcomes. Indeed, African Americans have historically shown a 2.5–3 fold increase population incidence of myeloma compared to the Caucasian population. We have identified a number of potentially biologically relevant genetic variants that show significant differences in ethnic distribution. Using both clinical trials as well as the Coriel [normal] cell line data base, we find in all three cases the same highly significant differences (Fishers Exact Test) between African Americans and Caucasians in functionally relevant genetic polymorphisms, as represented by E9486 univariate analysis of IL-6 (p<.00001), LT-a (p<.0001), ERCC312 (p<.0001), XRCC399 (p=.006), IL-1RA (p<.00001), GST-M (p=.0008), and ERCC751 (p<.02). Subsequently, from trial S9321 we have found differences in a number of clinical outcomes associated with ethnicity. When toxicities between Caucasians and African Americans were examined, similar severe toxicity rates were noted after VAD induction related to neuropathies, nausea, and bone pain; whereas statistically significant differences were noted for infection rates, hyperglycemia, fatigue, dyspnea, and thrombosis (p<.04). During high dose melphalan treatment toxicities were not statistically different. Because significant association between IL-6 genotype and ethnicity was noted, we also examined serum levels of sIL-6R and CRP, available from trial E9486. African Americans patients show significantly lower sIL-6R levels compared to Caucasian patients (mean 149 vs 213 ng/ml; p<.0001). Interestingly, there is a significant association between IL-6 SNP genotype and sIL-6R distribution, with the high IL-6 producer GG genotype (in 90% African Americans) having the lowest sIL-6R compared to the CC or CG genotypes (p=.02). Regression analysis of IL-6 SNP and ethnicity on sIL-6R reveals that ethnicity is significantly associated with sIL-6R distribution after adjustment for IL-6 SNP genotype (p=.001) but not vice versa (p=.91), indicating the association of IL-6 SNP genotype with sIL-6R is due to its association with ethnicity. Together the data demonstrate that while associations may result from co-segregation of ethnic genotypes, they may influence disease risk and outcomes related to important genetic factors distributed unequally in different ethnic populations. Such differences may, for example, alter IL-6 responses. Further, multivariate analysis will be developed. Validation of genotype associations found in different ethnic populations will be an important consideration in evaluating myeloma etiology and outcomes.

Abstract Waldenström’s macroglobulinemia (WM) is an incurable low-grade lymphoproliferative disorder characterized by bone marrow (BM) infiltration of a clonal population of small B-lymphocytes, plasmacytoid lymphocytes and plasma cells that secrete monoclonal IgM antibody. Because it is difficult to obtain tumor metaphases for karyotype studies, few recurrent chromosomal abnormalities have been reported and the genetic basis of the disease remains poorly defined. Therefore, we performed a comprehensive high-resolution study to identify genomic abnormalities involved in WM pathogenesis. Fifty-seven WM patients were analyzed using a combination of array-based comparative genomic hybridization (aCGH)(N=42); gene expression profiling (GEP)(N=22), DNA sequencing (N=24) and cIgM-FISH (N=57). Agilent 244A and Affymetrix U133 platforms were used in the aCGH and GEP experiments, respectively. An NF-κB index was calculated from GEP data, as a surrogate marker of NF-κB transcription activity. NFKB2 sub cellular localization was determined by immunofluorescence staining. Overall, 83% of samples have aCGH defined chromosomal abnormalities, with a median of 3 abnormalities per patient (range 0 to 27). We identified 16 recurrent regions of copy number change found in >5% (3 or more patients); 10 deleted and 6 amplified regions. The most common abnormality was the entire or partial deletion of 6q, identified in 40% of cases. Four nonoverlapped minimal deleted regions were identified on 6q (MDR1 to MDR4), each of them being present in at least 14 of 17 patients