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Abstract The impact of fluorescence in-situ hybridization (FISH) on outcome in AL amyloidosis remains uncertain. We analyzed the response and overall survival (OS) of 692 AL amyloidosis patients with available FISH testing at diagnosis. First line treatment was categorized as autologous stem cell transplant or three non-transplant regimens (melphalan-based; bortezomib-based, and immunomodulatory drug (IMiD)-based). Forty-nine percent of patients had t(11;14), 37% del 13q/monosomy 13 and 19% had trisomy/tetrasomy. Analysis by abnormality type was restricted to t(11;14) and trisomy/tetrasomy sub-groups as chromosome 13 abnormalities were commonly associated with the other abnormalities. Patients with t(11;14) had lower rate of very good partial response or better (≥VGPR) compared to those lacking t(11;14) (56% vs 70%, P=0.001). By regimen stratification, this difference was maintained for bortezomib-based (52% vs 77%; P=0.004) and IMiD-based therapy (13% vs 54%; P=0.04) (Figure 1). Patients with trisomy/tetrasomy had no difference in the rate of ≥VGPR compared to those who did not (66% vs 63%, P=0.62), with no difference within regimen types. OS was similar between t(11;14)-positive and negative patients (median 43 vs 57 months; P=0.58). However, sub-analysis by regimen type showed a significantly inferior OS among t(11;14)-positive bortezomib-treated patients (median 15 vs 27 months; P=0.05) and t(11;14)-positive IMiD-treated patients (median 12 vs 32 months; P=0.05) (Figure 2). Among t(11;14)-positive bortezomib-treated patients, the OS difference was maintained among favorable-prognosis patients, but was absent for poor-prognosis sub-groups (Table). Trisomy/tetrasomy was associated with inferior OS (median 29 vs 69 months; P=0.001), a difference that was maintained for melphalan (median 15 vs 32 months; P=0.01) and borderline significance for bortezomib (median 14 vs 38 months; P=0.09). Multivariate analysis confirmed an independent effect on OS for trisomy/tetrasomy in the study cohort and for t(11;14) among bortezomib-treated patients. FISH analysis is essential in newly diagnosed AL amyloidosis, as it provides prognostic information among treatment groups and may influence the selection of induction treatment. Patients with t(11;14) should be considered for ASCT at diagnosis. Disclosures Dispenzieri: Celgene: Research Funding; Alnylam: Research Funding; pfizer: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jannsen: Research Funding. Kumar:Glycomimetics: Consultancy; AbbVie: Research Funding; Array BioPharma: Consultancy, Research Funding; Kesios: Consultancy; Onyx: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; BMS: Consultancy; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Millennium: Consultancy, Research Funding; Celgene: Consultancy, Research Funding. Kapoor:Amgen: Research Funding; Takeda: Research Funding; Celgene: Research Funding.

Abstract Background Suppression of uninvolved immunoglobulins is a common finding in multiple myeloma and the preservation of uninvolved immunoglobulins at diagnosis is associated with improved progression-free and overall survival. However, little is known about the impact of myeloma treatment on levels of uninvolved immunoglobulins, and the link between changes in uninvolved immunoglobulins during therapy and treatment response, disease progression and survival. Methods We identified patients who received therapy for newly diagnosed multiple myeloma at our institution between 2001 and 2014, and who had data available on absolute lymphocyte count (ALC) and quantitative uninvolved immunoglobulins (Ig) before commencing treatment. The ALC and levels of uninvolved Ig after 4 cycles of therapy were abstracted from the electronic medical record; patients who switched or stopped treatment, or died, before this time point were excluded. To assess change in ALC, the percentage difference in ALC between baseline and 4 cycles was calculated; for uninvolved Ig, the average of the percentage difference between baseline and 4 cycles for