Paulus, Aneel

Abstract Background: Deubiquitinating enzyme (DUB) inhibitors are an emerging class of compounds, which are increasingly being regarded for their anti-cancer activity and therapeutic potential. The 19S regulatory particle of the proteasome contains two DUBs, USP14 and UCHL5, which are critical for the proper unfolding and deubiquitination of proteins prior to their entry into the 20S proteasome β-catalytic core. In B/plasma cell malignancies such as Waldenströms macroglobulinemia (WM) and multiple myeloma (MM), protein homeostasis and optimal proteasome functionality are paramount for tumor survival. This is evidenced by the success of 20S proteasome inhibition with bortezomib and carfilzomib, which have demonstrated remarkable clinical benefit in patients with WM or MM. As such, the proteasome degradation pathway represents a highly attractive and clinically validated, yet still largely unexplored therapeutic target. Here, we provide first evidence of the cytotoxic effects and molecular sequelae associated with a novel 19S proteasome DUB inhibitor, VLX1570, which selectively targets USP14 and UCHL5, in preclinical models of B/plasma cell cancers and their drug resistant tumor subclones. Materials: VLX1570 was obtained from Vivolux AB, Sweden. Bortezomib was purchased from Sellekchem, Houston TX. Human myeloma cell lines (OPM2, U266, KMS11), human WM cell lines (BCWM.1, MWCL-1 and RPCI-WM1), their respective bortezomib-resistant (BR) subclones as well as ibrutinib-resistant (IR) derivatives of BCWM.1 and RPCI-WM1 were used in experiments (total n=12). Peripheral blood mononuclear cells (PBMCs) from healthy donors were used to assess for cytotoxicity of VLX1570 in non-tumor cells. Results: A 72hr MTS assay first established sensitivity of plasma cell cancer models towards VLX1570, including drug resistant subclones (EC50 range, 20 – 90nM). Next we assessed whether loss of viability was due to apoptosis and observed dose-dependent annexin-V staining in ~50 – 70% of wild-type MM and WM cells, ~45 – 55% in corresponding BR models and ~50% in IR subclones when exposed to VLX1570 (100nm – 500nM) for 24hrs. VLX1570 was tested at similar concentrations in PBMCs and induced minimal cell death. To understand if VLX1570-induced apoptosis was mitochondrial mediated, we assessed mitochondrial outer membrane permeability (MOMP) in all plasma cell cancer models treated with the DUB inhibitor (100 – 500nM) and found a dose-dependent increase in MOMP (p<0.00025 – 0.000001). Activation of the mitochondrial/intrinsic apoptotic pathway was also evidenced by cleavage of caspase-9 and 3 on immunoblot analysis. As inhibition of protein deubiquitination results in accumulation of polyubiquitinated protein conjugates, we examined global ubiquitinated protein levels and found increasing amounts of high molecular weight poly-ubiquitinated protein in VLX1570 treated tumor cells in a dose-dependent manner. This prompted us to further delineate the potential cellular response mechanisms that relay the antitumor activity of VLX1570 in malignant plasma cells. Immunoblot analysis of drug sensitive and (bortezomib or ibrutinib) resistant MM and WM cell lines revealed several changes in ER stress response proteins, notably induction of HSP70 and splicing of XBP1; the latter event which was less prominent in BR cell lines treated with bortezomib. This suggested the ability of VLX1570 to overcome resistance through a rapid and potent proteotoxic effect, which overwhelmed the tumor cells stress response mechanisms beyond its capacity for survival. Finally, as abnormalities in the NFkB signaling pathway are implicated in malignant plasma cell survival, we found markedly decreased nuclear translocation of NFkB (p-P65) protein in tumor cells treated with VLX1570. Conclusions: The DUBs of the 19S proteasome cap offer an attractive target within the proteasome degradation system and whose inhibition by VLX1570 is able to circumvent mechanisms that support resistance to b-catalytic PI (bortezomib) or BTK inhibitor (ibrutinib) therapy. The studies undertaken thus far, coupled with more rigorous mechanistic and in vivo efficacy analyses currently underway, provides rational for the clinical development of DUB inhibitors for use in malignant B/plasma cell malignancies. Disclosures Martin: Janssen: Honoraria.

