ALBERT

Description: Introduction The incidence of multiple myeloma (MM) increases with age, yet some cytogenetic changes are actually more common in younger patients with MM (Avet-Loiseau J Clin Oncol 2013).  This suggests that a mechanism other than chromosomal changes underlies the increased incidence with age.  Senescent cells secrete a number of proinflammatory cytokines, chemokines, growth factors and proteases resulting in the senescence-associated secretory phenotype (SASP), which can promote tumor growth.  Preclinical data suggests that myeloma bone marrow stromal cells express the SASP (Andre PLOS ONE 2013). We hypothesized that SASP factors correlate with age in patients with MM. Methods Peripheral blood serum and matched bone marrow aspirate plasma from patients with multiple myeloma were evaluated for selected factors associated with the SASP using quantitative multiplex immunoassay (Rules Based Medicine, Austin TX USA).  SASP factors with a known role in MM [interleukin-6 (IL-6), interleukin-8 (IL-8), interleukin-15 (IL-15), granulocyte-macrophage colony-stimulating factor (GMCSF), intercellular adhesion molecule 1(ICAM1), osteoprotegerin (OPG), hepatocyte growth factor (HGF), insulin-like growth factor-binding protein(IGFBP-1), interleukin-1 beta (IL1b), monocyte chemotactic protein 1(MCP-1), macrophage inflammatory protein-1 alpha(MIP-1a), angiogenin, leptin,  vascular endothelial growth factor receptor 1(VEGFR1) and stem cell factor(SCF)] were selected. The relationship between age and SASP factors were analyzed using Kendall tau rank correlation coefficient. Results Samples from 25 patients (each with peripheral blood serum and matched bone marrow aspirate plasma) were analyzed.  The median age was 62 (range 47 - 74). Disease states were as follows: 36% newly diagnosed/untreated, 24% pretransplant and 40% relapsed.  ISS stage included 40% stage I, 28% stage II and 32% stage III.  Three of the selected SASP factors in the peripheral blood correlated   with age:  IL-8 (Kendall Tau 0.334, p=0.027), OPG (Kendall Tau 0.289, p=0.046) and MCP-1 (Kendall Tau 0.332, p=0.022).  No SASP factors tested in the bone marrow plasma were significantly correlated with age. Conclusions We demonstrated age-associated differences in the SASP factors IL-8, OPG and MCP-1 in the peripheral blood of myeloma patients.  Future research will examine differences between patients with myeloma and age-matched controls without cancer. Disclosures: Vij: Celgene : Honoraria, Research Funding, Speakers Bureau; Millennium: Honoraria, Speakers Bureau; Onyx: Honoraria, Research Funding, Speakers Bureau. Stockerl-Goldstein:Celgene : Speakers Bureau; Celgene : Speakers Bureau; Millennium: Speakers Bureau; Millennium: Speakers Bureau.

Description: Abstract 4002 African-Americans (AA) have a 2–3-fold higher risk of multiple myeloma (MM) relative to Whites (Gebregziabher, 2006). We have formed a consortium and are conducting a multi-center study with 9 clinical centers and 4 NCI Surveillance, Epidemiology and End-Results (SEER) Program population-based cancer registries to determine the causes of the disease in this population and explain the excess risk (Myeloma in African-American Patients, MAP). Participation involves providing a blood or saliva specimen for DNA and answering a lifestyle and medical history questionnaire. At the end of the data collection period, a genome-wide scan will be performed and our results compared to those from 2,000 African-American controls participating in cohort studies. Patients with African ancestry (predominantly African-Americans) are identified from outpatient clinic rosters or from population-based cancer registries. For patients recruited at clinics, information on subtype, cytogenetics, FISH and lytic bone lesions is abstracted from medical records. To date, 601 patients have agreed to be in the study and we have received DNA samples from 592 patients; 54.6% are female and 45.4% are male. The mean age at diagnosis is 57 years (SD =11.2) with a median age at diagnosis of 58 years (range 27 to 90 years of age). Of the 514 subjects who completed a questionnaire, 7.8% were obese at age 20 (body mass index 〉 30) and 39% were obese 5 years prior to diagnosis. A first-degree relative with MM was reported by 17 cases (3%), 74% higher than the lifetime risk of 1.7% in the general population based on SEER data. In addition, cases reported 21 first-degree relatives with leukemia (4%), 7 with non-Hodgkin lymphoma (1%) and 14 with Hodgkin lymphoma (3%). To date, clinical information has been abstracted for 351 patients. Of these, 207 (58%) have active disease with the following distribution: stage I (30%), stage II (27%) and stage III (43%). The remainder have relapsed (13%), refractory (1%), relapsed and refractory (4%), or smoldering myeloma (6%), or are in remission (18%). The subtype distribution is: IgG (74%), IgA (11.4%), IgD (0.9%) and IgM (0.3%), and light chain only (13.5%); a distribution significantly different from that observed in a predominantly White population (P

