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Abstract Background Cranial radiotherapy (RT) is associated with risk for cognitive and adaptive dysfunction. Proton RT (PRT) is a technique hypothesized to spare cognition by reducing exposure to nontarget brain tissue. However, little is known regarding functional outcomes in survivors of pediatric brain tumor (BT) treated with PRT. The present study examined the relationship between cognitive and adaptive outcomes in pediatric BT survivors post‐PRT. Methods Survivors treated with either focal (n = 33) or craniospinal irradiation (CSI; n = 37) PRT completed neurocognitive evaluations approximately 5 years post‐treatment. Results of intelligence testing and ratings of adaptive functioning are reported. Mediation models examined the relationship among radiation field, cognition, and adaptive functioning. Results The PRT CSI group demonstrated worse cognitive outcomes than the PRT Focal group across each cognitive index (Cohen's d = 0.56–0.70). Parent ratings of adaptive functioning were also worse in the PRT CSI group than the PRT Focal group (Global Adaptive Composite, d = 0.53; conceptual skills, d = 0.67). Cognitive performance fully mediated the relationship between radiation field and adaptive outcomes, while controlling for group differences in tumor histology and RT dose. Conclusions Focal PRT survivors demonstrated generally positive outcomes with weaknesses in processing speed and aspects of adaptive functioning. CSI exposure was associated with more consistently poor cognitive and adaptive outcomes. The increased risk for adaptive dysfunction in the PRT CSI group appeared due to the effects of CSI on cognition. Efforts to reduce the volume of tissue exposure to RT remain important.

Abstract FMS-like tyrosine kinase 3 internal tandem duplications (FLT3-ITD) in acute myeloid leukemia (AML) are associated with early relapse after standard chemotherapy and poor survival. Quizartinib (AC220) is an oral FLT3 receptor tyrosine kinase inhibitor that has shown the highest level of single agent activity seen with a FLT3 targeted agent in FLT3+ relapsed AML to date. This Phase 1 dose escalation study is the first study to report data with quizartinib in combination with standard induction and consolidation chemotherapy in patients aged 18-60 years with newly diagnosed AML, regardless of FLT3-ITD status. The dose escalation was conducted using a modified 3+3 design, where 6 pts were enrolled at each dose level. The pts were given cytarabine 200 mg/m2 x 7 days and daunorubicin 60 mg/m2 x 3 days (7+3) for induction and high dose cytarabine 3 g/m2(HiDAC) q12hours on days 1, 3, and 5 for consolidation. Quizartinib was administered daily for either 7 or 14 days, starting at Day 4 of induction and/or consolidation chemotherapy. Patients were allowed to proceed directly to a stem cell transplant after achieving a response or receive further quizartinib as maintenance therapy after consolidation if they were not transplant eligible. Three dose levels were tested; dose level 1 (DL1) at 60 mg for 7 days, dose level 2 (DL2) 60 mg for 14 days, and dose level -1 (DL-1), 40 mg for 14 days. Through May 31, 2013 18 pts were enrolled in the study, and the safety information at all 3 dose levels are presented. The median age of pts was 43 years (range 22 to 60). Of the 18 patients, 16 had the FLT-ITD mutation. At DL1, one of the 6 patients had a DLT (grade 3 hyponatremia). At DL2, two of the 6 patients had a DLT (grade 3 QTc prolongation and grade 4 pericarditis) which exceeded the pre-specified criteria so DL-1 was then explored. At DL-1, one of the 6 patients had a DLT (grade 3 constrictive pericarditis). The most common (20%) treatment-related adverse events (AEs) were nausea (42%), diarrhea (32%), anemia (26%), febrile neutropenia (26%), neutropenia (21%), fatigue (21%), pyrexia (21%) and thrombocytopenia (21%). The most common (10%) Grade 3 or 4 treatment-related AEs were febrile neutropenia (26%), thrombocytopenia (21%) anemia (21%)), neutropenia (21%), leucopenia (16%), and nausea (11%). The data from this Phase 1 study demonstrates for the first time that quizartinib can be safely administered with induction and/or consolidation chemotherapy in newly diagnosed younger patients with AML. The MTD was identified as 40 mg for 14 days or 60 mg for 7 days. The efficacy results from this Phase 1 study will be available at the time of presentation. Based on these findings, multiple Phase 3 studies in newly diagnosed AML patients are planned. Disclosures: Altman: Novartis: Consultancy; Araid: Consultancy; BMS: Consultancy; Teva: Consultancy; Astellas: Consultancy. Foran:Astellas: Research Funding. Trone:Ambit: Employment. Gammon:Ambit: Employment. Cortes:Ambit: Research Funding.