each uninvolved Ig (IgA and IgM for IgG myeloma, IgG and IgM for IgA myeloma, IgG and IgA for IgM and IgD myeloma, and IgG, IgM and IgA for light-chain only myeloma) was calculated. Treatment response at 4 cycles was retrospectively assigned according to International Myeloma Working Group criteria. Time to treatment failure (TTF) was defined as time from start of initial therapy to start of next line of therapy or death (if no additional treatment was received). A landmark analysis was used to calculate overall survival (OS) from the date of follow-up after 4 cycles of therapy. The Kruskal-Wallis, Chi-Square, and log rank tests were used to detect differences in medians, proportions, and survival times respectively. Results A total of 421 patients were included in this analysis. The median age was 63 years (range 33-91), 254 patients (60.3%) were male and median follow-up was 6.5 years (95% CI 5.6-7.3); the vast majority of patients had IgG (n=247 [58.7%]), IgA (n=98 [23.3%]) or light-chain only myeloma (n=68 [16.2%]). First line therapy comprised of pulse-dose dexamethasone (DEX, n=92 [21.9%]), lenalidomide-dexamethasone (RD, n=176 [41.8%]), bortezomib-dexamethasone (VD, n=22 [5.2%]), bortezomib-cyclophosphamide-dexamethasone (VCD, n=84 [20.0%]), and bortezomib-lenalidomide-dexamethasone (VRD, n=47 [11.2%]). Across the entire cohort, the median change in ALC and uninvolved Ig after 4 cycles of treatment was -11.0% (range: -92.7 to +718.8) and +9.0% (-77.7 to +1094.4) respectively; treatment with VCD was associated with the greatest median declines in ALC (DEX: -0.1%; RD: -9.9%; VD: -20.8%; VCD: -40.9%; VRD: -15.3%) and uninvolved Ig (DEX: -0.5%; RD: +15.5%; VD: +44.0%; VCD: -14.0%; VRD: +76.0%, both p<0.001). Conversion from suppression to normalization of the primary uninvolved Ig (IgA in IgG myeloma, and IgG in all other myeloma types) after 4 cycles was seen more frequently with the use of RD (13.1%) and VRD (12.8%) compared to DEX (4.7%), VCD (1.3%), or VD (4.8%), χ2=21.8, p=0.040. When considering only patients in whom the primary uninvolved Ig remained suppressed between baseline and 4 cycles, a ≥25% reduction in the primary uninvolved Ig occurred more frequently with the use of DEX (51.5%) and VCD (34.5%) compared to RD (24.8%), VD (23.5%) or VRD (25.7%), χ2=15.1, p=0.005 (Table 1). Although an average reduction in uninvolved Ig between baseline and 4 cycles (ΔIg<0) was independently associated with a lower likelihood of achieving very good partial response (VGPR) of better on multivariate analysis adjusting for age, sex and treatment regimen (OR=0.40 [0.24-0.63], p<0.001), there were no differences in TTF (2.0yrs vs. 2.0yrs, p=0.783) or OS (8.0yrs vs. 8.0yrs, p=0.721) between patients with ΔIg<0 (n=169) and those with ΔIg≥0 (n=222). Conclusions Myeloma treatments produce differential impacts on immune parameters, with VCD causing the greatest reduction in lymphocytes and uninvolved Ig, implying general targeting of plasma cells, in comparison to lenalidomide, which appeared to be more tumor-specific with relative sparing of lymphocytes and uninvolved Ig. While an average decrease in uninvolved Ig was an independent predictor of a lower likelihood of achieving VGPR or better after 4 cycles of therapy, it was not associated with a shorter TTF or poorer OS. Disclosures Kumar: BMS: Consultancy; Glycomimetics: Consultancy; Onyx: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Kesios: Consultancy; Millennium: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; Array BioPharma: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; AbbVie: Research Funding. Dispenzieri:GSK: Membership on an entity's Board of Directors or advisory committees; Prothena: Membership on an entity's Board of Directors or advisory committees; pfizer: Research Funding; Jannsen: Research Funding; Alnylam: Research Funding; Celgene: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding. Kapoor:Amgen: Research Funding; Celgene: Research Funding; Takeda: Research Funding. Bergsagel:Amgen, BMS, Novartis, Incyte: Consultancy; Novartis: Research Funding.