Description: Multiple myeloma (MM) is 2-3 times more common among African-Americans compared to non-Hispanic whites. The 2-3-fold increased risk among family members of cases suggests a genetic contribution to risk. Genome-wide association studies (GWAS) in populations of European ancestry have identified seven novel risk loci at 2p23.3 (rs6746082), 3q26.2 (rs10936599), 3p22.1 (rs1052501), 6p21.32 (rs2285803), 7p15.3 (rs4487645), 17p11.2 (rs4273077) and 22q13.1 (rs877529) (Broderick, et al. Nat Genet, 2011, Chubb, et al. Nat Genet, 2013), three of which were replicated in another European series (Martino et al., Br J Haematol, 2012). Here we examined the index signals and conducted fine-mapping for each locus in a case-control study of 1,049 multiple myeloma cases and 7,084 controls of African ancestry to identify better markers of risk and novel independent loci in seven previously reported regions in this high risk population. Incident cases were recruited from 10 clinical centers and SEER cancer registries from 2011 to 2013 and genotyped using the Illumina HumanCore GWAS array. Control data were obtained from previous genome-wide studies of breast and prostate cancer, genotyped using the Illumina 1M-Duo in 4425 male controls from the African Ancestry Prostate Cancer Consortium (consisting of 14 independent studies) and 2632 female controls from a breast cancer GWAS of African-American women (consisting of 9 independent studies). Imputation to 1000 Genomes (March 2012 release) was conducted for regions around six of the previously identified single nucleotide polymorphisms [SNPs] (the HLA region harboring rs2285803 is still being imputed, results will be presented). A case-control analysis of SNPs/indels 〉1% frequency within 250 kb of each index variant was conducted using unconditional multivariable logistic regression adjusting for age, sex and five leading principal components. Region-specific alpha levels were determined through permutation tests. The minimum alpha level across the six regions was α=0.002. All previously reported risk variants were common in African-Americans (minor allele frequency [MAF] 〉0.05). For five of the six SNPs, we had ≥94% power to detect the same effect observed in non-Hispanic whites, and 64% power for the less common variant rs10936599 (MAF=0.07). We observed directionally consistent effects (odds ratio [OR]〉1) for the six risk variants tested, with three replicating at p≤0.05 (7p15.3, p=1.4x10-7; 17p11.2, p=0.05; 22q13.1, p=0.02). For three of the six regions, we observed better markers of risk in African-Americans that were correlated with the index SNP in Europeans (7p15.3, rs56333627, p=1.5x10-5, r2=0.89; 17p11.2, rs34562254, p=2.9x10-3, r2=0.90; 22q13.1, rs2092410, p=1.1x10-4 r2=.71). The missense variant identified in the 17p11.2 region (rs34562254, Pro251Leu) is located in TNFRSF13B, which encodes the protein TACI, a B cell surface receptor which plays a role in B cell maturation, apoptosis and antibody production by inducing activation of transcription factors including NFAT and NFκβ. In addition, there is evidence suggesting that TACI is involved in MM pathogenesis. Our results demonstrate that many of the risk loci for MM found in European ancestry populations are also risk loci in men and women of African ancestry and that by fine-mapping, we are able to identify variants that better capture risk in populations of African ancestry. Disclosures Terebelo: Celgene Corp: Membership on an entity's Board of Directors or advisory committees. Lonial:Millennium: The Takeda Oncology Company: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Novartis: Consultancy, Research Funding; Bristol-Myers Squibb: Consultancy, Research Funding; Onyx Pharmaceuticals: Consultancy, Research Funding.