Abstract Background: Disparities in MM survival among different racial groups persist despite improvements in overall survival (OS). We report a comprehensive review of the SEER Medicare database to elucidate the causes of differences in disease presentation, management practices, cost of care and their relationships to outcomes among the MM patients (pts) from different racial groups. Methods: Pts diagnosed with MM between 1991-2010 with continuous Medicare coverage (1 year prior to diagnosis-date of death/end of 2012) were included. MM complications (MM-C); hypercalcemia (C), renal dysfunction (R), anemia (An), bone fractures (B), dialysis (D) occurring prior to/within 30 days of MM diagnosis (at diagnosis; AT-D), or any time later (after diagnosis; AF-D) were summarized. Demographics, survival (PEDSAF files) and disease characteristics, drug/stem cell transplant (SCT) utilization (NCH, OUTSAF, PDESAF files) were obtained. Trends in incidence of MM-C, treatment type over time (proportional odds) and their association with race (logistic regressions) were compared. Associations between race, MM-C AT-D and MM related death using Fine and Gray's competing risk methods were analyzed. Medicare claims adjusted for inflation (2013) within the first 6 months (mth)/total MM care were summed by drug and total charges. Median cost of care by race and year of diagnosis were evaluated by Kruskal-Wallis (univariate) and proportional odds models (multivariate). Results: A total of 35842 pts (52.1% males) with median age of 76 yr (range 18-104) were included. Mutually exclusive racial subgroups were: White (W, 72%), Hispanic (H: 7.3%), African-American (AA, 16.2%), Asian (A, 4.1%), other (0.3%). A significantly increasing trend in the prevalence of all MM-C AT-D was seen over time (all p<0.001). For AF-D, all MM-C initially increased but decreased from 2006-2010 except D that showed continued increase (Fig 1A). For race, MM-C were significantly different, with AA having the most C, R, An and D while W having the most B (Fig 1B). Inferior OS was seen with male gender (p=0.006), increasing age, earlier years of diagnosis, belonging to W or H race, C, R and B (all p<0.001), but not with An (p=0.298) or D (p=0.378). Trends in OS over time showed a significant interaction with race in 1991-1995 (p<0.001), 1996-2000 (p=0.004) and 2001-2005 (p<0.001) but not in 2006-2010 (p=0.182), possibly due to shorter follow up. Medicare claims analysis showed that pts receiving any treatment increased from 12.8% in 1991-1995 to 59.3% in 2006-2010 (p<0.001). Specific therapy utilization, including SCT and all drug classes/agents evaluated increased except for cytotoxic chemotherapy utilization (melphalan/cyclophosphamide), which decreased (Fig 2A). Any therapy utilization was significantly different by race (p<0.001) with highest for H (36.5%) and lowest for AA (31.6%). Specific treatments differed significantly by race (Fig 2B). Cost of care analysis showed significant increase over years for median drug claims (0.23k to 3.63k) and total claims (5.11k to 27.8k) during first 6 mth as well as for any time after MM diagnosis (drug: 1.3k to 9.9k, total: 21.9k to 84k) (p<0.001 for all). Median drug claims in first 6 mth were highest among AA (1.3k) and lowest among A (0.63k) (p<0.001). Same was true for total claims in first 6 mth (p<0.001). For any time after diagnosis, H had the highest drug (p<0.001) and total (p=0.081) claims. There were significant interactions between year of diagnosis, race and cost of care with H seeing the highest increase in drug claims in first 6 mth (p<0.001) and any time (p=0.002). Conclusion: MM-C have generally decreased AF-D due to improved therapeutics although AA continue to have the highest rates of MM-C. Our data shows that utilization and cost of MM care have increased tremendously with resulting improved outcomes, but significant racial disparities persist. These disparities may be in part due to impaired access to new agents from lack of supplemental insurance for certain racial groups. Drug utilization and cost of care disparities may also be due to differences in co-morbidities, MM-C or access leading to differential healthcare utilization and should be explored in order to ameliorate disparities in outcomes. Disclosures Ailawadhi: Pharmacyclics: Consultancy; Novartis: Consultancy; Amgen Inc: Consultancy; Takeda Oncology: Consultancy.

Background: MM is associated with significant morbidity even at the time of presentation and there is ample data to support that MM treatment improves overall survival (OS) as well as quality of life (QoL) due to effective symptom control. Patient refusal to recommended cancer treatment is not common in clinical practice but has been reported in certain cancers. There is no data on characteristics of MM patients who refuse treatment despite physician recommendation and outcomes of such patients. Methods: We used the National Cancer Database (NCDB) from 2004-2015 to extract data on adult MM patients who refused any systemic therapy as part of their initial care despite physician recommendation. Information on patient age, gender, race/ethnicity, education, year of diagnosis, income, geographical location, comorbidities, systemic treatment, survival time and vital status was obtained. Average annual percent change (AAPC) and average percent change (APC) were calculated to analyze the trends, and periods with similar APC were compared for statistically significant changes by applying join point regression. Multivariate models were employed to identify factors predicting refusal to therapy and to assess its impact on OS. Results: Of 75,734 eligible patients who were recommended treatment for MM (chemotherapy and or immunotherapy), 2138 (2.8%) patients did not receive any treatment due to refusal. Significantly higher number of females, patients in older age groups (age groups 60-79 and ³ 80 years), Medicare recipients and with ≥2 comorbidities refused treatment recommendation. On multivariate analysis, advanced age groups 60-79 years (OR = 1.47; 95% CI 1.27-1.31 p&lt;0.001) and ³80 years (OR = 5.02; 95% CI 4.23-5.96, p&lt;0.001), female gender (OR =1.16 ; 95% CI 1.05-1.27, p&lt;0.001), patients with certain primary payor types including Medicaid (OR = 1.59; 95% CI 1.28-1.98, p&lt;0.001), Medicare (OR = 1.63; 95% CI 1.43-1.87, p&lt;0.001) and uninsured (OR = 1.81; 95% CI 1.38-2.38, p&lt;0.001), and presence of ³2 comorbidities (OR = 1.39; 95% CI 1.2-1.61, p&lt;0.001) were the independent factors associated with higher likelihood of refusing treatment. Whereas being seen at academic research programs (OR = 0.7; 95% CI 0.6-0.8, p&lt;0.001), higher education (OR =0.81 ; 95% CI 0.67-0.98, p=0.03), geographical location (Midwest OR =0.87 ; 95% CI 0.76-0.99, p=0.04), longer distance to facility being at 3rd quartile (10.1-26.2 miles: OR =0.78 ; 95% CI 0.68-0.89, p&lt;0.001) or 4th quartile (&gt;26.2 miles: OR = 0.59; 95% CI 0.51-0.68, p&lt;0.001) were associated with lower likelihood of refusing treatment. The overall rate of refusing treatment by MM patients was quite stable during 2004-2015 with an AAPC of 1.1 (95% CI -1.1-3.3 p=0.3). However, on fitting scatter plot into Joinpoint regression model, a concerning trend in the more recent years was noted. While the rate of refusing recommended treatment decreased during 2004-2008, a rising trend was observed during the period 2008-2015 with an APC of 3.8 (95% CI 1.3-6.4, p≤0.001) (Fig 1a). Patients who were recommended treatment but refused had significantly worse survival than those who received treatment (median survival 17.7 vs 52.9 months, Cox hazard ratio 1.21; CI 1.17-1.24, p&lt;0.001) (Fig 1b). Conclusions: The percentage of MM patients refusing any systemic treatment as a part of their initial care despite physician recommendation appears to be increasing in recent years and this needs to be systematically addressed. Disparities in refusal to recommended treatment are independently associated with several variables including age, gender, comorbidities, geographical location, facility and insurance type. These need to be addressed urgently since there are several effective and well-tolerated anti-MM treatments which can potentially benefit patients in case the initial socioeconomic, clinical and psychosocial barriers are overcome. Disclosures Chanan-Khan: Xencor: Research Funding; Pharmacyclics: Research Funding; Merck: Research Funding; Jansen: Research Funding; Mayo Clinic: Employment; Ascentage: Research Funding; Millennium: Research Funding; AbbVie: Research Funding. Ailawadhi:Pharmacyclics: Research Funding; Celgene: Consultancy; Amgen: Consultancy, Research Funding; Cellectar: Research Funding; Janssen: Consultancy, Research Funding; Takeda: Consultancy.