with the abnormality. Gain of 6p was the second most common abnormality (17%) and its presence was always concomitant with 6q loss. Other recurrent deletions were 13q14 (10%) and 7q22, 8p, 11q22-q23, 11q23-q24 and 17p11-p13 (7% each). Copy gains were identified as partial or entire gains of chromosomes 18 (17%), 4 (12%) and 3 (10%), 8q (10%) and Xq27.1-q28 (10%). Three patients had either homozygous deletions or LOH with mutations affecting both alleles of TRAF3 on 14q32. TRAF3 inactivation was correlated with an increased NF-kB transcriptional signature and it was associated with activation of the non-canonical NFkB pathway. Additionally, we identified the inactivation of TNFAIP3, another negative regulator of the NF-kB pathways, in one of 24 patients. Finally, interstitial deletions identified in 4 patients at 13q14 identified a 1.1 Mb MDR, including MIRN15A and MIRN16-1. These findings confirm that focal 13q14 deletion is not restrict to B-CLL and that the MIRN15A/MIRN16-1 abnormalities might be common to several indolent B-cell diseases. Overall, we identified TRAF3 and TNFAIP3 inactivation in 5.3% and 2.4%, respectively. To our knowledge, this is the first study showing the inactivation of bona fide tumor suppressor genes in WM patients. Furthermore, these genes are negative regulators of NF-kB signaling pathway, highlighting its biologic importance in sustaining and limiting growth in WM. Mutational activation of this pathway, which is normally activated by ligand-receptor interactions within the BM microenvironment, suggest a therapeutic role for inhibitors of NF-KB pathway activation in the treatment of WM.

Abstract The objective of this study was to analyze protein changes that occur a the molecular level with novel therapeutic agents used in MM in order to identify potential combinations for clinical trials. We employed antibody protein microarrays (BD Clonetech, CA) to measure changes in the patterns of protein expression in Kas 6/1 MM cell line after treatment with bortezomib, dexamethasone, CC-5013, and 17-AAG. The antibody array is a new technique that assays protein differences directly by hybridizing fluorescently labeled protein mixtures from cell extracts onto glass slides spotted with 512 different monoclonal antibodies specific for human proteins. Induction of apoptosis was assessed by Annexin/Propidium iodide FACS analysis at 24 and 48 hours using different concentrations of the inhibitors. Protein arrays were performed at concentrations and treatment times that did not induce more than 25% apoptosis to ensure adequate analysis of early changes in signaling pathways. Bortezomib 5nM at 10 hours, dexamethasone 100mM, CC-5013 250nM, and 17-AAG 1mM at 24 hours were used. Control cells were treated with vehicles ETOH or DMSO at the same concentrations as the inhibitors. To assess differential protein expression, the mean of the Cy5/Cy3 ratios for each sample and its control were analyzed using the Clontech software and an internally normalized ratio (INR) was calculated. INR values >1.3 or <0.77 were considered as valid changes in protein abundance for this study. All inhibitors induced the upregulation of apoptosis proteins including BAK, BIK, SMAC/DIABLO, and caspase 14. Several proteins were inhibited by all 4 inhibitors indicating common pathways affected by these agents. These included members of the PI3K pathway (PI3K-p85a, p70S6kinase, and cyclin dependent kinases), MAPKinases (ERK1 and 2), antiapoptotic protein Bclx, heat shock proteins Hsp70 and HSP60, and ubiqutin/NFkB pathway (Ubch6, IKKalpha, and IKBe). These results indicate that inhibitors of the PI3K pathway such as mTOR inhibitors, IKK inhibitors or MAPkinase inhibitors may be used in the future in combination with bortezomib, dexamethasone, CC-5013 or 17-AAG. Fatty acid synthetase was downregulated by bortezomib and dexamethasone indicating potential use of fatty acid synthase inhibitors in combination with bortezomib or dexamethasone in future clinical trials. These results suggest that antibody protein arrays may be used in the rational design of combinations of targeted therapies in MM.

