Binder, Moritz

In this phase 1 trial, inhibition of granulocyte-macrophage colony-stimulating factor (GM-CSF) was associated with clinically meaningful responses in 5 of 15 patients with relapsed or refractory chronic myelomonocytic leukemia (CMML). Preliminary data suggest that this approach may be tractable in CMML bearing activating NRAS mutations.

8039 Background: Treatment of MM has evolved significantly over the past decade, with increasing use of multi-drug combinations for initial therapy. In addition, supportive care approaches have also improved. We examined how these improvements have translated to survival outcomes in patients with newly diagnosed MM. Methods: Patients (n=3449) with a diagnosis of MM made between 2004 and 2017 and seen at Mayo Clinic within six months of the diagnosis, were included in this analysis. Patients were divided into three groups based on the year of diagnosis; group 1- 2004-07 (n=831), group 2-2008-12 (n=1161), and group 3-2013-17 (n=1457). Survival of the groups were estimated using Kaplan-Meier method, and compared using log rank test. Results: The median age was 64 years (22 to 96); 60% were male and 40% were female. 14% were >75 years, 33% were aged 65-75 and 53% were <65 years. The median overall survival for the whole cohort was 5.7 years (95%CI; 5.4, 6.3). The median OS for the groups 1, 2 and 3 were 3.9, 6.3 and NR, respectively; p<0.001. The 4-year survival estimates were 50%, 62%, and 75%, respectively. We then explored the improvements in patient subgroups. While all patients experienced improvements in OS over time, improvement in group 3 was most prominent for those >75 years. In patients <65 years, the 4-yr OS for groups 1, 2 and 3 were 57, 71, and 79% respectively. In patients 65-75 years of age, the 4-yr OS for groups 1, 2 and 3 were 48, 60, and 75% respectively. In patients >75 years, the 4-yr OS for groups 1, 2 and 3 were 24, 35, and 56% respectively. While patients with high-risk disease did not see as much benefit in the earlier period, substantial progress was seen in the last group. The 3-yr OS for patients with high-risk cytogenetics were 52, 55, and 73% for groups 1, 2 and 3 compared to 67, 75, and 85% for standard-risk cytogenetics respectively. 2067 patients were staged according to the International Staging System and the median OS for stages 1, 2 and 3 were 6.5, 4.6 and 2.4 in group 1; 9.2, 6.6 and 3.5 in group 2 and NR for any of the stages in group 3. Conclusions: The results confirm continued improvement in survival of newly diagnosed multiple myeloma patients, including elderly and high-risk MM.

Introduction: Advances in the understanding of disease biology, the introduction of new drugs, and better supportive care have improved outcomes in multiple myeloma (MM). Most improvements have been observed in clinical trial and tertiary referral center populations but questions remain about the generalizability of these findings to patients treated in the community. Methods: We studied all patients diagnosed with MM between 01/01/2001 and 12/31/2015 who had complete demographic and overall survival (OS) data available and were seen at Mayo Clinic (MAYO) or followed in the Surveillance, Epidemiology, and End Results Program (SEER, 18 registry data 2000 - 2016, 11/2018 submission). We retrieved age at diagnosis, sex, date of diagnosis, date of last follow-up, and OS for all patients. OS was defined as the time from diagnosis to death from any cause. Patients who were alive at the end of follow-up (12/31/ 2016) were censored. OS estimates were calculated using the Kaplan-Meier method. Age- and sex-adjusted Cox models were used to assess the association between the 5-year interval of diagnosis and OS. Expected OS estimates were calculated based on United States general population rate tables (Human Mortality Database) using a conditional approach. Standardized mortality ratios (SMR) were calculated by dividing the number of observed deaths by the number of expected deaths in age- and sex-matched general