Description: Multiple myeloma (MM) is a malignancy of plasma B-cells that is invariably preceded by monoclonal gammopathy of undetermined significance (MGUS), a pre-neoplastic plasma cell proliferative disorder. C57Bl/KaLwRij (KaLwRij) is a spontaneous inbred mouse strain predisposed to benign idiopathic paraproteinemia (BIP), a plasma cell dyscrasia that parallels many features of human pathology including progression to myeloma. In both humans and mice, the genetic basis for MGUS/MM risk is unknown. We sought to identify the genetic basis for MGUS/MM risk in KaLwRij mice to shed light on genes or pathways that mediate disease risk in humans. Using an integrative approach, we combined KaLwRij x B6 haplotype analysis (418 genes) and a MM patient association study (180 genes) to identify five candidate genes likely to contribute to both murine BIP-susceptibility and human MM risk. Surprisingly, we found KaLwRij mice had homozygous germline deletion of one of the five candidate genes, Samsn1, a putative negative regulator of B-cell activation. Consistent with the reported inhibitory function of SAMSN1 in B-cells, KaLwRij mice had enhanced naïve B-cell response in vitro following stimulation with IL4 and LPS and in vivo following immunization. We found that re-expression of Samsn1 in KaLwRij-derived myeloma cell line 5TGM1 decreased MM tumor growth in vitro, suggesting that loss of Samsn1 contributes to tumor growth in part through a cell intrinsic mechanism. Importantly, germline risk alleles may also influence cell types beyond the pre-malignant B-cells. It is established that the host environment also plays a critical role in supporting myeloma growth in KaLwRij mice. We found that Samsn1 is highly expressed in macrophages, but not in other MM-supportive cell types including osteoclasts and bone marrow stromal cells. Myeloma-associated macrophages play critical roles in supporting tumor growth and are broadly classified as anti-tumor M1 macrophages and tumor-promoting M2 macrophages. Microarray analysis of macrophages from B6 and KaLwRij mice prior to onset of BIP revealed three differentially expressed genes, but only one, Samsn1, is conserved in the human genome. We found that both unpolararized primary peritoneal and MCSF cultured bone marrow macrophages from healthy KaLwRij mice had markedly elevated expression of pro-tumorigenic M2 macrophage markers FIZZ1 and YM1 compared to B6 controls, despite the absence of activating cytokines. To confirm that loss of Samsn1 influenced macrophage activation and M2 polarization, we obtained bone marrow macrophages from mice with a targeted deletion of Samsn1 and found that unpolarized Samsn1-/- cells had similarly increased pro-tumor M2 macrophage marker expression. To evaluate the biologic significance of Samsn1 loss in macrophages on MM tumor growth, we established 5TGM1 MM tumors and injected M2 polarized macrophages from B6, KaLwRij, or Samsn1-/- mice. We found that MM tumor burden was markedly enhanced by the addition of a Samsn1-/- or KaLwRij macrophages compared to wild type macrophages. Thus, we found that loss of Samsn1 in macrophages enhances M2 polarization, prior to MGUS/MM development and can promote established myeloma tumor growth. Together, this data suggests that Samsn1 is a gene contributing to BIP-susceptibility in KaLwRij mice through mutually exclusive functions in multiple cell types including B-cells and macrophages. It is likely that SAMSN1 and its pathway members contribute to human MM progression, and may represent a point for preventative therapeutic intervention. Disclosures No relevant conflicts of interest to declare.

Description: Introduction: Multiple Myeloma (MM) is a hematologic malignancy that is universally preceded by Monoclonal Gammopathy of Undetermined Significance (MGUS). Obesity is the only known modifiable risk factor for the development of MM, though it is unclear if this is due to increased MGUS incidence or transition of MGUS to MM. In an effort to better understand how obesity may influence the progression of MGUS to MM, we analyzed patient data from the U.S. Veterans Health Administration (VHA). Methods: The VHA database was used to identify patients diagnosed with MGUS between October 1, 1999 and December 31, 2009 using ICD-9 code 273.1. Data was obtained on patient demographics, myeloma direct treatments, weight, height, and other clinical characteristics. Transition to MM was identified using two occurrences of ICD-9 code 203.0 or use of myeloma directed therapy within six months of a single use of ICD-9 code 203.0. Additionally, two investigators reviewed patient records to confirm the diagnosis and verify the diagnosis date. The World Health Organization (WHO) Body Mass Index (BMI) classification (normal-weight: 18.5≤BMI