Background: Although diffuse large B cell lymphoma (DLBCL) can be cured using immuno-chemotherapy, 40% of patients experience relapse or refractory disease. Large-scale profiling studies have mainly focused on DLBCL at diagnosis, resolving different outcome groups based on gene expression (e.g. cell-of-origin (COO) or molecular high grade), MYC/BCL2 translocations (double-hit lymphoma) or gene mutations and copy number aberrations (Schmitz et al, NEJM 2018; Chapuy et al, NatureMedicine 2018). In comparison, longitudinal studies have been hindered by the limited availability of sequential biopsy samples. To date, the relapse-specific gene mutations identified are limited and inconsistent across studies. In our study, we have focussed attention on the changes in gene expression profile (GEP) accompanying DLBCL relapse. Methods: We retrospectively collected archival paired diagnostic/relapse formalin fixed paraffin embedded tumor biopsies from 38 de novo DLBCL patients collected from multiple UK sites treated with rituximab-based immuno-chemotherapy, where partial or complete remission was reported following treatment. COO classification was performed by the Lymph2Cx assay on NanoString to distinguish activated B-cell-like (ABC) and germinal center B-cell-like (GCB) subtypes. The Ion AmpliSeq™ Transcriptome Human Gene Expression Kit was used to measure the expression levels of > 20,000 genes on the paired samples. Results: COO remained stable from diagnosis to relapse in 17 ABC-ABC pairs, 11 GCB-GCB pairs and 4 unclassified (UNC)-UNC pairs. Frank COO switching was observed in 6 cases (1 ABC-GCB, 2 ABC-UNC, 2 GCB-UNC, 1 UNC-ABC). Pairs with stable COO were taken forward for further analysis. Gene expression analysis using the limma R package identified 163 and 136 genes as differentially expressed (DE) (p <= 0.01 and absolute log2FC > 1) between the diagnostic and relapse biopsies in ABC and GCB tumors respectively, with only a one gene overlap. Gene Set Enrichment Analysis further suggested that ABC and GCB relapses are mediated via different mechanisms, with tumor growth and proliferation signatures enriched in ABC relapses, whilst adaptive immunity-related signatures accompanied GCB relapses. Next, we aimed to utilise our relapse-specific genes to identify outcome predictors at diagnosis using publicly available GEP datasets. In order to increase our discovery power and accuracy, a larger set of DE genes from the paired differential analysis (796 genes in ABC pairs and 387 from GCB pairs) were selected (p <= 0.05) and subsequently used in a training cohort (GEP from Reddy et al, Cell 2017). The Prediction Analysis for Microarrays R (PAMR) algorithm identified a 30-gene signature within DE genes from ABC pairs (Fig1.A), capable of separating the 249 ABC cases into 136 low and 113 high-risk cases with significantly inferior overall survival (Hazard Ratio (HR)=1.89, log-rank p=0.0017, measure of goodness-of-fit C-index=0.71; Fig1.B). No equivalent signature was found in the GCB cases using this approach. The prognostic significance of this 30-gene discriminator was successfully validated using a linear predictor in two independent GEP datasets: 1) a population-based cohort (Lenz et al, NEJM 2008) with 93 R-CHOP-treated ABC cases identifying 47 low and 46 high-risk cases (HR=1.92, p=0.046, C-index=0.77; Fig1.C) and 2) a clinical trial dataset (REMoDL-B, Davies et al, Lancet Oncol 2019) with 255 ABC cases identifying 110 low and 145 high-risk ABC cases (HR=1.95, p=0.0051, C-index=0.70; Fig1.D). Conclusions: Here we describe a 30-gene discriminator in ABC-DLBCL, derived from genes differentially expressed between diagnosis and relapse, that allowed the definition of clinically distinct high and low risk subgroups in ABC-DLBCLs at diagnosis. The clinical translation of such a tool may be useful to guide therapy for this unfavourable subgroup of ABC-DLBCLs. Validation of this signature is currently underway in additional datasets and further study is required to understand the contribution of these genes in DLBCL pathology. Disclosures Korfi: Roche: Consultancy. Burton:Celgene: Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other: Travel; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bristol-Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees. Rule:TG Therapeutics: Consultancy, Honoraria; Napp: Consultancy; Kite: Consultancy; Pharmacyclics: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Sunesis: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Roche: Consultancy, Honoraria, Research