Background: Median age at diagnosis for MM is 69 years with approximately 33% of the newly diagnosed MM (NDMM) patients aged ≥80 years (elderly). Yet, outcomes data and clinical trial participation in elderly MM patients are limited due to frailty and frequent comorbidities. Moreover, elderly patients are not candidates for stem cell transplant (SCT) and age is an independent poor prognostic marker, leading to disparate outcomes. The present study evaluated trends in outcomes and predictors of survival among elderly NDMM patients in the United States (U.S.). Methods: Using Surveillance Epidemiology and End Results (SEER) database, we extracted data on age, gender, geographical regions, year of diagnosis, and vital status for elderly patients (age ≥ 80 years) with MM from 1975 to 2016. Relative survival (RS) was estimated as the ratio of observed survival to the survival expected in the general population in the absence of malignancy. This adjusted for the competing causes of mortality prevalent in elderly patients. Mortality rates were age-adjusted. To estimate trends in mortality, we estimated annual percentage change (APC) and average annual percentage change (AAPC) by fitting the data in the join point regression model using the NCI's Join point Regression Program, Version 4.5.0.1. A multivariate analysis was conducted to analyze the predictors of overall and myeloma-specific mortality among elderly patients fitting into Cox proportion hazard regression model. Results: A total of 17,265 elderly MM patients were eligible for the study. Majority were females (n=9,487, 55%), were non-Hispanic whites (NHW) (n=12,895, 74.7%) and were diagnosed in the Western region of the U.S. (n=8,541, 49.5%). The median age was 84 years (IQR 81-87). The median RS for the whole period (1975-2016) was 19.8 months with 1- and 5- year RS of 60.1% (95%CI: 58.8-61.3) and 20.9% (95%CI: 19.5-22.3) respectively. The median RS increased from 8.45 months in 1975 to 29.86 months in 2013. One and 5- year RS also increased from 42.7% (95%CI: 32.4-52.5) and 12.9% (95%CI: 5.8-22.7) in 1975 to a 1- and 5-year RS of 72.3% (95%CI: 65.4-78.1) and 31.1% (95%CI: 23.4-39.1) in 2013, respectively (Fig.1). However, the age standardized mortality rate for the whole period showed an increasing trend with an AAPC of 2.3 (0.5-4, P<0.001). On fitting joinpoint regression, 2 distinct joinpoints were identified, calendar years 1977 and 1989 (Fig 2). Most of the increase in mortality rate was noted in the period 1975-1989. Since 1989, the mortality rates have shown a decreasing trend which is marginal but statistically significant, with an APC of -0.41 (95%CI: -0.7- -0.1, p<0.001). On multivariate analysis, increasing age (p<0.001) and non-northeast location (p<0.01) were associated with higher overall and MM-specific mortality. Female gender was associated with lower overall mortality (p<0.001) but not myeloma-specific mortality. While "other" race/ethnicity (not NHW, non-Hispanic black; NHB or Hispanic) was associated with lower risk of overall and myeloma-specific mortality, NHB were associated with a lower MM-specific (p<0.001) but not overall mortality. Conclusions: Our results suggest that although RS has improved significantly in the elderly patients, the mortality rates have not changed drastically over the years. Besides, factors like advancement in diagnosis and treatment which have improved RS, early diagnosis (leading to lead time bias) may also be contributing. Furthermore, there are several gender-specific, geographic and racial/ethnic disparities in outcomes of elderly MM patients, which need to be assessed prospectively. Although, a small decline in mortality rates in the more recent time is promising, further studies are warranted on interventions including aggressive supportive care directed at elderly patients with MM, so that MM survivorship can be improved. There should be strong consideration to increaseenrollment of the elderly in prospective clinical trials so that evidence-based guidelines can be developed. Disclosures Manochakian: Takeda: Membership on an entity's Board of Directors or advisory committees; Guardant Health: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Novocure: Membership on an entity's Board of Directors or advisory committees. Chanan-Khan:Merck: Research Funding; Ascentage: Research Funding; Millennium: Research Funding; Jansen: Research Funding; Mayo Clinic: Employment; Pharmacyclics: Research Funding; AbbVie: Research Funding; Xencor: Research Funding. Ailawadhi:Janssen: Consultancy, Research Funding; Takeda: Consultancy; Celgene: Consultancy; Amgen: Consultancy, Research Funding; Cellectar: Research Funding; Pharmacyclics: Research Funding. Off Label Use: Do not remove- this information is relevant to Abstract ID 125629: TAK-169 is a dimeric fusion protein of an anti-CD38 antibody single chain variable fragment fused to a modified Shiga-like toxin-A subunit..