United States population controls. Linear regression models were fit to test for linear trends in early mortality and SMR over time (per 5-year interval). P-values below 0.05 were considered statistically significant. Results: The median age at diagnosis was 3 years lower in patients at MAYO (64 years, 15% ≥ 75 years, 60% male, n = 3293) compared to SEER (67 years, 29% ≥ 75 years, 55% male, n = 61779). After a median follow-up of 2.8 years the median OS was longer in MAYO compared to SEER (5.4 versus 4.0 years, HR 0.82, 95% CI 0.78 - 0.86, p &lt; 0.001) and remained statistically significant after adjusting for age and sex (HR 0.91, 95% CI 0.86 - 0.95, p &lt; 0.001). Early mortality (1-year mortality) decreased between 2001-2005 and 2011-2015: From 20% to 11% at MAYO and from 26% to 19% in SEER. When grouping OS by year of diagnosis (in 5-year-intervals) improvements were seen in both populations (A) and remained statistically significant after adjusting for age and sex. The relative improvements were similar comparing the 5-year period after the introduction of the novel therapies (2006 - 2010) to 2001 - 2005 and more pronounced in MAYO for the most recent 5-year interval (2011 - 2015, A). This trend was reflected in a steady temporal improvement in 5-year OS estimates in MAYO including the most recent 5-year interval (2011 - 2015, B bottom left). In SEER there was a comparable increase between the first two 5-year intervals but a lesser improvement in more recently (2011 - 2015, B bottom left). A diagnosis of MM remained associated with significant excess mortality in all age groups over time in both populations (B top). There was a decrease in excess mortality over time at MAYO (SMR decline per 5-year interval 1.3, 95% CI 0.9 - 1.8, p &lt; 0.001) while there was little change in SEER (SMR decline 0.0, 95% CI -0.3 - 0.3, p = 0.917, B bottom right). Further stratifying by age at diagnosis, the decrease in excess mortality was observed mostly in patients &lt; 75 years at MAYO (SMR decline per 5-year interval 1.7, 95% CI 1.5 - 2.0, p &lt; 0.001, C bottom left) and to a lesser extent in older patients (SMR decline 0.4, 95% CI 0.2 - 0.6, p &lt; 0.001, C bottom right). No such trends towards improvement were observed in either age group in SEER (C bottom). In older patients, early mortality remained approximately 30% in both populations despite continued improvements, while the 5-year OS estimates for the most recent 5-year interval (2011 - 2015) were 37% at MAYO and 26% in SEER (C top). Conclusions: Both early mortality and long-term survival have improved over time. Reductions in excess mortality were largely confined to younger patients with access to specialized care. Patients ≥ 75 years represent more than a quarter of all patients in the community, a third of them died within one year of the diagnosis, and only one in four was alive five years later. Older patients with MM remain a vulnerable population and have derived only limited benefit from recent advances in the field. Safe and effective therapies for older patients with MM remain an unmet need. Figure Disclosures Gertz: Ionis/Akcea: Consultancy; International Waldenstrom Foundation: Research Funding; Alnylam: Consultancy; Prothena Biosciences Inc: Consultancy; Celgene: Consultancy; Janssen: Consultancy; Spectrum: Consultancy, Research Funding; Annexon: Consultancy; Appellis: Consultancy; Amgen: Consultancy; Medscape: Consultancy, Speakers Bureau; Physicians Education Resource: Consultancy; Abbvie: Other: personal fees for Data Safety Monitoring board; Research to Practice: Consultancy; Teva: Speakers Bureau; 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; i3Health: Other: Development of educational programs and materials; Springer Publishing: Patents & Royalties; Amyloidosis Foundation: Research Funding. Dispenzieri:Alnylam: Research Funding; Akcea: Consultancy; Takeda: Research Funding; Pfizer: Research Funding; Janssen: Consultancy; Intellia: Consultancy; Celgene: Research Funding. Lacy:Celgene: Research