Abstract Background: The combination of MPD and amyloidosis is rare, and this patient population's clinical outcome is not well studied. Methods: Pts with a MPD and amyloidosis were identified via an clinical note search engine that searches through the electronic medical records of patients seen at Mayo Clinic Rochester, Jacksonville, and Scottsdale between 1990 and 2016. Terms used included amyloid or amyloidosis, chronic myelogenous leukemia or CML, essential thrombocytopenia or ET, and polycythemia vera or PV. Demographic and clinical data were abstracted from the medical record. Pts with both disorders were analyzed and their mortality rates along with median time to death were calculated. Prevalences at the Mayo Clinic were calculated for the years 2014 and 2015. Results: Twenty-three pts diagnosed with both a MPD and amyloidosis were identified. Thirteen (56.5%) were male, 10 (43%) were female. Eleven (47.8%) were initially diagnosed at the Mayo Clinic. Types of amyloidosis were as follows: Eleven (47%) had immunoglobulin light-chain (AL), four had localized (17%), two (8.7%) had wild-type transthyretin (ATTR), one (4.3%) had mutant ATTR, and five (21.8%) were unknown. Types of MPD were as follows: Seven (30%) had polycythemia vera (PV), seven (30%) had chronic myelogenous leukemia (CML), five (22%) had myelofibrosis, and four (17%) had essential thrombocytosis (ET). Fifteen (65%) were initially diagnosed with a MPD. Median time to last follow-up from second diagnosis was 1.7 years, and median time to death following second diagnosis was 1.4 years. The mortality rate was 87% in the total population. The median time to death for AL and PV was 2.7 years, AL and CML 1.0 years, and AL and ET 1.17 years. Myelofibrosis did not occur with AL. The most common combination was AL and PV, which accounted for five (22%) of the cases. Treatment regimens for the patients with AL were varied. Multiple drugs were combined with dexamethasone including melphalan, velcade, pomalidomide, lenalidomide, doxorubicin, and revlimid. Cyclophosphamide, bortezomib, and dexamethasone (CyBorD) were used in two cases. The mean time to diagnosis of amyloidosis from symptom onset was 10.3 months. Prevalences of AL and a MPD in 2014 and 2015 at the Mayo Clinic were 2.8% and 1.5%, respectively. Conclusions: The mortality rate for the combined diagnoses is high. The most common combination of diagnoses was that of AL and PV, which was associated with a mean time to death of 2.7 years. Disclosures Al-Kali: Celgene: Research Funding; Onconova Therapeutics, Inc.: Research Funding.

Abstract Background: Cytogenetic evaluation using fluorescence in situ hybridization (FISH) at the time of diagnosis is essential for initial risk stratification in multiple myeloma. Despite the absence of cytogenetic high-risk abnormalities a subset of patients does experience poor overall survival comparable high-risk disease (i.e. median overall survival less than three years after diagnosis). We aimed to identify demographic, clinical, and cytogenetic characteristics predicting poor three-year overall survival in patients with standard-risk cytogenetics. Methods: We studied 428 patients who were diagnosed with multiple myeloma between July 2004 and July 2014 at Mayo Clinic Rochester, underwent FISH evaluation within six months of diagnosis, and received treatment with novel agents (immunomodulator, proteasome-inhibitor, or a combination thereof). Patients with high- and intermediate-risk cytogenetics as well as patients lost to follow-up within three years were excluded. High-risk cytogenetics were defined as del(17p), t(14;16), and t(14;20). Intermediate-risk cytogenetics were defined as t(4;14) and gain(1q). Bone marrow aspirates were evaluated for deletions, monosomies, trisomies, and tetrasomies using chromosome- or centromere-specific FISH probes. IGH rearrangements were evaluated using an IGH break-apart probe and evaluating up to five potential partners (FGFR3, CCND1, CCND3, MAF, and MAFB). A multivariable-adjusted logistic regression model was used to assess the associations between the parameters of interest and three-year overall survival. Discrimination and calibration of the model were evaluated using the c-statistic and the Hosmer-Lemeshow test, respectively. The odds ratios of the identified predictors were rounded up to the next integer and assigned as points in a scoring system. Receiver operating characteristic analysis was used to determine the optimal cut-point and associated test performance characteristics. P-values below 0.05 were considered statistically significant. Results: The median age at diagnosis was 65 years (31 - 95), 259 (61%) of the patients were male. The median overall survival was 7.4 years (6.1 - 8.6) for the entire cohort (n = 428), 10.5 years (8.3 - NR) for those who survived at least three years (n = 327, 76%), and 1.6 years (1.2 - 1.7) for those who did not survive three years after diagnosis (n = 101, 24%). The factors associated with poor three-year overall survival and the derived scoring system are summarized in Table 1. Conclusions: Patients with multiple myeloma and standard-risk cytogenetics are a heterogeneous group. One fourth of the patients are experiencing less than three years of overall survival after diagnosis. Stage, age, extent of bone marrow involvement, karyotype, and platelet count at the time of diagnosis were helpful in identifying patients at risk for poor three-year overall survival. These findings emphasize the importance of further risk stratification in this patient population and warrant external validation. Disclosures Dispenzieri: Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Jannsen: Research Funding; pfizer: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; GSK: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding; Alnylam: Research Funding. Kapoor:Takeda: Research Funding; Amgen: Research Funding; Celgene: Research Funding. Kumar:AbbVie: Research Funding; BMS: Consultancy; Amgen: Consultancy, Research Funding; Takeda: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Noxxon: Consultancy, Honoraria; Janssen: Research Funding; Skyline: Consultancy, Honoraria.