Background: The development of novel treatment strategies has extended the median survival of MM to nearly a decade but the disease remains incurable and relapse is inevitable. The Bcl-2 pathway is highly relevant to MM cell survival and can be mitigated therapeutically. AT-101 is a novel, orally available pan Bcl-2 inhibitor (Bcl-2, Bcl-xl, Mcl-1, and Bcl-w). Preclinical in vitro and in vivo studies showed that AT-101 enhanced cytotoxicity of lenalidomide-dexamethasone (Rd). We conducted a phase I study in RRMM patients to establish the effective dose of AT-101 with Ld as well as record safety and preliminary efficacy of this combination (NCT02697344). Methods: Key eligibility criteria included: RRMM with measurable disease (serum monoclonal protein ≥1.0 g/dL or urine monoclonal protein >200mg/24 hour or serum immunoglobulin free light chain >10mg/dL AND abnormal serum free light chain ratio). Patients must have received 1-3 prior treatment regimens and have an absolute neutrophil count ≥1.0 x 109, platelets 75 x 109, creatinine clearance ≥50 mL/min, and ECOG performance status ≤2. AT-101 dosing was designed to reach a maximum daily target of 20mg (Cohort 1; 10 mg PO QD, Cohort 2; 20 mg PO QD) utilizing a standard 3 +3 dose escalation design in combination with standard doses of Rd. Treatment was given as outpatient for a maximum of 12, 28-day cycles. For pharmacodynamic studies, AT-101 alone was given in cycle 1, with R (25 mg on days 1-21) and d (40 mg weekly) added cycle 2 onwards. Results: Enrolled patients (n=10) included 60% males with median age 68.5 years (range 55-75) and median time since MM diagnosis 4.5 years (range 0.6-8.3). MM ISS stage was II/III in 7 patients and 8/10 had high-risk cytogenetics with 4 each having del17p and 1q+. Only 1 patient had t(11;14).Patients had received median 2 prior lines of therapy (range 1-3), with 7 having had prior autologous stem cell transplant (ASCT) and the initial induction regimen being bortezomib (V), R and dexamethasone (d) (VRd) in 8, Rd in 1 and cyclophosphamide (C) with Vd (VCd) in 1 patient. At the time of study entry, 3 patients were R refractory while 2 were refractory to both, V and daratumumab (Dara). Median duration of treatment was 7.5 cycles (range 2-12) and 3 patients completed all planned 12 cycles of treatment. Among the evaluable patients, dose limiting toxicities (DLTs) at 20 mg daily dose of AT-101 with 25 mg of R and 40 mg weekly included one patient with grade 4 febrile neutropenia and grade 4 neutropenia lasting 9 days and one patient with grade 4 thrombocytopenia lasting 8 days. G3/4 adverse events (AEs) included atrial flutter (n=1), white blood cell count decrease (n=3), neutropenia (n=5), febrile neutropenia (n=1) and thrombocytopenia (n=2), and back pain (n=1) . No G3/4 non-hematological AEs were noted. Any grade non-hematologic AEs seen in at least 20% (n=2) patients included fatigue (n=9), neuropathy (n=6), nausea (n=3), diarrhea (n=5), constipation (n=3), and creatinine increased (n=2). No patients experienced tumor lysis syndrome. Overall response rate (ORR) was 44% (2 each with very good partial response, VGPR and PR) and clinical benefit rate (CBR) was 89% with 2 additional patients showing minor response (MR) and 2 experiencing stable disease (SD) (Fig 1). Patients with high-risk disease had an ORR of 43% and a CBR of 100%. Median progression-free survival (PFS) for all patients was 8.1 months. Correlative analysis from patients who showed an objective response to treatment revealed a significant increase in bone marrow Th-effector cells, NK cells and cytotoxic CD8+ T-cells along with a significant decrease in immunosuppressive T-regulatory and B-regulatory cells was noted after 1 complete cycle of the combination therapy (p<0.05, Fig 2). Conclusions: This is the first reported clinical trial combining a Bcl-2 inhibitor with immunomodulatory drugs (IMiDs) in MM. AT-101-Rd is a clinically active regimen with an ORR of 40% in predominantly high-risk RRMM patients with an acceptable toxicity profile. Additional patients with MM experienced clinical benefit despite refractory status to prior therapy in this early phase clinical trial. These early findings support the further investigation of AT-101 specifically, and Bcl-2 inhibitors in general, with IMiDs in patients with MM. Disclosures Ailawadhi: Celgene: Consultancy; Amgen: Consultancy, Research Funding; Pharmacyclics: Research Funding; Cellectar: Research Funding; Janssen: Consultancy, Research Funding; Takeda: Consultancy. Chanan-Khan:Xencor: Research Funding; Pharmacyclics: Research Funding; Merck: Research Funding; Jansen: Research Funding; Mayo Clinic: Employment; Ascentage: Research Funding; Millennium: Research Funding; AbbVie: Research Funding. OffLabel Disclosure: AT-101 is not currently FDA-approved for treatment of any condition.