Funding. Maurer:Nanostring: Research Funding; Morphosys: Membership on an entity's Board of Directors or advisory committees; Celgene: Research Funding. Dingli:alexion: Consultancy; Janssen: Consultancy; Millenium: Consultancy; Rigel: Consultancy; Karyopharm: Research Funding. Kapoor:Takeda: Honoraria, Research Funding; Celgene: Honoraria; Janssen: Research Funding; Amgen: Research Funding; Sanofi: Consultancy, Research Funding; Glaxo Smith Kline: Research Funding; Cellectar: Consultancy. Leung:Takeda: Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; Aduro: Membership on an entity's Board of Directors or advisory committees; Omeros: Research Funding. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: 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. The presence of specific cytogenetic abnormalities is known to confer a poor prognosis, less is known about the cumulative effect of multiple cytogenetic high-risk abnormalities. We aimed to evaluate the prognostic implications of the presence of multiple cytogenetic high-risk abnormalities at the time of diagnosis. Methods: We studied 226 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 presented with cytogenetic high-risk abnormalities. High-risk cytogenetics were defined as t(4;14), t(14;16), t(14;20), del(17p), or 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). Kaplan-Meier overall survival estimates were calculated and the log-rank test was used to compare overall survival in patients with single and multiple cytogenetic high-risk abnormalities. A multivariable-adjusted Cox regression model was used to assess the effect of multiple cytogenetic high-risk abnormalities on overall survival adjusting for age, sex, and Revised International Staging System (R-ISS) stage. P-values below 0.05 were considered statistically significant. Results: The median age at diagnosis was 65 years (32 - 90), 129 (57%) of the patients were male. The median overall survival was 3.5 years (3.1 - 4.9) for the entire cohort (n = 226), 4.0 years (3.3 - 5.1) for those with one cytogenetic high-risk abnormality (n = 182, 80%), and 2.6 years (1.7 - 3.1) for those with two cytogenetic high-risk abnormalities (n = 44, 20%). There were no patients with more than two cytogenetic high-risk abnormalities. Ninety-eight patients (45%) had a high-risk translocation, 77 (35%) had del(17p), 39 (18%) had a high-risk translocation plus del(17p), and 5 (2%) had gain(1q) plus either a high-risk translocation or del(17p). Figure 1 shows the Kaplan-Meier overall survival estimates stratified by the number of cytogenetic high-risk abnormalities (n = 226). The presence of two cytogenetic high-risk abnormalities (compared to one) was of prognostic significance after adjusting for age, sex, and R-ISS stage (HR 2.01, 95% CI 1.27 - 3.19, p = 0.003, n = 205). Conclusions: Approximately one in five patients with newly diagnosed high-risk multiple myeloma presented with two high-risk abnormalities at the time of diagnosis. These patients experienced inferior overall survival suggesting a cumulative effect of multiple cytogenetic high-risk abnormalities. The relatively low number of observed gain(1q) was likely related to the fact that not all patients were evaluated for that abnormality. Therefore the presented hazard ratio represents a conservative effect estimate and may underestimate the true effect. Figure 1 Figure 1. Disclosures Dispenzieri: GSK: Membership on an entity's Board of Directors or advisory committees; Jannsen: Research Funding; Alnylam: Research Funding; Celgene: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; pfizer: Research Funding. Kapoor:Takeda: Research Funding; Celgene: Research Funding; Amgen: Research Funding. Kumar:Janssen: Consultancy, Research Funding; BMS: Consultancy; AbbVie: Research Funding; Millennium: Consultancy, Research Funding; Onyx: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Array BioPharma: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; Kesios: Consultancy; Glycomimetics: Consultancy.

