Slager, Susan L.

Introduction: Richter's syndrome (RS) represents transformation of chronic lymphocytic leukemia (CLL) into a highly aggressive lymphoma with dismal prognosis. Transcriptomic alterations have been described in CLL but most studies focused on peripheral blood samples with minimal data on RS-involved tissue. Moreover, transcriptomic features of RS have not been well defined in the era of CLL novel therapies. In this study we investigated transcriptomic profiles of CLL/RS-involved nodal tissue using samples from a clinical trial cohort of refractory CLL and RS patients treated with Pembrolizumab (NCT02332980). Methods: Nodal samples from 9 RS and 4 CLL patients in MC1485 trial cohort were reviewed and classified as previously published (Ding et al, Blood 2017). All samples were collected prior to Pembrolizumab treatment. Targeted gene expression profiling of 789 immune-related genes were performed on FFPE nodal samples using Nanostring nCounter® Analysis System (NanoString Technologies, Seattle, WA). Differential expression analysis was performed using NanoStringDiff. Genes with 2 fold-change in expression with a false-discovery rate less than 5% were considered differentially expressed. Results: The details for the therapy history of this cohort were illustrated in Figure 1a. All patients exposed to prior ibrutinib before the tissue biopsy had developed clinical progression while receiving ibrutinib. Unsupervised hierarchical clustering using the 300 most variable genes in expression revealed two clusters: C1 and C2 (Figure 1b). C1 included 4 RS and 3 CLL treated with prior chemotherapy without prior ibrutinib, and 1 RS treated with prior ibrutinib. C2 included 1 CLL and 3 RS received prior ibrutinib, and 1 RS treated with chemotherapy. The segregation of gene expression profiles in samples was largely driven by recent exposure to ibrutinib. In C1 cluster (majority had no prior ibrutinb), RS and CLL samples were clearly separated into two subgroups (Figure 1b). In C2 cluster, CLL 8 treated with ibrutinib showed more similarity in gene expression to RS, than to other CLL samples treated with chemotherapy. In comparison of C2 to C1, we identified 71 differentially expressed genes, of which 34 genes were downregulated and 37 were upregulated in C2. Among the upregulated genes in C2 (majority had prior ibrutinib) are known immune modulating genes including LILRA6, FCGR3A, IL-10, CD163, CD14, IL-2RB (figure 1c). Downregulated genes in C2 are involved in B cell activation including CD40LG, CD22, CD79A, MS4A1 (CD20), and LTB, reflecting the expected biological effect of ibrutinib in reducing B cell activation. Among the 9 RS samples, we compared gene profiles between the two groups of RS with or without prior ibrutinib therapy. 38 downregulated genes and 10 upregulated genes were found in the 4 RS treated with ibrutinib in comparison with 5 RS treated with chemotherapy. The top upregulated genes in the ibrutinib-exposed group included PTHLH, S100A8, IGSF3, TERT, and PRKCB, while the downregulated genes in these samples included MS4A1, LTB and CD38 (figure 1d). In order to delineate the differences of RS vs CLL, we compared gene expression profiles between 5 RS samples and 3 CLL samples that were treated with only chemotherapy. RS samples showed significant upregulation of 129 genes and downregulation of 7 genes. Among the most significantly upregulated genes are multiple genes involved in monocyte and myeloid lineage regulation including TNFSF13, S100A9, FCN1, LGALS2, CD14, FCGR2A, SERPINA1, and LILRB3. Conclusion: Our study indicates that ibrutinib-resistant, RS-involved tissues are characterized by downregulation of genes in B cell activation, but with PRKCB and TERT upregulation. Furthermore, RS-involved nodal tissues display the increased expression of genes involved in myeloid/monocytic regulation in comparison with CLL-involved nodal tissues. These findings implicate that differential therapies for RS and CLL patients need to be adopted based on their prior therapy and gene expression signatures. Studies using large sample size will be needed to verify this hypothesis. Figure Disclosures Zhao: Merck: Current Employment. Blumenschein:Merck: Current Employment. Yearley:Merck: Current Employment. Wang:Novartis: Research Funding; Incyte: Research Funding; Innocare: Research Funding. Parikh:Verastem Oncology: Honoraria; GlaxoSmithKline: Honoraria; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; Ascentage Pharma: Research Funding; Genentech: Honoraria; AbbVie: Honoraria, Research Funding; Merck: Research Funding; TG Therapeutics: Research Funding; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding. Kenderian:Sunesis: Research Funding; MorphoSys: Research Funding; Humanigen: Consultancy, Patents & Royalties, Research Funding; Gilead: Research Funding; BMS: Research Funding; Tolero: Research Funding; Lentigen: Research Funding; Juno: Research Funding; Mettaforge: Patents & Royalties; Torque: Consultancy; Kite: Research Funding; Novartis: Patents & Royalties, Research Funding. Kay:Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Acerta Pharma: Research Funding; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; MEI Pharma: Research Funding; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Abbvie: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Rigel: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees. Braggio:DASA: Consultancy; Bayer: Other: Stock Owner; Acerta Pharma: Research Funding. Ding:DTRM: Research Funding; Astra Zeneca: Research Funding; Abbvie: Research Funding; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Octapharma: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees.