Introduction Waldenstrom macroglobulinemia (WM) is a rare, incurable, indolent non-Hodgkin lymphoma that is preceded by an IgM monoclonal gammopathy of undetermined significance (IgM MGUS). In recent years, better understanding of the pathobiology of WM and IgM MGUS has strengthened the hypothesis that they may represent different stages of the same disease. Studying the relationship between these two conditions is the essential first step to understanding the mechanisms driving the malignant transformation from IgM MGUS to WM. Recently long non-coding RNAs (lncRNAs) have garnered significant recognition for their roles in the regulation of gene expression and cellular function. lncRNA can regulate gene expression of neighboring protein-coding genes through multiple mechanisms such as by recruiting chromatin modifiers and increasing accessibility of genes to transcription proteins, or by directly binding to enhancers or promoters. Here we present the first analysis of the lncRNA expression profile in patients with WM compared to IgM MGUS. Methods Twenty-one patients with untreated WM (n=14) and IgM MGUS (n=7) seen at Mayo Clinic were included in this analysis. Malignant cells were isolated from bone marrow samples using CD19 and CD38 positive selection. Total RNA was extracted and sequencing was performed using the Illumina HiSeq4000 NGS platform. Differentially expressed lncRNAs in WM compared to IgM MGUS were defined as log2 fold change (FC) > 1.0 (upregulated) or < -1.0 (downregulated) and a false discovery rate (FDR) < 0.05. The nearest gene to each lncRNA was also identified and their gene expression was detected. Using the Ingenuity Pathway Analysis software and taking into account the transcriptional expression and known function of these genes, a correlation between cell function and disease analysis was performed. Results A total of 119 lncRNAs were differently expressed between WM and IgM MGUS (17 transcripts were upregulated in WM, while 102 were downregulated in WM). Sixteen unique genes were identified as the nearest gene to 17 upregulated lncRNAs, while 18 genes were identified as the nearest genes to the top 18 downregulated lncRNAs in WM compared to IgM MGUS. Several of the upregulated lncRNA in WM were in proximity to known oncogenes. The well-known oncogenic lncRNA PVT1 was found to be upregulated in WM compared to IgM MGUS (log2 FC 1.35, FRD 0.04). PVT1 is overexpressed in several malignancies and associated with inhibition of apoptosis and increased cell proliferation. PVT1 is in close proximity to MYC and co-expression of PVT1-MYC has been described in multiple cancers. PVT1 also potentiate MYC amplification by increasing MYC protein stability, therefore promoting malignant cell growth. The lncRNA TCB1D27, also upregulated in WM compared to IgM MGUS, is located in close proximity to the oncogene TNFRSF13B (TACI), which was found to be overexpressed in WM patients (log2 FC 1.61, FDR <0.001). TACI is a receptor for BLyS/BAFF, which modulates the development of normal B-cells and plays a role in various B-cell malignancies. In fact, BLyS/BAFF level is known to be increased in WM and to promote survival and proliferation of WM B cells. The upregulated lncRNA RP11-25K21.1 in WM is located in close proximity to the oncogene FCGR2B (CD32B), which was also upregulated in WM compared to IgM MGUS (log2 FC 1.59, FDR 0.001). Overexpression of CD32B was previously shown to be associated with inferior outcomes in DLBCL and FL patients, presumably secondary to an increased internalization and clearance of rituximab due to increased CD32B expression on malignant cells. Several other upregulated lncRNAs in WM compared to IgM MGUS are also in proximity of other oncogenes such as PCED1B, POLD3, CLLU1, and SMAD7. Finally, we considered the expression of the nearest genes and their reported cell function and association with diseases. Several genes that are known to have a role in the cell proliferation and/or neoplasm development were noted to be upregulated in WM (figure 1). Conclusion We present the first report of lncRNAs expression in WM and IgM MGUS in addition to a concurrent analysis of the gene expression of the nearest protein-coding genes. Several known oncogenes are in proximity of overexpressed lncRNAs in WM compared to IgM MGUS that could indicate potential implications in the pathobiology of these diseases and the mechanism driving the malignant transformation to WM. Disclosures Paludo: Celgene: Research Funding; Celgene: Research Funding; Verily Life Sciences: Research Funding; Verily Life Sciences: Research Funding. Dasari:The Binding Site: Patents & Royalties: US Patent Rights on Mass Spectroscopy Licensing agreement with The Binding Site, Research Funding. Kapoor:Celgene: Honoraria; Cellectar: Consultancy; Janssen: Research Funding; Sanofi: Consultancy, Research Funding; Amgen: Research Funding; Takeda: Honoraria, Research Funding; Glaxo Smith Kline: Research Funding. Ailawadhi:Amgen: Consultancy, Research Funding; Pharmacyclics: Research Funding; Takeda: Consultancy; Janssen: Consultancy, Research Funding; Cellectar: Research Funding; Celgene: Consultancy. Gertz:Amyloidosis Foundation: Research Funding; i3Health: Other: Development of educational programs and materials; Medscape: Consultancy, Speakers Bureau; Ionis/Akcea: Consultancy; Celgene: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Teva: Speakers Bureau; Alnylam: Consultancy; Prothena Biosciences Inc: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Physicians Education Resource: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Research to Practice: Consultancy; Johnson and Johnson: Speakers Bureau; DAVA oncology: Speakers Bureau; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees; Proclara: Membership on an entity's Board of Directors or advisory committees; Springer Publishing: Patents & Royalties; International Waldenstrom Foundation: Research Funding. Novak:Celgene Coorperation: Research Funding. Ansell:Affimed: Research Funding; Regeneron: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; LAM Therapeutics: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Bristol-Myers Squibb: Research Funding; Bristol-Myers Squibb: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; Trillium: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Mayo Clinic Rochester: Employment; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding; Seattle Genetics: Research Funding; Mayo Clinic Rochester: Employment; LAM Therapeutics: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Affimed: Research Funding; Trillium: Research Funding; Regeneron: Research Funding; Affimed: Research Funding; Affimed: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; LAM Therapeutics: Research Funding; Trillium: Research Funding; Mayo Clinic Rochester: Employment; Regeneron: Research Funding; Bristol-Myers Squibb: Research Funding; Affimed: Research Funding; Seattle Genetics: Research Funding; Affimed: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Bristol-Myers Squibb: Research Funding; LAM Therapeutics: Research Funding; Regeneron: Research Funding; Seattle Genetics: Research Funding; Trillium: Research Funding.