Abstract Background: Bone disease in myeloma occurs as a result of complex interactions between myeloma cells and the bone marrow microenvironment. To date, no studies have evaluated the potential impact of genetic polymorphisms upon and/or within this microenvironment. Patients and Methods: Peripheral blood DNA from 282 patients enrolled in the Total Therapy 2 (TT2) protocol was studied using the previously reported Affymetrix 3k BOAC custom chip to evaluate relevant genetic polymorphisms. DKK1 gene expression and high risk GEP gene signatures were assessed as previously reported (Blood109:4470–4477 and 109:2276–2284 2007). Patients were classified using both full skeletal x-rays and MRI findings. The lower cut-off used was absence of focal abnormalities on x-ray and/or <7 focal lesions on MRI (see JCO25:1121–1128 2007). Results: The top 200 SNPs were first evaluated based upon univariate P values linked to limited or extensive bone disease. The top 50 SNPs with the smallest P values were then selected (eliminating closely linked genes) for recursive partitioning analysis. The recursive partitioning was conducted both with and without the insertion of known biologically relevant SNPs. The pruned tree developed with recursive partitioning proved to be quite stable and incorporated 4 dominant SNPs: rs 3766934 Epoxide hydrolase (EPHX1); sr3783408 MAP kinase; sr 1062637 RNA helicase DDX18; and sr3181366 TNFSF8-TNF-α. No alternate SNP substituted for EPHX1 in the recursive model. The 4 SNP signature of EPHX1 GG, MAP4K5 AG/AA, DDX18 GG/CC plus TNFSF8 CT/TT was highly correlated with the number of MRI lesions: mean 8.66 lesions versus 3.33 for alternate SNPs (P<.001). In the univariate association of standard prognostic factors, 4 SNP signature and 70 and 17 gene models for high risk, the best correlation with bone disease was with the 4 SNPs (P<.0001) followed by the 17 gene GEP model (P=0.05). Using stepwise multivariate regression analysis the best correlation with bone disease was Log2DKK-1 expression (P=.0001) but closely followed by SNPs EPHX1 (P=.0009); MAP4K5 (P=.0071) plus TNFSF8 and serum LDH (P=.02). The various analyses training (2/3) and validation sets were used with assessment of sensitivity and specificity. The microenvironmental 4 SNP signature combined with GEP DKK1 provided the best prediction of myeloma bone disease and overall outcome. Conclusions: This first assessment of genetic polymorphisms linked to myeloma bone disease in myeloma has led to the identification of polymorphisms with both potential biologic relevance and utility in prognostic models of myeloma bone disease including risk stratification for bisphosphonate use. Validation of these findings may allow a search for potential therapeutic targets.

Abstract Background: The serum free light chain (FLC) ratio is a readily available laboratory test that has independent prognostic significance in monoclonal gammopathy of undetermined significance (MGUS) (Blood2005;106:812–17) and solitary plasmacytoma (Blood2006;108:1979–83). The purpose of this study was to determine if the FLC ratio will be of prognostic value in multiple myeloma (MM). Methods: We used a well characterized cohort of 1027 newly diagnosed MM patients seen at Mayo Clinic from January 1, 1985 to December 31, 1998 (Mayo Clin Proc2003;78:21–33) to ensure adequate follow up. Archived serum samples from blood drawn within 30 days of initial diagnosis were available on 790 of the 1027 patients. Quantitation of serum free κ and λ concentrations was performed on the archived sera by immunonephelometry, using specific antibodies on a BNII nephelometer. FLC ratio was calculated as κ /λ, i.e., free κ concentration divided by free λ, reference range 0.26–1.65. If the FLC ratio is >1.65, κ is considered to be the “involved” FLC and λ the “uninvolved” FLC, and vice versa if the ratio is less than 0.26. Incorporation of FLC into the International Staging System (ISS) was assessed in 576 of 790 patients (73%), in whom samples or data were available to estimate the ISS. Results: 790 patients (median age 66 years) were studied. The FLC ratio was outside the reference range in 95.1% of patients. The median involved κ and λ concentrations were 37.1 and 71.3 mg/dL, respectively. A cut-point κ /λ FLC ratio of <0.03 or >32 was chosen for further modeling analysis on the basis of its separation of the cohort into two roughly comparable parts. Overall survival was significantly inferior in patients with an FLC ratio <0.03 or >32 (n=479 patients) compared to those with an FLC ratio that was 0.03–32 (n=311 patients), with median survival of 30 versus 39 months, respectively, P<0.001 (hazard ratio 1.3, 95% CI 1.12–1.54). The FLC ratio (<0.03 or >32) retained independent significance after adjusting for the International Staging System (ISS) (P=0.03). The FLC ratio made the most significant contribution to predicting prognosis in patients with ISS Stage 2 (n=265 pts), separating this category of patients into those with 5 year survival rates of 20.5% (FLC ratio <0.03 or >32; n=152 pts) versus 35.2% (FLC ratio 0.03–32; n=113 pts), P=0.02. We studied the additional prognostic value of the serum FLC to the variables used in the ISS by defining FLC ratio <0.03 or >32, Sβ2M ≥3.5 g/L, and serum albumin <3.5 g/dL as three risk factors in a risk-stratification model. Patients with 0, 1, 2, or 3 risk factors had significantly different overall survival, with median overall survival times of 51, 39, 30 and 22 months, respectively, P<0.001. Conclusions: The serum FLC ratio at initial diagnosis is an important predictor of prognosis in myeloma. We show that the serum FLC ratio can be incorporated into the ISS, providing the greatest prognostic value in ISS Stage 2 patients, as well as providing a new risk-stratification model.