Background MBL is a precursor to chronic lymphocytic leukemia (CLL) and is subclassified into low-count (LC) MBL (absolute B-cell count<0.5x109/L) and high-count (HC) MBL (absolute B-cell count between 0.5 and 5x109/L). We previously reported that a polygenic risk score (PRS) based on a weighted average of 41 CLL-susceptibility variants was associated with risk of both MBL and CLL among a cohort of individuals from CLL families. Here we evaluate this PRS in an independent cohort of MBL and CLL individuals of European ancestry (EA), all of whom were ascertained agnostic to CLL family-history status. We also evaluate the PRS by MBL subtype (LC/HC), and in African American (AA) CLL cases and controls. Methods We genotyped 535 EA MBLs (139 HC-MBL, 396 LC-MBLs), 735 CLLs (640 EA, 95 AA), and 2,866 controls (2,631 EA, 235 AA) from the Mayo Clinic CLL Resource, Duke University, and Weill Cornell Medical College. We computed the CLL-PRS for each individual and used logistic regression to estimate odds ratios (OR) and 95% confidence intervals, adjusting for age and sex. To assess discriminatory accuracy, we computed the c-statistic. Among EA individuals, we calculated a trend test among LC-MBL, HC-MBL, and CLL risk using the P-value for heterogeneity from a polytomous logistic regression analysis. Moreover, we plotted a boxplot for the PRS among controls, LC-MBL, HC-MBL, and EA CLL, as well as for AA CLL cases and controls, and tested the statistical difference using the Kruskal Wallis test and Mann-Whitney test, respectively. Results We found a significant association of PRS with overall MBL risk (OR=1.87, P=1.1x10-28) with good discrimination (c-statistic=0.72). Significant associations were also found for LC-MBL (OR=1.75, P=7.5x10-19, c-statistic=0.72), HC-MBL (OR=2.22, P=1.4x10-17, c-statistic=0.74), and CLL of EA (OR=2.60, P=1.2x10-62, c-statistic=0.78), with a significant difference among these cohorts (Figure 1.A) and a significant positive trend across these cohorts (Pheterogeneity=8.4x10-6). Although we observed a 33% increased risk of CLL in AA (c-statistic=0.57), the PRS was borderline significant (P=0.07, Figure 1.B). Conclusion The CLL-PRS is a strong prediction-tool for risk of CLL and MBL among individuals of EA. Future studies are needed to improve the PRS for AAs including performing GWAS of AA in order to identify CLL-susceptibility SNPs that are more representative within known CLL loci and to discover novel CLL loci that are unique for AAs. Disclosures Parikh: GlaxoSmithKline: Honoraria; Janssen: Honoraria, Research Funding; Ascentage Pharma: Research Funding; AbbVie: Honoraria, Research Funding; Merck: Research Funding; TG Therapeutics: Research Funding; Genentech: Honoraria; Pharmacyclics: Honoraria, Research Funding; MorphoSys: Research Funding; AstraZeneca: Honoraria, Research Funding; Verastem Oncology: Honoraria. Braggio:DASA: Consultancy; Bayer: Other: Stock Owner; Acerta Pharma: Research Funding. Brander:Genentech: Consultancy, Honoraria, Other, Research Funding; Juno/Celgene/BMS: Other, Research Funding; MEI Pharma: Other, Research Funding; Ascentage: Other, Research Funding; ArQule: Consultancy, Other, Research Funding; NCCN: Other; Teva: Consultancy, Honoraria; Tolero: Research Funding; AstraZeneca: Consultancy, Honoraria, Other, Research Funding; Pharmacyclics LLC, an AbbVie Company: Consultancy, Honoraria, Other, Research Funding; Pfizer: Consultancy, Other; TG Therapeutics: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding; Novartis: Consultancy, Other; AbbVie: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding; Tolero: Research Funding; Teva: Consultancy, Honoraria; DTRM: Other, Research Funding; BeiGene: Other, Research Funding; Novartis: Consultancy, Other; NCCN: Other; Verastem: Consultancy, Honoraria, Other, Research Funding. Cerhan:NanoString: Research Funding; BMS/Celgene: Research Funding. Kay:Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; MEI Pharma: Research Funding; Abbvie: Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees. Furman:Acerta: Consultancy; AstraZeneca: Consultancy, Research Funding; Beigene: Consultancy; Abbvie: Consultancy; Pharmacyclics: Consultancy; Sunesis: Consultancy; TG Therapeutics: Consultancy, Research Funding; Verastem: Consultancy; Incyte: Consultancy; Genentech: Consultancy; Janssen: Consultancy, Speakers Bureau; Loxo Oncology: Consultancy; Oncotarget: Consultancy. Shanafelt:Mayo Clinic: Patents & Royalties: and other intellectual property; Genentech, Pharmacyclics LLC, an AbbVie Company, AbbVie, GlaxoSmithKline, and Merck: Research Funding.