Description: Abstract 968 Introduction: The incidence of DLBCL increases with age and the population ≥80 is the fastest growing segment of the elderly population. Optimal treatment of these very elderly DLBCL pts remains unclear. While chemo-immunotherapy can be curative, benefits of treatment must be balanced against toxicities in older, frail pts. Previous studies have suggested that doxorubicin treatment is associated with better survival in the very elderly population, though only on univariate analyses. To better understand the relationship between treatment and survival in pts ≥80, we performed a retrospective analysis of veterans to examine the relationship between treatment and overall survival (OS). Methods: We identified 523 DLBCL pts ≥80 diagnosed between 1998 and 2008 in the VHA Central Cancer Registry. We excluded pts with primary cutaneous or central nervous system DLBCL and pts treated with unknown agents outside the VHA. Data on stage, LDH, co-morbidities, date of death, treatment and supportive care medications were obtained for each pt. Treatment related mortality (TRM) was defined as death in the 30 days following any cycle of therapy. OS was defined as time from diagnosis to death. ECOG Performance Status (PS) at diagnosis was either obtained from pt charts or assessed from physician, nursing, and physical therapy notes available for each patient. Results: Of the 476 pts that met inclusion criteria, 193 received at least one dose of doxorubicin therapy (DT), 92 were treated without doxorubicin (non-DT) and 191 received no system therapy (NST). Median OS times were 30.2 months, 12.3 months, and 1.9 months in the DT, non-DT, and NST groups, respectively (Log-rank p

Description: Introduction African-American ethnicity, male sex, older age and obesity are accepted risk factors for multiple myeloma (MM). Obesity early in life is a risk factor for many cancers, including MM; most studies have focused on populations of European origin. African-Americans have a higher prevalence of obesity than other populations, and may have a distinct genetic contribution to this condition. We established a multi-center collaborative study to investigate possible explanations for the excess risk of MM among African-Americans. The aim of the present case-case analysis was to determine whether body mass index (BMI) was associated with risk factors and clinical characteristics at presentation in African-American MM patients. Methods Patients diagnosed with active MM since January 1, 2009 were recruited from nine outpatient centers and three Surveillance, Epidemiology, End-Results Program (SEER) population-based cancer registries. Information on weight and height at 20 years of age and at 5 years prior to diagnosis was obtained from questionnaires. Clinical information collected included age at diagnosis, stage, percent plasmacytosis on bone marrow biopsy, β2 microglobulin level, Ig serotype, light vs. heavy chain disease, and presence of lytic bone lesions. BMI (ht/wt2) was categorized into 3 levels (normal 30) according to World Health Organization standard. The Pearson chi-square test was used to test the association between BMI category, and risk factors and clinical characteristics. Mean ages at diagnosis across BMI categories were compared using linear regression and a t-test for trend calculated. Results To date, 1,044 African-American MM patients have been enrolled and of those, 1,014 provided a DNA sample. At present, 970 patients have completed a questionnaire, clinical records have been abstracted for 823 patients, and 509 patients have some information on gender, age at diagnosis, weight, height and clinical characteristics.The mean age at diagnosis was 59. Increasing BMI at age 20 was associated with younger age at diagnosis (p= 0.0004), whereas BMI at 5 years prior to diagnosis was not associated with age at diagnosis (p=0.9477). Among men, mean age at diagnosis decreased with increasing BMI at age 20 (p= 0.0125) (Table 1a) and at 5 years prior to diagnosis (p=0.0252) (Table 1b). Among women, the trend was signficant at age 20 (p=0.0018) (Table 1a) but not at 5 years prior to diagnosis (p= 0.7094) (Table 1b). Increasing BMI was not significantly associated with any other clinical characteristics. Conclusion/Discussion In a large collection of African-American MM patients, we observed a strong association between increasing BMI at age 20 and younger age at diagnosis. A similar trend was observed in men only at 5 years prior to diagnosis, consistent with previous reports. Obesity is one of the few known potentially modifiable risk factors for MM. Younger age at diagnosis reflects an earlier accumulation of either or both genetic and environmental risk factors. Obesity at an early age may influence MM risk through shared biological pathways such as interleukin-6 and insulin-like growth factor, by contributing to chronic B-cell activation, thereby increasing susceptibilty for MM later in life. The significance of the gender difference for the association closer to diagnosis is unclear and requires additional study. Disclosures: Terebelo: Amgen: Honoraria; Millennium: Honoraria. Mehta:Celgene: Speakers Bureau; Millennium: Speakers Bureau. Zonder:Skyline: Consultancy. Orlowski:Bristol-Myers Squibb: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Celgene: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Millennium: The Takeda Oncology Company: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Onyx: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Resverlogix: Research Funding; Array Biopharma: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Genentech: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Merck: Membership on an entity’s Board of Directors or advisory committees. Lonial:Celgene Corporation: Consultancy; Millennium: Consultancy; Novartis: Consultancy; Bristol Myers Squibb: Consultancy; Sanofi: Consultancy; Onyx: Consultancy.