Background: Ibrutinib (ibr) is a small-molecular inhibitor of Bruton's Tyrosine Kinase (BTK), active in the treatment of various B-cell malignancies. B-cell receptor signaling blockade by BTK inhibition using ibr down regulates IRF4 (survival transcription factor) which is down regulated by lenalidomide (R) as well, suggesting possible synergistic effect on cell death. Higher doses of ibr (560-840 mg daily) have been used in combination regimens for MM with no significant dose-limiting toxicities (DLTs) but the combination of ibr and len has not been previously tested. We present safety and preliminary efficacy of the combination ibr, R, and dexamethasone (d) in RRMM patients. Methods: This is a phase I dose escalation study (NCT03015792) of 28-day cycles of ibr (420 mg daily, 560 mg daily, 700 mg daily or 840 mg daily) days 1-28 in combination with R 25 mg PO days 1-21, and d 40 mg PO weekly utilizing a 3+3 dose-escalation design. Eligible RRMM patients had progression after ≥2 prior lines of treatment, measurable disease as per International Myeloma Working Group criteria, ECOG performance status ≤2, adequate bone marrow (BM) (absolute neutrophil count ≥1.0 x 109, platelets ≥50,000 cells/mm3 for patients with BM plasmacytosis <50% or ≥30,000 cells/mm3 for patients with BM plasmacytosis ≥50%), kidney (creatinine clearance ≥30 mL/min), and liver function [total bilirubin ≤1.5 x upper limit of normal (ULN), aspartate aminotransferase and alanine aminotransferase ≤3 x ULN], and PT/INR ≤1.5 X ULN. Treatment was to be continued till progressive disease (PD) or any unacceptable toxicity. The primary objective was to determine the maximum tolerated dose (MTD) of ibr+Rd in RRMM and secondary objective was to evaluate safety profile of this regimen. Results: As of July 26 2019, 18 patients had been enrolled in the trial. Three patients had to be replaced (2 at 700 mg cohort, 1 each due to withdrawal and ineligibility, and 1 at 840 mg due to withdrawal). Median age of all patients was 67 years (range 49-79) with 9 of the 15 evaluable patients being females. Evaluable patients as per ibr dose level included 3 at 420 mg, 3 at 560 mg, 3 at 700 mg, and 6 at 840 mg. Four out of 15 patients had high-risk cytogenetics. Median prior lines of treatment were 4 (range 2-13) and prior treatments included bortezomib in 87% (n=13), carfilzomib in 47% (n=7), ixazomib in 47% (n=7), lenalidomide in 87% (n=13), pomalidomide in 40% (n=6), thalidomide in 40% (n=6), daratumumab in 60% (n=9), and stem cell transplant in 53% (n=8). High risk cytogenetics [del 17p, t(4;14), t(14;16), t(14;20)] were noted in 4 of the 15 evaluable patients (27%). Median follow up for alive patients was 8.6 months (range 1.1-25.1 months) and the median number of treatment cycles was 2 (range 1-5). Most common reason for treatment discontinuation was PD (40%) followed by adverse events (AEs) (26.7%). Only 1 DLT possibly related to ibr was a grade 3 rash at the 840 mg dose. Grade 3/4 AEs at least possibly related to study treatment included anemia (n=3), thrombocytopenia (n=3), neutropenia (n=3), leucopenia (n=3), lymphopenia (n=2), febrile neutropenia (n=1), and rash (n=2). Overall, the most common all grade AEs included anemia (n=12), thrombocytopenia (n=10), fatigue (n=10), neutropenia (n=8), leucopenia (n=5), and diarrhea (n=5). (Figure 1) No treatment-related deaths were noted. Overall response rate (ORR) was 7% with partial response (PR) noted in 1 patient. Additionally, 1 patient achieved a minor response (MR) and 10 patients had stable disease (SD) for a clinical benefit rate (CBR) of 80%. (Figure 2) PD was noted in 1 patient and 2 patients did not get response assessment. Ibr 840 mg (daily) with R 25 mg (days 1-21) and d 40 mg weekly was considered the MTD of this regimen. The median progression-free survival (PFS) for the 15 evaluable patients was 4.5 months (95% CI: 1.8-not reached). Conclusions: We report the first phase 1 trial of combining a BTK inhibitor with Rd in RRMM patients. MTD of ibr was determined as 840 mg (daily) in combination with R 25 mg (days 1-21) and d 40 mg weekly. This dose of ibr is consistent with some other trials showing the benefit of a higher dose of ibr in various regimens for treatment of B-cell malignancies. We noted this regimen to be well-tolerated without much high-grade AEs. Disease stabilization was noted in majority of patients. These data lay the basis for a larger trial in a more uniform cohort of patients to better define the efficacy of this regimen. Disclosures Ailawadhi: Celgene: Consultancy; Amgen: Consultancy, Research Funding; Pharmacyclics: Research Funding; Cellectar: Research Funding; Janssen: Consultancy, Research Funding; Takeda: Consultancy. Chanan-Khan:AbbVie: Research Funding; Xencor: Research Funding; Pharmacyclics: Research Funding; Merck: Research Funding; Jansen: Research Funding; Mayo Clinic: Employment; Ascentage: Research Funding; Millennium: Research Funding. OffLabel Disclosure: Ibrutinib is not FDA-approved for the treatment of multiple myeloma. The regimen of ibrutinib with lenalidomide and dexamethasone is not FDA-approved for the treatment of multiple myeloma.