Introduction: Lymphoma is the most common cancer among adolescents and young adults (AYAs). We examined changes in health-related quality of life (HRQoL) and its predictors in AYA patients (pts). Patients and Methods: We identified AYA pts (aged 18-39) enrolled 2002-2015 in a prospective cohort of pts with newly diagnosed lymphoma from the University of Iowa and Mayo Clinic Molecular Epidemiology Resource, part of the Lymphoma Epidemiology of Outcomes cohort. Enrollment could occur prior to or after initiation of treatment. We measured HRQoL using the Functional Assessment of Cancer Therapy-General (FACT-G) questionnaire at baseline, 12, and 24 months. FACT-G yields five HRQoL domain scores: emotional well-being (EWB), functional WB (FWB), physical WB (PWB), social/family WB (SFWB), and total FACT-G score (a sum of the domains). Pts completing <80% of the FACT-G questions were excluded. Linear mixed models with random subject intercepts estimated changes in FACT-G scores from baseline. The covariates in multivariate analysis were lymphoma subtype, stage, and treatment. Interaction effects between treatment (chemotherapy and/or radiation) and subtype were added to the model. We calculated effect sizes (ES) for the magnitude of mean change scores: 0.2, 0.5, and 0.8 were considered small, medium, and large ESs, respectively. Only ESs for mean score differences with p<0.05 are reported. Results: We identified 467 pts; median age at diagnosis was 30 years, median follow up was 5.9 years. 53% of pts completed the baseline FACT-G assessment pre-treatment, 47% completed after treatment began. Pts assessed after treatment initiation had lower baseline total FACT-G (ES -0.25), FWB (ES -0.27), and PWB scores (-0.46); but baseline EWB was higher in pts assessed prior to treatment (ES 0.20). There was no association between HRQoL scores at baseline or over time and lymphoma subtype, stage, or treatment type, or interactions. Total FACT-G scores modestly improved over time, ES 0.32 at 1 year and ES 0.45 at 2 years after enrollment. EWB, FWB, and PWB also improved over time (ES 0.36, 0.44, 0.30 at 1 year; and 0.49, 0.56, 0.38 at 2 years, respectively). SFWB scores slightly worsened over time (ES -0.24 at 1 year and -0.12 at 2 years). Conclusions: AYA pts with lymphoma had higher baseline total FACT-G scores, FWB and PWB prior to therapy initiation compared to after initiation. HRQoL improved from diagnosis through the first 2 years after diagnosis, except for SFWB. Neither stage, lymphoma subtype, nor treatment type affected change in HRQoL. The lack of improvement in SFWB suggests social interventions and future studies should examine factors impacting SFWB in AYA pts. Disclosures Cohen: Genentech, BMS, Novartis, LAM, BioInvent, LRF, ASH, Astra Zeneca, Seattle Genetics: Research Funding; Janssen, Adicet, Astra Zeneca, Genentech, Aptitude Health, Cellectar, Kite/Gilead, Loxo: Consultancy. Flowers:Leukemia and Lymphoma Society: Membership on an entity's Board of Directors or advisory committees; National Cancer Institute: Research Funding; AbbVie: Consultancy, Research Funding; Cancer Prevention and Research Institute of Texas: Research Funding; Eastern Cooperative Oncology Group: Research Funding; Burroughs Wellcome Fund: Research Funding; Kite: Research Funding; V Foundation: Research Funding; TG Therapeutics: Research Funding; Millennium/Takeda: Consultancy, Research Funding; Acerta: Research Funding; Spectrum: Consultancy; Pharmacyclics/Janssen: Consultancy; Karyopharm: Consultancy; OptumRx: Consultancy; Gilead: Consultancy, Research Funding; Genentech, Inc./F. Hoffmann-La Roche Ltd: Consultancy, Research Funding; Denovo Biopharma: Consultancy; Celgene: Consultancy, Research Funding; BeiGene: Consultancy; Bayer: Consultancy. Cerhan:BMS/Celgene: Research Funding; NanoString: Research Funding.

Background Diffuse large B-cell lymphoma (DLBCL) is the most common aggressive non-Hodgkin lymphoma subtype with a 5-year survival of ~64%. While DLBCL is treated using immunochemotherapy (IC) with curative intent, 20%-40% of patients do not reach remission or relapse post IC. Clonal somatic mutations have been associated with aging, hematologic malignancies (predominately myeloid), and reduced OS in the general population. The objective of this study was to evaluate the association of clonal somatic mutations with event-free survival (EFS) and overall survival (OS). Methods We studied newly diagnosed DLBCL cases treated with IC who were enrolled in the Molecular Epidemiology Resource (MER) of the University of Iowa/Mayo Clinic Lymphoma Specialized Program of Research Excellence (SPORE). Clinical and treatment data were abstracted from medical records and all patients were systematically followed for disease outcomes. Pre-treatment DNA was extracted from matched peripheral blood and paraffin-embedded tumor tissue, and whole exome sequencing was conducted at 100x coverage. From the peripheral blood, allele counts from GVCF files produced by HaplotypeCaller in GATK were extracted for 42 genes commonly associated with clonal hematopoiesis (e.g. DNMT3A, TET2, and ASXL1). Mutations were deemed clonal somatic if the population minor allele frequency was <0.5% in ExAC and had a variant allele fraction (VAF) that deviated from 0.5 using a binomial distribution test at p<0.001. Furthermore, mutations