Abstract Title: Primary Therapy with Bortezomib—The Role of Induction, Maintenance, and Re-Induction in Patients with High Risk Myeloma. Update of Results from E2A02. Angela Dispenzieri, MD1, Susanna Jacobus, PhD2, David Vesole, MD3 and Philip R. Greipp, MD1. 1Hematology, Mayo Clinic, Rochester, MN, United States, 55905 and 2Biostatistics, Eastern Cooperative Oncology Group, Boston, MA, United States, 02115. 3Saint Vincent’s Hospital, New York, NY 10010 Background: Single agent bortezomib as upfront therapy in patients with multiple myeloma (MM) results in response rates of 38% and the drug has been touted to be especially effective in patients with high risk disease. We sought to explore response rate, the role of maintenance and reinduction in a cohort of patients with high-risk MM. Methods: Patients with newly diagnosed high-risk myeloma (beta-2 microglobulin [B2M] >= 5.5., plasma cell labeling index [PCLI] >= 1, or deletion 13q) and adequate organ and functional status were eligible. Patients were treated with bortezomib 1.3 mg/m2 day 1, 4, 8, and 11 every 21 days for 8 cycles as induction. After induction, patients were scheduled to receive bortezomib 1.3 mg/m2 every other week indefinitely. Elective peripheral stem cell mobilization (growth factor alone) was allowed after 4 cycles of bortezomib. Patients relapsing on maintenance schedule had full induction schedule resumed. Responses as defined by the EBMT criteria were determined after each cycle and needed to be confirmed after at least 6 weeks. Results: Between March 15, 2004 and March 10, 2005, 44 patients enrolled on study. Among the 42 eligible treated patients, median age was 63; 51% were male. All patients had high risk disease: deletion 13q (6/41); PCLI >=1% (17/33); t(4:14) (4/27) and B2M >= 5.5 (34/43). Nineteen patients completed induction, i.e. 8 cycles of bortezomib. The most common causes for discontinuing therapy were: progressive disease (n=17), AE (n=7), alternate therapy (n=4), death (n=1), and other (n=11). Forty-eight percent of patients achieved a partial response (PR) or better with induction (0 complete responses, 2 very good PR, 17 PR, 3 minimal responses, 5 no response, 9 progressive disease, and 6 inevaluable or missing). Response rates across risk groups did not differ with a PR or better for patients with deletion 13q (2/6); PCLI >=1% (8/17); t(4:14) (2/4) and B2M >= 5.5 (15/33). One patient’s response was upgraded to CR during maintenance. The rate of painful peripheral neuropathy during all courses of therapy was: grade 1, n=25; grade 2, n=2; and grade 3, n=2. With a median follow-up of 41.6 months (95%CI 36.6–43), 43% of patients have died. Median overall survival (OS) has not been reached (Figure), and the 1- and 2-year OS rates were 88.1% (95%CI 73.7–94.9%) and 76.2% (95%CI 60.3–86.4%) respectively. The median progression free survival (PFS) was 16.3 months (95%CI 6.2–26.6) and the 1- and 2-PFS were 76.7% (95%CI 58.8–87.6%) and 38.3% (95%CI 20.6–55.9%), respectively. Fifteen patients went on to maintenance. The distribution by risk group for patients entering maintenance was not different across groups: deletion 13q, 3/6; high PCLI, 6/17; high B2M, 11/33; t(4;14), 1/4; and p53, 0/2. For those entering maintenance, the median PFS was 19.8 months (Figure), and the 1 year PFS rate was 75% (95%CI 40.8–91.2%). Of the 7 patients progressing on maintenance who received reinduction with bortezomib, no patient responded. Only 2 remain on therapy. Figure Figure Conclusions: In high risk patients, upfront bortezomib results in response rates comparable to those reported for unselected cohorts of newly diagnosed myeloma patients. For patients responding to therapy, maintenance therapy is feasible. Reinduction was unsuccessful in high risk patients failing maintenance.