Abstract Introduction Waldenstrom macroglobulinemia (WM) is a rare disease accounting for only 1-2% of all hematologic malignancies and with an overall annual, age-adjusted incidence of approximately 3.5 to 5.5 cases per million-person years. With approximately 13,000 active hematologist/oncologists in the US, most of who are in the community oncology setting, it's estimated that a hematologist/oncologist will only diagnose a WM case approximately every 8 years. Therefore, the clinical experience of a general hematologist/oncologist in the management of WM is likely very limited compared to more prevalent malignances. Previous studies in the setting of rare cancers suggest a correlation between higher volume of care and improved outcomes. Therefore, we explored the volume-outcome relationship in WM using the National Cancer Data Base (NCDB). Methods Patient-level data from the NCDB, a nationwide, facility-based, database covering approximately 70% of all newly diagnosed cancer cases in the US, was queried for all new WM cases diagnosed between 2004 and 2014. Only patients requiring treatment were included. Treatment facilities were divided into quartiles based on the average annual volume of newly diagnosed cases of WM seen. Cox regression was used to analyze the association between facility WM volume and survival, adjusted by demographics (sex, age, race), socioeconomic status (income, education, insurance type), geography (area of residence, treatment facility type, travel distance), comorbidity factors (Charlson-Deyo score), and year of diagnosis. Time-to-event analysis was calculated from frontline therapy initiation date using the Kaplan-Meier method and the log-rank test. Results A total of 3,732 patients with WM treated in 831 facilities were included. The median age at diagnosis was 70 years and 75% of the patients were treated within 20 miles from their residency zip code. Patient characteristics per treatment facility volume quartile are shown in table 1. The median annual facility volume was 1 new WM patient/year (range 0.1 to 21). The median follow-up from frontline treatment was 5 years. The unadjusted median OS by facility volume was: Q1: 6.5 years (95% CI: 5.7-7.4), Q2: 7 years (95% CI: 6.3-8.2), Q3: 8.2 years (95% CI: 7.1-8.9), and Q4: NR (95% CI: 8.5-NR), p<0.0001 (figure 1). The estimated 5-year OS by facility volume was: Q1: 56%, Q2: 61%, Q3: 64%, Q4: 71%, p<0.0001. Multivariate analysis including all variables showed in Table 1 demonstrated that facility volume was independently associated with all-cause mortality. Compared to patients treated at Q4 facilities, patients treated at lower-quartiles facilities had a higher incremental risk of death (Q3 hazard ratio [HR], 1.07 [95% CI: 0.88 to 1.29] p=0.46; Q2 HR, 1.34 [95% CI: 1.11 to 1.63] p=0.002; Q1 HR, 1.52 [95% CI: 1.23 to 1.88] p=<0.0001). Conclusion Our results suggest that a volume-outcome relationship exits in WM as patients treated initially at higher-volume facilities had a lower risk of mortality. Although differences in the underlying disease biology, referral patterns after initial therapy, or cumulative treating-physician experience could not be assessed, these potential biases would only underestimate the magnitude of the volume-outcome relationship reported. Disclosures Ansell: Celldex: Research Funding; Trillium: Research Funding; Takeda: Research Funding; Regeneron: Research Funding; Pfizer: Research Funding; Affimed: Research Funding; Merck & Co: Research Funding; Bristol-Myers Squibb: Research Funding; Seattle Genetics: Research Funding; LAM Therapeutics: Research Funding. Gertz:Medscape: Consultancy; janssen: Consultancy; Alnylam: Honoraria; Ionis: Honoraria; Physicians Education Resource: Consultancy; Prothena: Honoraria; Teva: Consultancy; Research to Practice: Consultancy; spectrum: Consultancy, Honoraria; celgene: Consultancy; Amgen: Consultancy; Abbvie: Consultancy; annexon: Consultancy; Apellis: Consultancy. Kapoor:Takeda: Research Funding; Celgene: Research Funding. Ailawadhi:Amgen: Consultancy; Janssen: Consultancy; Pharmacyclics: Research Funding; Celgene: Consultancy; Takeda: Consultancy. Reeder:Affimed: Research Funding. Witzig:Celgene: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding. Dispenzieri:Celgene, Takeda, Prothena, Jannsen, Pfizer, Alnylam, GSK: Research Funding. Lacy:Celgene: Research Funding. Kumar:Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; AbbVie: Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Membership on an entity's Board of Directors or advisory committees, Research Funding.