had to have a minimum alternate read count of at least 5 reads, a VAF greater than or equal to 10%, and met at least one of the following criteria: CAVA impact of "HIGH"; pathogenic/likely pathogenic per ClinVar; or reported in COSMIC at least 10 times. EFS was defined as time from diagnosis to disease progression, relapse, retreatment, or death due to any cause. The association of clonal somatic mutations with prognosis was estimated using Kaplan-Meier curves, and hazard ratios (HR) and 95% confidence intervals (CI) from Cox regression. Associations were adjusted for age at diagnosis, sex, and the International Prognostic Index (IPI). Results The study consisted of 261 DLBCL patients treated with IC. The median age at diagnosis was 65 years (range 20-90) and 56% were male. With a median follow-up time of 5.1 years (range 0.1-15.0), there were 100 events and 80 deaths. A total of 17 (6.5%) patients had clonal somatic mutations, and16 patients were over the age of 60. A total of 8 (of 42) genes had clonal somatic mutations, with SF3B1, ASXL1, and TET2, being the most frequent (4 individuals per gene). VAFs ranged from 0.10 to 0.28 and none of the patients had multiple mutations. Additionally, the clonal somatic variants found in the peripheral blood were abscent in the tumor sample. Of the 17 patients with clonal somatic mutations, 12 had an event while 88 patients without a mutation had an event. In a univariate analysis, clonal somatic mutations were associated with inferior EFS (HR=2.55, 95% CI 1.39-4.68, p=0.002; Figure 1A). After adjusting for age, sex, and IPI, clonal somatic mutations remained associated with inferior EFS (HR=2.02, 95% CI 1.09-3.74, p=0.026). Clonal somatic mutations were also associated with inferior OS in the univariate analysis (HR=2.06, 95% CI 0.99-4.29, p=0.053), which attenuated after multivariate adjustment (HR=1.59, 95% CI: 0.76-3.34, p=0.22, Figure 1B). Although based on small numbers, mutations in SF3B1 were associated with inferior EFS (HR=3.25, 95% CI 1.16-9.12, p=0.025), but did not reach significance for OS (HR=2.56, 95% CI 0.78-8.38, p=0.120). Conclusions In this novel study of newly diagnosed DLBCL patients, clonal somatic mutations were identified in 6.5% of patients and were associated with inferior outcomes. Additional research is required at deeper sequencing to validate these findings and integration with tumor genomics is required to understand the prognosis of DLBCL patients with smaller clonal populations. Disclosures Shah: Dren Bio: Consultancy. Maurer:Celgene / BMS: Research Funding; Pfizer: Membership on an entity's Board of Directors or advisory committees; Morphosys: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Nanostring: Research Funding. Martin:Celgene: Consultancy; Karyopharm: Consultancy, Research Funding; Morphosys: Consultancy; Regeneron: Consultancy; Incyte: Consultancy; Kite: Consultancy; Cellectar: Consultancy; Bayer: Consultancy; Beigene: Consultancy; Sandoz: Consultancy; I-MAB: Consultancy; Janssen: Consultancy; Teneobio: Consultancy. Witzig:AbbVie: Consultancy; Incyte: Consultancy; Acerta: Research Funding; Karyopharm Therapeutics: Research Funding; Immune Design: Research Funding; Spectrum: Consultancy; Celgene: Consultancy, Research Funding; MorphSys: Consultancy. Nowakowski:NanoString: Research Funding; Seattle Genetics: Consultancy; Curis: Consultancy; Kymera: Consultancy; Kite: Consultancy; Ryvu: Consultancy, Membership on an entity's Board of Directors or advisory committees; MorphoSys: Consultancy, Research Funding; Celgene/BMS: Consultancy, Research Funding. Novak:Celgene/BMS: Research Funding. Cerhan:NanoString: Research Funding; BMS/Celgene: Research Funding.

Abstract Chronic lymphocytic lymphoma (CLL) has one of the highest familial risks among cancers. Monoclonal B-cell lymphocytosis (MBL), the precursor to CLL, has a higher prevalence (13%-18%) in families with 2 or more members with CLL compared with the general population (5%-12%). Although, the rate of progression to CLL for high-count MBLs (clonal B-cell count ≥500/µL) is ∼1% to 5%/y, no low-count MBLs have been reported to progress to date. We report the incidence and natural history of MBL in relatives from CLL families. In 310 CLL families, we screened 1045 relatives for MBL using highly sensitive flow cytometry and prospectively followed 449 of them. MBL incidence was directly age- and sex-adjusted to the 2010 US population. CLL cumulative incidence was estimated using Kaplan-Meier survival curves. At baseline, the prevalence of MBL was 22% (235/1045 relatives). After a median follow-up of 8.1 years among 449 relatives, 12 individuals progressed to CLL with a 5-year cumulative incidence of 1.8%. When considering just the 139 relatives with low-count MBL, the 5-year cumulative incidence increased to 5.7%. Finally, 264 had no MBL at baseline, of whom 60 individuals subsequently developed MBL (2 high-count and 58 low-count MBLs) with an age- and sex-adjusted incidence of 3.5% after a median of 6 years of follow-up. In a screening cohort of relatives from CLL families, we reported progression from normal-count to low-count MBL to high-count MBL to CLL, demonstrating that low-count MBL precedes progression to CLL. We estimated a 1.1% annual rate of progression from low-count MBL, which is in excess of that in the general population.