Introduction: Abnormal metaphase cytogenetics are associated with inferior survival in newly diagnosed multiple myeloma (MM). These abnormalities are only detected in one third of cases due to the low proliferative rate of plasma cells. It is unknown if metaphase cytogenetics improve risk stratification when using contemporary prognostic models such as the revised international staging system (R-ISS), which incorporates interphase fluorescence in situ hybridization (FISH). Aims: The aims of this study were to 1) characterize the association between abnormalities on metaphase cytogenetics and overall survival (OS) in newly diagnosed MM treated with novel agents and 2) evaluate whether the addition of metaphase cytogenetics to R-ISS, age, and plasma cell labeling index (PCLI) improves model discrimination with respect to OS. Methods: We analyzed a retrospective cohort of 483 newly diagnosed MM patients treated with proteasome inhibitors (PI) and/or immunomodulators (IMID) who had metaphase cytogenetics performed prior to initiation of therapy. Abnormal metaphase cytogenetics were defined as MM specific abnormalities, while normal metaphase cytogenetics included constitutional cytogenetic variants, age-related Y chromosome loss, and normal metaphase karyotypes. Multivariable adjusted proportional hazards regression models were fit for the association between known prognostic factors and OS. Covariates associated with inferior OS on multivariable analysis included R-ISS stage, age ≥ 70, PCLI ≥ 2, and abnormal metaphase cytogenetics. We devised a risk scoring system weighted by their respective hazard ratios (R-ISS II +1, R-ISS III + 2, age ≥ 70 +2, PCLI ≥ 2 +1, metaphase cytogenetic abnormalities + 1). Low (LR), intermediate (IR), and high risk (HR) groups were established based on risk scores of 0-1, 2-3, and 4-5 in modeling without metaphase cytogenetics, and scores of 0-1, 2-3, and 4-6 in modeling incorporating metaphase cytogenetics, respectively. Survival estimates were calculated using the Kaplan-Meier method. Survival analysis was stratified by LR, IR, and HR groups in models 1) excluding metaphase cytogenetics 2) including metaphase cytogenetics and 3) including metaphase cytogenetics, with IR stratified by presence and absence of metaphase cytogenetic abnormalities. Survival estimates were compared between groups using the log-rank test. Harrell's C was used to compare the predictive power of risk modeling with and without metaphase cytogenetics. Results: Median age at diagnosis was 66 (31-95), 281 patients (58%) were men, median follow up was 5.5 years (0.04-14.4), and median OS was 6.4 years (95% CI 5.7-6.8). Ninety-seven patients (20%) were R-ISS stage I, 318 (66%) stage II, and 68 (14%) stage III. One-hundred and fourteen patients (24%) had high-risk abnormalities by FISH, and 115 (24%) had abnormal metaphase cytogenetics. Three-hundred and thirteen patients (65%) received an IMID, 119 (25%) a PI, 51 (10%) received IMID and PI, and 137 (28%) underwent upfront autologous hematopoietic stem cell transplantation (ASCT). On multivariable analysis, R-ISS (HR 1.59, 95% CI 1.29-1.97, p < 0.001), age ≥ 70 (HR 2.32, 95% CI 1.83-2.93, p < 0.001), PCLI ≥ 2, (HR 1.52, 95% CI 1.16-2.00, p=0.002) and abnormalities on metaphase cytogenetics (HR 1.35, 95% CI 1.05-1.75, p=0.019) were associated with inferior OS. IR and HR groups experienced significantly worse survival compared to LR groups in models excluding (Figure 1A) and including (Figure 1B) the effect of metaphase cytogenetics (p < 0.001 for all comparisons). However, the inclusion of metaphase cytogenetics did not improve discrimination. Likewise, subgroup analysis of IR patients by the presence or absence of metaphase cytogenetic abnormalities did not improve risk stratification (Figure 1C) (p < 0.001). The addition of metaphase cytogenetics to risk modeling with R-ISS stage, age ≥ 70, and PCLI ≥ 2 did not improve prognostic performance when evaluated by Harrell's C (c=0.636 without cytogenetics, c=0.642 with cytogenetics, absolute difference 0.005, 95% CI 0.002-0.012, p=0.142). Conclusions: Abnormalities on metaphase cytogenetics at diagnosis are associated with inferior OS in MM when accounting for the effects of R-ISS, age, and PCLI. However, the addition of metaphase cytogenetics to prognostic modeling incorporating these covariates did not significantly improve risk stratification. Disclosures Lacy: Celgene: Research Funding. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Alnylam: Research Funding; Celgene: Research Funding; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding. Kapoor:Celgene: Honoraria; Sanofi: Consultancy, Research Funding; Janssen: Research Funding; Cellectar: Consultancy; Takeda: Honoraria, Research Funding; Amgen: Research Funding; Glaxo Smith Kline: Research Funding. Leung:Prothena: Membership on an entity's Board of Directors or advisory committees; Takeda: Research Funding; Omeros: Research Funding; Aduro: Membership on an entity's Board of Directors or advisory committees. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