Abstract Background Conflicting results have emerged, especially with respect to the impact on overall survival (OS), from trials evaluating lenalidomide maintenance (LM) therapy after induction therapy alone or post-autologous stem cell transplant (ASCT) in multiple myeloma (MM). We performed a systematic review and meta-analysis of existing outcome data from LM trials to evaluate role of lenalidomide as maintenance strategy in MM. Patients and methods A comprehensive search of electronic databases and abstracts through June 2013 was performed to identify randomized controlled trials (RCTs) that compared LM vs. placebo/no maintenance. Single arm studies were excluded. Pooled hazard ratio (HR) or odds ratio (OR) estimates with 95% confidence intervals (CIs) were calculated using the random-effects model for clinical endpoints of progression free survival (PFS), OS, response rate (RR) and adverse events (AEs), including second primary malignancies (SPMs). Analyses were performed using Comprehensive Meta-Analysis Software Version 2. We assessed between-study heterogeneity with the Cochran Q test and quantified its extent with the I2 statistic. Results Overall, five RCTs, with data extractable from four phase III trials (3 publications and 1 abstract) were identified (n= 1935). All studies were RCTs with an adequate randomization. MRC MM XI study was excluded from analyses as survival data are not available. Two placebo controlled trials (IFM 05-02, CALGB 100104) addressed the role of LM post-ASCT, one placebo-controlled trial (MM-015) studied LM therapy in the non-transplant setting and the remaining trial (RV-MM-PI209) had a 2 X 2 design comprising of both ASCT and non-transplant randomized arms followed by a second randomization of LM versus no maintenance. There was no heterogeneity for estimate of PFS results (Cochran Q, p=0.68; I2=0%), but considerable heterogeneity for estimate of OS (Cochran Q, p=0.09; I2= 55%), among the studies. There was significant prolongation of both PFS (HR 0.49, 95% CI, 0.41–0.58, p<0.001) and OS (HR 0.77, 95% CI, 0.62–0.95, p=0.013) with LM vs. placebo/no maintenance (Figure 1). Best response during maintenance was reported only in 2 studies and odds of responding (very good partial response or better) were not significantly different with LM (OR 1.28, p=0.3). Grade 3-4 AEs data were available from 3 trials for calculation of pooled OR with LM compared with placebo. We observed a nearly two-fold increase in the risk of SPMs with LM (OR 1.99; 95% CI, 1.31–3.04; p=0.001). Patients on LM were more likely to have grade 3-4 AEs than placebo: neutropenia (OR 4.9, p<0.001), thrombocytopenia (OR 2.7, p<0.001), fatigue (OR 2.3, p=0.01) and venous thromboembolism (OR 3.2, p=0.02). Odds of discontinuing treatment were also significantly higher in patients on lenalidomide (OR 2.9, p<0.001). Conclusions Meta-analysis of RCTs demonstrates significant improvement in PFS and modest improvement in OS with LM. There is an increased risk of grade 3-4 adverse effects, including SPMs with LM. Substantial heterogeneity for estimate of OS among protocols is a limitation of this analysis. Lack of uniform access to lenalidomide upon disease progression in the placebo/no maintenance arms of the constituent studies should be taken into account while interpreting aggregate effect estimates for OS in this meta-analysis. OS: Cochran Q p=0.09, I2=55%, substantial heterogeneity PFS: Cochran Q p=0.68, I2=0%, minimal heterogeneity Disclosures: Off Label Use: Lenalidomide for maintenance therapy in multiple myeloma. Kumar:Merck: Consultancy, Honoraria; Celgene: Consultancy, Research Funding; Millennium: The Takeda Oncology Company: Research Funding; Novartis: Research Funding; Genzyme: Research Funding. Dispenzieri:Celgene, Millenium, Jansenn, Pfizer: Research Funding. Bergsagel:Onyx: Consultancy. Lacy:Celgene Corporation: Research Funding.