Abstract Most human cancers converge to a deregulated methylome with reduced global levels and elevated methylation at select CpG islands. To investigate the emergence and dynamics of the cancer methylome, we characterized genome-wide DNA methylation in preneoplastic monoclonal B-cell lymphocytosis (MBL) and chronic lymphocytic leukemia (CLL), including serial samples collected across disease course. We detected the aberrant tumor-associated methylation landscape at CLL diagnosis and found no significant differentially methylated regions in the high-count MBL-to-CLL transition. Patient methylomes showed remarkable stability with natural disease and posttherapy progression. Single CLL cells were consistently aberrantly methylated, indicating a homogeneous transition to the altered epigenetic state and a distinct expression profile together with MBL cells compared with normal B cells. Our longitudinal analysis reveals the cancer methylome to emerge early, which may provide a platform for subsequent genetically driven growth dynamics, and, together with its persistent presence, suggests a central role in disease onset. Significance: DNA methylation data from a large cohort of patients with MBL and CLL show that epigenetic transformation emerges early and persists throughout disease stages with limited subsequent changes. Our results indicate an early role for this aberrant landscape in the normal-to-preneoplastic transition that may reflect a pan-cancer mechanism. See related commentary by Rossi, p. 6. This article is highlighted in the In This Issue feature, p. 1

Introduction: In 2017, a two-dose recombinant zoster vaccine (RZV) containing glycoprotein E (gE) and a novel adjuvant was approved to prevent herpes zoster and its complications in adults ≥50 years of age in the US. There are limited data on the immunogenicity and safety of RZV in patients with chronic lymphocytic leukemia (CLL). Methods: Between 8/15/2018 and 11/4/2019, RZV-naïve patients with CLL and monoclonal B-cell lymphocytosis (MBL) seen at Mayo Clinic, Rochester, MN were enrolled in this IRB-approved study. All participants received two doses of vaccine, at 0 and 2 months after enrollment. Cell-mediated immunity was measured by dual-color interferon γ (IFN- γ) and interleukin 2 (IL-2) FLUOROSpot in peripheral blood mononuclear cells (PBMC) after depletion of ≥50% leukemic B cells. Results were reported in spot forming cells (SFC)/106 PBMC in wells stimulated with gE overlapping peptides or varicella zoster virus (VZV) inactivated cell lysate. Response rate was defined as the proportion of participants who achieved a ≥2-fold increase in IFN- γ or IL-2 SFC/106 PBMC one month after the second dose of vaccine compared with pre-vaccination baseline levels. We also determined the geometric mean fold rise (GMFR) and geometric mean count (GMC) of SFC /106 PBMC at baseline and 90 days after the first dose of vaccine. Two cohorts were enrolled: Cohort 1 consisted of individuals with previously untreated MBL and CLL; and Cohort 2 consisted of CLL participants who were on Bruton tyrosine kinase inhibitor (BTKi) therapy. We compared the response data to historic age-and sex-matched healthy controls who received RZV. Chi-square or Fisher's exact tests measured differences in response rates and Kruskall-Wallis tested for differences in continuous variables. Among CLL participants, multivariable regression analysis was used to investigate the association between day 90 SFC and prior BTKi treatment, accounting for age at RZV, age at CLL diagnosis, sex, and day 0 SFC. Results: Sixty-one participants were enrolled. Paired samples were available for 41 participants (22 in Cohort 1 and 19 [18 ibrutinib and 1 acalabrutinib] in Cohort 2), and 68 age- and sex-matched healthy controls. Baseline characteristics of MBL/CLL participants are shown in Table 1. Compared to healthy controls, participants with MBL/CLL had a significantly lower IFN-γ VZV-specific response rate (41% vs. 63%, p=0.03) and IFN-γ gE-specific response (56% vs. 96%, p<0.001); although there were no differences in IL-2 response rates to VZV (51% vs 68%, p=0.09) or gE (95% vs. 100%, p=0.14, Table 2). There were differences in GMFR between participants with MBL/CLL and controls that reached statistical significance for IFN-γ and IL-2 gE-specific responses and borderline significance for IFN-γ VZV-specific responses (Table 2). VZV-specific response rates did not significantly differ between individuals with untreated MBL/CLL and those receiving BTKi (52% vs. 28%, p=0.12 for IFN- γ; (62% vs. 39%, p=0.15 for IL-2), nor did IL-2 gE-specific responses (96% vs. 95%, p=1.0). However, untreated MBL/CLL participants had significantly higher IFN- γ gE-specific response rate compared to BTKi-treated individuals (73% vs. 37%, p=0.02, Table 2). IFN- γ and IL-2 VZV- and gE-specific SFC GMC was significantly higher at Day 90 compared to Day 0 in all vaccinees, although the magnitude of response was significantly lower in MBL/CLL participants compared to healthy controls (Table 3). Among participants with MBL/CLL, age at diagnosis, age at receipt of RZV, and sex did not predict response to vaccination after accounting for prevaccination values. No serious adverse events were noted among MBL/CLL participants while on this study. Additional analyses including determination of humoral immunogenicity and long-term follow up to ascertain risk of herpes zoster infection are ongoing at this time. Conclusion: RZV was associated with lower cell mediated immunogenicity in MBL/CLL participants compared to healthy older adults. Among individuals with CLL, BTKi treatment was associated with decreased cell mediated immunogenicity of the vaccine. Given the inferior response rates, an additional dose of RZV may be considered to boost responses and should be studied in this patient population. Disclosures Johnson: GSK: Research Funding. Ding:Abbvie: Research Funding; Astra Zeneca: Research Funding; DTRM: Research Funding; alexion: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; Octapharma: Membership on an entity's Board of Directors or advisory committees; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; Beigene: Membership on an entity's Board of Directors or advisory committees. Kenderian:Humanigen: Consultancy, Patents & Royalties, Research Funding; Torque: Consultancy; Novartis: Patents & Royalties, Research Funding; Kite: Research Funding; Gilead: Research Funding; Juno: Research Funding; BMS: Research Funding; Tolero: Research Funding; Mettaforge: Patents & Royalties; Lentigen: Research Funding; MorphoSys: Research Funding; Sunesis: Research Funding. Wang:Novartis: Research Funding; Incyte: Research Funding; Innocare: Research Funding. Kay:Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Rigel: Membership on an entity's Board of Directors or advisory committees; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Cytomx: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees; Sunesis: Research Funding; Abbvie: Research Funding; MEI Pharma: Research Funding; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Acerta Pharma: Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding. Levin:GSK: Research Funding. Kennedy:ICW Ventures: Research Funding. Weinberg:GSK: Research Funding. Parikh:GlaxoSmithKline: Honoraria; AstraZeneca: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; TG Therapeutics: Research Funding; Merck: Research Funding; AbbVie: Honoraria, Research Funding; MorphoSys: Research Funding; Verastem Oncology: Honoraria; Pharmacyclics: Honoraria, Research Funding; Genentech: Honoraria; Ascentage Pharma: Research Funding.