Abstract Background: The free light chain (FLC) assay allows a nephelometric measurement of this free kappa and lambda light chains that circulate as monomers or dimers, not bound to the immunoglobulin heavy chain. Estimation of the free light chain levels and their ratio has utility in screening, prognostication and treatment response assessment in multiple myeloma, and is particularly useful in light chain myeloma. Previous studies have suggested that absence of a functional rearrangement on at least one of the IgH allele is the basis of light chain myeloma. Translocations involving the immunoglobulin heavy chain (IgH) locus on chromosome 14 can be detected using FISH in over half of the patients with myeloma. We hypothesized that presence of an IgH translocation may be associated with compromised production of heavy chains and leads to unbalanced, excess production of clonal light chain. Methods: From February 1988 to May 1992, 653 patients with previously untreated multiple myeloma were enrolled on the phase III clinical trial E9486. Serum free light chains were run on stored sera obtained at baseline in 495 patients as part of a previous study. Among these patients, 314 patients were previously studied using FISH for presence or absence of IgH translocations, p53 abnormalities and deletion 13 and were included in the current analysis. Results: The median difference between the involved and uninvolved FLC (FLCdiff) was higher among the group of patients with any IgH translocation abnormality compared to those with none (Figure 1). This was particularly evident among the patients with a t(14;16) who had the highest FLCdiff. In a multivariate analysis, we examined if the prognostic value seen with FLCdiff was independent of the presence of IgH translocations t(4:14) and t(14;16), which are associated with a worse outcome. The presence of t(4;14) or t(14;16) was associated with FLCdiff groups using a cutoff point of 185, with 13% of those with FLCd ≤185 and 27% of those with FLCd > 185 having the translocations (P= 0.008). At the cutoff value of 185, the prognostic value of the FLC-diff on progression free and overall survival appears to be independent of these high risk IgH translocations (P-value=0.03 and 0.003, respectively for PFS and OS) We then examined the prognostic value of the FLC-diff in the group of patients without these two high risk abnormalities and were able to confirm that they remained prognostic for PFS (P=0.009) and OS (p=0.005). However, among the group of patients with either of the two high risk IgH abnormalities, FLCdiff estimate added little to assessment of their outcome (P=0.97 and 0.20, respectively for PFS and OS). Conclusion: Elevated free light chain levels are associated with presence of IgH translocations and these patients are more likely to harbor the high risk genetic abnormalities. Routine FISH testing for patients with newly diagnosed myeloma will allow us to confirm these and allow better risk stratification of the patients. Additional work needs to be done to help us better understand the molecular basis for unbalanced light chain excretion by myeloma cells and the current finding of the association with IgH translocation abnormalities should form the basis for this work. Figure 1. Distribution of FLC ratio (inv vs. uninv) and FLC difference (inv − uninv) among patients. Solid squares represent patients with t(4;14) or t(14;16) or t(11;14) or other 14q32 translocation; open circles represent patients without t(4;14), t(14;16), t(11;14) and any other 14q32 translocations. The horizontal dashed lines refer to FLC ratio original values of 100 and 1000, and vertical dashed lines refer to FLC difference original values of 10 and 100. Solid line indicates significant association (P<=0.05) between the dichotomized FLC groups and translocation status. Figure 1. Distribution of FLC ratio (inv vs. uninv) and FLC difference (inv − uninv) among patients. Solid squares represent patients with t(4;14) or t(14;16) or t(11;14) or other 14q32 translocation; open circles represent patients without t(4;14), t(14;16), t(11;14) and any other 14q32 translocations. The horizontal dashed lines refer to FLC ratio original values of 100 and 1000, and vertical dashed lines refer to FLC difference original values of 10 and 100. Solid line indicates significant association (P<=0.05) between the dichotomized FLC groups and translocation status.