Funding; Astra-Zeneca: Consultancy, Honoraria; Celgene: Consultancy, Honoraria. Crosbie:Janssen: Honoraria. Scott:Celgene: Consultancy; Janssen: Consultancy, Research Funding; NanoString: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution], Research Funding; Roche/Genentech: Research Funding. Rimsza:NanoSting: Patents & Royalties: Named inventor on a patent licensed to NanoSting [Institution]. Davies:Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Honoraria, Research Funding; Bayer: Research Funding; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Honoraria, Research Funding; Karyopharma: Membership on an entity's Board of Directors or advisory committees, Research Funding; GSK: Research Funding; Acerta Pharma: Honoraria, Research Funding; ADCT Therapeutics: Honoraria, Research Funding; BioInvent: Research Funding; Kite Pharma: Membership on an entity's Board of Directors or advisory committees; MorphoSys AG: Honoraria, Membership on an entity's Board of Directors or advisory committees. Gribben:Abbvie: Consultancy, Honoraria, Research Funding; Acerta/Astra Zeneca: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding. Okosun:Gilead Sciences: Honoraria, Research Funding. Johnson:Epizyme: Honoraria, Research Funding; Novartis: Honoraria; Kite: Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Honoraria; Boehringer Ingelheim: Honoraria; Takeda: Honoraria; Genmab: Honoraria; Celgene: Honoraria; Incyte: Honoraria. Fitzgibbon:Epizyme: Membership on an entity's Board of Directors or advisory committees, Research Funding; Gilead: Speakers Bureau.

Introduction: Several recent studies have shown a gender disparity in professional doctoral introductions at major medical conferences, with female speakers being less likely to be introduced with a professional title. We sought to examine whether a similar disparity existed at the American Society of Hematology (ASH) Annual Meeting. Methods: In this retrospective observational study, 8 investigators reviewed available presentations from video archives of the 2018 ASH Annual Meeting. Presentations were excluded if gender could not be identified and/or speaker did not have a doctoral degree. We collected data on speaker gender, speaker academic/non-academic rank, speaker geographic location, speaker training status, speaker session type and introducer gender were all collected. A "professional address" was defined as either "Dr. [First and Last Name]" or "Dr. [Last Name]." Descriptive statistics and regression modelling were used to analyze the data. Results:Of the videos reviewed, 645 presentations were eligible for analysis; 380 (59%) speakers were men and 264 (41%) were women. A comparison of male and female speaker cohorts is seen in Table 1. Forty-eight percent of both men and women held a Medical Doctor degree (MD), and the rest were MD/PhD or PhD graduates. Substantially more men (28%) were full professors compared to women (13%). Almost half (47%) of session types for both men and women speakers were designated as "basic science." In an adjusted analysis, more women (N=174, 66%) compared to men (N=225, 59%) received a professional address (P&lt;.01). 43% of women were introduced by a female introducer and 42% of men were introduced by a female introducer (P=.79). In addition, 48 of the introducers (19%) for women and 68 of the introducers (18%) for men had a PhD or MD/PhD. In a logistic regression model adjusting for session type, academic rank, degree, geographic location, trainee status, and gender of introducer, there were no significant gender-based differences in professional introduction [Table 1; Odds Ratio (OR) 0.71, P=.06]. In addition, speakers with MD introducers were more likely to have a professional introduction compared to PhD introducers (OR 2.15, P=.03) regardless of sex. Conclusions: Our study demonstrates that women were at least as likely as men to receive a professional address at the 2018 ASH Annual Meeting. These results differ from previous studies of other professional medical conferences. These findings may reflect the strong presence of PhD graduates as both speakers and introducers. Both forms of bias (gender and degree-based) merit further study and interventions including speaker training to ensure combatting unconscious bias. Disclosures Velazquez: Midatech: Other: Husband owns stock in this company; Portola Pharmaceuticals: Other: Husband owns stock in this company; Corbus Pharmaceuticals: Other: Husband owns stock in this company; Johnson & Johnson: Other: Husband is employed by this company.