Introduction Monoclonal gammopathy of undetermined significant (MGUS) is a premalignant plasma cell disorder that is common in individuals over age 50. MGUS prevalence estimates to date have generally been based on results of serum electrophoresis and immunofixation (for heavy chain [HC] MGUS) and additionally, free light chain (for light chain [LC] MGUS). Mass-spectrometry assays, however, can detect lower levels of monoclonal (M) proteins, identify the isotype and provide accurate quantification of the M-protein. Given the evidence that MGUS is likely present at least 10 years prior to its detection, mass spectrometry may provide more accurate estimates of underlying MGUS. We examined the prevalence of HC-MGUS using matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry among three risk groups: European Americans (EA), African Americans (AA) and first-degree relatives (FDR) of patients with multiple myeloma (MM), MGUS, chronic lymphocytic leukemia (CLL) or non-Hodgkin's lymphoma (NHL). Methods We sampled all AA and a random sample of EA participants ages 50 and older enrolled in the Mayo Clinic Biobank. We also selected unaffected first-degree relatives (limiting to ages 50 and older) from our ongoing family study of hematological malignancies. We screened serum samples by the MALDI-TOF mass spectrometry assay, which is clinically used at Mayo Clinic (known as MASS-FIX) for detection and isotypes of M-proteins. The assay uses isotype-specific nanobody enrichment coupled to MALDI-TOF mass spectrometry. For each of the risk groups, HC- MGUS prevalence was estimated by age (50-59, 60-69, 70+). Age- and sex-adjusted prevalence rates were calculated by direct standardization to the 2010 US population. Ninety-five percent confidence intervals (95% CI) for the prevalence rates and comparisons across the three groups were based on the Poisson distribution. Because free LC information was unavailable, LC-MGUS was not estimated. Results A total 327 AA, 854 EA and 792 FDR were screened for M-proteins using the MASS-FIX assay. All three groups had similar sex (42-44% male) and age distributions (mean[SD] age was 64.5[9.5] yrs., 64.4[8.8] yrs. and 64.9[10.5] yrs. for AA, EA and FDR, respectively). As previously noted using conventional detection methods, the overall prevalence of HC-MGUS was higher in the AA population (16.5% [95%CI: 12.2%, 20.8%]) and FDR (21.5% [95%CI: 18.3%, 24.7%]) than in EA (11.2% [95%CI: 8.8%, 13.5%]), both p-values <0.0001. This pattern was generally seen across age groups (Table 1), with increasing prevalence with age. FDR of MM or MGUS cases had a higher prevalence (22.2% [95%CI: 18.4%, 26.0%]) than FDR of CLL or NHL cases (18.8% [95%CI: 13.3%, 24.4%]), although the difference was not statistically significant (p-value=0.82). Overall prevalence estimates of HC-MGUS using MASS-FIX were at least three-fold higher than estimates using conventional methods alone (i.e. age- and sex-adjusted prevalence in Olmsted County, MN, was 3.1% [95% CI: 2.9%-3.4%]). Conclusion We provided some of the first data on prevalence of HC-MGUS across three risk groups, using a sensitive method for detecting monoclonal proteins. The MASS-FIX assay resulted in substantially higher absolute rates of HC-MGUS (at least 3-fold higher) relative to conventional methods. Further, the prevalence of HC-MGUS among the AA and FDR was significantly higher than the EA population. Thus, the more sensitive assay identified greater absolute numbers of individuals with MGUS, but resulted in similar relationships as seen in prior studies across these risk groups. Our results have implications for future studies of the etiology of MGUS and its progression. Disclosures Dispenzieri: Janssen: Research Funding; Pfizer: Research Funding; Alnylam: Research Funding; Intellia: Research Funding; Celgene: Research Funding; Takeda: Research Funding. Kumar:Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Karyopharm: Consultancy; Genecentrix: Consultancy; Cellectar: Other; Carsgen: Other, Research Funding; Merck: Consultancy, Research Funding; Dr. Reddy's Laboratories: Honoraria; Adaptive Biotechnologies: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Kite Pharma: Consultancy, Research Funding; BMS: Consultancy, Research Funding; Tenebio: Other, Research Funding; Sanofi: Research Funding; MedImmune: Research Funding; Novartis: Research Funding. Murray:The Binding Site: Patents & Royalties: Patent Use of Mass Spec to identify monoclonal proteins licensed to The Binding Site.