Abstract Background: While B-cell receptor (BCR) signaling is essential for the development, of normal B cells, its aberrant hyper-activation results in neoplastic transformation of B-lymphocytes. Recent investigations using small molecule inhibitors validate the BCR pathway as a valuable target. Bruton’s tyrosine kinase (BTK) is one of the components of a signaling hub that transduces signals from the BCR into the cell for its activation and has been shown to be a therapeutic target. Ibrutinib (PCI-32765), an irreversible BTK inhibitor has shown clinical efficacy in CLL, mantle cell lymphoma (MCL) and Waldenströms macroglobulinemia (WM). Ibrutinib binds to cysteine-481 of the BTK protein and blocks its phosphorylation, resulting in termination of BCR-mediated activation of cells with a concomitant induction of death. Despite the clinical success of ibrutinib, a high percentage of patients achieve only partial response and eventually acquire resistance to the drug, resulting in aggressive relapse of the disease. A mutation of Cys481-Ser in BTK (ibrutinib-BTK binding site) has been reported to be one of the reasons for the development of ibrutinib resistance (IR). To understand the mechanisms resulting in acquisition of IR, we developed preclinical models of IR in WM and MCL. Materials: Ibrutinib was obtained from Pharmacyclics, CA. Validated human WM models (BCWM.1, RPCI-WM1 and MWCL.1 cell lines) and human MCL models (Jeko-1 and Maver cell lines) were used for the study. Results: BTK was constitutively phosphorylated at Y223 and Y551 in all the cell lines tested and this was inhibited by ibrutinib in a dose dependent manner. Phosphorylation of other kinases in the cascade such as SYK (Y323 and Y525/526) and PLCg2 (Y759 and Y1217) were also inhibited while AKT phosphorylation at both Ser473 and Thr308 was consistently increased in presence of ibrutinib. Treatment with ibrutinib induced cell cycle arrest in the G1 phase by 24h followed by apoptosis. Cell growth assays (MTS assay) showed that BCWM.1 was the most sensitive cell line followed by MWCL-1, RPCI-WM1, Maver and Jeko-1. Exposure of WM and MCL cells for prolonged periods of time with progressively increasing concentrations of ibrutinib resulted in outgrowth of clones (IR WM and MCL cell lines) that were resistant to apoptosis with a slow growth rate as compared to wild type parental cells. IR cells attained 2 – 20 fold resistance to ibrutinib as compared to the respective parental lines as determined by MTS assay. Sequence analysis of the BTK gene in all the cell lines revealed no mutation in IR cells at Cys481 suggesting that in an acquired IR state, resistance to ibrutinib can be developed independent of BTK Cys481 mutation. Interestingly, we found p-BTK levels to be markedly reduced in IR cells. Ibrutinib reversal experiments suggested that while a continuous presence of ibrutinib is needed for inhibition of BTK phosphorylation, a stable IR state could be maintained (for >1 month) in the absence of ibrutinib. This suggested the cells reliance on a parallel survival pathway, independent of BTK phosphorylation. Focused mRNA (Nanostring nCounter assay) and immunoblot analysis revealed significant changes in the expression profiles of several cellular elements. These included transcription factors such as PU.1, IRF4, BLIMP1, BCL-6 b-catenin as well as the phosphorylated ERK1/2, STAT1 and 3 suggesting a reprogramming of critical cellular networks, which IR tumor cells might be utilizing to overcome ibrutinib-induced cytotoxicity. Importantly, we observed that IR cells retained high levels of p-AKT and showed an increase in expression of BCL2 family members, as well as BCL-2 itself. Treatment of IR cells with ibrutinib +/- MK2206 (AKT inhibitor), or ABT-199 (BCL-2 inhibitor), synergistically induced cytotoxicity in IR cells, suggesting the importance of these parallel survival pathways (AKT/BCL2) in maintaining an IR state. Conclusion: Here we demonstrate that in the absence of BTK Cys481 mutation, an IR state is associated with reprogramming of transcriptional networks countering ibrutinib-induced toxicity by activation of AKT and BCL-2. Our current data exposes multiple vulnerabilities within IR cells, which can be therapeutically exploited to potentially delay onset of IR, by targeting alternative oncogenic mechanisms that are activated in presence of sustained BTK inhibition. Disclosures No relevant conflicts of interest to declare.