Background: The 2018 iwCLL guidelines recommend close observation of early stage CLL pts who do not meet indications for therapy ("watch and wait" strategy). Prior attempts at early therapeutic intervention in unselected early-stage CLL pts using alkylating agents such as chlorambucil and chemoimmunotherapy failed to show a significant benefit; and these therapies were associated with substantial toxicities. The introduction of Bruton tyrosine kinase (BTK) inhibitors has revolutionized the treatment landscape of CLL. The German CLL Study group recently presented results of the CLL12 study which demonstrated a significant improvement in event-free survival (EFS) among untreated early stage high risk CLL pts who received ibrutinib compared to placebo (median EFS not reached vs. 47.8 months, respectively; Langerbeins, EHA, 2019). Acalabrutinib is a more selective second-generation BTK inhibitor that has fewer adverse events in pts with CLL, and has shown equally impressive clinical activity for CLL pts. We are conducting an investigator initiated randomized phase 2 study to compare acalabrutinib with or without obinutuzumab (a glycoengineered anti-CD20 monoclonal antibody approved in the treatment of CLL) among high risk early stage CLL pts. Study Design: All pts with newly diagnosed (<2 years from registration) previously untreated early stage CLL who do not meet the 2018 iwCLL guidelines for initiation of therapy are eligible for enrollment in this study. Pts undergo risk stratification according to the CLL-International prognostic index (CLL-IPI) which consists of the following 5 variables: age >65 years (1 point), Rai stage I-IV (1 point), del17p and/or TP53 mutation (4 points), unmutated immunoglobulin heavy chain (IGHV) genes (2 points), and serum β2-microglobulin >3.5 g/dL (2 points). Pts with high (4-6) and very high (7-10) risk CLL-IPI are randomly (1:1) assigned to acalabrutinib 100 mg orally twice daily (Arm A) or acalabrutinib with obinutuzumab at a standard approved schedule (Arm B). Treatment with acalabrutinib is continued for a minimum of 2 years unless the patient has unacceptable side effects or withdraws consent. Pts with low (0-1) and intermediate (2-3) risk CLL-IPI score are assigned to an observation arm with follow-up once every 6 months for 2 years, and then according to routine clinical practice (Arm C). Endpoints: The primary endpoint of the intervention arms (Arms A and B) is the achievement of minimal residual disease (MRD)-negative complete remission in the bone marrow after 2 years of therapy. MRD is assessed using an 8-color flow cytometry with a detection limit of 0.01%. The primary endpoint of the observation arm (Arm C) is time to first therapy. Secondary endpoints for all arms are: progression-free survival, overall survival, and safety. Statistical design: A randomized trial comparing the experimental arm (acalabrutinib plus obinutuzumab) against the control arm (acalabrutinib alone) will be conducted as described by Rubinstein. A sample size of 36 pts per arm provides 80% power to detect an improvement in MRD-negative complete response rate from 10% to 30%, using a one-sided test at a significance level of 0.10 (EAST 6.4). We anticipate accruing an additional 8 high/very high risk pts (4 in each arm) to account for ineligibility, cancellation, or major treatment violation. The total enrollment for Arms A and B will be 80 pts. We will enroll 40 pts to Arm C; for a total enrollment of 120 pts. Key correlatives: Comprehensive profiling to assess the innate and adaptive immune system in paired peripheral blood and bone marrow will be conducted in all pts registered to Arms A and B at baseline, 12 and 24 months after enrollment. In addition, bone marrow hematopoietic function will be assessed in all pts at these time points. We will employ a CLL focused custom 61-gene panel to estimate tumor mutational burden as well as mutational profiles for each patient at baseline, 12, and 24 month time points, as well at the time of disease progression. Preliminary results: The trial is registered at clinicaltrials.gov NCT03516617. The trial opened to accrual at all three Mayo Clinic sites (Rochester, MN; Jacksonville, FL; and Scottsdale, AZ) in September 2018. Twenty-eight pts have been registered; the baseline characteristics are shown in Table 1. The trial is expected to complete enrollment in September 2020; and the primary analysis will be available in September 2022. Disclosures Parikh: Janssen: Research Funding; AstraZeneca: Honoraria, Research Funding; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; AbbVie: Honoraria, Research Funding; Acerta Pharma: Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria. Ding:DTRM Biopharma: Research Funding; Merck: Research Funding. Ailawadhi:Pharmacyclics: Research Funding; Cellectar: Research Funding; Takeda: Consultancy; Amgen: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Celgene: Consultancy. Kenderian:Novartis: Patents & Royalties, Research Funding; Tolero: Research Funding; Humanigen: Other: Scientific advisory board , Patents & Royalties, Research Funding; Lentigen: Research Funding; Morphosys: Research Funding; Kite/Gilead: Research Funding. Chanan-Khan:Mayo Clinic: Employment; Ascentage: Research Funding; Millennium: Research Funding; Jansen: Research Funding; AbbVie: Research Funding; Xencor: Research Funding; Pharmacyclics: Research Funding; Merck: Research Funding. Kay:Infinity Pharmaceuticals: Other: DSMB; Celgene: Other: Data Safety Monitoring Board; Agios: Other: DSMB; MorphoSys: Other: Data Safety Monitoring Board. OffLabel Disclosure: Drug: Acalabrutinib Purpose: treatment of CLL

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.

Introduction: Recent advancements in the treatment of multiple myeloma (MM) have centered on engaging the immune system to target multiple myeloma cells. Although these therapies are being combined with immunomodulatory imide drugs (IMiDs) and corticosteroids, the individual contributions of these drugs on the immune system of MM patients has not been examined in the upfront setting. In this study, we examined the peripheral blood immunophenotypes of newly diagnosed multiple myeloma (NDMM) patients receiving the IMiD lenalidomide with or without the corticosteroid dexamethasone. Methods: To characterize immunophenotypes, we utilized flow cytometry to profile white blood cell populations from 35 patients enrolled in a clinical trial testing the efficacy of lenalidomide with and without dexamethasone in NDMM (NCT00772915). In this trial, all patients were initiated on single-agent lenalidomide. Dexamethasone was initiated in patients that did not meet desirable responses or for disease progression. At each cycle, peripheral blood was stained with a 17-marker antibody panel against several immune lineages and functional surface markers. We grouped patients into two groups: 1) lenalidomide alone or 2) lenalidomide with dexamethasone according to their treatment regimen at each cycle timepoint. Results: First we confirmed anti-myeloma cell activity for both groups by measuring a steady decline in circulating plasma cells in both groups. Examining peripheral blood immunophenotypes showed an expected decrease in T cells and a smaller decrease in B cells in both groups of patients. Closer inspection of B cell populations revealed a switch towards a more immature B cell phenotype in both treatment groups. This was measured as a switch from CD19-CD20+ cells to CD19+CD20- B cells. Inspection of T cell subsets revealed that patients receiving single-agent lenalidomide had a sustained decrease in the levels of CD4+ T cells and increase in the levels of CD8+ T cells. This was seen in both naïve and regulatory T cells evidenced by a decrease in the CD4/CD8 ratio among CD28+ T cells as well as CD25+ T cells. Importantly, this alteration did not lead to sustained alterations in the overall level of CD25+ or CD28+ T cells, and the addition of dexamethasone reverses this trend. In addition to the effects seen on T and B cell numbers, we detected expansions of NK cell populations in patients receiving lenalidomide alone. This expansion is detected as an overall increase in CD56+ mononuclear cells with the majority of cells being CD56+CD3- cells. Conclusions: Our data show that lenalidomide and dexamethasone therapy have shared but distinct effects on peripheral blood immunophenotypes in NDMM. Both drugs alter B cells numbers and populations leading to an expansion of CD19+CD20- B cells. However, lenalidomide alone decreases the CD4/CD8 T cell ratio; and, lenalidomide more strongly expands NK cell populations. The addition of dexamethasone reverses this trend and leads to a restoration of the CD4/CD8 ratio. This suggests that lenalidomide without dexamethasone might be counterproductive in immunotherapies intended to recruit CD4+ T cells. Conversely, lenalidomide alone could increase the efficacy of immunotherapies dependent on NK cell recruitment such as antibody-dependent cellular cytotoxicity (ADCC). This information may benefit future investigations of immune responses in MM patients and improve the adoption of immunotherapies to MM patients. Figure Disclosures Kumar: Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