Introduction: Chronic myelomonocytic leukemia (CMML) is a clonal hematopoietic neoplasm characterized by sustained peripheral blood (PB) monocytosis and an inherent risk for leukemic transformation. Clonal origins of the disease can be detected in hematopoietic progenitor cells (CD34+/CD38-), while the complete spectrum of mutational evolution can be seen in circulating monocytes (CD14+). Cell sorting strategies have been employed to select cells in CMML, and while there are adequate monocyte numbers in the PB, there are very few circulating progenitor cells. In addition, attrition related to the selection process significantly depletes primary cells available for biological experiments and multiomics studies such as RNA-seq, ChIP-seq, ATAC-seq, and DIP-seq. While single-cell methods may be able to overcome this challenge, bulk sequencing methods remain a robust and cost-effective approach. We hypothesized that, secondary to the stem cell origin of this disease and significant myeloproliferation, PB mononuclear cells (MNC) would provide comparable results with regards to transcriptomic analysis, in comparison to cell selection procedures. Methods: Peripheral blood obtained from 15 molecularly annotated patients with WHO-defined CMML was ACK-lysed and subjected to a Ficoll procedure for collection of MNC. MNC were left unsorted (n=5) or further selected for CD34+/CD38- (n=5) and CD14+ (n=5) using a fully automated RoboSep-S (StemCell Technologies) protocol. All samples were then subjected to bulk whole transcriptome shotgun sequencing (using Illumina TruSeq and an Illumina HiSeq 4000). After data quality control, counts of detectable transcripts were log2-normalized and Pearson's product-moment correlation coefficients were calculated to evaluate the correlation between the two cell-sorting strategies and unsorted cells in terms of detectable transcripts. To visualize sample differences log2-normalized transcripts counts were centered and scaled per gene for a select number of genes relevant to myeloid biology as well as a number of housekeeping genes. Results: Fifteen patients with WHO-defined CMML, median age 69 years (55-73 years), 66% male, were included. Next generation sequencing for somatic mutations was performed on PB MNC obtained at CMML diagnosis (Figure 1, top heatmap). Considering the small sample size, mutations were evenly distributed among groups with the exception of ASXL1 (higher frequency in CD14+ and CD34+/CD38- cells), ZRSR2 (higher frequency in unsorted cells), and TET2 (lower frequency in CD14+ cells). The three groups were also well matched with regards to other CMML-related variables such as WHO and FAB morphological subtypes, cytogenetic abnormalities, and risk stratification by the Mayo Molecular Model. Transcriptomic analysis revealed a strong positive correlation between the median number of log2-normalized detectable transcripts in unsorted cells and CD34+/CD38- cells (ρ = 0.96, p < 0.001, top scatterplot). Likewise, there was a strong positive correlation between the median number of log2-normalized detectable transcripts in unsorted cells and CD14+ cells (ρ = 0.91, p < 0.001, bottom scatterplot). The latter correlation was marginally lower, which was explained by increased global gene expression in 3 of the 5 CD14+ samples (bottom heatmap). Increased gene expression in these 3 samples involved key myeloid genes and housekeeping genes known to have stable expression across human tissues alike. In comparison to PB MNC, both cell sorting strategies resulted in significant depletion of primary cells required for other experiments, and for procedures such as ChIP-seq, DIP-seq and ATAC-seq (CD34+/CD38- had greater depletion than CD14+). Additional experiments to assess this strategy for the above mentioned epigenetic studies are currently being planned. Conclusions: Accounting for sample differences, different cell sorting strategies (unsorted, CD34+/CD38- selection, and CD14+ selection) yielded similar results when performing bulk transcriptomic assessments on PB MNC from patients with CMML. For the purpose of gene expression profiling there was no clear advantage with CD34+/CD38- or CD14+ selection. These results support the use of unsorted cells for bulk transcriptomic analysis in CMML. Figure 1 Disclosures Patnaik: Stem Line Pharmaceuticals.: Membership on an entity's Board of Directors or advisory committees.