Abstract Background: Cryoglobulinemia(CG) is a relatively uncommon disorder which has been recognized as a syndrome for nearly forty years. The further classification into types I, II, and III was established thirty years ago, with Type II consisting of a monoclonal immunoglobulin possessing activity towards a polyclonal component. In the interim, many disease associations have been described and various therapies tried, but clinical trials remain rare, and the natural history, causes, and pathways of CG require further investigation. Methods: We examined the records of all patients seen at the Mayo Clinic, Rochester, with Type II CG between 3/2/1994 and 11/27/2000 using a prospectively held dysproteinemia database. Results: Of 66 total patients 30 were male(45%) and 36 were female(55%) with mean ages of 52.7±11.0 and 60.9±12.6, respectively. 63 patients were Caucasian, with one each of African, Hispanic, and other. 34 patients(52%) presented with purpura, 16 with edema(24%), 12 with neuropathy(18%), 12 with fatigue, 10 with arthralgia(15%), 8 with weight loss(12%), 5 with livido reticularis(8%), 4 with leg ulcers(6%), and 2 with infarcted extremities(2%). Of our patients, 13 had Type II CG (20%) unassociated with infection or lymphoma. 38 patients(58%) had hepatitis C(HCV), of whom 12 underwent genotyping with 10 having genotype 1a or 1b and 2 having genotype 2a or 2b. No patients had isolated Hepatitis B(HBV) though 8 HCV patients were coinfected with HBV. One patient each had CMV and EBV. 7 patients(10%) had Sjogren’s disease, and 1 had scleroderma. 11 patients (17%) had a lymphoproliferative disorder (LPD), and 5 more went on to develop LPD. Of these, 7 patients had a B-cell LPD, 4 had a MALT lymphoma, 4 had a non specific LPD, one had a lymphoplasmacytic lymphoma, and one had Gaucher’s thrombocytopenia. Significant renal disease developed in 23 patients(35%), with 12 being membranoproliferative glomerulonephritis (18%) and 3 being mesangioproliferative glomerulonephritis. Pertinent laboratory finding included a mean cryocrit of 7.6%±12.5, a positive rheumatoid factor in 36 out of 36, and hypocomplementemia in 33 of 41(80%). Liver function testing was reflective of the patient’s hepatitis status. Serum electrophoresis in 48 patients revealed the following patterns: 22 were normal(46%), 15 had a γ peak(31%), 5 polyclonal patterns(10%), 5 hypogammaglobulinemia, and one a β-γ peak. Of 32 samples where a monoclonal antibody was isolated 29 were IgM (91%), and 3 IgG (9%). The light chains were 88% κ, with 12% λ. Treatment was generally guided by the comorbidities, and many (30%) required no specific treatment for Type II CG. In the 38 HCV patients, 17 received interferon with or without ribavirin and 18 were deemed not to need treatment, while 2 received steroids alone and 1 was lost to follow up. In 28 patients without HCV 20 received steroids(71%), while 5 received other treatments and 3 were untreated. Of 46 patients who received any treatment, 27 (59%) achieved no response or had disease progression and required a change in therapy. To date, 8 patients have died, with none of deaths specifically attributable to complications of cryoglobulinemia. Conclusion: Type II CG is a non fatal disease most frequently associated with HCV. Optimal disease specific treatment is as yet undefined, and is generally directed at the underlying comorbidity when possible. Not all cases require treatment and many can be followed symptomatically.