Introduction: Whereas morphological assessment and cytogenetics have been the cornerstone for the diagnosis of myelodysplastic syndrome (MDS), flow cytometry and mutational analyses are novel, evolving techniques. These diagnostic procedures play a role in identifying pre-MDS cases including idiopathic cytopenia of undetermined significance (ICUS) and clonal cytopenia of undetermined significance (CCUS). Aim: To assess flow cytometric findings in ICUS and CCUS and their correlation with progression to MDS or myeloid neoplasm (MN), concurrent genetic aberrations, and underlying pathological evolution. Methods: Patients (Pts) who had undergone evaluation to rule out MDS and had retrospectively undergone flow cytometry, cytogenetic, mutational and morphological assessment were included. Flow cytometry results were classified as normal (no abnormality or 1 equivocal result), abnormal (2 abnormalities or at least 1 abnormality and 1 equivocal result), or atypical (1 abnormality or 2-3 equivocal results). Next generation sequencing included mutation analysis of: ASXL1, BCOR, BRAF, CALR, CBL, CEBPA, CSF3R, DNMT3A, ETV6, EZH2, FLT3, GATA1, GATA2, IDH1, IDH2, JAK2, KIT, KRAS, MPL, MYD88, NOTCH1, NPM1, NRAS, PHF6, PTPN11, RUNX1, SETBP1, SF3B1, TERT, TET2, TP53, U2AF1, WT1, ZRSR2. Results: A) Characteristics: 229 pts were assessed (median age 60 and 69% were males). Based on pathologist interpretation, 87 (38%) pts met diagnostic criteria of MDS, 106 (46%) pts had normal/reactive bone marrow (BM), and 36 (16%) pts had BM findings suspicious for MDS. Median time to follow-up was 24 months for MDS pts, and 32 months for pts with cytopenias. B) Morphology: Pts who had a BM biopsy that was suspicious for MDS by pathologist interpretation were more likely to develop MDS compared to pts with normal/reactive pathology report with an incidence rate (IR) of 16% versus 0.9% (p= .0005). Pts who were suspicious for MDS based on the BM biopsy were more likely to have underlying mutations compared to pts with normal/reactive BM (IR 83% versus 69%, p= .2). C) Flow cytometry: In the non-MDS cohort, 96 (67%) pts had normal flow results, 29 (20%) pts had atypical flow, and 17 (12%) pts had abnormal flow results compared to 16 (18%) pts, 18 (21%) pts, and 53 (61%) pts in the MDS cohort, respectively. Of the pts who had normal flow result (n=112), 16 were MDS, 16 were suspicious for MDS/MN, and 80 were normal/reactive. Pts who had biopsy interpretation suspicious for MDS/MN were more likely to have abnormal flow cytometry compared to normal/reactive BM biopsy (IR 55% versus 24%, p=.0003). IR of MDS was 4% in normal flow, 3% in atypical flow, and 12% in abnormal flow (p= .5). Likewise, IR of MN was 4% in normal flow, 20% in atypical flow, and 30% in abnormal flow (p= .1). D) Genetics (cytogenetics and mutation profiling): Cytogenetics was normal in 123 (86%) pts and abnormal in 19 (13%) pts. Pts who had abnormal cytogenetics were more likely to develop MN (IR 57% versus 5%, p= .002). Out of the 50 non-MDS pts tested for NGS, 38 (76%) were positive for mutations. 15 (39%) pts had 1 mutation, 8 (21%) pts had 2, 3 (8%) pts had 3, 6 (16%) pts had 4, 2 (5%) pts had 5, 1 (3%) pt had 7, and 1 (3%) pt had 8 mutations (61% had >1 mutation). Pts with positive mutations were more likely to develop MDS during follow-up compared to pts who did not have mutations (IR 16% versus 0%, p=.06). Additionally, flow cytometric aberrations significantly correlate with the number of mutations (p= .03). MN correlated significantly with BCOR mutation and RUNX1 (IR 60% (p= .008) and 50% (p=.02), respectively. E) Interaction between variables: In pts with positive mutations, flow cytometry did not correlate with progression to MDS with an IR of 17% of MDS in normal flow, 11% in atypical flow, and 17% in abnormal flow, (p= .9). There was no impact on overall survival neither in pts with abnormal flow results vs normal nor in pts with positive mutations vs wild type. Conclusion: Conventional diagnostic techniques remain the cornerstone of MDS diagnosis with flow cytometry and NGS arising as novel techniques that correlate significantly with progression of pre-MDS pts to MDS. Flow had an impact on pathology final interpretation but did not add value in pt with a positive mutation analysis. Larger studies are needed to confirm our findings. Disclosures Patnaik: Stem Line Pharmaceuticals.: Membership on an entity's Board of Directors or advisory committees. Al-Kali:Astex Pharmaceuticals, Inc.: Research Funding.