Abstract Introduction: The kidney is affected by immunoglobulin light chain amyloidosis (AL) in more than 50% of patients who present with the disease, but long-term predictors for and outcomes after renal replacement therapy have not been well described in this patient group Patients: 145 patients with AL who participated in Mayo Clinic treatment trials and were monitored for at least 11 years. No patient was lost to follow-up Results: Among patients presenting with renal AL, 42% ultimately received renal replacement therapy compared with 5% of patients who did not have an initial presentation involving the kidney. Table 1. Monoclonal Protein Studies in 145 Patients With Immunoglobulin Light Chain Amyloidosisa Patients, No. (%) Monoclonal Protein Renal Amyloid at Presentation (n=84) Nonrenal Amyloid at Presentation (n=61) a P=.02 l more likely to cause renal presentation None 7 (8) 2 (3) k 6 (7) 12 (20) l 71 (85) 47 (77) Table 2. Characteristics of All 145 Patients With Immunoglobulin Light Chain Amyloidosis Amyloid Renal (n=84) Nonrenal (n=61) P Value Abbreviations: IQR, interquartile range; NA, not applicable. a included in the definition of renal amyloidosis Patients with l immunoglobulin light chain amyloid were significantly more likely to have renal involvement and had significantly greater urinary protein loss than patients with κ or no monoclonal light chain amyloid Age, median (IQR), y 61 (52–67) 62 (55–68) .47 Sex, male/female 52/32 40/21 .72 24-hr urine protein loss, median (IQR), g/d 7.0 (4.4–11.7) 0.3 (0.1–6.4) NAa Creatinine, median (IQR), mg/dL 1.1 (0.9–2.2) 1.1 (0.9–1.3) .22 Cardiac involvement (yes/no) 35/48 48/16 .0001 Table 3 Distribution of Urinary Protein and Creatinine Based on Monoclonal Protein Monoclonal Protein Test k (n=18) l (n=118) None (n=9) P Value Abbreviation: IQR, interquartile range. Patients with renal amyloid who ultimately received dialysis support had significantly higher serum creatinine and 24-hour urine protein levels at presentation. Absence of cardiac involvement at diagnosis predicted an increased likelihood of dialysis All patients (N=145) 24-hr urine protein loss, median (IQR), g/d 0.73 (0.16–2.37) 3.61 (0.35–7.8) 5.68 (0.3–12.2) .001 Creatinine, median (IQR), mg/dL 1.1 (0.9–1.3) 1.1 (0.9–1.3) 1.5 (1.2–1.6) NS Patients with renal amyloid at presentation (n=84) 24-hr urine protein loss, median (IQR), g/d 2.93 (1.1–5.0) 7.2 (4.8–11.8) 7.8 (3.8–12.6) .04 Creatinine, median (IQR), mg/dL 1.0 (0.8–2.6) 1.1 (0.9–2.2) 1.5 (1.1–1.6) NS Table 4 Characteristics of 84 Patients Presenting With Renal Amyloidosis Dialysis Subsequently Not Required Characteristic Required (n=35) (n=49) P Value Abbreviation: IQR, interquartile range. The median time from diagnosis to dialysis was 29.5 months for those that went into renal failure.). However, the actuarial risk reached 50% at 12 years Kaplan-Meier failure curve demonstrating the actuarial time from diagnosis to the start of dialysis therapy N=145 For 38 patients who received dialysis, median survival from day 1 of dialysis was 10.4 months Kaplan-Meier survival of 38 patients from the start of dialysis therapy Age, median (IQR), y 60 (52–67) 62 (52–67) .90 Sex, male/female 21/14 31/18 .76 24-hr urine protein loss, median (IQR), g/d 7.4 (5.0–14.8) 5.9 (3.7–9.1) .03 Creatinine, median (IQR), mg/dL 1.4 (0.9–2.8) 1.1 (0.9–1.5) .01 Cardiac involvement (yes/no) 9/26 26/23 .01 Conclusion: In our study, 26% of all patients with AL ultimately received renal replacement therapy compared with 42% of patients who presented with renal AL specifically. The presenting 24-hour urine protein loss and creatinine values predict which patients will require dialysis. Median survival for patients starting dialysis is less than 1 year. Presence of l light chain amyloid predicts an increased likelihood of renal involvement and, when the kidney is affected, increased proteinuria.