Abstract Background: Multiple myeloma (MM) is characterized by the invasion of malignant plasma cells into the bone marrow. While first line treatment options result in significant clinical benefit to patients, spatiotemporal clonal evolution results in disease relapse and mortality. Advances in genomics have armed clinicians with unprecedented insight into the molecular architecture of MM cells, however, the clinical benefit derived by genomics-guided intervention has been limited. We present a novel computational biology modelling (CBM) tool, which takes into account the combined effect of individual mutations, gene copy number abnormalities and large scale chromosomal changes in order to predict the salient molecular pathways utilized by the MM cell for survival. By reverse-engineering MM cell architecture in silico, the CBM tool is able to predict drug response and resistance mechanisms. Thus, our aim was to determine the accuracy of the CBM tool in predicting treatment response of relapsed/refractory MM patients for future management of their disease, in a more individualized manner. Methods: Cytogenetics and somatic mutations (by targeted NGS) for 15 MM patients were input into the CBM model to predict responses to different therapeutic combinations. All patients were relapsed to prior treatment. CBM uses PubMed and other online resources to generate patient-specific protein network maps of activated and inactivated disease pathways. We simulated the specific combinations of the drugs per patient and measured the quantitative drug effect on a composite MM disease inhibition score (i.e., cell proliferation, viability, apoptosis and paraproteins). The actual clinical outcome of the treatments was compared with predicted outcomes. Results: Fifteen patients were analysed using CBM for prediction of treatment response after NGS was performed. 13/15 were clinically evaluable, of which 1 was a responder and 12 were non-responder. 6/13 patients were treated on clinical trial and 7/13 were on drug combinations per physician decision. CBM correctly predicted 1 responder and 11 non-responder with a PPV of 50%, NPV 100%, specificity 91.67%, sensitivity 100%. The accuracy of CBM prediction was 92.30%. CBM also predicted the response of prior drug therapies for its non-response at relapse. For prior drug treatment options, 14 patients were evaluable. All the 14 patients were clinically non-responders and CBM correctly predicted for 13 patients with NPV 100%, Specificity 92.85% and overall accuracy of 92.85%. The majority of patients did not respond to therapies recommended at relapse. As an example, the operative molecular pathways from 2 patients who did not respond to combination treatment, either pre-NGS or post-NGS profiling, are shown in Fig. 1 and Table 1. CBM identified amplification (AMP) of chromosome (chr) 1 (WNT3A, IL6R, CKS1B, MCL1, PIK3C2B, USF1), chr 3 (HES1, PIK3CA, CTNNB1, WNT7A, FANCD2), chr 5 (IL6ST, IRF1, GLRX, SKP2), chr 7 (CDK5, EZH2, IL6, CAV1, ABCB1), chr 9 (NOTCH1, HSPA5, FANCC, FANCG), chr 15 (DLL4, FANCI, ALDH1A2), chr 19 (ERCC1, ERCC2, USF2); deletion(DEL) of chr 13 (CUL4A) , chr 16 (AXIN1, CDH1) and TP53 mutation in different combinations, which confer resistance to therapies at relapse. Conclusions: The CBM technology represents a potential means to identify therapeutic options for MM patients based on the patients individual tumor-genome profile and which can also be deployed for uncovering drug resistance mechanisms. This tool may aid clinicians in decision making for recommending the most appropriate therapy based on standard of care agents or clinical trials; thus improving patient outcomes and reducing unnecessary costs or drug-related toxicities. Disclosures Singh: Cellworks Research India Private Limited: Employment. Sauban:Cellworks Research India Private Limited: Employment. Husain:Cellworks Research India Private Limited: Employment. Kumar:Cellworks Research India Private Limited: Employment. Kumari:Cellworks Research India Private Limited: Employment. Tyagi:Cellworks Research India Private Limited: Employment. Abbasi:Cell Works Group Inc.: Employment. Vali:Cell Works Group Inc.: Employment. Ailawadhi:Pharmacyclics: Research Funding; Takeda: Consultancy; Celgene: Consultancy; Amgen: Consultancy; Janssen: Consultancy.

Abstract Background: Therapeutic advancements have led to significant improvement in outcomes for MM patients. Revised diagnostic criteria from International Myeloma Working Group focus on initiating treatment before the onset of end-organ damage. Thus, timeliness of initial therapy can significantly improve patient morbidity and outcomes. Such an analysis has not been reported for MM. Methods: We analyzed patients diagnosed with MM between 2004-2015 from the National Cancer Database (NCDB). Patients who received systemic treatment any time within the first year of diagnosis were included; those treated later than one year were considered possibly initially diagnosed with smoldering myeloma and hence, excluded. Time to initial treatment was divided into centiles with the 4 centiles analyzed being 0-7 days, 8-18 days, 19-37 days and >37 days. We performed univariate and multivariate analyses to compare sociodemographic and clinical factors influencing patient distribution across these timeliness categories and trends over time. Results: A total of 53,665 patients were included with 15,282 in 0-7 days, 12,462 in 8-18 days, 12,723 in 19-37 days and 13,198 in the >37 days treatment categories. Distribution across these centiles over time is shown in Figure. Univariate analyses showed a significant difference in distribution across the timeliness categories by year of diagnosis, patient age, gender, race/ethnicity, education level, insurance type, comorbidity score, treatment facility type, geographical location and distance to treating facility (all p<0.001) but no effect of income level. Multivariate analysis showed that there was a significantly higher likelihood of being in 4th centile (>37 days to treatment) for women (p<0.001), African Americans (p<0.001) or Hispanics (p=0.03; reference: Whites) or diagnosed in more recent years (p<0.001). Patients were less likely to be in the 4th centile if they were ≥80 years (HR 0.89, 95% CI 0.81-0.98, p=0.02), had >0 Charlson comorbidity score (p<0.001), were uninsured (p=0.02) or had Medicaid (p=0.03) as compared to having private insurance, were in non-community treatment facilities or geographical location other than Northeast (p<0.001). Patient education, income level or distance from treating facility was no longer significant. Conclusions: Several factors were found to affect timeliness of treatment in MM. We noted relatively faster time to initial treatment in elderly, uninsured or those who were treated in academic/comprehensive cancer programs but a delay in treatment for women and racial/ethnic minorities among other factors. These factors need to be addressed for equitable access and treatment practices and to realize improved outcomes for all. Figure. Figure. Disclosures Ailawadhi: Amgen: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Takeda: Consultancy; Pharmacyclics: Research Funding.