Introduction: High-risk multiple myeloma can be defined by the presence of specific cytogenetic abnormalities (structural) or by characteristic changes in bone marrow and peripheral blood biomarkers (functional). While both entities are characterized by therapeutic resistance, frequent disease relapses, and adverse survival outcomes, the underlying molecular mechanisms remain incompletely understood. Methods: We performed gene expression profiling (GEP) using an Affymetrix GeneChip Human Genome U133 Plus 2.0 microarray on CD138+ bone marrow cells from 137 patients diagnosed with multiple myeloma between 2004 and 2012. All patients underwent Fluorescence In-situ Hybridization (FISH) evaluation, plasma cell labeling, International Staging System (ISS) risk stratification, and GEP prior to initiating treatment with novel agents. The presence of del(17p), t(4;14), t(14;16), and t(14;20) on FISH, a plasma cell labeling index (PCLI) > 2%, and ISS stage III were considered high-risk abnormalities: FISH-HR (n = 15, structural high-risk, at least one high-risk FISH lesion), PCLI-HR (n = 20; functional high-risk, PCLI > 2%), and ISS-HR (n = 12; functional high-risk, ISS stage III). For each HR group we sampled standard risk (SR) controls in a 4:1 ratio. After data quality control and normalization, differential gene expression was estimated using limma. Statistical significance was adjusted for multiple comparisons using a false discovery rate-based approach for genome-wide experiments (q-value). We employed PANTHER pathway analysis for the differentially expressed genes in each HR group. We implemented a simple gene expression score (GES) by calculating the sum of quartiles of the normalized gene expression values for genes differentially expressed in more than one HR group (GES = ΣUP(quartile - 1) + ΣDN(4 - quartile)) and externally validated its prognostic significance (UAMS TT2 / TT3, GSE24080). Survival outcomes were analyzed using the methods described by Kaplan, Meier, and Cox. Computation and visualization were performed in R. Results: Median age at diagnosis was 63 years (32 - 87), 53% of the patients were male. High-risk disease was associated with inferior overall survival, regardless of the used definition (left Kaplan-Meier plots): FISH-HR (HR 4.3, 95% CI 1.9 - 9.8, p < 0.001), PCLI-HR (HR 2.7, 95% CI 1.4 - 5.3, p = 0.004), and ISS-HR (HR 2.8, 95% CI 1.2 - 6.5, p = 0.015). There were 59 (FISH-HR), 424 (ISS-HR), and 507 (PCLI-HR) differentially expressed genes (q < 0.050 for all genes, volcano plots). PCLI-HR and FISH-HR demonstrated a predominance of transcriptional up-regulation while ISS-HR had a balanced gene expression profile with a similar number of genes being up- and down-regulated. The involved cellular pathways were different across the HR groups except for anti-apoptotic signaling (bar graphs). All HR groups had distinct gene expression profiles with no complete overlap between all HR groups. There were 71 genes with overlap between two HR groups (69 up-regulated, 2 down-regulated, Venn diagrams). The median GES was 97 (18 - 206, higher numbers indicating higher expression of up-regulated and lower numbers of down-regulated high-risk genes) in 559 patients treated on UAMS TT2 / TT3 (GSE24080). Tertiles of the GES were associated with event-free survival (HR 1.4, 95% CI 1.2 - 1.6, p < 0.001) and remained independently prognostic after adjusting for age, sex, and ISS stage (HR 1.3, 95% CI 1.1 - 1.5, p < 0.001). Conclusions: High-risk multiple myeloma remains associated with inferior overall survival, regardless of the used definition (structural or functional). The subtypes of high-risk disease have distinct gene expression profiles and involve different cellular pathways, providing important clues to the underlying biology. A 71 gene signature derived from the different high-risk subtypes was of prognostic significance in a clinical trial population after adjusting for known prognostic factors. Figure Disclosures Lacy: Celgene: Research Funding. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Stewart:Takeda: Consultancy; Seattle Genetics: Consultancy; Roche: Consultancy; Ono: Consultancy; Celgene: Consultancy, Research Funding; Ionis: Consultancy; Janssen: Consultancy, Research Funding; Oncopeptides: Consultancy; Amgen: Consultancy, Research Funding; Bristol Myers-Squibb: Consultancy. Bergsagel:Celgene: Consultancy; Ionis Pharmaceuticals: Consultancy; Janssen Pharmaceuticals: Consultancy. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