INTRODUCTION T-cell prolymphocytic leukemia (T-PLL) is a rare, aggressive malignancy of mature T-cells. Although responses may been seen with initial alemtuzumab-based therapy, relapse is inevitable and relapsed/refractory disease carries a dismal prognosis. T-PLL has shown in vitro sensitivity to venetoclax, and short-lived clinical responses to venetoclax monotherapy (Smith, Blood Advances 2020; Boidol, Blood 2017) or when given in combination with pentostatin (Alfayez, Leukemia & Lymphoma 2020). Given the lack of standard treatment options, we reviewed the outcomes of patients (pts) with relapsed T-PLL on venetoclax-based therapy. METHODS Using an institutional clinical database of pts with T-PLL seen in the Division of Hematology at Mayo Clinic, Rochester, MN, all pts treated with venetoclax or venetoclax-based therapies in a relapsed/refractory setting were identified. Clinical, laboratory, and pathology data, as well as treatment dosing and toxicity were ascertained retrospectively from the medical records. Diagnostic criteria and response definitions were utilized as per the T-PLL International Study Group (Staber, Blood 2019). RESULTS Between 8/2017 and 5/2020, 9 pts with relapsed/refractory T-PLL treated with venetoclax were identified. The median age was 63 years (range 49-75), and one-third were male. Baseline characteristics are detailed in Table 1. Rearrangement of TCL1 family genes was present in all 8 pts evaluated with fluorescence in situ hybridization (FISH). Using conventional cytogenetics, a complex karyotype was present in 4/6 pts tested. The median prior lines of therapy was 3 (range 1-4), including alemtuzumab in 8 of 9 pts (intravenous 7/8); and two pts had undergone prior hematopoietic stem cell transplantation (1 allogeneic; 1 autologous) after achieving a complete remission. Additional individual pt details are included in Table 2. Prior to venetoclax therapy initiation, 2 pts had B-symptoms (2 night sweats; 1 fever) and 6 pts had an ECOG score ≥ 2. Lymphadenopathy and splenomegaly were present in 6 and 9 pts, respectively. Extranodal involvement included 3 pts with cutaneous involvement and 5 pts with effusions (4 ascites; 1 pleural). The target maximum dose of venetoclax (800 mg [n=4]; 400 mg [n=1]) was reached by 5 pts at a median of 12 days (range 7-40 days). The other 4 pts had disease progression after a median of 10 days (range 5-22 days) during the dose ramp-up, including 2 pts undergoing rapid dose escalation. Altogether, 6 of the 9 pts initiated venetoclax with a rapid dose escalation. Bendamustine was given with venetoclax in 5/9 pts; median number of cycles 1 (range 1-4) with variable starting dosing (range 60-100 mg/m2). The disease control rate was 56%; best response was partial remission (PR) in 4 (44%) pts and stable disease (SD) in 1 (11%) pt. The 1 pt with SD received venetoclax monotherapy; however, the overall response rate among pts who received the combination of venetoclax and bendamustine was 80% (4/5 pts). One pt with a partial remission met all criteria for complete remission but did not have a confirmatory bone marrow biopsy. Cutaneous disease improved in 2 of 3 pts (both with PR as best response), and effusions improved in 2 of 5 pts (1 PR and 1 SD as best response). Among those in PR, the median decrease in absolute lymphocyte count was 67x109/L and the median decrease in lactate dehydrogenase was 1,162 U/L (normal range 122-222 U/L). Median duration of treatment for all pts was 42 days (range 4-201 days). All pts ultimately died during follow-up with a median overall survival of 53 days (range 4-464 days); Figure 1. All pts experienced at least one adverse event and 8 of 9 pts had a grade ≥ 3 toxicity, most commonly edema (n=7) and neutropenia (n=6). Five pts required dose interruptions due to neutropenia (n=3), tumor lysis syndrome (n=1), and edema (n=1). Three pts had dose reductions, all from 800 mg dosing, due to hematologic toxicity (n=2) and nausea (n=1). No pts discontinued venetoclax as a result of adverse events. CONCLUSION Treatment of pts with relapsed/refractory T-PLL remains a significant unmet need. The 9 pts described herein represent the largest cohort of pts treated with venetoclax-based therapy in this setting to the current date. Despite initial reports of clinical efficacy, our results show that venetoclax (with or without bendamustine) has modest efficacy in the treatment of relapsed/refractory T-PLL after prior alemtuzumab exposure. Disclosures Parikh: TG Therapeutics: Research Funding; Verastem Oncology: Honoraria; GlaxoSmithKline: Honoraria; AbbVie: Honoraria, Research Funding; Genentech: Honoraria; Merck: Research Funding; MorphoSys: Research Funding; Pharmacyclics: Honoraria, Research Funding; Janssen: Honoraria, Research Funding; Ascentage Pharma: Research Funding; AstraZeneca: Honoraria, Research Funding. Shah:Dren Bio: Consultancy. Bennani:Verastem: Other: Advisory Board; Affimed: Research Funding; Purdue Pharma: Other: Advisory Board; Kite/Gilead: Research Funding. Wang:Incyte: Research Funding; Novartis: Research Funding; Innocare: Research Funding. Kenderian:MorphoSys: Research Funding; Lentigen: Research Funding; Gilead: Research Funding; Juno: Research Funding; BMS: Research Funding; Tolero: Research Funding; Sunesis: Research Funding; Kite: Research Funding; Novartis: Patents & Royalties, Research Funding; Torque: Consultancy; Humanigen: Consultancy, Patents & Royalties, Research Funding; Mettaforge: Patents & Royalties. Kay:MEI Pharma: Research Funding; Oncotracker: Membership on an entity's Board of Directors or advisory committees; Abbvie: Research Funding; Morpho-sys: Membership on an entity's Board of Directors or advisory committees; Acerta Pharma: Research Funding; Cytomx: Membership on an entity's Board of Directors or advisory committees; Juno Theraputics: Membership on an entity's Board of Directors or advisory committees; Dava Oncology: Membership on an entity's Board of Directors or advisory committees; Bristol Meyer Squib: Membership on an entity's Board of Directors or advisory committees, Research Funding; Tolero Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees, Research Funding; Rigel: Membership on an entity's Board of Directors or advisory committees; Agios Pharma: Membership on an entity's Board of Directors or advisory committees; Pharmacyclics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sunesis: Research Funding; Astra Zeneca: Membership on an entity's Board of Directors or advisory committees. Ding:Octapharma: Membership on an entity's Board of Directors or advisory committees; Astra Zeneca: Research Funding; alexion: Membership on an entity's Board of Directors or advisory committees; Beigene: Membership on an entity's Board of Directors or advisory committees; MEI Pharma: Membership on an entity's Board of Directors or advisory committees; Merck: Membership on an entity's Board of Directors or advisory committees, Research Funding; DTRM: Research Funding; Abbvie: Research Funding. OffLabel Disclosure: Venetoclax: off-label use in treatment of relapsed/refractory T-cell prolymphocytic leukemia

Introduction Monoclonal gammopathy of undetermined significance (MGUS) is a premalignant clonal disorder, which progresses at a rate of 1% per year to multiple myeloma (MM), or other plasma-cell or lymphoid disorders. MGUS is common and occurs in approximately 3% and 5% of persons 50 and 70 years of age or older, respectively. Clinical factors reported to be associated with MGUS progression include MGUS isotype, abnormal serum free light-chain ratio (FLCr), and high serum monoclonal protein (M protein) level (>=1.5 g per deciliter). Body mass index (BMI) has also been seen associated with MGUS progression, but has not been evaluated in context of established clinical prognostic factors. Here, we evaluate the contribution of BMI to MGUS progression beyond clinical prognostic factors in a population-based study and examine differential associations by sex. Methods We studied 594 patients residing in Olmsted County Minnesota, who were identified with MGUS in a screening study conducted between1995 through 2003. Patients with light-chain MGUS were not included. Patients were screened for M-protein [normal (<1.5 g/dl) or high (≥1.5 g/dl)], FLCr [normal (0.26-1.65) or abnormal (<0.26 and/or >1.65)], and isotype (IgG, IgM, IgA, bi-clonal). Follow-up time was calculated from date of MGUS screening to date of last follow-up, death, or progression to MM or another plasma-cell or lymphoid disorder. BMI (kg/m2) was calculated using height and weight values reported close to sample date (80% of patients within 2 years), and then categorized into BMI<25 and BMI≥25. We used Cox regression to estimate the association of BMI with risk of MGUS progression to MM or another plasma-cell or lymphoid disorder, univariately, and accounting for clinical factors. Analyses were also stratified by sex. We report hazard ratios (HR) and 95% confidence intervals (CI). Results Of the 594 patients, 51% were male, and the median age at screening date was 73 (range:50-98 years). The immunoglobulin type was IgG in 71% of patients, IgM in 17%, IgA in 10%, and bi-clonal in 2%. High M protein level was observed in 22% and abnormal FLCr in 28%. BMI≥25 was observed in 67% of patients. The median follow-up time was 10.5 years (range:0-25). Over a median of 6,846 person-years, 465 patients (78%) died and 57 patients progressed and developed MM (N=39), amyloidosis (N=8), lymphoma (N=5), or Waldenstrom macroglobulinemia (N=5). The overall rate of progression was 0.87 events (CI:0.67-1.12) per 100 person-years, and higher among males (1.01, CI:0.73-1.42) than in females (0.72, CI:0.48-1.08), however, the difference was not statistically significant (P=0.24). In univariate analyses, BMI≥25 (HR=2.14, CI:1.05-4.36, P=0.04), non-IgG isotype (HR=2.84, CI:1.68-4.80, P=0.0001), high M protein (HR=2.57, CI: 1.50-4.42, P=0.001), and abnormal FLCr (HR=3.39, CI:1.98-5.82, P<0.0001) were associated with increased risk of progression (Table 1.A). These four factors were independently associated with MGUS progression in a multivariable model, with a c-statistic=0.75 (CI:0.68-0.82). When stratifying by sex, associations of BMI with progression were stronger among females than males (Table 1.B) [c-statistic=0.81 (CI:0.72-0.90) vs 0.71 (CI:0.60-0.82) for females vs. males respectively], however, a test for interaction between BMI and sex was not statistically significant (P=0.15). Conclusions In this study we found evidence that high BMI is a prognostic factor independent of isotype, M protein, and FLC ratio in the full cohort, however, this was mainly driven by the effect in females rather than males. Future studies should further investigate sex differences in evaluating prognostic factors among MGUS patients. Disclosures Dispenzieri: Intellia: Research Funding; Pfizer: Research Funding; Alnylam: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Janssen: Research Funding. Kumar:Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Cellectar: Other; Kite Pharma: Consultancy, Research Funding; Tenebio: Other, Research Funding; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; MedImmune: Research Funding; Sanofi: Research Funding; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Merck: Consultancy, Research Funding; Adaptive Biotechnologies: Consultancy; Genecentrix: Consultancy; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Dr. Reddy's Laboratories: Honoraria; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Novartis: Research Funding; Carsgen: Other, Research Funding; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member.