Background: Myelodysplastic syndrome (MDS)/myeloproliferative neoplasm (MPN) with ring sideroblasts and thrombocytosis (MDS/MPN-RS-T) was formally included as a unique WHO-defined entity in the 2016, iteration of the classification of hematological neoplasms (under MDS/MPN overlap syndromes). Patients with MDS/MPN-RS-T have features of MDS-RS-single lineage dysplasia (SLD), persistent thrombocytosis (platelet count ≥450x109/L), with proliferation of large atypical megakaryocytes. Anemia, including red blood cell transfusion dependency (RBC-TD) is a major problem. While extensive studies have documented erythroid response rates (ERR) to erythropoiesis stimulating agents (ESA) in MDS and MDS-RS-SLD, the data in MDS/MPN-RS-T is less clear. We carried out this study to asses ERR in ESA treated patients with MDS/MPN-RS-T. Methods: After approval by the IRB, patients with 2016, WHO-defined MDS/MPN-RS-T were included in the study. The bone marrow (BM) morphology, cytogenetics and BM RS% were retrospectively reviewed. All study patients underwent next generation sequencing for 29 myeloid-relevant genes, obtained on BM mononuclear cells, at diagnosis, or at first referral, by previously described methods (Patnaik et al., BCJ 2016). Treatment details, including the type of ESA used, dose administered, side effects and reason for discontinuation were retrospectively abstracted. Erythroid responses were assessed using the 2006, international working group (IWG) MDS and the 2015, IWG MDS/MPN response criteria. Results: Forty seven patients with MDS/MPN-RS-T were identified, of which 37 (79%) patients received ESA treatment at any time point during their disease course; median age 73 years (range, 52-93), 46% male.The hemoglobin at diagnosis (HB) and baseline erythropoietin (EPO) levels were 9.1 gm/dL (range, 6.6-12.1) and 39 IU/L (range, 8-500), respectively. Ten (29%) patients were RBC-TD at baseline. None of the 37, ESA-treated patients were on concomitant cyto-reductive therapy for thrombocytosis. Twenty (54%) patients were treated with erythropoietin-a, 13 (35%) with darbepoetin, and 4 (11%) with both sequentially. Median doses were 40,000 IU weekly (range, 20,000-80,000) for erythropoietin-a and 200 mcg every 2 weeks (range, 100-500), for darbepoetin. Median treatment duration was 14 months (range, 1-173) and causes for discontinuation included; ESA failure/loss of response in 20 (54%), sustained HB rise in 1 (3%) and other causes, including adverse events in 4 (11%) patients. With regards to safety, the following events were considered potentially ESA related; treatment emergent hypertension in 2 (5%), venous thromboembolism, ischemic stroke and splenic infarction in 1 (3%) patient each, respectively. All patients with thrombotic/ischemic events had been on low dose aspirin prophylaxis. Erythroid responses by the IWG MDS and MDS/MPN response criteria were assessable in 35 (95%) patients: with 16 (46%) meeting criteria for an erythroid response, by both assessment systems. The median duration of ER was 20 months (range, 2-172). In comparison to ESA non-responders, those that responded were more likely to have baseline EPO levels ≤44 IU/L (ROC analysis; median, 28 vs 112 IU/L; p=0.0080), while there was a trend for inferior responses associated with RBC-TD (p=0.0857). Age, gender, baseline white blood cell and platelet counts, type of ESA used, BM RS %, JAK2V617F, SF3B1, DNMT3A, TET2 and ASXL1 mutational status did not impact ESA response (Table 1). On a univariate survival analysis (OS), survival was not significantly different between ESA responders vs non-responder (median OS, 76 vs 45 months; p=0.2929). After ESA failure, 7 (19%) patients received hypomethylating agents (HMA), while 5 (14%) received lenalidomide. There were no erythroid responses to HMA, while 1 of 3 (33%) assessable lenalidomide treated patients achieved a morphological complete response. Conclusion: Erythropoiesis stimulating agents are effective first line therapies for the management of anemia in patients with MDS/MPN-RS-T, with 46% achieving an erythroid response (median duration of response of 20 months). Low baseline endogenous EPO level (<44 IU/L) was the best predictor of response, with a trend towards an inferior response in the presence of RBC-TD. In the context of clonal thrombocytosis, potentially related thrombotic/ischemic events were documented in 8% of patients. Disclosures Al-Kali: Astex Pharmaceuticals, Inc.: Research Funding. Patnaik:Stem Line Pharmaceuticals.: Membership on an entity's Board of Directors or advisory committees.