Background: Voxelotor (GBT440) is a small molecule allosteric effector with high specificity for hemoglobin (Hb) that inhibits Hb S polymerization by increasing hemoglobin oxygen affinity. Developed as an oral, once-daily medication, it is undergoing phase 3 randomized clinical trials in sickle cell disease patients. Therapeutic monitoring of Hb quantitative fractions is routine in sickle cell disease patients to assess medication and transfusion effects and future treatment requirements. In the clinical laboratory, some therapies can alter the Hb fraction percentages or characteristic protein migration/elution patterns and can mimic complex hemoglobinopathy disorders causing misinterpretation or unnecessary additional testing. We present the effects of voxelotor on hemoglobin identification/monitoring testing in multiple testing platforms. Methods: A whole blood anticoagulated sample from a male patient who was undergoing treatment for sickle cell disease was received for routine hemoglobin testing. Five additional samples with similar features were also received from three male patients (age range of all patients was 18 to 22 years) with sickle cell disease. Hemoglobin protein analysis was performed using standard methods including cation-exchange high performance liquid chromatography (HPLC), capillary electrophoresis (CE), isoelectric focusing (IEF), intact globin chain mass spectrometry (MS), sickle solubility and hemoglobin stability studies. DNA sequencing of the alpha (HBA1/HBA2) and beta globin (HBB) genes was performed on one sample. Results: CE (initial and 50:50 mix, figures 1A and 1B, respectively) revealed a Hb S peak with a shoulder and additional small peaks at position 203 (D zone) and 234 (cusp of zones E/A2). In some cases the 234 peak interfered with instrument designation of the A2 peak (50:50 mix with normal) and shifted the Hb S peak into the E zone which risks variant misidentification (figure 1C). Our laboratory overcame this limitation by substituting the normal sample with beta thalassemia trait to enhance the Hb A2 peak after mixing. HPLC tracings (figure 1D) showed a duplex peak pattern in the D and S windows with separate peak quantification percentages (index case showed elution at 4.18 and 4.37 minutes with 14.9% and 66.4%, respectively). The dual peaks detected by HPLC partially mimicked compound Hb S/D-Punjab. IEF (figure 1E) showed additional bands at -4.7, and -11.5 (Schneider-Barwick ratios). The additional peaks identified by CE and IEF mimicked an alpha chain hemoglobin variant; however, the expected hybrid patterns were atypical prompting further investigation. Sickle solubility was positive, heat stability studies were negative and mass spectrometry did not definitively detect abnormal peaks other than βS. DNA sequencing of the alpha and beta globin genes did not reveal abnormalities other than homozygous Hb S. Similar hemoglobin patterns were identified in all samples tested. Conclusion: Voxelotor treatment in sickle cell patients results in a distinctive pattern alteration in hemoglobin testing. Methods may not give accurate variant percentage estimation and the treatment may result in shifts in variant mobility causing erroneous laboratory results. Novel therapies are increasing in the treatment of hemoglobin disorders and medication effect should be a consideration when atypical patterns are encountered in the laboratory. Knowledge of these artifacts by clinicians and laboratorians is paramount to avoid erroneous diagnosis, unnecessary additional testing and inaccurate Hb variant quantitation for monitoring purposes. Notification of current treatment regimens to testing facilities is highly recommended in these patients. Figure 1 Disclosures No relevant conflicts of interest to declare.