Abstract Background: Venous thrombotic events (VTE) are a common complication of therapy with the lenalidomide plus dexamethasone regimen. The incidence of VTE with RD is approximately 20%, and can be lowered with the use of effective thromboprophylaxis, avoidance of erythropoietin, and the use of lower doses of dexamethasone. The goal of this study was to determine the impact of VTE on overall survival of patients with newly diagnosed myeloma by studying events occurring in ECOG E4A03 phase III trial of lenalidomide plus high (standard) dose dex (RD) versus lenalidomide plus low dose dex (Rd) in newly diagnosed myeloma (MM). Methods: Pts with untreated, symptomatic MM were eligible. Pts in the RD arm (Arm A) received lenalidomide 25 mg/day PO days 1–21 every 28 days plus dex 40 mg days 1–4, 9–12, and 17–20 PO every 28 days; pts in the Rd arm (Arm B) received lenalidomide at the same dose plus dex 40 mg days 1, 8, 15, and 22 PO every 28 days. The trial initially did not mandate routine thromboprophylaxis, but recommended that such treatment be considered. After the first 264 patients were enrolled the trial was amended to require mandatory thromboprophylaxis of aspirin for all patients, with a recommendation to use stronger thromboprophylaxis with either warfarin (target INR 2–3) or low molecular weight heparin among patients in the RD arm. Results: 445 pts (median age, 65 yrs) were accrued; 223 randomized to RD, 222 to Rd. Median follow-up time is 30 months. Overall VTE including deep vein thrombosis (DVT) and pulmonary embolism (PE) occurred in 18.5% of patients; 25.6% in Arm A and 11.4% in Arm B. Rates for the first 4 cycles of treatment were 20.2% in Arm A and 8.2% in Arm B, P<0.01. Rates did not change substantially before and after the prophylaxis amendment. A partial response (PR) or higher was seen in 82.1% of pts who experienced VTE compared with 74.6% of pts who did not experience VTE, P=0.19. Overall VGPR rates also were not inferior. Pts who had VTE, however, had significantly higher other grade 3–5 toxicities such as hyperglycemia (14.6% vs 7.5%, P=0.051), cardiac ischemia (4.9% vs 0.8%, P=0.002), non-neuropathic weakness (13.4% vs 6.4%, P=0.039), infection/pneumonia (17.1% vs 11.1%, P=0.138) and fatigue (18.3% vs 10.5%, P=0.060). In a Cox PH model, VTE status as a time-varying covariate was marginally significant: HR 1.54 95%CI (0.96–2.47), P=0.074, suggesting patients that develop VTE have a higher hazard of death. Conclusions: The occurrence of VTE may adversely affect the survival of patients with newly diagnosed myeloma receiving Rev-Dex. VTE was associated with a higher frequency of other serious adverse events. Prevention of VTE events is a priority. Besides lowering the dose of dexamethasone, studies investigating optimum thromboprophylaxis are needed.