Description: Abstract 760 Introduction: The incidence of multiple myeloma (MM) increases with age, and the prognosis worsens. Comorbidities increase in prevalence with age, yet little is known about the impact of comorbid medical conditions on outcomes in MM. Methods: In a retrospectively-assembled cohort study, all patients with MM diagnosed between 1998 and 2009 at a Veterans' Administration (VA) hospital were identified in the VA central cancer registry. Patients who received no treatment within 6 months of diagnosis were excluded, eliminating those with smoldering myeloma or who received supportive care only. Comorbidities were ascertained from ICD-9 codes present prior to the diagnosis of MM, and categorized using the Romano adaptation of the Charlson Comorbidity Index (CCI). The independent effects of age, race and comorbidities were examined using Cox proportional hazards modeling. The impact of individual comorbidities on survival was also examined, controlling for age and race. Results: A total of 2,968 patients were identified. The median age was 69 (range 27–92). The vast majority of patients (98%) were male; 28.6% of the patients were black. The median Charlson Comorbidity Index score was 2 (range 0–13). The frequencies of selected comorbidities were: diabetes (31%), renal impairment (23.8%), cardiovascular comorbidities (38.8%) and pulmonary (26.6%). The median overall survival (OS) for the entire cohort was 28.6 months at a median follow up of 26.8 months (range 0–137 months). On multivariate analysis, age was significantly associated with mortality [Hazard Ratio (HR) 1.03 per year (95% confidence intervals (CI) 1.03–1.04), p

Description: Insulin-like growth factor-1 (IGF-1), insulin, and IL-6 are dysregulated in multiple myeloma pathogenesis and may also contribute to multiple myeloma etiology. To examine their etiologic role, we prospectively analyzed concentrations of serologic markers in 493 multiple myeloma cases and 978 controls from 8 cohorts in the Multiple Myeloma Cohort Consortium. We computed odds ratios (ORs) and 95% confidence intervals (CIs) for multiple myeloma per 1-SD increase in biomarker concentration using conditional logistic regression. We examined heterogeneity by time since blood collection (≤ 3, 4- ≤ 6, and 〉 6 years) in stratified models. Fasting IGF binding protein-1 concentration was associated with multiple myeloma risk within 3 years (OR, 95% CI per 1-SD increase: 2.3, 1.4-3.8, P = .001) and soluble IL-6 receptor level was associated within 6 years after blood draw (OR ≤ 3 years, 95% CI, 1.4, 1.1-1.9, P = .01; OR4- ≤ 6 years, 95% CI, 1.4, 1.1-1.7, P = .002). No biomarker was associated with longer-term multiple myeloma risk (ie, 〉 6 years). Interactions with time were statistically significant (IGF binding protein-1, P-heterogeneity = .0016; sIL6R, P-heterogeneity = .016). The time-restricted associations probably reflect the bioactivity of tumor and microenvironment cells in transformation from monoclonal gammopathy of undetermined significance or smoldering multiple myeloma to clinically manifest multiple myeloma.

Description: Abstract 3142 Introduction: Advancing age is associated with poorer prognosis in patients with multiple myeloma (MM). Comorbidities increase in prevalence with age, but the impact of comorbidities on survival in patients with MM is not known. The purpose of this study was to examine the impact of comorbidities on survival in multiple myeloma. Methods: All patients (pts) with MM diagnosed and treated at Washington University School of Medicine in St. Louis, Missouri from 1999–2010 were identified from the Barnes-Jewish Hospital Oncology Data Services Database. The institution's cancer registrars retrospectively collect clinical, demographic and survival data in accordance with the American College of Surgeons Commission on Cancer guidelines. Comorbidities are graded as None, Mild, Moderate or Severe using the ACE-27 comorbidity index [Piccirillo et al. J Reg Mgmt 1999]. Patients without data on comorbidities were excluded from the study. The primary endpoint was overall survival (OS), calculated from the date of diagnosis and censored at the time of last follow-up. OS was estimated using the Kaplan-Meier method, and compared between comorbidity groups using the Log-Rank test. The independent effects of age and comorbidities were evaluated using Cox Proportional Hazards Modeling. Results: 569 patients were identified in the database. Median age of patients was 59 years (range 33–91 years); 54.8% were male, 45.2% were female; 74.9% were white, 23.2% were black, and 1.9% were other races/ethnicities. Based on the ACE-27 comorbidity index, 181 pts (31.8%) had no comorbid medical conditions, 226 (39.7%) had mild comorbidities, 115 (20.2%) had moderate comorbidities, 47 (8.3%) had severe comorbidities. In the entire cohort, the median OS was 49.2 months [95% confidence intervals (CI) 42.9 – 55.6 months]. Survival by comorbidity category and age group are shown in table 1. The differences in survival between comorbidity groups in each age group and the entire cohort were statistically significant (log-rank p