Abstract Background: Patients with light chain amyloidosis (AL) often have delayed diagnosis and present with significant symptomatology; this may result in decreased quality of life (QOL). With improving treatment options providing longer survival, it is increasingly important to assess QOL. However there is paucity of data in the literature addressing QOL in AL patients. We prospectively employ a "Hematology Patient Reported Symptom Screen" (HPRSS) which consists of three questions about fatigue, pain and overall QOL. The aim of this study is to understand if HPRSS parameters predict various clinical outcomes. Methods: Eligibility for this retrospective study was as follows: 1) New diagnosis of AL between 2009-2014; 2) baseline HPRSS documented in the medical record; and 3) at least a year of follow-up, which included either death within or follow-up through 12 months after diagnosis. The HPRSS questions were rated on a 1-10 scale, with 10 being the worst for fatigue and pain, and 10 being the best for overall QOL. Scores were abstracted from visits at time of diagnosis, and at 12 months +/- 1 month post-diagnosis. We considered a 2-point difference in serial scores a "change" over time. Results: For the 302 patients in this study, the baseline median scores [interquartile range] for fatigue, pain, and QOL were 6 [3,7], 2 [0,5] and 5 [3,8], respectively. Median overall survival (OS) was 39.1 months, with 102 deaths in the first year. There were significant differences in baseline HPRSS between those who lived longer than one year and the early death patients in the domains of fatigue (5 [IQR 3, 7] vs. 7 [IQR 5, 8], p<0.0001) and QOL (6 [IQR 4, 8] vs. 5 [IQR 3, 7], p=0.006), but not in pain (2 [IQR 0, 5] vs. 2 [IQR 0, 5]). There were significant baseline differences in the early death group for alkaline phosphatase, bilirubin, creatinine, and Mayo stage. Patients who received ASCT had the best baseline fatigue 4 [2.5,6] and QOL 7 [5,8] scores and were significantly different from those who did not receive ASCT [fatigue p<0.0001) and QOL (p<0.0001)] On univariate analysis fatigue and QOL were prognostic for OS. On multivariate analysis Mayo 2012 staging, autologous stem cell transplant and baseline fatigue remained independently prognostic. When analyses were restricted to the 125 patients with HPRSS measurements at 12 months, we found that over time QOL scores improved significantly 6 [IQR 3.5, 8] to 7 [IQR 5, 8] (two sided Wilcoxon signed rank p=0.01), but fatigue (5 [IQR 2, 5] to 4.5 [IQR 3, 6]) and pain scores (2 [IQR 0 ,4] to 1.5 [IQR 0, 4]) did not. Patients with worse baseline parameters tended to have improvement in QOL by 12 months while those with the best baseline parameters tended to decline in QOL although not statistically significant. When we included the 102 patients who died within 12 months to the comparison, the early death patients had the worst baseline parameters and there were significant differences across all 4 groups for most characteristics (Table 1). There was no association between achieving hematologic or organ response with change in QOL. Conclusion: Asking patients with AL to rate their fatigue and QOL using a 10-point scale has predictive value. Patient reported fatigue at diagnosis is an independent prognostic factor for survival. Survival at one year was associated with significant improvement in QOL. Table 1. Baseline parameters between patients with early death and/or survive 12 months. Grouped by Patient Reported QOL at 12 months Relative to Baseline Dead by 12 months, n=102 Improved, n=44 Stable, n=55 Worsened, n=26 pa HPRSS scores [IQR] Baseline QOL Baseline fatigue Baseline pain 12 month QOL 12 month fatigue 12 month pain 5 [3,7] 7 [5,8] 2 [0,5] NA NA NA 4 [3-5] b,c,d6 [4-8] b,c2 [0-4] 7 [6-9] b,d4 [1.25-6] 1 [0-3] 7 [4-8] 4 [2-7] 2 [1-5] 7 [4-8] 5 [3-6] 2 [0-4] 8 [7-10] 2.5 [0-5.25] 2 [0-6.25] 5 [3-7] 5 [3-6] 2.5 [1-4] <0.0001 <0.0001 NS NS 0.001 NS dFLC, mg/dL 48 (2.89-726) 30 (1.1-494) 19 (36-455) 22 (0.2-2097) 0.008 Troponin, ng/mL 0.065 (<0.01-0.84) 0.02 (<0.01-1.6) 0.01 (<0.01-0.19) 0.01 (<0.01-0.14) <0.0001 NT-proBNP pg/mL 5222 (159-70,000) 1766 (26-16868) 1381 (24-19180) 496 (56-2973) <0.0001 Received Transplant (%) 4 (4) 13 (33) 36 (50) 13 (50) 0.0002 a Significant by Wilcoxon across all 4 categories; b Significant difference between Improved and Worsened; c Significant difference between Improved and Stable; d Significant difference between Worsened and Stable Disclosures Kumar: Millenium: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Abbvie: Research Funding; Janssen: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Novartis: Research Funding; Onyx: Consultancy, Research Funding. Thompson:Kite Pharma: Research Funding.