Introduction: While the molecular target of immunomodulators such as pomalidomide (POM) and lenalidomide (LEN) has been identified, the mechanisms underlying therapeutic resistance remain incompletely understood. The uniformly emerging resistance to therapy over time in the absence of identifiable cereblon pathway mutations in the majority of patients raises questions about alternative mechanisms including aberrant gene expression. Methods: We performed gene expression profiling using an Affymetrix GeneChip Human Genome U133 Plus 2.0 microarray on CD138+ bone marrow cells from patients with relapsed / refractory (RRMM) and newly diagnosed (NDMM) multiple myeloma prior to initiating treatment. Patients were treated on two phase II clinical trial protocols (MC0789: POM ± dexamethasone in RRMM; MC0884: LEN ± dexamethasone in NDMM) between 2007 and 2012. We categorized patients based on their IMWG response as non-responders (SD) and responders (VGPR+). We selected 15 responders and 15 non-responders from MC0789 (n = 30) and compared overall survival, gene expression patterns, and involved cellular pathways between the two groups. We selected 5 responders and 5 non-responders from MC0884 (n = 10) for targeted validation of differentially expressed candidate genes. After data quality control and normalization of gene expression values, differential gene expression was estimated using limma. Statistical significance was adjusted for multiple testing in the discovery set using a false discovery rate-based approach for genome-wide experiments (q-value). We used Gene Ontology and PANTHER pathway analysis for functional annotation of differentially expressed genes. Overall survival estimates were calculated using the Kaplan-Meier method. Computation and visualization were performed in R. Results: Median age at treatment initiation on MC0789 was 65 years (40 - 82), 65% of the patients were male. Pomalidomide resistance was associated with an increase in mortality (median overall survival 1.6 versus 6.4 years, p = 0.009, Kaplan-Meier plot). There were 1076 differentially regulated genes between responders and non-responders (521 up- and 555 down-regulated, q < 0.050 for all genes, volcano plot). Expression of CRBN was 1.5-fold down-regulated in non-responders (q = 0.005). Supervised hierarchical clustering of the top 500 differentially expressed genes demonstrated distinct patterns in pomalidomide-resistant disease (heatmap). Gene ontology analysis revealed protein synthesis as one of the most enriched biological processes (bar graph). Pathway analysis showed a 6-fold enrichment (FDR = 0.007) of the ubiquitin proteasome pathway in pomalidomide-resistant disease. Differentially expressed genes involved key protein degradation pathways, epigenetic modifiers, and transcription factors. Targeted validation in MC0884 revealed 13 common genes with at least 1.5-fold differential expression (5 up- and 8 down-regulated), 12 of which have previously been implicated in the regulation of apoptosis, tumor glucose metabolism, Rho and Wnt signaling, miRNA-driven resistance to chemotherapy, and ubiquitin-dependent protein degradation (Table and Sankey diagram). The most up-regulated gene in non-responders was MYRIP, a gene coding for a vesicle trafficking protein associated with platinum resistance and suppression of pro-apoptotic BCL-2 family members in solid malignancies. The most down-regulated gene was FRZB, a gene coding for a negative regulator of Wnt signaling, previously implicated in the progression of monoclonal gammopathy of undetermined significance to multiple myeloma. Conclusions: Overall survival of patients with pomalidomide-resistant RRMM remains poor. Pomalidomide resistance was associated with differential gene expression in several potentially targetable cellular pathways beyond the known drug target cereblon. Targeted validation of candidate genes revealed common cellular pathways in immunomodulator-resistant disease. Elucidating the exact molecular mechanisms underlying immunomodulator resistance is of considerable interest for biomarker development and the identification of novel therapeutic targets and warrants further exploration. Figure Disclosures Lacy: Celgene: Research Funding. Dispenzieri:Celgene: Research Funding; Alnylam: Research Funding; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Akcea: Consultancy; Takeda: Research Funding. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.