Abstract Malignant plasma cell (PC) disorders are clonal diseases based on their immunoglobulin variable region sequence signature. However, intratumor phenotypic, genetic, and morphologic heterogeneity is often observed, fueling the notion that a subpopulation of the malignant PC clone may have extensive self-renewal properties whereas others may not. Little information exists regarding the relationship between these putative tumor subpopulations that is instrumental to our understanding of the growth, progression and therapeutic targeting of PC disorders. We recently described establishment of two novel cell lines from one patient initially diagnosed with primary amyloidosis (ALMC-1), who eventually progressed to a combination of AL and symptomatic multiple myeloma (MM; ALMC-2). Although both cell lines are clonally related, they exhibit a number of intriguing differences, including a marked variability in their makeup of mononuclear (MoN) and multinuclear cells (2 − >10 nuclei; MuN). The ALMC-1 cell line consistently displays a much larger fraction of MuN cells (~50%) than the ALMC-2 cell line (~20%). By contrast, the growth rate of the ALMC-2 cells is significantly higher than ALMC-1 cells suggesting an inverse relationship between growth rate and fraction of MuN cells. It has been demonstrated that MoN plasmablastic morphology is a predictor of poor survival in MM, however the clinical significance of MuN PCs, which are frequently observed in bone marrow biopsies, has yet to be determined. We therefore used the ALMC-1 and ALMC-2 cell lines to begin to test the hypothesis that the MoN fraction in both cell lines contains cells with extensive self-renewal properties whereas the MuN cells are no longer capable of cell division. The central questions become by what mechanism are MuN PCs generated and how are MoN PCs maintained? Two hypotheses that can explain the dual persistence of both types of cells are: random cell fusion; regulated or sporadic cell division of MoN cells into 2 daughter cells, one of which divides normally and the other one fails to undergo cytokinesis. To address the first possibility, each cell line was transfected with GFP or YFP. Single positive (GFP or YFP) cells were then mixed and cocultured for assessing the frequency of dual positive cells by flow cytometry at various time points. However, studies to date suggest this mechanism does not occur. To begin to address the second possibility and determine whether extrinsic factors, e.g., cytokines, may regulate the rate of generation of MuN PCs, we cultured both cell lines +/− IL-6 and IGF-I and assessed numbers of MoN and MuN PCs. Initial analyses suggest that IL-6, but not IGF-I, increases the proportion of MoN PCs in both cell lines. To address the hypothesis that MuN PCs are no longer capable of growth, cells were labeled with bromodeoxyuridine (BrDU) to assess the capability of MuN cells to synthesize DNA. We observed that MuN PCs incorporating BrDU did so uniformly in each nucleus present in the cell. We then assessed the ability of cell division of MuN cells by quantitating normal vs abnormal metaphases in both cell lines and observed that >90% of metaphases were present in MoN PCs, suggesting that MoN PCs largely give rise to MuN PCs and the latter are likely compromised in cytokinesis. As centrosomes play a critical role in regulating cell division and centrosome abnormalities have been noted in MM by others, we next used gamma-tubulin immunofluorescence to detect centrosomes. MoN PCs exhibited uniformly normal centrosome numbers and positioning while MuN PCs showed clear centrosomal abnormalities including accumulation of centrosomes, centrosome clustering, and multiple directional centrosome polarization, suggesting a mechanism by which the MuN cells may be generated. In summary, our data suggest that MuN PCs lack growth potential and that intrinsic and/or extrinsic factors may drive accumulation of these cells. These observations support the possibility that patients with a larger proportion of MuN PCs may have differences in clinical outcome from those patients with largely MoN PCs. To test this, we have begun hematopathological analysis of a large series of patients diagnosed with various plasma cell disorders. Knowledge of the signals that regulate the balance between MoN and MuN cells could lend itself toward identification of therapeutic modalities that may maximize differentiation of tumor cells into end-stage cells.

Abstract Background: Outcome of patients with Multiple Myeloma (MM) is influenced by a variety of baseline prognostic factors, most importantly presence of chromosomal abnormalities. Nevertheless, these biologically determined risk-factors do not account for a significant subset of patients whose outcome varies greatly from what one expects based on the underlying prognostic characteristics. We have previously demonstrated that outcome in myeloma is dictated not only by baseline risk-factors but also response to therapy (R2, risk and response dependent outcome). We studied response duration following initial therapy as a prognostic factor for long-term overall survival in myeloma in three ECOG clinical trials that enrolled patients with newly diagnosed myeloma. Methods: Data from three studies with long-term, mature follow up were analyzed: E9486, E5A93, and E1A00. The regimens used in these studies included Thalidomide/Dex, Dex, VBMCP, VBMCP + alpha-IFN, and VBMCP + Cyclophosphamide. Among progressed/relapsed patients, the association between time to progression and overall survival since relapse was explored using Cox proportional hazards model, in which time to progression was analyzed as a continuous variable. In addition, the association between response duration and overall survival since relapse was explored similarly among relapsed responders. Treatment effect and calendar time of diagnosis have been adjusted in the model. Also, to determine the best cut off point associated with the best differentiation of patients with short OS after relapse, an outcome-oriented method using log likelihood value was applied. Results: Among the 1136 patients enrolled in the three studies, 625 patients who have documented disease relapse have been included in the current study. Of these, 471 patients had responded to the treatment before relapse. Only 33 patients are alive as of Dec., 2007. For all 625 patients, the time to progression (continuous variable) was significantly associated with overall survival from the time of relapse/progression (P<0.0001), with hazard ratio of 0.77 (95%CI: 0.72~0.81) at time to progression increasing by 1 year (i.e., the later the progression/relapse, the lower the risk). The best cutoff point of the time to progression is 3 yrs (the 75th percentile). The hazard ratio of patients progressing within 3 yrs since randomization vs. after 3 yrs is 2.4 (95% CI: 1.9 ~ 2.9) and P-value<0.0001. The median OS from relapse was 0.96 years for the former vs. 2.43 years in the latter group (Figure). Among the 471 relapsed responders, the response duration (continuous variable) was also significantly associated with overall survival since relapse (P<0.0001), with hazard ratio of 0.76 (95%CI: 0.70~0.81) at response duration increasing by 1 year (i.e., the longer the response duration, the lower the risk). The effects seen with each regimen are detailed in the table. The best cutoff point of the response duration is 2 yrs (median). The hazard ratio of patients with response duration less than or equal to 2 yrs vs. more than 2 yrs is 2.1 (95% CI: 1.7 ~ 2.6) and P-value<0.0001. Conclusions: Among patients treated with alkylator based therapy, the duration of response from the initial therapy is an important predictor of the subsequent outcome among patients with myeloma. Given the heterogeneity of the disease and imprecise predictive ability of the known baseline prognostic factors, the duration of response to initial therapy should be taken into account, to deliver risk and response-adapted therapy. The prognostic value of this feature across different clinical trials, points towards the role of underlying disease biology, both disease aggressiveness and ability to rapidly develop resistance to therapies as two important determinants of outcome. Table 1: Hazard ratio of overall survival since relapse for patients progressed within 3 yrs since randomization vs. after 3 yrs in each treatment arm Treatment arm Treatment arm HR (95% CI) P-value TTP<=3yrs vs. >3 yrs Thal/Dex N/A N/A Dex 0.4 (0.05, 3.9) 0.46 VBMCP(E5A93+ E9486) 1.9 (1.4, 2.7) 0.0001 VBMCP+alpha2IFN (E5A93+ E9486) 3.0 (2.2, 4.1) <0.0001 VBMCP+CYCLOPHOSPHAMIDE 2.3 (1.5, 3.6) 0.0001 Response duration <=2 yrs vs. >2 yrs Thal/Dex 0.2 (0.003, 18.5) 0.51 Dex 0.15 (0.02, 0.98) 0.048 VBMCP(E5A93+ E9486) 1.7 (1.2, 2.3) 0.0009 VBMCP+alpha2IFN (E5A93+ E9486) 3.0(2.1, 4.3) <0.0001 VBMCP+CYCLOPHOSPHAMIDE 2.1 (1.4, 3.3) 0.006 Figure 1: Overall survival since relapse between patients progressed within 3 yrs since randomization vs. after 3 yrs. Figure 1:. Overall survival since relapse between patients progressed within 3 yrs since randomization vs. after 3 yrs.